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Influence of client social class on therapists’ perceptions and evaluations Hutchings, Anita Clare 1998

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THE INFLUENCE OF CLIENT SOCIAL CLASS ON THERAPISTS' PERCEPTIONS AND EVALUATIONS By Anita Clare Hutchings B.A., Bishops University, 1986  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS in THE FACULTY OF GRADUATE STUDIES (Department of Counselling Psychology)  We accept this thesis as conforming to the required standard  THE UNIVERSITY OF BRITISH COLUMBIA June 1998 ©Anita Clare Hutchings, 1998  In  presenting  degree freely  at  this  the  available  copying  of  department publication  of  in  partial  fulfilment  University  of  British  Columbia,  for  this or  thesis  reference  thesis by  this  for  his thesis  and  scholarly  or for  her  Department  DE-6  (2/88)  Columbia  I  I further  purposes  gain  the  shall  requirements  agree  that  agree  may  representatives.  financial  permission.  T h e U n i v e r s i t y o f British Vancouver, Canada  study.  of  It not  be is  that  the  Library  an  granted  by  allowed  advanced  shall  permission  understood be  for  the that  without  for head  make  it  extensive of  my  copying  or  my  written  11  ABSTRACT  This study was designed to explore whether initial information on client social class would impact negatively on the therapist's perception, evaluation and proposed treatment of the client. Respondents were randomly selected (N= 300) from the membership lists of the British Columbia Psychological Association and the Canadian Guidance and Counselling Association (British Columbian members). The return rate was 37% (N= 111). Of these, 49 were returned from the British Columbia Psychological Association and 62fromthe Canadian Guidance and Counselling Association. Each respondent read the client information forms. They then filled out a questionnaire containing a seven-point Likert scale, a qualitative response section, a semantic differential of opposing adjectives, a respondent relationships form, and a demographics section. Half of the questionnaires contained the description of a lower social class client, and half contained the description of a middle class client. All remaining information was identical. Examination by total sample population, association and gender all produced significant results linked to client social class. The lower class client was evaluated as less intelligent, less knowledgeable, less capable, less clean, less hostile, louder, and more emotional than the middle class client. The CGCA respondents produced lowerfrequenciesof presenting problems for the lower class client. Doctoral degree respondents produced less significant bias than respondents with master's degrees. An unusual pattern of evaluation linked to respondents' years of experience was apparent, however results by client social class were not significant. Caution is advised when translating results to real-life situations since counsellors may not necessarily respond in the same way in a real counselling setting as they would to a hypothetical client.  iii TABLE OF CONTENTS Abstract  ii  Table of Contents  iii  List of Tables  vi  List of Figures  viii  Preface  ix  Acknowledgement  x  INTRODUCTION  1  LITERATURE REVIEW  5  Portrait of Life in the Working Class Life Choices and Experiences Education Work Leisure Stressful Life Events Health Self Esteem and Self-Worth Values and Beliefs Social and Political Ideology Parental Values Education Sex Roles Emotional Expression  5 6 6 10 11 12 13 15 18 18 21 23 24 24  The Schematic Model Schemas Categorization Stereotypes Lower Class Stereotypes The Schematic Model Applied to Counselling  26 26 27 28 32 34  Class and Psychotherapy Acceptance for Therapy Continuation in Therapy Perceptions and Expectations Resistance  38 39 40 43 44  iv  TABLE OF CONTENTS Testing Bias Adaptive Functioning, Presenting Problem, and Outcome  45 47  QUESTIONS/HYPOTHESES  53  METHOD  55  Design Independent variable = Client Socio-economic Status Pilot Study Participants Procedure Characteristics of Respondents Stimulus Material Dependent Variable Measures Data Analysis Summary RESULTS Respondents' Client Ratings and Evaluations Problem Evaluation Results Choice of Therapy, Presenting Problems, and Length of Therapy Choice of Therapy Explanations for Choice of Therapy Presenting Problems Length of Therapy Summary Client Characteristics Respondents' Personal Network and Relationship To Client Evaluations Respondents' Social Class Background Respondents' Levels of Education Respondents' Years of Experience Summary DISCUSSION Client Characteristics Results Findings by Total Sample Population Findings by Association Findings by Respondent Level of Education Findings by Gender  55 55 58 59 60 61 68 69 69 71 72 73 73 73 75 75 79 80 85 86 87 93 96 98 102 108 109 109 110 111 112 113  V  TABLE OF CONTENTS Findings by Respondents' Years of Experience Explanations for Choices of Therapy Issues/Presenting Problems Findings by Association Findings by Gender Suggested Length of Stay in Therapy Findings by Association Problem Evaluation Results Choice of Therapy Summary Implications Strengths and Limitations Suggestions for Future Research Conclusion  114 115 116 117 117 120 120 122 123 124 125 127 129 131  BIBLIOGRAPHY  133  APPENDICES  139  Appendix A: Therapist Decision-Making  139  Appendix B: Independent T-Tests Results of Respondents' Years of Counselling Experience  148  Appendix C: Independent T-Tests of Respondents' Evaluations of the Problem  149  Appendix D: Chi-Square Analyses of Important Issues  164  Appendix E: Client Characteristics - T-Tests for Independent Samples  234  Appendix F: Client Characteristics - Analyses of Variance  244  Appendix G: Problem Evaluation - Analyses of Variance  254  VI  LIST OF TABLES  Table 1 Table 2  Hollingshead's Occupational and Educational Characteristics of Five Socio-economic Levels  56  Student Vignette Ratings of Hypothetical Client's Social Class  58  Table 3  Demographic Characteristics of Respondents  62  Table 4  Total Sample Scores on Respondent Ratings of the Class III and Class V Client Respondents' Choice of Therapy by Association and by Total Sample Population  Table 5 Table 6 Table 7 Table 8 Table 9  74 76  Choices of Cognitive and Behavioural Therapies by Total Sample Population and by Respondent Association  77  Choices of Cognitive and Behavioural Therapies by Total Sample Population and by Respondent Association  78  Respondents' Choices of Most Important Client Issues Needing Address  82  Respondents' Average Recommended Length of Stay in Therapy Based on Client Social Class (N = 87)  86  Table 10  Effect of Client Social Class on Respondents' Ratings  89  Table 11  Significant Results of T-Tests of Client Ratings by Association Significant Results of T-Tests on Evaluations of Client  90  Characteristics by Respondents' Gender  92  Table 13  Respondents' Personal Network  94  Table 14  Client Characteristics Showing Significance By Client Social Class and Respondent Degree Rating Means For Motivation For Change and Prognosis Based On Respondents Years of Experience  Table 12  Table 15  100 104  vii  LIST OF TABLES Table 16  Mean Client Characteristic Scores by Respondents' Years of Experience  105  Vlll  LIST OF FIGURES Figure 1  Respondents' Social Class Background  Figure 2  Respondents' Years of Experience  97 103  Preface  Counsellors and psychologists enter their professions out of a sincere desire and commitment to provide caring, respectful help to their clients. As a result of their training and personal values, they are probably better equipped than most members of the general population to see clients as individuals and to view their problems in a non-judgemental, unbiased way. At the same time, however, these professionals live and work in our larger society, and it would be truly surprising if the stereotypes and prejudices of that society had no effect on these individuals and their work. The research that is reported in this document examines psychologist and counsellor bias in the area if client social class. It documents examples of bias, and, as such, must be a cause for concern to any therapist who honours the values of respect and client welfare. At the same time, there are several areas where the levels of bias could be interpreted as being reassuringly low. While longitudinal interpretations are beyond the scope of the current study, it is possible that this snapshot has captured some positive change; however, that is a question that remains for future research. My personal experiences from having grown up in a poor family, and my deep concern for disadvantaged individuals, is reflected in the choice of this research topic and, perhaps, in the perspective I bring to discussing my findings. While I acknowledge the possibility that my own perceptions may reflect some bias, I believe that our open discussion of these issues will only further a common desire to be of assistance to our clients.  X  Acknowledgements  First and foremost, I want to thank Dr. Beth Haverkamp for her patience, assistance, and support, and for her interest in the subject of social class in the counselling setting. Having her at the university provided me with the safety and support I needed to continue to hold on to my own beliefs and values. Secondly, I would like to thank my children, Roxanne, Tchad, Leon and Jonathan, and my brother Rick Hutchings for their own stories of courage, and for their belief in my ability to succeed. Next, I want to thank Jenifer Jones for her dedication of energy and hours in proof-reading the final copy and assisting with the appendices. I also want to thank her for her emotional support and taking on more of the housework during the last few months of putting this research project together. I also want to thank Fiona Graham and Janet Bianic for their support and encouragement over the past several years. Finally, to the Linedrivers who, without knowing it, helped keep me safe and sane on numerous occasions over the years, I send my love and thanks.  1 Introduction  A counsellor's primary task is to understand a client and his/her problems in order to encourage and/or facilitate change. While therapists are aware of the importance of and strive towards unprejudiced and honest dealings with every client, these interactions occur in an interpersonal context and, as such, are susceptible to errors and biases in perception. There is a considerable body of research that seems to indicate that people, including counsellors, are poorer judges of their interactions than they perceive themselves to be (Arkes, 1981). While we can often recognize perceptual errors in others, many of us remain oblivious to our own errors in perception. Therapists are no exception to this occurrence. For the purposes of this study, I chose to investigate the subject of counsellor biases that may occur before or during the counselling process, and are related to differences in client social class. The literature, while relatively sparse, clearly establishes that social class has been a powerful factor in how persons are perceived and judged by others (Garfield, 1986; Herr, 1989; Lorion, 1986). While the majority of counsellors comefrommiddle class backgrounds, the majority of clients who arrive for treatment are from lower class backgrounds (McCarthy et al., 1991). The environment from which the client and counsellor come, including cultural values, may be very different. In addition, we live within a society that upholds middle class values and attitudes as being the norm to strive towards. The values that we hold help create our personal attitudes towards people, places and situations (Herr, 1989; Lerner, 1973). These personal attitudes affect our beliefs about and our feelings towards  2 others. This being the case, the extent to which a majority of counsellors understand and relate to lower social class individuals is questionable. The dominant culture's beliefs, stereotypes, prejudices and judgements of a group will often impact in negative ways on members of the non-dominant culture (Herr, 1989; Morris & Williamson, 1989). Research in the area of schema and, more importantly, stereotype formation and activation, suggests that membership within a particular target group works to prime or activate the group stereotype within the perceiver's memory. Once an individual is categorized as belonging to a particular group or category, individual characteristics and behaviour are evaluated in ways that support the existing belief or stereotype. Characteristics and behaviour that do not support the stereotype may be overlooked while behaviour that supports the stereotype receives special attention. When the socially defined stereotype consists of predominantly negative traits, the impact within a counselling perspective can be particularly significant. Since clinicians are not exempt from the cultural attitudes, beliefs and stereotypes that make up their own societal background, and initial evaluation is of particular importance within the counselling domain, detection and awareness (or lack of) of bias and stereotyping is of particular relevance. As stated by Herr (1989), "Poor people are not rich people without money. Their values, risk-taking, sense of self, sense of power, and focus on the past, present, and future are all conditioned by the environment in which they find themselves." (p. 152) In addition, by lacking a familiarity with and understanding of the client's value system, the counsellor's own values and intervention strategies may conflict with the client's. Therapists may label a client as resistant or unresponsive when, in fact, the  3  counsellor's own lack of societal and cultural awareness may contribute to create a situation where the client is inappropriately labelled and judged. Within the field of psychology, the focus has traditionally been on individual and intra-psychic influences on mental health. In recent years, the focus has expanded to include the impact of social and environmental factors on psychological well-being. While cross-cultural counselling, in particular, has taken on prominence within the psychological literature, social class appears to have a place within the research and counselling domains only in so much as ethnic and racial minorities are disproportionately represented in the lower classes (Pederson, 1981). This could lead readers to conclude that while social class is an important factor for cross-cultural counselling, it is not necessarily a factor to be considered when counselling non-ethnic minority members. Much of the existing research on social class has been carried outfroma sociological perspective. These studies have revealed that social class and social class background impact on the individual in a variety of ways including their life experiences and choices, self-esteem and self-worth, and on the values they hold (Coclough & Beck; Rosenberg & Pearlin, 1978; Rubin, 1976). The issue of social class appears to have received only limited recognition and study within the psychological literature. Psychological research has revealed a class bias in diagnosis and treatment, with lower and working class clients being more likely to receive more severe diagnoses, and less likely to receive talk-oriented treatment (Garfield, 1986). Epidemiological studies have revealed significantly higher rates of health-related problems and psychological disorder among the lower social classes (Frank & Mustard,  1994; Wilkins, 1988). In addition, a national study (Wilkins, 1988) indicates that factors directly related to social class such as education and income are strongly related to rates of disorder. Most of the psychological research pertaining to social class was carried out in the United States in the 1960s and 1970s. There has been little psychological research performed within Canada focused on social class. Attention to class has been especially sparse within the pastfifteenyears. Considering the economic decline within the past 1015 years, this appears to be a serious gap within the Canadian research area. In addition, a trend in recent sociological research has been to move away from using the term lower class, and incorporate a generalised term such as the disadvantaged, or subgroup-specific terms such as transient workers, and the homeless. While the term lower class has a negative connotation, and could be interpreted as perpetuating a stereotype, North America society has tended to view itself as relatively classless. We are rarely encouraged to define or articulate differences in terms of class, or in terms of the inherent power differences. For these reasons, I have chosen to continue to use the terms lower social class and lower socio-economic status throughout this research study. For this study I was particularly interested in examining how counsellor beliefs, attitudes and decisions influence a lower socio-economic status client's acceptance for and duration of therapy, and whether the counsellor's awareness of a client's socio-economic status impacts on how the client is perceived, evaluated, and treated. I investigated this question within an experimental design, using a random sample of psychologists and counsellors from across British Columbia.  5 Literature Review  The task of this literature review, is to examine what research pertaining to social class has been generated to date. Three broad areas appear to be of particular relevance. First, in order to develop a more realistic and less stereotypic view of the lower socioeconomic status client, I will attempt to shed light on the possible effects upon the individual of growing up and living within the lower social classes. Second, since counsellors perceive and understand their clients using the same cognitive processes that other individuals use in perceiving people, it is important to present a conceptual overview of the social cognitive processes involved with person perception and evaluation, with special focus on the development and maintenance of biases in the form of stereotypes. Thirdly, I will explore the relationship of psychology and social class as a significant area for the activation and maintenance of negative stereotyping. In summary, I will attempt to include studies which provide an overview of life in the working class, rudimentary information on the cognitive schematic model and stereotyping, as well as studies in the field of psychology that examine the client's acceptance into therapy, socio-economically affected dropout rates, therapist-perceived client attributes and therapist expectations of the lower class client, and outcome variables of therapy. Portrait of Life In The Working Class  To facilitate change, the counsellor must be capable of understanding and accepting the client. Failure to adequately recognize and respect social class differences may be of particular relevance within the field of counselling psychology. In order to be of greatest service to the client, the counsellor must be capable of putting aside socially  prescribed definitions and stereotypes of the working class and the poor in order to develop a clear understanding of the particular client and the contexts of his or her life. Various studies, predominantly from within the field of sociology, have revealed that class status and class background have an impact on individuals in a variety of ways, including their life experiences and choices, self-esteem and self-worth, and values and beliefs. In both the United States and Canada, higher incomes have been associated with higher status, power, and unlimited access to a variety of resources, while lower incomes are associated with lower status, less power, and restricted access to resources (Bullock, 1995). In this section I will attempt to elaborate on several life variables that may be effected by class membership. Life Experiences and Choices  Education. Rubin (1976), in her in-depth study of life in the white working class in America, provides a powerful insight into the effects of class on a person's opportunities, choices, and educational experiences. Rubin interviewed 50 white working class couples, and another 25 white middle class couples as a comparison group. She found that the working class participants had gotten married and had children at an earlier age than their middle class counterparts, requiring them to get jobs to support their families. While one might assume that the working class participants had the same life and educational opportunities as the middle class, and simply made different choices, Rubin (1976) stresses that the struggles and crises experienced in the working class families limit the alternatives they perceive and experience, and therefore the choices they make. While theoretically both the American and Canadian school systems are open and accessible to all, middle class children in fact have a head start throughout childhood (Lareau, 1987;  7 Rubin, 1976). Middle class children attend school having had adequate food, properly attired for the season and educational activities, having less daily disruptions (e.g. frequent moving, less health problems), more parental support, and more exposure to, information about, and opportunities for higher education (Lareau, 1987; Rubin, 1976). Laureau (1987), in her qualitative study of family-school relationships in white working-class and middle-class communities, found that while schools have standardized views of the acceptable and proper roles of parents in schooling, lower social class parents have less access to the educational, capital and cultural resources required to comply with teachers' requests for parental participation (e.g. money, time, parents' level of education, materials, personal connections, etc.). Guppy, Mikicich and Pendakur (1984) carried out research in order to systematically examine historical changes in Canadian educational inequalities based on the social class background of the students. Guppy et al. examined groups of birth cohorts spanning a forty year period from 1913 to 1952, using a total sample of population of 44,868 respondents. Social origin was operationalized using the parents' levels of education and father's occupation (which was collapsed into four main categories: 1) professional/managerial; 2) white collar; 3) blue collar; and 4) farmer. Parental education was based on three categories: on whether one parent, neither parent or both parents had completed high school. Results showed that the disparity in high school completion rates based on social origin has diminished over time, although significant disparities were still evident. Guppy et al. (1984) also found that, while the average years of education has increased for all social classes, the actual reduction in educational disparities across social  8 classes appeared significant only when the 1938-1942 birth cohort was considered. They suggest that the reduction of disparities evidenced at that time may be directly related to the educational reforms that occurred in Canada during the 1950s and 1960s. Because of theirfindings,they questioned whether the economic decline of the 1980s (and presumably the 1990s as well) might not lead back to a further retrenchment of educational disparities based on social class background, as was evident earlier in the century. Guppy et al. (1984) noted that significantly greater disparities based on social class origin existed at the university level, and showed only a modest trend towards reduction over time. However, in noting the greater levels of social class disparity at the university level, they stated that examining why the disparities tend to heighten at higher levels of education did not fall within the scope of their study. While their study did suggest that inequalities have moderately declined over time in the area of general level of education, they also stress that their study did not show a diminishment of the impact of social class on the acquisition of specific types of education that might yield more value to the individual. For instance, if college and undergraduate degrees become increasingly ineffectual for occupational and financial attainment, then professional and graduate degrees may become increasingly important as a means of intergenerational mobility for the lower social classes. Coclough and Beck (1986), carrying out a national longitudinal research study involving a sample of 5,671 American male high school students, suggest that the American educational structure reproduces social class and contributes to the maintenance of class-based inequalities inherent in its society. They make three major assertions. First, they assert that private schools, primarily accessible to the middle and upper classes, result  9 in the reproduction of advantaged class positions. Second, recent trends show that the poor, Black and other ethnic minorities, and less educated individuals, remain in inner city areas, while the more affluent tend to move to the suburbs. The differentiation of financial resources available between inner city and suburban schools means that more affluent schools acquire and maintain more resources than the inner city schools. Even though some schools designated as 'Inner City' may receive extra funding, schools in suburban areas remain ahead in fund-raising capacity, volunteer professional resources, space, and equipment (Colclough and Beck, 1986). Third, although curriculum tracking is considered to be ability based, standard intelligence tests, developed by a middle class education system, still may tend to reflect middle class white male perspectives, and therefore again provide white middle class children with a head start. In addition, Coclough and Beck (1986) note that past studies (Rosenbaum, 1976, cited in Coclough & Beck, 1986) have demonstrated that while tracking fosters the illusion of meritocracy, factors such as individual levels of motivation and ability have had only a limited effect on actual placement within a particular track. Coclough and Beck's (1986) study found that the majority of children placed in the 'manual' rather than the 'mental' track were from the working class, while the opposite was true for the middle class. A seven-year follow-up revealed that being placed in the college or vocational track had a significant influence on the likelihood of class mobility and class reproduction (Colclough and Beck, 1986). A significant limitation of this study, however, is its lack of generalizability to the female student population, as the study involved only male students. Rubin (1976) and Laureau (1987) noted that most of the working class families in their studies did not expect their children to attend college or university, and in  10 Rubin's (1976) study, this expectation was lower for daughters than for sons. While statistics show that Canadian students are becoming better educated, by 1991 studentsfromthe lowest social class in Canada were dropping out of high school at a rate 2.5 times that of non-poor families (Canada Council on Social Development, 1996). Work. By the age of 25 years, more than half of the working class men in Rubin's (1976) study had held an average of 6-10 jobs. Generally, these jobs were in blue collar positions such as construction labourer, assembly-line worker, or gas station attendant. Some left jobs because of low pay and poor working conditions. For many, the job changes were involuntary due to shutdowns, lay-offs, and industrial accidents (Rubin, 1976). Most blue collar jobs allow for less independent judgement, freedom, and autonomy than white collar jobs and offer few intrinsic rewards. Frequently, they entail a truncated career ladder and incur little social status and prestige. While some of the men at the higher end of the blue collar ladder felt a certain amount of pride and satisfaction with their jobs, they remained frequently dependent upon unions and striking for pay increases. The fear of unemployment and one's family doing without necessities, was a everyday fear among the working class men (Rubin, 1976). Because, traditionally, career has been the significant marker of a successful man, Rubin (1976) noted that many of the blue collar workers expressed a sense of failure and discontent with their life situations. Those who managed to secure more stable long-term positions expressed a sense of resignation to a situation consisting of stable yet stagnant long-term work. This resignation is very poignantly noted by Rubin: "Imagine the consequences to the shape and form of that human life. Imagine, too, an environment in which the same paucity of choices is the reality of most lives - no friends or relatives  11 around who see a future with plenty of possibilities stretching before them; no one expects very much because experience has taught them that such expectations end painfully" (Rubin, 1976, p. 163). By 1994, over 17% of Canadians (20% of all children) were living in poverty (Statistics Canada, 1995). Close to half of this number includes families and individuals who are earning wages that keep them below the poverty line (Statistics Canada, 1995). While in times of economic distress the middle-class will also suffer more instability and unemployment, the levels of poverty and distress are far more significant for those already living near the edge even in the periods of comparative economic stability. Leisure. Rubin (1976) found that relationships with family members were at the heart of working class social life, while activities such as dinner parties (almost nonexistent among the working class) were the central focus of middle class leisure life. While one of the leisure activities of the working class men in Rubin's study included going out to "have-a-drink-with-the-boys,"fittingneatly into one of the classic stereotypes of the blue collar worker in our society, Canadian statistics (Wilkins, 1988) report that frequent drinking is more common among the middle and upper income groups than among the poor. In addition, infrequent drinking (less than one drink a week) or abstention is most common among the very poor, those with little education, and persons whose first language is neither English nor French (Wilkins, 1988). Rubin found that the lack offinancialresources meant that leisure activities within the working class families included the children. Individual sporting activities, such as skiing and tennis, were much less popular among the working class, probably because of the associatedfinancialcost, and low-cost sporting activities such as bowling were far  12 more popular (Rubin, 1976). Stressful Life Events.  Several researchers have focused on the differences  between middle class and lower class individuals' experiences of, and reactions to, stressful life events and living conditions, as well as the frequency of such events. Belle (1990) proposes that low income and minority women experience more frequent, threatening, and uncontrollable life events such as crime and violence, illness and death of children, imprisonment of husbands, lack of adequate housing, food, clothing, and childcare, living in dangerous neighbourhoods, and everyday discrimination based on gender, class status, and race or ethnicity. Their everyday living involves enduring significantly higher stressful living conditions than their middle class counterparts. Dohrenwend (1973) surveyed 124 heads of households to examine whether lower and working class families experienced more stressful life events than middle and upper class families. The sample included men and women from a variety of religious, racial and ethnic backgrounds. Participants were divided into two categories of social class: those who had not graduated from high school, and those who had graduated high school or more. Using a checklist of events, Dohrenwend (1973) found that lower social class members and women were exposed to significantly higher numbers of stressful life events that produced high rates of change and instability in their lives. Her findings also indicated a positive correlation between stressful life events and levels of psychological distress (Dohrenwend, 1973). Rubin (1976) found that, while the middle class participants in her study would generally fantasize about being a child again, the working class participants would not. In fact, the dominant memories of the working class individuals tended to be ones of both  13 emotional and material pain and deprivation. Even in the families where the recollections were of a loving and stable home, the working class adults recalled at least periods of unemployment, poverty, and deprivation. Health. According to Frank and Mustard (1994), in their review of research focusing on determinants of health, virtually all research investigating health and its relationship to social class has found that health status is directly related to social class. Health status is generally best among the higher income groups and worse among the lowest income groups. Moreover, they found that a social class gradient exists for almost every major disease studied world-wide. As one moves up or down the ladder of social class, both health and length of life increases with upward movement and decreases with downward movement. In a longitudinal study spanning almost twenty years, the Whitehall Study (Frank & Mustard, 1995) followed the health of over 10,000 British civil servantsfromfour different occupational groups. These were: administrative, professional/executive, clerical, and labourers. Frank and Mustard (1995) note that what is significant in this study is that the obvious social gradient related to health was evidenced in a working population not faced with hazardous working environments, poverty, unemployment, or extreme affluence. Those lower down in the socio-economic hierarchy had a higher rate of deathfromcoronary heart disease, strokes, gastro-intestinal diseases, smoking and nonsmoking related cancers, accidents and suicides. The risk of heart attack was 2.5 times greater for labourers than for administrators. Age standardized mortality rates were 3 times higher for those at the bottom than at the top of the socio-economic ladder. While the study revealed that lifestyle issues such as smoking were strongly influenced by where  14 the individual was in the social hierarchy, and that those on the lower end of the scale were more likely to smoke, Marmot (as cited in Frank & Mustard, 1995) revealed that adjusting for factors such as cholesterol, smoking, and blood pressure reduced the social class gradient for coronary heart disease by only 25%. Moreover, the Whitehall study concluded that differences in medical care did not account for the startling difference in mortality linked to position within the work hierarchy. Through their review of the research, Frank and Mustard (1995) suggest that 1) the quality of support and interaction an individual has bears heavily on one's health and sense of well-being, and 2) that one of the dominant factors influencing health and wellbeing is an individual's sense of achievement, self-esteem, and control over one's work and life. This belief is also strongly supported by extensive reviews of health determinants world-wide carried out by the Canadian Public Health Association (1997). Moreover, this review (Canadian Public Health Association, 1997) and Mustard and Frank (1995) found that adverse physical (nutrition and housing) and psycho-social (social ties and social support) environments in early childhood have a significant negative effect on health, behaviour, competence and coping skills in adult life. Lower social class families are more frequently faced with a lack of adequate social support systems. While universal access to health care has existed in Canada since the early 1970s, the Canadian Public Health Association (1996) points out that it has had little impact on reducing health inequalities linked to socio-economic status. The Canada Council on Social Development (1996) points out that, among poor families in Canada, the incidence of low birth weight and premature birth is significantly  15 higher. They state that poor children are also at a greater risk of injuries, and are more likely to smoke and develop drug problems, than children from higher social class families. Results of a 1990 province-wide government study in Ontario (Canada Council on Social Development, 1996) found that teens in lower income families (less than $30,000 annually) were 1.8 times more likely to smoke than teens in higher income families (over $50,000 annually). Childrenfromfamilies in the lowest income levels are 1.7 times more likely than children in other families to have a psychiatric disorder, and die at a rate twice as high as childrenfromfamilies at the highest income level (Canada Council On Social Development, 1996). Lower income families are far more likely to live in over-crowded housing, experience more frequent and extended periods of unemployment, stressful family relationships and parental mental health issues. The inability to adequately provide for or improve future circumstances within the lower class families, in itself, produces increased levels of stress within the family. The ability to fulfil one's personal needs can create a sense of efficacy and well-beingfrequentlylacking for many lower social class families. Self-Esteem and Self-Worth Several researchers (Belle, 1990; Rosenberg and Pearlin, 1978; Rubin, 1976) have proposed that many working class individuals feel little control over their lives, leading to anxiety, depression and a negative sense of self. As previously mentioned, while some members of the working class may hold jobs that pay well, most of these jobs tend to have little job security, may be dangerous, and frequently lead to health problems. Consequently, many working class individuals feel constantly on the edge, and do not feel as though they have succeeded, even when they are earning a higher wage (Rubin,  16 1976). In addition, most of the semi and unskilled blue collar jobs are significantly lacking in occupational autonomy, self-direction and job complexity, areas consistently found in research (Gecas & Seff, 1989; Sennett & Cobb, 1972) to be positively associated with self- esteem. Those individuals without jobs are even more profoundly affected by a feeling of inadequacy, given that they live within a society that sees success as an individual matter with all people having a roughly equal chance at the rewards (Bullock, 1995; Morris & Williamson, 1982; Rubin, 1976). Rosenberg and Pearlin (1978) analysed data collected from a sample of 1,988 school students in grades three through twelve in the Baltimore area and 2,300 Chicago area adult residents aged eighteen to sixty-five. Schools were randomly selected based on median income of census tract and proportion of non-white students. Students were then randomly selected from within the schools. Children's self-esteem was measured using a six-item Guttman scale, while adults' self-esteem was measured using the 10-point Rosenberg scale. Social class was measured using the Hollingshead Index of Social Position (Hollingshead & Redlich, 1958) which includes levels of education, occupation and income to determine social class. Correlations were then computed between social class and each of the items encompassed in the two scales for measuring self-esteem. Results showed no difference in levels of self-esteem among children linked to social class. However, the older the individual, the lower the self-esteem and this correlated positively to social class, with self-esteem being lowest among the lower social class adults. Although results were significant, correlations were low. Problems with this study include the fact that both scales used to measure selfesteem had low numbers of items. In addition, it is possible that the instruments  17 themselves may not be an accurate measure for assessing the construct of self-esteem. However, the study did provide interesting information about the possible long-term effects of social class standing. Gecas and Seff (1989), in attempting to further delineate the relationship between social class and self-esteem, carried out a phone study involving parents of high school studentsfromfiveschool districts within Eastern Washington. The sample population was a subset of a larger study that had administered questionnaires to high school students within the five districts. For the phone study, 173 (67%) fathers in intact families with adolescent children agreed to participate. The mean age of the fathers was 46, and approximately half held blue collar and half held white collar jobs. Subjects were asked to rate themselves on a 12-item semantic differential, which was comprised of adjectives descriptive of high to low levels of self efficacy and self worth. Results of the semantic differential were then correlated with social class, education, and responses to questions relating to work conditions such as job complexity, job control, job routinization, job supervision, and job prestige. Results showed a direct significant effect of level of education on self-evaluations and self-esteem. Results also showed significant indirect effects of social class on self evaluations through the occupational conditions of control over job, routinization, and complexity of work. They found that, overall, the effect was stronger for self-efficacy than for self-worth. They concluded that this was not surprising when one considers that the workplace is a major context for access to and expression of efficacy. In jobs involving little control over one's work, low levels of complexity, and routinization, it is predictable that self-esteem would be negatively affected. Values and Beliefs  18 The values one develops are affected by social class membership. Class differences have been noted in social and political beliefs and voting patterns, in the characteristics parents value in their children, in education, in sex roles, and in emotional expression (Johnston and Ornstein, 1985; Rubin, 1976). Social and political ideology. Several research studies have found significant differences in socio-political beliefs linked to social class. Johnston and Ornstein (1985) make note of various empirical studies which concluded that individualsfromlower ranking occupations, less education and less income are more likely to support union movements, government economic intervention, increased spending on social welfare measures, and a general reduction in social inequality. They note that the research concludes that individualsfrommore privileged backgrounds, higher incomes, and higher occupational status are more likely to participate in politics and to support existing inequalities. These studies also found that the disadvantaged, on the other hand, were more likely to support social change, yet did not possess the political resources to bring about the equality. Johnston and Ornstein (1985), using data accumulated through a national Canadian sample survey involving 3300 personal interviews, attempted to systematically examine possible political ideological class differences. In their study, the social classes of each of the respondents was classified according to three differing although overlapping Marxist typologies and also by their occupation, occupational status, level of education, and income. The subjects were all asked to respond to questions dealing with workers' rights, social welfare issues, redistribution of income, distribution of power, involvement and  19 satisfaction with government, and the legitimacy of protest activities. Significant class differences were found towards trade unions, provision of social welfare benefits, and the redistribution of income on all three of the class measures in attitudes. Differences along class lines appeared stronger than using any other measure of stratification (e.g. income alone). The results also clearly showed that even though none of the class measures may be exact in themselves, and while the magnitude of the difference between the working class and the bourgeoisie (or middle class) may change depending on the issue, the working class (and lower class) remained consistently politically on the left in comparison with higher levels of class (Johnston & Ornstein, 1985). Interestingly, their research also found that additional schooling appeared to create results further to the right as level of education increased, although they had no explanation for this finding. While one might assume that higher levels of education tends to produce more liberal views of society and more support for societal change, Canadian studies indicate that increased levels of education appears to have a conforming effect in support for the dominant ideology and dominant institutions (Baer & Lambert, 1982; Johnston & Ornstein, 1985). Baer and Lambert (1982), using data collected from a Canadian sample of 3,288 persons all above the age of eighteen, found that the higher the levels of education: 1) the less the respondents supported spending on social services; 2) the less they felt there was too much of a difference between the rich and the poor; 3) the less they felt that the rich should pay a greater proportion of the tax bill; and 4) the less they felt that government has an obligation to provide jobs for the unemployed who want to work. The lack of positive support for changing the existing social inequalities gradually increased among  20 those individuals who had completed high school up to those holding doctorate and professional degrees. All results were highly significant at the .0001 level. Conversely, those individuals with less than high school completion (a variable of class) supported more funding for social services, more government sponsored jobs, higher taxes for the rich, and felt that the gap between the rich and poor was too great. Baer and Lambert (1982) also investigated the effects of parental occupation and education of the respondents and found no significant differences. The respondents' own level of education remained significant in every case. In observing possible differences based on language, Baer and Lambert (1982) also found that French Canadians showed more of a tendency to support egalitarian social changes, except for those individuals at the highest educational levels. Griffin and Okeneba-Sakyi (1993), in investigating causal attributions of poverty, found differences based on class background in the beliefs of the causes of poverty. Using a sample of 207 undergraduate students in Sociology at an American university, their analysis showed that, with all other independent variables held constant, those students comingfromworking class families were 40% less likely to attribute poverty to individuals' actions than those students coming from upper class families. Griffin and Okeneba-Sakyi (1993) suggest that further studies should investigate whether differences in attributional styles reflect socialization processes whereby attributions to individuals or groups are reinforced by learned schematic stereotyping. A limitation of their study is that working- class background university students are not necessarily representative of the working or lower classes. However, their research would appear to support previous studies that suggest more egalitarian and social effect leanings on the part of individuals  21 from the lower social classes. Parental Values. Rubin found that working class participants in her study tended to place greater value on those characteristics that reflect conformity, such as neatness and obedience to authority (Rubin, 1976). Conversely, middle class participants placed greater value on characteristics that reflect self-direction, such as curiosity and self-control. Thus, the higher the social class, the less value was placed on conformity and obedience, and the more was placed on independent thought and direction (Rubin, 1976). Kohn and Schoenbach (1993) analysed data from studies carried out in the United States, Poland, Ireland, Germany, Italy, Thailand, and Japan to explore whether certain parental values were limited to national or political boundaries. Earlier work by Kohn (1969), consisting of a national study in the United States involving a sample size of over 3,000, had revealed class differences in characteristics fathers valued in their children. The working and lower class participants had expressed a greater value for characteristics that reflected conformity, neatness and obedience. Middle class participants had placed greater value on characteristics reflecting self-direction and independence. Results of the international data analysis noted an underlying dimension of self-direction versus conformity in parental values. Further investigation of the studies in Poland, the United States and Japan noted a correlation of social class and parental values of self-direction versus conformity among both fathers and mothers for both boys and girls in the United States and Poland. Parents from the lower social class displayed a preference for conformity and obedience in their children, while the higher social classes preferred independence and self-direction in their children. In Japan, however, while the class-based correlations for boys resembled that of the United Stated and Poland, conformity was  22 considered a valued characteristic for girls in both social classes (Kohn & Schoenbach, 1993). A Canadian study by Pineo and Looker (1983), using a sample of 400 families from the Hamilton Regional Assessment lists, found similar patterns for higher values of self-direction among the white collar parents and lower values of conformity than among the blue collar parents. Pineo and Looker (1983) also noted that, on the average, Canadian parents tend to place a higher value on self-direction and a lower value on obedience to parents than do their American counterparts. In addition, Canadian parents tended to place a greater value on being a "good student." Pineo and Looker speculate that Canadians are more willing to cede authority over their children to outside agencies such as schools, and therefore see the responsibility for control of the child less exclusively that of the parents. While there are evident differences within the two countries on specific values, the overall tendency remains the same. The Canadian blue collar parents, although not as dramatically as the American blue collar parents, endorsed higher levels of conformity than the white collar parents. As Rubin (1976) points out, working class individuals usually work in jobs where the values of conformity to the rules (being paid to work, not think) far outweighs the benefits of stepping out of line. In addition, jobs for the working class tend to involve littlefreedomfor creativity and individuality. Sennett and Cobb (1972) point out that the limitedfreedomon the job can contribute to a sense of inadequacy and low self-esteem. Middle class careers, on the other hand tend to place greater value on individual thought and expression, which can enhance one's sense of self-value and dignity.  23  Education. Values regarding education also reveal some significant class differences. Rubin (1976) and Laureau (1987) found that working class parents felt that school should be strict, while middle class parents believed that it should be enjoyable and loose. Rubin (1976) suggests two alternatives for the class differences. On the one hand, the working class parents' own feelings of failure or inadequacy may stimulate fears of failure for their children if the children do not learn important academic skills. On the other hand, the working class parents may also have high fears that encouraging creativity and independence in their children will not provide them with the necessary skills to make it in the working class world, where conformity and following orders are the keys to any degree of success. Neither Laureau (1987) nor Rubin (1976) found any class difference in parental desire for their children to succeed. Both working-class and middle-class parents equally valued educational success, and wanted their children to do well in school. Laureau (1987) also found that both working-class and middle-class parents all saw themselves as supportive and helping their children to succeed educationally. However, the ways in which they promoted educational success differed. Working-class parents were much more likely to turn over the responsibility for their children's education to the school, while middle-class parents tended to see their children's educational as more of a collaborative and interactive effort. Laureau (1987) states that the lower-class parents' lower levels of education, lower occupational prestige with the teachers, and limited time and financial resources produces a situation within which lower-class parents are more apt to feel that the educational success of their children is better left in the hands of the professionals.  24  Sex Roles. Depictions of working class families in the media have typically portrayed working class men as macho and demanding, with relatively subservient wives (e.g. Archie Bunker; Homer Simpson). Rubin (1976), in her exploration of class differences in sex roles, found that middle class couples, while asserting an ideology of equality between the partners, were no more egalitarian in their behaviour than the working class couples in her study. In working class couples, the women openly used language acknowledging the power and authority of the husband. In contrast, the middle class women used language suggesting equality, yet the power differential within the relationships remained evident in behaviour. Rubin (1976) hypothesized that since middle class men have more power and authority in the work place than do working class men, their tendency may be to exhibit a less overtly authoritarian role within the family. Conversely, since working class men have relatively little power on the job, they may tend to fulfil their traditional male role expectations by asserting more overt power within the family. Emotional Expression. Several researchers have proposed that the value and emphasis on emotional expression varies based on class membership. A qualitative study carried out among a group of working class women from a Toronto Rape Crisis Centre revealed that emotional expressiveness was taught and valued in their families (Ignagni et al., 1988). By comparison, middle class individuals are taught to operate from the head, and to talk about feelings rather than expressing them. The working class women also reported that their expression of strong personal emotions such as anger or frustration made many middle class women uncomfortable (Ignagni et al., 1988). Both Cardea (1985) and Hughes (1987), in their personal narratives of their  25 experiences as white working class women, describe their emotional expression of anger as being socially unacceptable to middle class individuals and institutions. Both felt that, while the middle class may emphasize emotional awareness, the working class value emotional expression (Cardea, 1985; Hughes, 1987). However, Hertzberg and Eschbach (1982) and Hertzberg (1989) propose that working class individuals are less likely to express strong emotions. They suggest that working class individuals survive the experiences of trauma, exploitation and dehumanization almost inherent to living in poverty by remaining frequently disconnected from their emotions. They maintain that being "in touch" with one's feelings presupposes a level of self-acceptancefrequentlynot available for individuals who are societally labelled as inferior or unacceptable, and whose life experiences differ from traditional values and ideals. While being out of touch with one's emotions would frequently be labelled as dysfunctional, Hertzberg and Eschbach (1982) contend that not being in touch with feelings may be a functional survival skill for individuals recurrently experiencing oppression. As the above review indicates, class status and background can influence not only one's experiences, but also ones choices, values and one's beliefs about self and others. In the next section, I will attempt to explore conceptual factors and their possible impact on how lower socio-economic status clients are perceived, interpreted and evaluated.  26  The Schematic Model  Schemas  In examining possible counsellor bias based on differences in social class, it is important to consider the cognitive processes that may be involved. Our understanding of people, situations and events does not begin anew with each new instance we might encounter. Each time we encounter new people and situations, we bring with us "our past experiences, knowledge, beliefs, and feelings about similar situations and people" (Crocker et al., 1984, p. 197). In order to understand both oneself and others, information must be acquired, interpreted, and accessible (Leyens, Yzerbyt, & Schadron, 1994). One representation of how individuals acquire, store and use information is in the form of cognitive structures called schemas. A schema is an abstract cognitive knowledge structure, stored in memory, that represents an individual's general knowledge about a particular 'domain stimulus,' including the defining features, relevant attributes, and interrelations among the attributes (Crocker et al., 1988; Fiske & Taylor, 1984). Schemas help us to interpret, organize, and integrate new information. Through the process of categorization, schemas simplify the encoding, storage and retrieval of relevant information, and shorten the time it takes to both process information, and to solve problems (Crocker et al., 1984). Schemas also function as an information filter in that information considered as irrelevant may be ignored or forgotten, while information interpreted as relevant to a particular schema may be integrated. When a perceiver is faced with information incongruent to his or her individual  27  schemata, the response may be one of assimilating the new information to fit within the schema, overlooking the new information, or accommodating the new information through "modifying or altering the schema in response to the demands of the environment" (Crocker et al., 1984, p. 198). Individuals may possess well developed schemas for particular situations, individuals or groups, or no schema at all, depending on the situation and the past knowledge and experience of the particular perceiver. Maturing schemas evolve and change with increasing experiences to which the perceiver may be exposed. The more information is acquired, the more developed the individual's schematic structure may become (Crocker, Fiske, & Taylor, 1984). While schemas may change through exposure to information that does not fit the particular schema that the perceiver or group possesses, a remarkable number of studies have pointed to the fact that although schemas do change, they can also be highly resistant to change (Crocker et al., 1988). In fact, Crocker et al. (1988) have noted that schemas can frequently "bias and distort the encoding, retention, and retrieval of schema-relevant information..." (Crocker et al., 1988, p. 198). Categorization. Integral to the understanding of the schematic model is the concept of categorization. Different pieces of incoming information may be integrated to form a category; subsequent category cues then activate an existing schema about a specific kind of person (e.g. politician), group of people (e.g. women) or situation (e.g. birthday party). Categorization simplifies the cognitive process by summarizing all of the features contained in one category under a particular title or name (Leyens et al., 1994), shortening the amount of time needed to understand or interpret the object of perception,  28 as well as providing meaning and familiarity to it. For instance, if we hear that a particular person is a long-distance runner, we have a certain idea of aspects or attributes entailed within the category and we have certain expectations of that person. We may assume the person has developed stamina, exercises regularly, and probably eats well. This constitutes our schema category of "long-distance runner." Categorizing provides us with a means of managing a myriad of information. It helps to make the environment more understandable and predictable by allowing the integration of new information with older information. In addition, when gaps occur within our schematic structure, inferences drawn from the schema are used to fill in the missing information. Contradictory or ambiguous information may be interpreted in ways that allow for its integration within the existing schema (Leyens et al., 1994). Stereotypes Stereotypes may be seen as a particular type of social role schema that organizes one's knowledge and expectations about other people who fall within certain socially defined categories. Stereotypes involve socially shared beliefs about personality traits and behaviours of specific groups of people (Fiske & Taylor, 1984; Leyens, Yzerbyt, & Schadron, 1994). As with schemas, stereotypes help simplify and organize information, and assist in the sorting and remembering of details (Leyens, Yzerbyt, & Schadron, 1994). While cognitive explanations of stereotyping stress the important function of stereotyping in thinking and communication, stereotyping holds a negative connotation (Leyens, Yzerbyt, & Schadron, 1994). Stereotyping groups and individuals can lead to perceptual distortions of them because there is no assurance that the content of the schema is accurate. Implicit in the concept of stereotype is the fact that certain groups of  29 individuals are negatively interpreted and evaluated. By stereotyping individuals, we perceive and judge an individual as interchangeable with other members of a particular category or stereotype. The individual is then expected to have certain attributes, behaviours, ,and standards based on their membership within the category, and individual differences can be overlooked or ignored (Leyens, Yzerbyt, & Schadron, 1994). Stereotypes frequently favour one group over another (Fiske & Taylor, 1984; Jones, 1988). In North American and European society, men are generally favoured over women, Whites over Aboriginals, Blacks, Hispanics, and other racial and ethnic groups, and the middle and upper social classes over the lower social classes. Expectations that members of certain groups will be more successful due to internally based attributes are significantly higher for the members of the favoured groups (Jones, 1988; Morris & Williamson, 1988).  For instance, studies have shown that when a man and a woman  perform exactly the same behaviour, a man's performance may be evaluated more favourably than a woman's (Foshi, Lai & Sigerson, 1994). The same is true of evaluations of individual capacity for change and levels of mental health based on membership in a particular socio-economic group (Frank, 1994; Sutton & Kessler, 1986). Stereotyping also impacts on the value assigned to specific tasks. Tasks viewed as appropriate for men are more favourably valued and perceived as more difficult than tasks usually designated as appropriate for women. This same upgrading and downgrading occurs for class related job occupations as well (Morris & Williamson, 1988; Rubin, 1976). Causal attributions for performance are also important and may be associated with a stereotype. The expectations and perceptions of favoured or "in-groups" are more  30  positive than those of unfavoured or "out-groups." When individuals behave according to expectations, their behaviour is attributed to stable or internal causes; when individuals behave inconsistently with prior expectations, their behaviour is attributed to unstable or external causes (Fiske and Taylor, 1984; Morrow & Deidan, 1992). Consequently, when favoured or in-group members succeed at tasks, their behaviour will be attributed to internal, stable causes, while when out-group members succeed, the behaviour will more likely be attributed to external causes, or the individual's behaviour may be perceived as exceptional and not representative of the group's usual behaviour (Fiske & Taylor, 1884; Morris & Williamson, 1988). Causal attributions can reinforce negative stereotypes by offering explanations of both stereotypic and counter-stereotypic behaviours that match the original stereotypic expectation. Behaviours which fall outside of that which is considered usual does not necessarily change the stereotype, but is simply perceived as an unstable or external event (Fiske & Taylor, 1984). Studies have shown that perceptions of out-groups show much less variability and complexity than perceptions of in-groups. One's own multiplicity of experiences and interactions with members of one's own groups produces a more varied view and understanding of those groups. Conversely, fewer interactions with members of outgroups allow for perception of less variability and complexity. Because out-groups are perceived as less variable and complex, individuals tend to make inferences about outgroup members based on little information. When a person is perceived as belonging to an out-group schema, the fit of the individual within the stereotype of the out-group is seen as being particularly tight (Fiske & Taylor, 1984).  31 In addition to variability and complexity, categorizing someone as an instance of a particular schema slants perception of what the person does. An analogue study by Sutton and Kessler (1986) found that the behaviour of lower SES (socio-economic status) clients was evaluated as more dysfunctional than the same behaviour of middle SES clients (Sutton, 1986). Perception of out-group members' behaviour is not only less variable and less complex, but more negatively perceived than the same behaviour by in-group members. (Fiske, 1984; Sutton, 1986). Stereotyping also tends to shape the perceivers' recollection of the individual's past behaviour and background. Fiske and Taylor (1984) describe a study in which a later revelation that a particular person was gay caused the perceivers to remodel and reconstruct memory so that factors were interpreted as leading up to the person's sexual orientation, and new factors were perceived that had not been obvious before. The retrieved information was moulded to fit the socially prescribed stereotype of the outgroup member. Research (Devine, 1989) has shown that schema-consistent information is remembered and favoured over schema-inconsistent information. Devine (1989), in a series of three studies, examined the effects of automatic and controlled components of cultural stereotyping. Using a commonly known stereotype in the United States, that Blacks are aggressive, Devine found that stereotypes are automatically activated in the presence of members of the specific target group. Even those White subjects who had been classified as 'non-prejudiced,' through their responses to the Modern Racism Scale, evaluated behaviours of others in stereotype-congruent ways when they were not capable of consciously monitoring the activated stereotype (Devine, 1989). Devine (1989)  32 suggests that, since individuals are frequently exposed to negative stereotyping, they may also be involuntarily exposed to automatically activated stereotypes, without conscious awareness, and that conscious personal monitoring may be a necessary component of counteracting negative stereotyping. Lower Class Stereotypes Leahy (1981), in a study of children ranging in age from 5-18 found that with increasing age there was a significant tendency to view the rich and poor as differing both in physical characteristics as well as in terms of being different kinds of people. As age increased, the descriptions increasingly involved perceiving the poor as lacking in ability and lacking in effort to change their circumstances. Leahy (1981) also noted that uppermiddle-class children were more likely to describe the poor as possessing negative personality traits, while poor children were more likely to describe poor people as worrying about having very little money. One of the earliest studies (Gough & Heilbrun, 1980) using the Adjective Check List to investigate the subjects of both class and race, asked black and white American college students to select, from a list of 85 adjectives, the ones they believed most descriptive of upper-class white Americans, lower-class white Americans, upper-class black Americans and lower-class black Americans. The most notable finding of the study was that the social class of the group influenced the choice of descriptors much more so than did race. The most frequently chosen adjectives for both upper-class white and black Americans, chosen by both white and black students were: intelligent, ambitious, industrious, neat and progressive. Both the white and black lower-class groups were  33 described as lazy, loud, ignorant and dirty. No specific traits emerged to describe the groups as a whole based on race (Bayton, McAlister, & Hamer, 1956, cited in Morris and Williamson, 1982; Gough & Heilbrun, 1980). Morris and Williamson (1982) provide a review of contemporary images of the lower class and poor that continue to reflect negative stereotypes based on social class, occupation, and education. The poor are frequently portrayed as being destitute because they share and pass on to their children a set of defective behaviours, values and personality traits. These supposed traits include laziness, inability to delay gratification, lack of respect for and interest in education, unwillingness to work, dishonesty, and sexual promiscuity combined with a disinterest in or ignorance about birth control (Ehrenreich, 1987, 1990; Sullivan, 1989). Bullock (1995), in her review of the research on social class, found that middleclass perceptions of welfare recipients included that they are typically dishonest, dependent, lazy, disinterested in education, and promiscuous. Single-parent women on welfare were typically stereotyped as devaluing the two-parent family, as having larger families in order to collect more welfare, and as being sexually promiscuous. The stereotype of the working-class man, typified in television series such as Archie Bunker, and more recently, Homer Simpson, portrays them as patriarchal, aggressive, racist, dishonest and slightly stupid. Common themes in movies tend to emphasize story lines suggesting love conquering all in poor girl/rich boy stories such as Pretty Woman, or rags to riches story lines such as in the television series The Fresh Prince of Bel-Air. A plethora of movies and television series suggest that many individuals succeed through intelligence, persistence and hard work, suggesting that the  34 lack of these qualities causes the resultant poverty among the lower class (Bullock, 1995). Few movies or sitcoms ever tend to portray the external causes of poverty and class systems such as lack of opportunity, an unequal education system, lack of access to material, financial and human resources, lack of job opportunities, lack of political power, lack of understanding of social class, and various forms of bias. North America has tended to view itself, until recently, as a relatively classless society. We are rarely encouraged to define or articulate differences in terms of class. The opportunity for less than a conscious awareness of class and the implicit stereotyping that goes on can allow for members of the lower class to simply be seen in derogatory terms such as ignorant, lazy, impulsive or loud. Over the past two decades, much effort has gone into the recognition of biases based on a person's gender, race or ethnicity. In a society that frequently denies the existence of a class structure, class bias may be a much more insidious problem. Differences from the middle class in-group are frequently viewed as individual deviances from the norm or individual failure. While the stereotype may automatically arise in the presence of a lower socio-economic status individual, the perceiver may not necessarily be aware that he or she is perceiving, interpreting and evaluating the individual through the biased stereotype of lower class. This may be equally true of counsellors, who are predominantly members of the middle and upper classes (McCarthy et al., 1991). The Schematic Model Applied to Counselling In applying the schematic model to a counselling setting involving lower SES clients, it seems apparent that the possibility of errors of perception, interpretation and evaluation are high. Most counselling therapists do not come from a lower class  35 background. Schematic stereotypes appear to be automatically activated in the presence of out-group or target members (Devine, 1989). Stereotypes tend to contain simplified and at times erroneous perceptions and interpretations of out-group members. The fit between the individual members and the stereotype of the group is frequently seen as being particularly tight, and schemas are resistant to change (Crocker et al., 1988). If, in addition to this, the counsellor has not developed an awareness of actual class differences and the life experiences of lower socio-economic status clients, the lower socio-economic status client may be entering a situation in which he or she will continue to be negatively perceived and evaluated (Hertzberg, 1990; Hertzberg & Eschbach, 1982). As previously noted, the typical stereotype of the poor in North America includes attributes such as irresponsible, lazy, uncontrolled, erratic, and an inability to delay gratification, etc. (Morris & Williamson, 1988; Muller, 1993). Newspapers and the media frequently portray the poor as welfare scam artists, or people who feel that society owes them a living (Morris & Williamson, 1988). It would seem illogical to believe that counsellors are immune to the societal stereotyping involving the lower social classes. The North American Work Ethic holds each individual responsible for his or her success or failure. This societal ideology implies that those who work hard will be rewarded with success, and that failure to reach one's goals and aspirations isfrequentlya result of personal deficiencies (Morris & Williamson, 1988). Traditional psychotherapy has focused more on individual responsibility for one's life, rather than including the importance of social context. This bias not only includes initial stereotypic reactions to clients, but can also influence the counsellor's choice of explanatory hypotheses as to the presenting problem and issue at hand, the direction of  36 therapy, the questions asked and unasked, and the counsellor's evaluation as to the appropriateness and success of the client's treatment (Smith, 1988; Turk & Salovey, 1988). Clinicians employ the same method of cognitive processing as other individuals. Initial intake contacts with a particular client, including presenting problem and physical appearance, may trigger schemas categorizing the client as a member of a particular outgroup (Smith, 1988). Studies show that, at intake, lower SES clients have been frequently deemed less acceptable for therapy and are more likely referred for psychotropic medication than middle and upper class clients (Garfield, 1986). In assigning responsibility for events, counsellors are more likely to attribute an individual's problems and levels of distress to internally based personality traits, while the client may attribute his/her actions and distress to external factors.  As pointed out by  Morrow and Deidan (1992), "This bias may be especially potent for female and minority clients who often have legitimate claims of discrimination and may often face significant external stressors." The disagreement in origin of the problem may, whether verbalized or not, produce a situation where the client is negatively evaluated. In addition, a lower class client, feeling that the professional is alwaysright,may begin to believe that he or she is responsible for all of the problems that may beset him or her, producing increased levels of guilt, stress and low self-esteem (Hertzberg, 1990; Morrow and Deidan, 1992). Stereotypes of the lower social classes may produce biased counsellor perceptions of a client, while excluding individuating information. As pointed out by Fiske and Taylor (1984), once an individual is categorized into a particular category, features attributed to the stereotype may be attributed to the client, new client information and actual client  37 attributes may be disregarded or overlooked, and category-consistent information may become salient. Research (Fiske & Taylor, 1984) shows that perceivers reconstruct reality in ways that support current beliefs about others. Since lower SES has been linked to higher levels of psychiatric disorder, it may be that attributes expressed by the client that fit certain disorders may also receive greater attention based on the client's SES. Studies have indicated that lower SES clients are categorized as having higher levels of dysfunction than middle class clients even when the categorization is based on the exact same behaviours (Frank, 1992; Sutton, 1986). Lower social class clients may appear distinctive in manner of dress, language, differences in levels of and extent of emotional expression, or choice of problem focus. Viewing the lower class client as distinct (i.e., different) may produce a greater focus of attention to expressions of attributes considered part of a lower social class client stereotype, and a lack of focus on expressions of attributes that do not fit the stereotype. Research investigating hypothesis testing has found that once a counsellor has adopted a particular hypothesis about a client, there is a significant tendency to perceive confirmatory information, while disconfirmatory information is overlooked or ignored. While previous research outcomes suggested that counsellors are generally unbiased in their questioning strategies to test client hypotheses, recent studies have found a strong confirmatory bias when investigating counsellor-generated hypotheses (Haverkamp, 1993; Strohmer et al., 1990), and no support for the previousfindingthat counsellors tended more towards the employment of a neutral hypothesis testing strategy when testing clientgenerated hypotheses (Haverkamp, 1993). As pointed out by Haverkamp (1993), previous testing for confirmatory bias had presented subjects with limited optional-choices  38 for hypotheses. Results of a strong confirmatory bias when self-generated hypotheses are available, may be reflecting an influence of pre-existing beliefs on counsellor choices and questioning patterns. Strohmer et al. (1990) noted a strong retrospective confirmatory bias in hypothesis testing. Even when client reports contained more disconfirmatory than confirmatory information, experienced counsellors remembered more of the hypothesis confirmatory information. Initial examination of research on schematic functioning, stereotyping and counselling suggests that there is ample room for bias to enter into the therapeutic interaction and process. Therefore in the final section of this literature review, I will focus attention on research that has specifically examined possible counsellor bias linked to client socio-economic status. Class and Psychotherapy Numerous studies carried out in both the United States and Canada have demonstrated higher rates of psychological disorders among the lower social classes (Dorenwend, 1973; Lorion & Felner, 1985; Wilkins, 1988). Reviews of the research also indicate a significant class bias in psychotherapeutic diagnosis and treatment (Garfield, 1986). Many of these studies were carried out in the 1960s and 1970s, when some attention was directed towards socio-economic status as an influencing factor in therapy. Little if any research has shown progress in eliminating class bias in therapy and, since the mid-seventies, research and education focused on socio-economic status has been minimal. Garfield (1986) and Lorion and Felner (1986) have suggested several areas where counsellor bias related to client socio-economic status might influence the therapeutic  39 process. These areas are: client acceptance for therapy, length of or continuation in therapy, counsellor perceptions and expectations of clients, and counsellor interpretation and evaluation of client levels of adaptive functioning, presenting problem and therapeutic outcome. Acceptance for Therapy Garfield (1986) reports that the overwhelming majority of the studies that focus on who gets accepted for therapy show, to varying degrees, a social class bias against acceptance of lower class clients. Garfield found that the more expert the therapeutic staff, the more selective the procedure for acceptance tended to be. Generally, this meant that clients who were more highly educated, perceived as more intelligent, more verbal and more motivated, were more frequently accepted for therapy. Kadushin (1969), in a study of the different kinds of clinics in New York City, concluded that social class was the most important feature distinguishing the applicants to the various clinics, and the more traditionally minded (orthodox psychoanalytic movement) a clinic was, the higher the social class of its accepted applicants. Hollingshead and Redlich (1958), in their classic New Haven study of social class and psychotherapy, found a significant difference in the services offered to clients based on social class. Long-term psychoanalytic treatment was offered mainly to middle and upper class clients, while more inpatient and drug therapy was offered to lower class clients. This held true even in state-supported mental health clinics offering reduced rates for treatment. While Garfield (1986) noted a tendency for therapists to perceive lower socioeconomic status clients as more apt to refuse therapy when offered, Garfield found only one study supporting such a belief, and concludes that, because of the lack of research in  40 this area, results are inconclusive. Continuation in Therapy Garfield (1986) reports that while many studies report a positive relationship between client education and length of stay in therapy, several reports have shown no difference at all. Garfield found some evidence that suggests that the lack of agreement between studies may be due partially to study factors such as pre-screening and acceptance procedures and the administration of drugs along with treatment. Garfield points out that, 1) where screening procedures are most stringent, dropout rates tend to be lower, but the samples tend also to be biased in favour of better educated clients; and 2) when administration of drugs is concurrent with therapy, dropout rates for all socioeconomic classes are lower. Several literature reviews have noted that dropout rates are significantly higher for lower class clients than for middle class clients. Berrigan and Garfield (1981) found no correlation based on age or sex of the clients, but a significant correlation between socioeconomic status (using the Hollingshead Index of Social Position) and premature termination. They found increasing proportions of dropouts as social class decreased, with a range of zero in Class I (highest social class) to 50% dropout rates in Class 5 (lowest social class). Furthermore, Class V patients tended to miss more scheduled appointments than any other socio-economic group. Edward Beckham (1992), in an attempt to identify characteristics of dropouts, examined four possible predictor variables. These were 1) patient attitudes about the nature of psychological disorders and psychotherapy; 2) practical difficulties for patients attending therapy; 3) patient's views of the therapist's ability to relate to the patient, and 4)  41 social class. The study involved 93 applicants accepted for treatment at a mental health clinic. Applicantsfilledout intake questionnaires, Cause of Illness Inventories, and the Barrett-Lennard Relationship Inventory (which measures the patient's initial impression of the therapeutic relationship). The only significant differences found were that family income was higher for the non-dropouts (perhaps indicating less practical problems usually associated with higher levels of dropouts), and a tendency for dropouts to have initially seen their therapists as less warm, empathic and genuine. This would appear to show that the patient'sfirstimpression of the therapist is very important. While Beckham makes no link between lower family income levels and initial impression of therapist's ability to relate, it seems possible that these may be connected even though general scores on socioeconomic status and early termination were not. Lower class individuals experience significantly higher numbers of stressors in their lives than the middle class, and frequently on a daily basis (Herr, 1989). The prevalence of psychological disorders is highest in the most socio-economically disadvantaged segments of our society (Lorion & Felner, 1985). Yet, research shows that the average number of sessions for both male and female working class clients is much lower than that of middle class clients (Hollingshead and Redlich, 1958; Garfield, 1986). In fact, McCarthy et al. (1991) state that the modal number of visits for working class individuals is one. Another study (Pettit, Pettit, & Welkowitz, 1974) investigating the relationship between values, social class and duration of therapy, found a relationship between the interaction of social class and the discrepancy between patient and therapist values and continuation. Pettit et al. (1974), using a sample of 249 clients at a moderate cost outpatient clinic, found a significant relationship between social class and all six factors of  42 personal values produced through the results of four separate values tests given to each client. On one particular factor (Authoritarian-Submissive versus Independent), high scores on 'respectful of and submissive to authority' on the part of the lower SES clients in combination with low scores on 'respect for independence' on the part of the therapist correlated with continuation in therapy; the greater the discrepancy, the longer the duration of therapy. No such discrepancy existed for middle and upper SES clients in relationship to continuation. Pettit et al. (1974) found that when the interaction of this particular factor was taken into account, there was a social class effect on continuation, with lower SES clients remaining in therapy for shorter durations. In another study (Brill & Storrow, 1960), where acceptance for psychotherapy related positively to social class status, clients were also evaluated as to their 'Psychological Mindedness' (understanding of and readiness for therapy). Low social class was found to be significantly related to low estimated intelligence, a tendency to view the problem as physical rather than emotional, a desire for symptomatic relief, lack of understanding of the psychotherapeutic process, and a lack of desire for psychotherapy. It is important to remember that these evaluations were not client self-evaluations but intake interviewer evaluations. In addition, the intake interviewer had less positive feelings for lower-class patients and saw them as less treatable by means of psychotherapy. Brill and Strorrow conclude by stating that thesefindingsseem to suggest some form of interaction between the attributes and expectations of lower class clients, and the attitudes and interpretations of middle-class therapists. While they do not go so far as to strongly suggest therapist bias, they indicated that it is a significant possibility. Perceptions and Expectations  43 It has been shown that lower class clients are more likely to be perceived as emotionally disturbed than are middle class clients (Hollingshead & Redlich, 1958; Lerner, 1973; Sutton & Kessler, 1986). Hollingshead and Redlich's study (1958) evaluated lower socio-economic status patients to be more unreliable, impulsive and having difficulty delaying gratification. Therapists also sensed a lack of rapport with low-income patients, and perceived them to be hostile, suspicious and uncertain as to the appropriateness or efficacy of therapy. Lorion and Felner (1985) also mention that more recent studies continue to make these same attributions to lower SES clients. As pointed out by Lorion (1974) and Lorion and Felner (1985), such noted attributes are not based on direct assessment, but on subjective therapist assessmentsfrominferred client behaviour. Lorion (1974) carried out an investigation of treatment attitudes and expectations based on client social class. His sample included 90 applicants for outpatient treatment divided into six subgroups of white Class III, IV and V males and females matched on age, marital status and religion. Results on the Mental Health Attitudes Survey (used to measure attitudes towards seeking help), and the Treatment Expectations Survey, showed no significant effects based on socio-economic status or sex. Lower SES applicants showed no more negative pre-treatment attitudes or expectations than their middle SES counterparts. This being the case, it would appear that direct responses from applicants and clients show no more obvious negative attitudes than higher SES applicants. Frank, Eisenthal and Lazare (1978), in their study and review, were critical of the view that lower class individuals have treatment expectations that are inappropriate and different from those of other patients. Using an 84-item questionnaire, the researchers  44  obtained responses from 278 walk-in-clinic patients and found no marked social class differences in the kinds of requests for help desired. Class I through IV showed no differences at all while Class V showed only nonsignificant differences on such items as requests for social interventions, administrative help and psychological expertise. They concluded that social class differences in treatment disposition and outcome might be reflecting the attitudes and beliefs of middle-class therapists rather than the attributes or behaviour of lower class patients. Resistance. Presumed unreliability (Hollingshead & Redlich, 1958) or, as defined by the more psychodynamically minded, 'resistance to therapy' is supposedly witnessed in lower SES clients in higher frequencies of missed sessions, arriving frequently late, or bringing young children into the sessions. However, as explained by several researchers (Garfield, 1986, Lorion & Felner, 1985; McCarthy et. al, 1991) lower socio-economic status individuals are more likely to arrive late or miss sessions due to lack of transportation, unreliable transportation, or no money for transportation. They may bring their children into sessions because they cannot afford day care or because the care they can afford is unreliable. Women coming to counselling may miss sessions or drop out for fear of being beaten for sharing information that a partner feels is threatening to him. Families receiving counselling through government run programs may fear revealing things for fear of losing custody of their children. When factors such as these combine, a therapist may assume a client is resistant or unreliable when, in fact, the social context of his/her life puts constraints on his/her ability to be available and open up to the same extent as more fortunate individuals. Both Brill and Strorrow (1960) and Lorion and Felner (1985) found that lower  45 SES clients desired somewhat more direct intervention on the part of the therapist, and therapy aimed at symptom relief. Hollingshead and Redlich (1958) also felt that lower SES clients were disappointed in not receiving direct advice and guidance with their problems. As pointed out by Lorion and Parron (1985 in Lorion and Felner, 1986), this is not surprising considering the contexts of the lives of many lower SES clients: Poverty, if nothing else, is characterized by an endless series of unpredictable crises which demand constantly reallocating meagre resources from one necessity to another. Everything one owns is already at risk for needing repair, credit, when available, is expensive and short-term, and savings must always be diverted from what is desired to what is needed. The therapist who understands the daily decision-making necessary to survive economic hardship is likely to appreciate both the client's resourcefulness and insistence that treatment be quick and symptoms be addressed immediately, (p. 83-84) What may be viewed as impulsivity, or difficulty in delaying gratification, may be the reflection of a realistic need to get things done quickly in order to deal with the daily life crisesfrequentlythe norm for individuals living in the lower socio-economic classes. In fact, Lorion and Felner (1985) suggest that the practical problems inherent to living in poverty may outweigh all other factors in accounting for high dropout rates for lower SES clients. Testing Bias. There is an abundance of research that shows that growing up in the lower classes affects how people perform on tests of abstract thinking, tests of intelligence, and tests of academic achievement (Frank, 1994). The norms established to evaluate people's performance on psychological tests arefrequentlydeveloped through  46  pretesting on sample middle class or unidentified mixed classes of individuals. Ehrenreich (1990), in his research on the possible effects of social class on normative responses to TAT cards, points out that while the research hints to possible differences in the ways middle class and lower class populations may respond, individuals are evaluated against the standard norms which are frequently middle-class based. Ehrenreich's subject population included 70 second-year community college students, 35 of who were middle class and 35 of who were lower class. Class was determined using both the subject's own class standing and the family of origin standing. Five TAT cards were shown on screen for 20 seconds each. The subjects were then given four minutes to write stories on each card. The stories were scored for numbers and intensity of drive expressions, levels of defences used, patterns of dependency, and locus of control. Significant differences were found in two areas, those of locus of control and dependency. The working class subjects more frequently portrayed the principal character as having an external locus of control, while the middle class subjects more frequently described the principal character as having an internal locus of control. The working class subjects were also more likely to provide stories reflecting themes of dependency. Ehrenreich (1990) notes that, by aggregating all of the stories written, the working class subjects showed a slightly higher tendency to portray bad objects rather than good objects in their stories, and portray stories with more themes of danger than those of safety. While this would produce different normative responses than middle class populations, it would appear quite normal to expect these results as lower class individuals do experience more stress and crises in their daily lives.  47 Ehrenreich (1990) points out that his research is limited in that his subjects are all female college students. Lower class college students are not necessarily representative of the lower class population, and males may not necessarily react in the same fashion as females to the TAT cards. Frank (1994) has demonstrated differences in people's responsiveness to the Rorschach (a test to assist in determining psychopathology) based on socio-economic status. However, research has also demonstrated that the same Rorschach protocol has been evaluated as reflecting greater levels of psychopathology when the clinician believes the respondent is an individual from a lower socio-economic status than when the clinician believes the individual is from a higher socio-economic status. Since this again appears to be clinician bias, it would be important to investigate what are acceptable healthy responses to a variety of psychological tests in order to determine whether responses are evaluated based on class held beliefs about what is health and what is illness, or whether the tests actually measure objective criteria for healthy functioning. Frank (1994) suggests further investigation of the Rorschach based on socio-economic status. This suggestion would do well to be applied to much of the personality and psychological testing presently available. Adaptive Functioning, Presenting Problem, and Outcome  Eric Hillerbrand (1988), in a study including 163 randomly selected counselling files of university student clients which were divided into three class groupings (upper, middle, and lower class), and 21 counsellors who were either counselling psychologists, interns, or counselling psychology practicum students, found no significant differences among the clients in presence of clinical syndromes or client symptoms, level of  48 psychosocial stress, number of sessions attended, cancellations and no-shows, and premature termination. Some of these results may be partially due to the fact that student counselling centres tend to focus on short-term goal focused therapy rather than long-term psychoanalysis. In addition, because only three class groupings were used, working class background students were categorized into either the middle class or the lower class. A more adequate grouping would have been to provide clearer class distinctions allowing for a working class grouping. Furthermore lower socio-economic status university students tend to be a select group and are not necessarily a representative sample from the lower class. Results did show, however, that lower SES student-clients were rated on intake as more dysfunctional than middle and upper SES student-clients. A significantly higher proportion of the middle and upper SES clients were also rated by their counsellors as having reached their counselling goals at termination in comparison with the lower SES clients. In addition, concordance rates between the client and intake interviewer for identification of presenting problems were much lower for lower SES clients than for the middle and upper SES clients, with higher proportions of the lower class students perceiving their problems to be more vocational than personal. These three ratings (adaptive functioning, presenting problem, and outcome) were all subjectively based intake interviewer assessments. The only significant differences in this particular study, then, lay in areas involving subjective judgement and interpretation on the part of the intake interviewer. This would seem to support much of the research investigating errors of perception, interpretation and evaluation carried out by social cognition researchers (Devine, 1989; Crocker et al., 1988; Haverkamp, 1993; Strohmer et  49 al., 1990). A review carried out by Beutler (1981) found a consistent and strong relationship between similarity of clients' and therapists' beliefs and values and subsequent improvement in therapy. Therapists appeared to be more comfortable with clients who spoke the same language and were more similar to them. This supports social cognition research that suggests more positive evaluations and higher levels of acceptance of ingroup members (Fiske & Taylor, 1984; Jones, 1988). Evans, Acosta, Yamamoto and Skilbeck (1984) evaluated 29 therapists on their efficacy with lower-income and minority patients before and after attendance in an orientation program to increase therapists' knowledge of and sensitivity to lower income and minority patients and their concerns. Patients of oriented therapists reported higher levels of satisfaction with therapy, felt they were better able to handle their problems, and were more likely to return for therapy in the event of future problems. Lerner (1972) and Lerner and Fiske (1973) carried out two studies to examine possible client and therapist characteristics contributing to positive outcome in psychotherapy. For both studies, 30 consecutively accepted outpatients at a large statesupported outpatient clinic received therapy from 14 therapists of varying theoretical orientations. Of the 30 outpatients, 10 were men, 20 were women, 17 were black and 13 were white. Ages ranged from 16 - 57, with a median range of 32. In the first study (Lerner, 1972), 11 client factors including social class, severity of psychological impairment (assessed by both the therapist and by an independent diagnostic test), present social unproductivity, past psychiatric hospitalization, age, race, and factors from two scaling tests (Klopfer Prognostic Scale and the California Scale) were examined.  50  Results showed no significant relationship between these client factors and therapeutic outcome. Outcome was found to be related to therapist factors, with the most significant factors for positive outcome being a democratic attitude on the therapist's part, and a preference for working with severely impaired and lower class clients. In the second study, Lerner and Fiske (1973) chose to examine client personality traits that previous researchers had chosen as being indicators of good prognosis for therapeutic outcome. These traits were: low preoccupation with somatic complaints, low tendency to externalize blame, low suspicion and guardedness, low tendency to act out, high levels of introspection, high general ego strength, high sophistication regarding the therapeutic process, high verbal fluency, high motivation for change, high estimated intelligence, and moderate degree of experienced anxiety. Measures of outcome were gathered through 1) clients' ratings; 2) therapists' ratings, and 3) the Rorschach Psychological Functioning Scale (using blind raters) pre-therapy to post-therapy change scores. Lerner and Fiske's (1973) results showed no significant relationship between high scores on the good prognosis personality traits and positive therapeutic outcome on any of the three measures. Clients with many favourable attributes did no better than clients with very few favourable attributes. Furthermore, sums of the good client attributes for therapy were related to both high social class and to low levels of psychopathology. As Lerner and Fiske (1973) point out, "lower-class and severely impaired clients do tend to be significantly more guarded and suspicious, less sophisticated about the therapeutic process than their more socio-economically and psychologically fortunate brethren. In addition, they seem slightly more likely to emphasize somatic complaints, to externalize  51 blame, and to strike their therapists, on the basis of initial contact at least, as less intellectually impressive." (p. 275) However, there was no indication that lower class clients tended to act out impulsively or lack introspective ability. The authors point out that while some therapists state that their client preferences have nothing to do with social class, many of the qualities many therapists look for in evaluating a client's prospect for therapy are very much linked to social class. Lerner and Fiske's (1973) study, however, did contain several limitations. There was no analysis made to determine whether race, sex or age had any significant effects on the study results. The therapists' use of a variety of different theoretical orientations with the clients may also be viewed as another confound. In addition, the original sample number had been 45, but 15 had either dropped out or had not finished therapy at the time of data collection. It would have been interesting to analyse client characteristics for those who had dropped out, including socio-economic data, as their leaving may have produced skewed results for the remaining 30 participants. In 1986, Sutton and Kessler carried out a study involving a random selection of clinical psychologists chosen from the membership register of the 1980 American Psychological Association. The psychologists were asked to evaluate three hypothetical clients on seven scales. Three social class variations (Class III, IV and V) of the same case history were prepared and reliability established. The seven ratings included: 1) the client's prognosis; 2) the client's motivation to change; 3) the client's self-concept; 4) the severity of the client's disorder; 5) the therapist's own personal interest in treating the client; 6) the likelihood of using psychotherapy as the main modality of treatment, and 7) the likelihood of referring for medication.  52 On five of the seven variables, the Class V, or lower class client received the poorest ratings. The only two scores that the Class V client was rated higher on were severity of illness and likelihood of referral for medication. With the same case history, Class V clients were given a poorer prognosis, their self-concepts were viewed as lower, there was significantly less interest in treating them, they were less likely to receive psychodynamic therapy, and were more likely to be referred for medication. While Sutton and Kessler mention that, since lower class patients tend to perform poorly on clinical measures, it is possible that psychologists are using this, along with other social cues to effectively judge lower class patients. However, they argue that this does not explain the lowered personal interest in treating lower class patients or the tendency to refer them for medication. Sutton and Kessler concluded that poorer scores on the parts of lower class clients in comparison to middle and upper class clients' scores may be as much determined by therapist attitudes as they are by lower class clients' attitudes. Their study clearly showed some bias on the part of the therapists in their subjective interpretations and evaluations of lower SES clients.  53 Questions/Hypotheses  Research carried out to date indicates that lower social class individuals have at times been deemed less acceptable for treatment, had fewer outpatient visits, were treated more frequently with medications rather than psychotherapy, and were more likely to be negatively perceived and evaluated (Garfield, 1986; Herr, 1989; Lorion & Felner, 1986). Some of the research also appears to indicate that a significant portion of the bias is therapist related (Lerner, 1973; Lerner & Fiske, 1974; Lorion, 1974; Sutton & Kessler, 1986). Lorion and Parron (1985) suggest that therapists have various stereotypes about the lower class client. These stereotypes include descriptions of lower class clients as unreliable, irresponsible, impulsive, and hostile. Lorion and Parron (1985) also note that therapists described lower class clients negatively in terms of styles of dress, language patterns, attitudes towards work, general lifestyles, and dependence on the welfare system. However, much of the psychological research is outdated and most of it is within the American context. I am interested in examining, within a Canadian context, whether current research will continue to indicate a negative influence of client social class on therapist perceptions, evaluations and decision-making. More specifically, would there be evidence that client socio-economic status impacts upon therapists' acceptance of clients for treatment, on diagnosis, on prognosis, on the probability of referring for psychiatric assessment, on perceived client attributes, on choice of therapy offered and presenting problems, and on recommended length of stay in therapy.  54 My hypotheses are: 1) Therapists will evaluate a lower class client more negatively than they will a middle class client. 2) Therapists will be less likely to accept a lower class client for therapy 3) Therapists will offer shorter durations of therapy for a lower class client. 4) Since higher levels of education appear to have a conservative effect on individuals, there will be more negative and stereotyped descriptions and evaluations of the lower class client by respondents with higher levels of education. 5) Respondents who have higher levels of interaction with lower social class individuals will rate them less negatively than respondents who have little interaction with lower social class individuals. 6) Respondents' years of counselling experience will not significantly impact on ratings. 7) Due to a heightened awareness of gender biases and the need for inclusion of social context within feminist counselling, female respondents will produce less negative evaluations of the lower class client than male respondents.  55 Method  Design To examine and test my hypotheses, I chose to carry out an experimental field study based on the design of Sutton and Kessler (1983). Two short written vignettes representing intake interviews were prepared to present the case histories of two hypothetical clients. The two clients (and vignettes) were identical on all variables except for the variable of social class. In addition, twofictitiousclient intake information sheets were prepared. These contained identical information except for levels of education and occupations of both the client and his parents. Identical scores on results of psychological testing were also provided. Independent Variable: Client Social Class  Social class (or socio-economic status) was operationalized through the development of the two client vignettes and accompanying intake information forms illustrating a middle and a lower socio-economic status client. The independent variable consists of the two hypothetical clients, identical on all variables except for socioeconomic status and background, which was identified through a combination of level of education, occupation and parents' levels of education and occupations. The Hollingshead Two-Factor Index of Social Position (ISP) was the primary source used to develop the social class differences for the independent variable because it is the most commonly used instrument for measuring socio-economic status in research in psychotherapy. In Hollingshead's model, socio-economic status (See Table 1) is divided into five classes based on a combination of levels of education and occupation  56 (Hollingshead & Redlich, 1958). Briefly, Classes I and II represent the upper and uppermiddle classes. Class III represents the middle class. Class IV represents the working class, and Class V represents the lower-working class or poor. Individuals are classified according to their years of education and their (or their father's) occupational status. Developed during thefifties,Hollingshead's ISP was based on one family income and Table 1 Hollingshead's Occupational and Educational Characteristics of Five Socio-economic Levels Class  Occupational Level  Educational Level  I  Salaried positions in policy making executive level; private practice professionals  Professional degrees; A.B. level and beyond  II  Salaried positions in business and professions; minor professionals included  A.B. level or partial college  III  "Middle class" administrative, clerical, sales, technical, and semiprofessional positions  High school diploma  IV  "Working class" skilled and semiskilled manual occupations in unionized trades and industries  High school or technical school diploma with some below tenth grade  V  "Poor" semi-skilled and unskilled manual occupations nonunionized with irregular employment  High school diploma infrequent with many not completing eighth grade  Note. The socio-economic status levels are referenced in Hollingshead and Redlich (1958). Table from Sutton (1983).  57 occupation. Levels of education have also changed over the past 40 years in that, average levels of education now tend to be higher by several years (Guppy et al.; 1984). Therefore, education levels for both the middle and the lower class clients were adjusted upward by several years. Using the modified Hollingshead Two-Factor Index of Social Position (1957) and incorporating the ideas of Wright et al. (1982) and Cardachi (1975) on degrees of control and decision making, half of the vignettes described a Class III, or middle-class client from a middle-class background, with a Bachelor of Applied Science, who worked as a buildings inspector with a relatively stable work history. The other half described a Class V, or lower class client, from a lower class background, with a grade nine education, who worked as an unskilled labourer (blue collar) with an unstable work history. An abundance of sociological literature points out that education and occupation alone do not fully address the issue of the degree of decision-making and control one possesses over one's work - factors closely linked to one's standing within the social class hierarchy. Some individuals within the same occupation may have little control over their job situation, while others have high levels of autonomy and control. For instance, the occupation of carpenter, usually classified as working class, could be a long-term unemployed individual (lower class), a worker in a company (working class), a semiautonomous employee (any class), a manager (middle class), or a business owner (middle to upper class). Using a Marxist analysis of class, the works of Eric Olin Wright (Wright, Costello, Hachen & Sprague, 1982) and G. Cardachi (1975) on class structure have incorporated the concepts of control over investments, decision making, other people's work and one's  58 own work in their analyses of and research into class structure in America. In short, those with the least control comprise the workers (the lower and working classes), those with some control and decision making capability in their work situations would be the managerial group and semi-autonomous workers (roughly the equivalent of the middle and upper-middle classes), while those with high levels of autonomy and control over others and investments would comprise the upper classes or the bourgeoisie. The hypothetical clients were developed with this in mind. Pilot Study Initial pretesting of the client social class variable and the questionnaire were carried out through the participation of volunteer students attending three Summer graduate classes in Counselling Psychology at the University of British Columbia (See j Table 2). Students were asked to rate the client's social class as either upper, middle, Table 2 Student Vignette Ratings of Hypothetical Client's Social Class Student Rating Hypothetical Client middle class client lower class client  upper 1  middle  working  10  2 14  lower  unsure 1  1  2  working or lower class. Of a total of 31 students who participated, fourteen rated the middle class vignette and seventeen rated the lower class vignette. Of the fourteen students who rated the middle class client, 10 rated him as middle class (77%), 2 rated him as working class, one as upper class, and one was unsure. Of the 17 who rated the lower  59 class client, 14 rated him as working class, 1 as lower class, and 2 were unsure. Based on their judgements of the client's social class, I proceeded to modify the social class aspect of the client vignettes to further clarify the lower class client's status and background. The final client vignettes were reviewed by my thesis committee supervisor and three independent participants with 100% inter-rater reliability, classifying the vignettes as predicted. In response to participants' comments on the questionnaires, adjustments were also made to the demographic information and the semantic differential sections to further clarify responding procedures. Participants Participants were members of the British Columbia Psychological Association (BCPA) and the Canadian Guidance and Counselling Association (CGCA) within British Columbia. Project approval and assistance were requested and received from both associations. To ensure adequate representation, random sampling was carried out by the associations to choose 300 practising therapists from within British Columbia, selected from the two associations' membership mailout lists. Each randomly selected member from each of the two associations received a questionnaire package through the mail. Participation was completely voluntary. To encourage participation, each respondent was offered the opportunity to enter their names in a drawing for a $25.00 gift certificate to the restaurant of their choice. To ensure anonymity and confidentiality, small separate envelopes for the respondent's name and address were included with the questionnaire responses to be detached from responses and put in a draw box. Respondents were also provided with a request form to be mailed in separately, in order to receive results of the  60 study after completion. A successful return was judged to require approximately 100 responses. Procedure Three hundred psychologists and counsellors, representing the 150 randomly selected members from each of the two participating associations, were randomly distributed either a middle or a lower class client case history, with 50% each of the middle and lower class client case histories allotted to each association. The case history included a completed intake information form, results of psychological testing, and notes from an initial intake session. Each subject received a package containing only one of the two case histories, a questionnaire including Likert rating scales and short answer questions, a client characteristics semantic differential scale using adjectives noted in the both sociological and psychological literature as frequently used descriptors for members of the lower social class, a section linking respondent's personal relationships according to occupation, a demographic questionnaire, and preliminary information with instructions for responding (See Appendix A). Two to three weeks after the initial mailout, a followup letter was sent out, encouraging those who had not already responded to respond. Responding procedure involved reading the case history information and answering the attached questionnaire. Subjects were instructed not to turn back to read the case history again when answering the questionnaire. By manipulating the case history on one variable, that of client social class, one can then observe if there is a relationship between the client's social class and respondents' ratings, responses, and evaluations. After responding to the client information questions, the respondents were to fill in the Personal Relationships form, and lastly to fill in the demographic information section.  61 Of the 300 questionnaire packages mailed, 8 were returned stamped that the individual had moved with no forwarding address, 3 disqualified themselves because they were not practising therapists, one returned the questionnaire stating that he chose not to participate, and one had received the questionnaire from both associations. In all, 111 (37%) responded. Of the returned questionnaires, 56 contained responses to information on the lower class client and 55 contained responses to information on the middle class client. Characteristics of Respondents Table 3 presents descriptions of the sample population. Respondents from both of the participating associations were predominantly Caucasian and from middle to upper class backgrounds. All in all, roughly half of the respondents were female (N= 58) and half were male (N= 52). However, there were differences in the numbers of males and females who responded from within the two associations. From the British Columbia Psychological Association approximately 41% of the respondents were female, while 59% were male. From the Canadian Guidance and Counselling Association approximately 61% of the respondents were female and 39% were male. These numbers are roughly the inverse of each other. The average level of education among CGCA respondents was a Master's degree, and among BCPA respondents it was a doctoral degree. Most of the respondents from both associations had attained degrees from either Counselling or Clinical Psychology programs. More than 75% of the respondents were over the age of forty. Of the 111 respondents, 105 were white. No significant differences between respondent groups (based on the client's social class) were noted on respondents' age, gender, race, or degree obtained.  62 Table 3  Demographic Characteristics of Respondents CGCA (#=62)  BCPA (N=49)  Ethnicity  /  %  f  %  White  56  90.3  49  100.  Aboriginal  1  1.6  Asian  2  3.2  Other  3  4.8  Total  62  100.  49  100.  Gender  /  %  /  %  Female  38  61.3  20  40.8  Male  24  38.7  29  59.2  Total  62  100.  49  100.  East Indian Black Hispanic  (table continues)  63 Table 3 (continued) CGCA (N = 62)  BCPA (N = 49)  Highest Degree Obtained  /  %  Bachelor's  6  9.7  1  2.0  Master's  36  58.1  18  36.7  Doctorate  12  19.4  27  55.1  Other  1  1.6  1  2.0  Unanswered  7  11.3  2  4.1  62  100.  49  100.  Total: Program of Highest Degree  %  /  /  %  /  %  Counselling Psychology  27  43.6  18  36.8  Clinical Psychology  11  17.7  17  34.8  Educational Psychology  3  4.8  5  10.2  Counsellor Education  6  9.7  2  4.1  Social Work  1  1.6  12  19.4  6  12.2  No graduate degree  1  1.6  Unanswered  1  1.6  1  2.0  62  100%  49  100%  Other  Total:  (table continues)  64  Table 3 (continued) CGCA (N = 62)  BCPA (N = 49)  Respondent Age  /  %  /  %  30-35  3  4.8  3  6.1  36-41  5  8.1  6  12.3  42-48  21  33.9  13  26.5  49-54  18  29.0  14  28.6  55-60  7  11.3  6  12.3  61-66  7  11.3  1  2.0  67 or older  1  1.6  6  12.3  (table continues)  65 Table 3 (continued) CGCA (N = 62)  BCPA (N = 49)  /  %  Some grade school  6  9.7  Completed grade school  5  8.1  7  14.3  Some high school  11  17.7  9  18.4  Completed high school  19  30.6  17  34.7  Some college  4  6.5  5  10.2  Completed college  5  8.1  4  8.2  Some university  3  4.8  Undergraduate degree  6  9.7  1  2.0  1  2.0  5  10.2  Mothers' Education Level  %  f  No formal education  Some graduate work Graduate degree missing  2  3.2  (01)  (1.6)  (table continues)  66 Table 3 (continued) CGCA (N = 62) Father's Education  BCPA (N = 49)  /  %  Some grade school  6  9.7  5  10.2  Completed grade school  7  11.3  2  4:1  Some high school  11  17.7  7  14.3  Completed high school  14  22.6  9  18.4  Some college  5  8.1  6  12.2  Completed college  3  4.8  2  4.1  Some university  2  3.2  1  2.0  Undergraduate degree  3  4.8  7  14.3  10  16.1  9  18.4  (01)  (1.6)  (01)  (2.0)  %  /  No formal education  Some graduate work Graduate degree missing  (table continues)  67 Table 3 (continued) CGCA  BCPA  Total  /  %  /  %  /  %  0- 4  10  16.4  6  12.5  16  14.4  5- 9  18  29.5  9  18.8  27  24.3  10-14  12  19.7  11  22.9  23  20.7  15 - 19  12  19.7  8  16.7  20  18.0  9  14.8  14  29.2  23  20.7  61  100.0  48  100.0  109  100.0  Years experience  20 +  CGCA  BCPA  Total  /  %  /  %  /  %  owner  10  16.13  7  14.29  17  15.32  manager/supervisor  16  25.81  18  36.74  34  45.95  skilled professional  12  19.36  9  18.37  21  64.87  1  1.61  1  2.04  2  66.67  13  20.97  7  14.29  20  84.69  semi/unskilled blue collar  3  04.84  1  2.04  4  88.29  farmer  7  11.29  4  8.16  11  98.20  2  4.08  Father's Occupation  semi/unskilled white collar skilled blue collar  father deceased/missing  100.00  68 No significant difference was noted on respondents' numbers of years experience and client social class. Respondents to the questionnaires containing the lower class client had an average of 11.72 years experience, while respondents to the middle class client had an average of 13.50 years experience (p = .23). There was, however, a significant difference in the numbers of years experience based on association membership, with the CGCA respondents having, on the average, 10.5 years experience, and the BCPA respondents having an average of 15.5 years experience (See Mests in Appendix B). Both fathers' and mothers' average levels of education for respondentsfromboth associations was high school completion. While this was higher than the average for individuals attending high school in the 1930s and 1940s (Guppy et al., 1984), it is not surprising when one considers the education levels of respondent population. Stimulus Material The case history describes a client with symptoms of generalized anxiety disorder (See Appendix A for vignettes descriptions), as described in the Diagnostic and Statistical Manual of Mental Disorders (1995). These symptoms include, restlessness, feeling of being on edge, trouble falling and staying asleep, irritability, and worry and anxiety over at least two life circumstances. The client is described as a 34-year-old white male who presented himself at a counselling centre for help with marital problems. Personal intake information lists him as being the third of five children, whose father had left when the client was quite young, leaving the mother to care for and support the children. During the intake interview the client's behaviour is described as agitated and anxious. The client is presently unemployed and stated that he had carelessly spent most of his income for that week. He stated that he  69 and his wife had argued over money and he had become angry and broken several objects before hitting his wife. He also stated having high fears of losing his children, little hope that counselling will help him, and mentioned that he had been drinking excessively lately. Standard psychological testing showed elevations at the 80th percentile for anxiety, the 82nd percentile for depression, and the 71st percentile for paranoia. Dependent Variable. The dependent variables for this study are the subjects' written perceptions and evaluations of the client, as noted through responses in the form of Likert rating scales, short answer questions, and a semantic differential scale. Measures. The questionnaire consists of items designed to note therapists' perceptions of, attitudes towards, beliefs about, and evaluations of lower SES clients (See Appendix A for copy of questionnaire). In Part I of the questionnaire, respondents were asked to rate the client along six likert scales with seven point ranges. The client was rated on: 1) the severity of the presenting problem: from very mild to very severe; 2) client motivation to change: from very strong to very weak; 3) client self-concept: from excellent to poor; 4) client prognosis: from favourable to bleak; 5) the probability of referring the client for psychiatric assessment: from very high to very low; and 6) counsellor's level of personal interest in treating the client: from very strong to very weak. To prevent response bias, the polarities of the scales were randomized. The counsellors were also asked to select what type of individual treatment they might use with this client, what issues and problems they felt were most important to addressfirst,and suggested length of stay in therapy. The second part of the questionnaire was a semantic differential scale. The semantic differential scale was originally developed by C. E. Osgood (1969) in order to  70 examine cross-cultural polarization of attitudes. For my study, the respondents were asked to rate the hypothetical client on a series of opposing pairs of adjectives that appear on a seven-point scale ranging from "very closely describes client" at points seven and one, to "unrelated" at the midpoint of four. By choosing to use a semantic differential scale, it was possible to select adjectives that were more directly relevant to the study of social class bias. The adjectives chosen for inclusion were selected from opposing pairs of adjective lists used by Osgood (1960) and adjectives that had been previously noted in the literature to have been stereotypical descriptors of lower socio-economic status individuals and/or groups (Hollingshead & Redlich, 1958; Jones, 1982; Morris & Williamson, 1982). The semantic differential allows for an evaluative judgement of a given object by the respondent. The object in this case is the clientfromeither a middle or a lower social class. As in the case of the six initial rating questions, the polarity of the scales were randomized. Osgood et al. (1970; 1984) extensively studied the reliability for lists of opposing adjective pairs, and found test-retest studies for reliability to produce coefficients ranging from .85 (Osgood, 1984) to .93 (Osgood et al, 1970). While also considered by Osgood and others (1970; 1984) to possess a high level of face validity in comparison with other attitudinal instruments of measure, some researchers have suggested its use only in conjunction with other measures. My choice for inclusion of a semantic differential scale focuses on the importance of using more than one measure to test for possible bias. While Sutton and Kessler were able to note bias in their original work carried out in 1981,1 felt that close to fifteen years later, taking into account a greater awareness of studies noting bias in a variety of forms, it was important to use several measures of difference. The  71  semantic differential scale, while showing some overlap with the initial six likert rating scales, allows for investigation of whether the subjects' perceptions and evaluations of the client are influenced by specific stereotypical social class descriptors. Part III of the questionnaire asked subjects to check off types of relationships they have with individualsfroma variety of occupations, including individuals receiving longterm social assistance. The types of relationships listed were acquaintance, close friend, relative, colleague and client. This section is a modification of a question utilized by Tindall (research in process) in his investigation of characteristics of individuals participating in the environmental movement on Vancouver Island. My intention in incorporating this section was to investigate whether various forms of contact with lower socio-economic status individuals might have a positive impact on the subjects' perceptions and evaluations of the client. The final section, Part IV, was a demographic questionnaire that included information on the participant's gender, race, age, marital status, social class background, including information on whether their family had had to rely on public assistance at any time, both parents' and respondent's educational background, counselling experience, and present work environment (e.g. private practice, non-profit agency, university setting, etc.). Data Analysis. Since it is essentially the same case history, a comparison of the rating scales results according to client SES, made it possible to determine whether there was a relationship between a client's social class and counsellors' perceptions and evaluations. Statistical analyses in the forms of f-tests and ANOVAs were used to examine both the Likert rating scales and semantic differential evaluation results. MANOVAS  72  were used to examine results on both scales based on the combination of therapist's years of experience, education, and therapist's degree of interaction with lower SES individuals and client's social class. For ease of analysis and reliability, a rater was recruited for Part I, to examine and categorize client presenting problems as noted by the respondents. Using chi-square analysis, differences in respondent choice of therapy and frequencies of client issues linked to client social class was examined. Comparison of results based on association membership and gender were also investigated for possible differences. For statistical significance, I chose to use a cutoff level using alpha = .05, however, results up to alpha = .10 are discussed as possible trends. All statistical analyses were conducted using the SPSS-X statistical program. Summary The premise of the current study is that, if the lower socio-economic status client received less positive ratings, was found less acceptable for treatment, or was descriptively evaluated less positively, based solely on the difference in social class, it would provide support for the hypothesis that therapists' perceptions are related to social class bias, lack of social class awareness and/or negative social class stereotyping. The next chapter will examine the results of this researcher'sfindingsto determine whether there are any differences in therapist ratings, perceptions, decisions and evaluations linked to client social class.  73 Results  This study was developed to investigate possible therapist bias linked to client socio-economic status (SES). Previous reviews of the research have found a pattern of negative perceptions, evaluations, and treatment of lower social class clients. Questionnaire results were analysed by total sample population, by professional association, and by gender. To examine whether information on client SES had an impact on the therapists' judgements and evaluations of the client, analyses of variance and f-tests were performed on the six continuous variables evaluating the therapist's conception of the client's problem (hereafter referred to as problem evaluation) and on the impression of the client measured with 19 pairs of opposing adjectives that comprised the semantic differential scale (hereafter referred to as the client characteristics). In addition, chi square analyses were performed to examine possible relationships between client social class and type and frequency of participant responses to open-ended questions on aspects of counselling. Possible interrelationships between a variety of respondent demographic information and responses linked to client social class were also investigated. Each section will be followed by a short summary of results as well as a final summary at the end of this chapter. Respondents' Client Ratings and Evaluations Problem Evaluation  The six variables comprising the problem evaluation were severity ofpresenting problem; perceived client motivation for change; perceived client concept; prognosis; likelihood of referring clientfor psychiatric assessment, and personal interest in treating  74 the client. These variables were measured on a seven point Likert-type scale (See Appendix A). For the purposes of comparison, all seven variable ratings in Table 4 were arranged with 1 equalling the most positive rating, and 7 equalling the poorest rating of the client. Overall, respondents rated client self-concept as relatively poor, with means of 5.85 and 5.87, respectively, for the middle class and lower class client. Client means for severity of presenting problem also received rather high ratings at 4.79 and 4.57 for the middle and lower class client. Means for interest in treating the client fell below mid-range at 2.91 for the lower class client and 3.02 for the middle class client, indicating a higher than average interest in treating (where 4 represents the midpoint). Motivation for change, prognosis, and likelihood to refer the client for psychiatric assessment fell approximately mid-way for both hypothetical clients. Table 4 Total Sample Scores on Respondent Ratings of the Class III and Class V Client Class III  Class V  Univariate F-tests (#=1,111)  Client ratings  N  M  SD  N  M  SD  F.  Severity  55  4.79  .81  56  4 57  .83  1.832  .18  Motivation  55  4.35  1.22  56  4 21  1.32  .296  .59  Client Self-Concept  55  5.85  .93  54  5 87  .80  .009  .92  Prognosis  53  3.42  1.31  56  3 70  1.14  1.453  .23  Psychiatric Assess  54  3.54  1.67  56  3 18  1.93  1.09  .30  Personal Interest  54  2.91  1.44  56  3 02  1.60  .144  .71  P  75  In contrast to Sutton and Kessler's (1981) research, multiple analyses of variance (F = 1.343,/? = .246) produced no significant differences overall in participant responses linked to client social class for any of the problem evaluation variables examined by total sample population, by association, or by respondent gender (See Table 4 for individual analyses of variance by total sample population). Because of the exploratory nature of the study, independent /-tests were also performed (See Appendix C) comparing the responses by total sample population, by association and by gender. Results produced significance on only one variable. On the variable prognosis for change, female respondents of the Class V client predicted a less favourable prognosis than the female respondents of the Class III client (Ms = 4.04, 3.28, SDs = 1.14, 1.31 respectively) t = 2.34, df= 54, p = .02. Male respondents produced no significant difference on the variable of prognosis linked to client social class. Choice of Therapy. Presenting Problems, and Length of Therapy  The second section of Part I included 3 open-ended questions (See Appendix A) that asked the respondents 1) to describe the theoretical and/or treatment approach they would use with the client and reasons for their choices; 2) to indicate which problems the respondent viewed as most important to address first; and 3) estimated length of stay in therapy. Choice of Therapy. The most frequent choices of therapy among all respondents and for both hypothetical clients were cognitive (n = 59), behavioural (n = 53) and affective (A = 18). Table 5 provides a breakdown of choices of therapy by association and r  by total sample population. In all, 61% of the BCPA respondents chose to include the use  76 of a cognitive approach and 50% included a behaviourally based approach (n - 30 and 25 respectively). Of the CGCA respondents, 47% chose to include a cognitive approach, and 47% included a behaviourally based approach (n = 29 and 28 respectively). Of the 23 BCPA respondents who returned questionnaires based on responses to the middle class client, 16 or 70% stated that they would include a cognitive approach, and 12 or 52% stated that they would include a behavioural approach. Of the remaining 26 participants from the BCPA who returned questionnaires containing ratings and evaluations of the lower class client, 14 or 54% stated that they would include a cognitive and 13 or 50% would include a behavioural approach in dealing with this client. Of the 32 CGCA subjects who returned middle class client questionnaires, 15 or 47% included the use of a cognitive approach, while 13 or 41% stated that they would include a behavioural approach. Of the remaining 30 who returned lower class client  Table 5 Respondents' Choice of Therapy by Association and by Total Sample Population Choice of Therapy  CGCA  BCPA  Total  Cognitive  11  8  19  Cognitive-Behavioural  10  19  29  Cognitive-Affective  1  Cognitive-Behavioural-Affective  7  Behavioural  10  Behavioural-Affective  1  Affective  5  2  3 1 5  8 15 1  1  6  77 Table 6 Choices of Cognitive and Behavioural Therapies by Total Sample Population and by Respondent Association CGCA  BCPA  Total  Class III (w = 32)  Class V (» = 30)  Class III (w = 23)  Class V Class III Class V (w = 26) (« = 55) (« = 56)  Cognitive  14(47%)  14(47%)  16(70%)  14(54%)  31(56%)  28(50%)  Behavioural  13(41%)  15(50%)  12(52%)  13(50%)  25(46%)  28(50%)  questionnaire responses, 14 or 47% suggested some form of cognitive therapy, while 15 or 50% suggested some form of behavioural approach. In examining choice of therapy by gender, of the 25 male respondents of the Class III client, 52% (n = 13) chose to include a cognitive approach and 52% (n = 13) chose to include a behavioural approach. Of the 28 male respondents of the Class V client, 53.6% (n = 15) chose to include a cognitive approach and 42.9% (n = 12) chose to include a behavioural approach. Among the 31 female respondents who chose to include a cognitive and/or behavioural approach for the Class III client, 61.3% (w = 19) chose a cognitive approach and 42% (n = 13) chose a behavioural approach, while for the Class V client (N= 27), 48.1% (« = 13) chose cognitive approach and 60% (n = 16) chose a behavioural approach. As can be seen in Table 7, the male respondents chose a cognitive approach equally for the middle and lower class client (based on percentage of total numbers). However, they chose behavioural therapy slightly more frequently for the middle class  78 client than for the lower class client. Female respondents chose cognitive therapy more frequently for the middle class client, and behavioural therapy morefrequentlyfor the lower class client. Table 7 Choices of Cognitive and Behavioural Therapies by Total Sample Population and by Respondent Association Male  Female  Class III  Class V  Class III  in = 25)  (n = 28)  (w = 31)  (n = 27)  Cognitive  13  15  19  13  Behavioural  13  12  13  16  Class V  No other respondent differences linked to the client's social class were noted in the types of therapy chosen. Respondents tended towards a directive and structured approach with both the Class III and Class V clients. Of the 68 respondents from the total sample population (N= 111) who stated that their approach would be either structured or openended, 51 stated they would use a more structured approach (BCPA = 26, CGCA = 25), 16 stated they would chose an open-ended approach (BCPA = 3, CGCA = 13), and one stated the use of both a structured and an open-ended approach. Of the 64 respondents who noted either a directive, nondirective, or combination approach with their client, 49 chose a directive approach (BCPA = 26, CGCA = 21), 11 chose a nondirective approach (BCPA = 2, CGCA =11), and 4 chose the use of both directive and nondirective approaches (BCPA = 1, CGCA = 3). Several respondents from both client groups noted  79 that they felt this particular client would do better with a more concrete, task-oriented form of therapy. Explanations For Choice of Therapy. In examining respondents' explanations for choosing their approach with their particular client, a striking pattern emerged. While this data is qualitative in nature, it seems important to note. From among the BCPA questionnaire responses to the lower class client, comments implying judgement of the client's ability, competence, or intelligence included the following: "Possible structured, cognith^ehavioural ....[reason] He's probably not too bright." "His personal information profile does not suggest that one would get very far with subtle." "Structured and directive at onset, cognitive-behavioural methods. Why: I.Q. likely average to low average; likely not therapy minded; concrete thinker; low education; ...suspicious, paranoid tendencies likely to be exacerbated by ..." "Considering education level, sophistication of thinking ..." "I would approach Robert in a practical manner' what can be done to help you' manner. I would want an assessment of learning abilities and vocational counselling/training." "He would have more immediate benefit from doing tasks that effect change as opposed to verbal dialogue which would likely increase his anxiety and inferior position with the therapist." No such statements relating to low aptitude, low level learning capabilities or general intelligence appeared in the comments referring to the middle class client. Although the clients were the same in all aspects except for those defining social class, comments about the middle class client included less negatively stereotyped descriptive statements such as: "His 'style' and orientation seem more consistent with a structured ..." "Cognitive, as he would be more uncomfortable with a more 'feeling' or open ended  80 approach." Or comments such as: "Robert appears to be a bright, reasonably focused fellow", or "Client could readily understand the concepts, tasks, and exercises involved and would benefit readily, quickly." From the CGCA respondents, comments for the lower class client again included statements suggesting lower intelligence, or the need for intelligence testing: "Vocational aptitudes and interests - check learning disabilities training." "Structured, directive and behavioural -1 suspect his cognitive abilities are limited." For the middle class client, comments included: "Client would need to appreciate method in a practical cognitive sense..." "Because client is a Engineer by training and profession, I would use a quite structured, problem-solving, solution-focused approach." None of the respondents who returned the middle class client questionnaires with the same results on psychological testing, and the same presenting symptoms and problems as the lower class client, suggested intelligence, aptitude, or learning disability testing. Presenting Problems. The second question asked respondents to identify the problems and issues the respondent felt would be the most important to address first with this client. Table 8 lists the issues generated by association and by total sample population. Respondents were not provided with lists of issues nor were they given a limit on the specific numbers of issues they might choose to note. Issue groupings were then developed and refined, through the assistance of an independent volunteer rater, based on issues listed by the respondents. Independent categorization of a random sample of one-third of the questionnaires, for this question only, was performed by the volunteer rater. The individual recruited to  81  assist in the scoring is a 48-year-old female who presently works with individuals and groups as a career consultant. She is also an action-oriented trainer and writer. The rater was provided with a brief set of written instructions and score sheets (See Appendix D), and was asked to carry out two tasks: 1) to list the issues noted by the respondents into prearranged categories on the score sheets, and 2) note any way that the categories might be rearranged to be more accurately descriptive of the issues being noted. The results produced a rate of agreement between this researcher and the volunteer assistant of 92% on first scoring and 100% on the second scoring. The bulk of the difference on first scoring occurred between two categories, which were fear of losing his children, and fearfulness/paranoia. After a brief discussion, it was agreed to collapse the two categories into one on second scoring. Other very minor differences included missed issues and psychological wording that needed clarification for the assistant. As is evident is Table 8, respondents tended to provide slightly higher frequencies of issues for the middle class client than for the lower class client. For the middle class client (N= 55), there were 216 notations of presenting problems to be addressed, in comparison to 190 for the lower class client (JV= 56). The difference in numbers is predominantly related to the CGCA respondents, who generated 110 and 134 frequencies of issues for the lower and middle class client respectively. Among BCPA responses, there were 80 frequencies of issues for the lower class client and 82 for the middle class client. Where expected frequencies for specific issues were large enough, chi square analyses were performed by total sample population, by association, and by gender (See Appendix D). By total sample population, frequencies of five of the seventeen issues  82 Table 8 Respondents' Choices of Most Important Client Issues Needing Address BCPA  Issue:  CGCA  TOTALS  Class V Class III Class V Class III Class V Class II] (n = 26) (« = 23) (n = 30) (/i = 32) (w = 56) (n = 55)  alcohol abuse  11  8  11  15  22  23  anger management  8  7  9  8  17  15  anxiety  3  9  4  7  7  16  childhood issues  2  2  7  6  9  8  depression  7  6  4  8  11  14  family/relationship issues  5  5  8  7  13  12  family violence  7  10  9  21  16  31  finances/money spending  1  3  5  3  6  6  general health issues  3  4  3  3  6  7  mental health issues  6  5  4  2  10  7  1  8  1  8  2  feelings/mood fearfulness/paranoia  4  5  5  15  9  20  self-directed  1  1  3  5  4  6  self-esteem issues  4  5  8  10  12  15  suicide  3  3  1  4  4  7  unemployment  6  3  7  9  13  12  vocational assistance  2  1  7  9  1  other  7  4  8  9  15  13  Total  80  82  110  134  190  216  83 produced differences shown to be significant. For the middle class client, three issues were generated significantly more frequently. These were, with df=\, anxiety .Y (n = 23) 2  = 4.24, p = .04, family violence X (n = 47) = 7.84, p = .01, and paranoiaX (n = 29) = 2  2  5.38, p = .02. For the lower class client, two were generated significantly more frequently. These were coping with feelings/mood X (n = 10) = 4.08, p = .04, and 2  vocation X (n= 10) = 4.08, p = .04. The issues of both coping with feelings/mood and 2  vocation had expected frequencies in one cell each of less than five, however, with Yates continuity correction, there was still a probability of .09 that results were significant. A point of interest emerges when one separates out the frequencies of fear of losing his children (n = 13) from the issue of fearfulness/paranoia (n = 29). Of those who had noted fear of losing his children, 10 listings were for the middle class client (5 from BCPA respondents and 5 from CGCA respondents) and 3 were for the lower class client (all 3 from CGCA respondents). Among CGCA responses, with df=\, family violence X (n = 30) = 6.57, p = .01, 2  and fearfulness/paranoiaX (n = 20) = 5.6, p = .02, produced significant differences, with 2  significantly higherfrequenciesfor the middle class client than for the lower class client. Frequencies of coping with feelings/mood X (n = 9) = 7.50, p = .01, and vocation X (n = 2  2  9) = 4.81, p = .03, were significantly higher for the lower class client than for the middle class client. Although the last two issues had expected frequencies of less than five, the Yates continuity correction was .02 for mood and .07 for vocation. Among BCPA responses, with df= 1, thefrequenciesof one issue produced significance: anxiety X (n = 12) = 5.02, p = .03. BCPA respondents noted anxiety 2  significantly morefrequentlyfor the middle class client than for the lower class client.  84 Differences in response patterns linked to client social class were also evident when examined by respondent gender. Female participants produced significant differences in the frequencies of family violence X (1, n = 24) = 4.97, p = .03, and 2  unemployment X (1, n = 16) = 4.38, p = .04. Female respondents noted the issue of 2  family violence significantly more frequently for the middle class client, while unemployment was noted significantly more frequently for the lower class client. They also exhibited a tendency to generate the issue of fearfulness/paranoia X (l,n 3  = 20) = 3.6,  p = .07 more frequently for the middle class client. Male participant responses produced no significant frequency differences on any of the issues, however, a tendencies towards difference were noted on the issues of anxiety X (\, n = 9) = 4.08,/? = .04, and family violenceX (1, n = 23) = 3.06, 2  2  p = .08. Note that on the issue of anxiety the alpha level is significant, however total frequency was only nine. For both of the issues mentioned, frequencies were higher for the middle class client than for the lower class client. The female respondents generated higher overall frequencies of presenting problems than the male respondents (TVs = 232 and 174 respectively). In examining results of the male respondents, 15 of the 18 issues had cell frequencies of less than 5, in comparison with 7 of the 18 issues for the female respondents. Because of this, any determination of gender differences based on these results would be speculative. Length of Therapy. The third open-ended question of Part I asked respondents to estimate the recommended number of sessions for this particular client. For recommended length of stay in therapy, many respondents produced ranges such as 10-15 sessions. Others omitted answering this question , or wrote that recommended length of  85 stay was, as yet, unknown (24 of 111 did not specify a recommended length of stay). Therefore, results for this question are based on 87 responses from the total sample population (See Table 9). For statistical purposes, range results were calculated with the midpoint treated as an average. Even numbers were rounded to the higher number in all cases (e.g. 10-15 sessions was calculated as 13 sessions). Table 9 Respondents' Average Recommended Length of Stay in Therapy Based on Client Social Class (N= 87)  n  M  SD  SE of Mean  middle class  25  17.68  12.62  2.52  lower class  21  11.71  6.05  1.42  middle class  22  12.45  7.16  1.53  lower class  19  14.79  9.34  2.14  middle class  47  15.23  10.65  1.55  lower class  40  13.17  8.02  1.29  CGCA  BCPA  Total  approximately 15 sessions suggested for the middle class client and 13 suggested for the As shown in Table 9, examination of responses based on total sample population did not produce a significant difference in recommended length of stay in therapy with lower class client. However, a significant difference in estimated length of stay in therapy  86 linked to client social class was produced from among the CGCA responses. The average recommended length of stay from the CGCA responses is 17.68 sessions for the middle class client and 11.71 sessions for the lower class client. Independent ^-testing shows this difference to be significant at the .05 level (t = 2.06, df = 37.13). BCPA respondents did not produce a significant difference in the suggested number of sessions between the middle and lower class client. The suggested average number of sessions was 12.45 for the middle class client and 14.79 for the lower class client (r = -.91, df= 39, p = .37). When results on suggested length of stay in therapy were examined by respondent gender, there was a notable difference in the male respondents' results for length of stay in therapy linked to client social class. Male respondents suggested 17.52 sessions for the middle class client and 11.95 sessions for the lower class client (SDs = 12.76, 7.61 respectively, t = 1.71, p = .096). While the difference appears apparent, standard deviations are large, suggesting that the male respondents were not a homogeneous group in their responses to this question. Female respondents suggested approximately the same length of stay for the middle class client and the lower class client. With middle class client means and standard deviations listedfirst,the female respondents produced the following results: Ms =13.04, 14.40, SDs = 7.80, 7.43, t = -.55, p = .58 (See /-tests in Appendix DI). Summary. Differences related to client social class were noted in respondents' explanations for choice of therapy. Among CGCA responses, the overallfrequenciesof issues generated were lower in those questionnaires returned by respondents who had received the lower class client questionnaires. Certain presenting problems (most notably  87 anxiety and family violence) were less frequently generated by respondents of the lower class client by total sample population and by association. In addition, from among the CGCA sample population, the issues of coping with feelings/mood as well as vocational assistance were morefrequentlygenerated by respondents to the lower class client, while the issue of fearfulness/paranoia was more frequently noted by the respondents to the middle class client. The lower class client also received recommendations for a significantly shorter suggested length of stay in therapy than the middle class client from the CGCA respondent population. Since respondents were not choosing from prescribed lists in answering these three open-ended questions, caution must be exercised in examining the findings. Broad ranges of responses were evident both in choices and descriptions of treatment offered, in respondents' choices of presenting problems and issues to be addressed, and in length of stay in therapy. Client Characteristics Part II of the questionnaire contained a semantic differential scale using client characteristics as descriptors, in an attempt to note possible respondent stereotyping linked to client social class. The scale prepared for this research contained 19 pairs of opposing adjectives scored on a seven point continuous scale. The client characteristics variables included (See Table 10), were chosen because they had appeared in past psychological and sociological research as social class descriptors (Hollingshead & Redlich, 1958; Morris & Williamson, 1982). Common descriptors of lower social class individuals and groups noted in  88 psychological and sociological research and literature include adjectives such as ignorant, hostile, dirty, unknowledgeable, emotional, unfriendly and lazy (Morris & Williamson, 1982). Other descriptors were chosen because they have been used to describe other minority groups and individuals (e.g. based on gender, ethnicity, race, sexual orientation, etc.) where negative stereotyping has been detected and researched (Devine, 1989; Miller, 1988). Multivariate analyses of variance of differences by client social class were performed and provided the following results: for the total sample population, F (19, 91) = 3.71, p = .00, for CGCA respondents, F (19, 42) = 3.18, p = .00, for BCPA respondents, F (19, 29) = 2.89,/? = .01, for female respondents, F (19, 38) = 2.08,/? = .03, and for male respondents, F (19, 33) = 2.26, p = .02. All results were highly significant. Table 10 provides the results of univariate analyses of variance based on client social class for the total respondent population. Differences can be noted on the following pairs: unintelligent/ intelligent (p = .00), ignorant/knowledgeable (p = .00), friendly/hostile (p = .03), loud/quiet (p = .02), emotional/controlled (p = .00) and incapable/capable (p = .01). In addition, results on the variable: clean/dirty, produced a tendency towards difference (p = .07). The middle class client was evaluated as less friendly than the lower class client. All of the remaining significant differences described the lower class client as less intelligent, less knowledgeable, louder, more emotional and less capable (and possibly less clean) than his middle class counterpart. Independent /-tests proved significant (including the descriptor of clean/dirty) on all seven of the same opposing pairs (See Appendix E).  89 Table 10 Effect of Client Social Class on Respondents' Ratings Class III (TV =55)  Class V Univariate F-tests (7V= 56) with(#=  1, 97) Descriptor:  M  SD  M  expressive/inexpressive  4.43  1.87  pessimistic/optimistic  2.04  trustworthy/untrustworthy  SD  F  P  4.38  2.17  .16  .69  1.32  2.29  1.62  .03  .87  3.93  1.67  3.80  1.53  .12  .73  competent/incompetent  3.89  1.44  4.23  1.64  .15  .70  unintelligent/intelligent  5.25  1.44  3.45  1.53  35.15  .00  involved/withdrawn  5.04  1.66  4.67  1.88  1.24  .27  industrious/lazy  3.58  1.41  3.82  1.18  .06  .80  impulsive/reliable  2.24  1.26  2.49  1.55  .01  .94  responsible/irresponsible  4.49  1.81  4.38  1.75  .07  .79  ignorant/knowledgeable  4.29  1.56  3.39  1.40  14.11  .00  friendly/hostile  4.76  1.20  4.21  1.49  4.96  .03  loud/quiet  4.65  1.50  3.96  1.63  5.97  .02  clean/dirty  2.98  1.37  3.71  1.30  3.28  .07  emotional/controlled  3.89  2.10  2.95  2.00  12.69  .00  moral/immoral  3.33  1.43  3.34  1.40  .01  .94  incapable/capable  4.20  1.66  3.55  1.56  6.98  .01  defensive/receptive  2.47  1.32  2.79  1.62  .11  .74  aggressive/peaceful  2.56  1.23  2.57  1.19  .01  .92  dishonest/honest  4.23  1.52  3.84  1.56  1.04  .31  90  In examining the two associations separately, some differences in client evaluation were noted. Independent /-tests found significant differences on five of the nineteen variables within the BCPA responses (See Table 11). These were: unintelligent/intelligent (p = .00), ignorant/knowledgeable (p = .02), loud/quiet (p = .05), clean/dirty (p = .02) and incapable/capable (p = .05). The lower class client was evaluated as less intelligent, less knowledgeable, louder, dirtier, and less capable than the middle class client by the BCPA respondents. Table 11 Significant Results of T-Tests of Client Ratings by Association BCPA  CGCA  (JV=49)  (JV=62)  M  SD  /-value  p  M  SD  /-value  p  unintelligent/intelligent middle class lower class  5.54 3.68  1.02 1.52  5.01  .00  5.03 3.27  1.68 1.53  4.28  .00  ignorant/knowledgeable middle class lower class  4.42 3.52  1.25 1.33  2.43  .02  4.19 3.29  1.78 1.47  2.18  .03  loud/quiet middle class lower class  4.75 3.96  1.26 1.46  2.03  .05  4.82 4.35  1.42 1.23  1.39  .17  clean/dirty middle class lower class  3.33 4.00  1.01 1.00  -2.32  .02  2.71 3.48  1.55 1.48  -2.01  .05  incapable/capable middle class lower class  4.29 3.36  1.55 1.66  2.03  .05  4.39 4.03  1.71 1.32  .92  .36  Examination of CGCA responses linked to client social class produced significant results on the following three variables: unintelligent/intelligent (p - .00), ignorant/knowledgeable (p = .03) and clean/dirty (p = .05). The lower class client was evaluated as less intelligent, less knowledgeable, and less clean. In addition, two other descriptors produced a tendency towards difference from within the CGCA responses. These were (with middle class means and standard deviations listedfirst):friendly/hostile (Ms = 4.68, 4.03, SDs = 1.35, 1.60) t = l.71,p = .09, and emotional/controlled (Ms = 3.97, 3.00, SDs = 2.29, 2.04) t = 1.15,p = .08. In these two cases the lower class client was rated as friendlier and more emotional than the middle class client. Investigation of differences linked to client social class by respondent gender also produced significant results (See Table 12). Evaluations by the female respondents produced significant differences on three of the sets of opposing pairs. These were: unintelligent/intelligent (p = .00), ignorant/knowledgeable (p = .03), and clean/dirty (p = .05). The lower socio-economic status client was evaluated by female respondents as less intelligent, less knowledgeable, and less clean than his middle class counterpart. Significant differences were noted in the male respondents' evaluations onfiveof the pairs of opposing adjectives. These were unintelligent/intelligent (p = .00), ignorant/knowledgeable (p = .02), loud/quiet (p = .05), clean/dirty (p = .04), and emotional/controlled (p = .05). The descriptor incapable/capable produced a tendency towards difference with an alpha level of .06. Male respondents evaluated the lower class client as less intelligent, less knowledgeable, louder, less clean, less controlled and possibly less capable than his middle class counterpart.  92 Table 12 Significant Results of T-Tests on Evaluations of Client Characteristics by Respondents' Gender (N= III) Female Respondents (n = 58) Descriptor:  Male Respondents (n = 53)  M  SD  /-value  P  unintelligent/intelligent middle class lower class  4.97 3.30  1.67 1.59  3.86  .00  ignorant/knowledgeable middle class lower class  4.13 3.21  1.78 1.45  2.15  clean/dirty middle class lower class  2.60 3.36  1.45 1.47  loud/quiet middle class lower class  4.55 3.78  emotional/controlled middle class lower class  3.97 2.96  SD  /-value  P  5.60 3.61  1.04 1.47  5.62  .00  .03  4.48 3.57  1.26 1.35  2.53  .02  -1.97  .05  3.44 4.07  1.12 1.02  -2.15  .04  1.65 1.83  1.69  .10  4.84 4.07  1.31 1.41  2.04  .05  2.29 1.99  1.77  .08  3.88 2.82  1.87 2.00  1.98  .05  M  Overall, significant differences linked to client social class were evident when results were examined by total sample population, by association and by gender. BCPA respondents produced significant differences on 5 and CGCA respondents on 3 of the descriptor pairs, and the variables. Male respondents produced significant differences on 5 and female respondents on 3 of the descriptor pairs.  93 Respondents' Personal Network and Relationship to Client Evaluations  Part IV of the questionnaire is a personal relationship grid (See Appendix A). Respondents' were asked to report whether they have relationships with individuals within particular occupations based on the following relationship types: friend, acquaintance, relative, colleague, and client. My aim in including the grid was to investigate whether respondents' contacts with individuals of the lower social classes (as defined simply by occupation for this section) would impact on respondents' evaluations and judgements of the lower social class client. The two categories of close contact and no contact with individuals from the lower social classes in the form of close friend, relative or client, were used as the independent variables. Responses to the problem evaluation and client characteristics scales were the dependent variables. Results showed no significant differences in evaluations of the clients based on contact with individuals of the lower social classes as listed in the personal network grid. However, the form was not designed to note how many contacts within a particular category any one respondent had. For example, while one respondent may have twenty friends on welfare and another may have one, both could check off the category of having a friend on welfare. The form used did not include any statistical data on numbers within any category, or qualitative information on closeness of the relationships. Another problem that arose in results within this section were the low numbers within certain categories. For the category welfare recipients, while 74 of the 111 respondents indicated having at least one client who was a welfare recipient, only 9 of the 111 indicated having a welfare recipient as a friend, and only 4 out of the 111 indicated having a relative who was a welfare recipient. Several other occupations showed  94 Table 13 Respondents' Personal Network Occupations  friend  relative  colleague  client  business owners/managers  65  64  52  63  professors  55  37  62  29  teachers  60  54  35  61  bankers  15  15  4  31  accountants  23  22  7  40  engineers  32  31  5  33  bus drivers  9  6  2  28  seasonal farm workers/fishers  13  8  3  38  auto mechanics  19  8  3  38  plumbers/electricians  10  12  2  36  waiters/waitresses  11  18  3  58  police officers  18  13  8  37  loggers/mill workers  10  13  3  48  3  8  2  25  federal/provincial politicians  10  3  2  10  computer specialists  24  28  20  46  biologists/botanists/chemists  18  16  11  19  nurses/physiotherapists  51  36  40  58  doctors  50  31  43  37  architects  12  5  3  20  lawyers  38  24  20  37  unskilled construction workers  7  9  janitors/cleaning personnel  5  2  4  50  gas station attendants  3  2  2  28  unskilled factory workers  2  3  38  welfare recipients  7  8  74  truck drivers (non owners)  9  4  41  50  19  firefighters  social workers  60  68  29  95  similar patterns within the categories of friends and relatives. Few respondents listed contact in the form of friendships or family relations with individualsfromthe lower and working class occupations listed in the grid. Within the category of friends, the eight occupations that were the least checked off were all lower to working class occupations. Those occupations were: bus drivers, fire fighters, unskilled construction workers, janitorial/cleaning personnel, gas station attendants, unskilled factory workers, and non-owner truck drivers. The eight mostfrequentlychecked off occupations within the category of friends were business owners/managers, professors, teachers, nurses/physiotherapists, doctors, lawyers, and social workers. In the category of relatives the pattern, although not identical, is similar. The lowest checked off occupations for relatives of respondents were: bus drivers, seasonal farm workers/fishers, auto mechanics,firefighters,janitors/cleaning personnel, gas station attendants, unskilled factory workers, welfare recipients, truck drivers, architects, and federal/provincial politicians. The most frequently checked off in the category of relatives were: business owners/managers, professors, teachers, engineers, computer specialists, nurses/physiotherapists, doctors and lawyers. It is evident, noting the categories checked off in the grid, that respondents have noticeably higher levels of contact through friendships and family relatives with nearly all of the occupational categories used to represent middle and upper class groupings. While the list of occupations is limited, one can assume, based on responses to the occupations used, that the respondents predominantly have much less contact through friendships or through blood relations with lower and working class individuals. In contrast, within the category of clients the most frequently checked off group was welfare recipient.  96 In examining for differences in problem evaluation and on the client characteristics, responses were grouped based on contact versus no contact with social class occupational groupings. Responses were compared in the categories of friendship, relative, and client. Those occupations chosen as representative of the lower class were the following: unskilled construction workers, janitors/cleaning personnel, unskilled factory workers, welfare recipients, gas station attendants, and non-owner truck drivers. (Further analyses also included loggers/mill workers and waiters/waitresses.) Using independent /-testing, a difference was found in the response pattern on only one of the problem evaluation scales. Respondents (n = 16) who had clients in all five of the lower class categories mentioned above, rated the lower class client significantly higher (t = 3, df- 20, 54, p - .01) on motivation for change than those respondents (n = 95) who had no clients in any of the five lower class occupations. Caution must be used however, since the group of respondents having clients in all five of the lower class occupations was dramatically lower than respondents who did not have clients in all five of these occupations. No differences were found on responses to the client characteristics linked to the contact and no contact groups. Attempts at further analysis were unproductive because of the low numbers of respondents who had contact with individuals within lower class occupations. Respondents' Social Class Background Through the demographic section of the questionnaire, information was gathered relating to the respondents' mothers' and fathers' levels of education and work experience while the respondents were growing up (See Appendix A) in order to estimate the respondents' social class backgrounds. More than 85% of the respondent population were over the age of forty. This means that many of them were children at a time when less  97 women were regularly participating in the paid workforce. Close to half of the respondents reported their mothers as not having worked outside of the home, making analysis of mothers' occupations less statistically useful. Therefore, for the purposes of analysis, respondent's social class background was based on the father's occupation(s) and level of education. In two cases where the father was listed as missing or deceased, social class background was based on the mother's occupation and education. Not all social class groups were equally represented from within the sample population (See Figure 1). Using the father's occupations and level of education, seventythree (65.77%) of the 111 respondents were from middle to upper class backgrounds. Of the remaining 38 respondents, 20 (18.02%) stated that their fathers were skilled blue Figure 1.  Respondents' Social Class Backgrounds Figure 1. Respondent's social class background based on father's occupations and level of education (N = 111).  98 collar workers, 11 (9.91%) farmers, 5 (4.51%) semi - unskilled blue collar workers, and 2 (1.80%) semi - unskilled white collar workers (See Figure 1). As reported in the Methods section, more than half of the respondents' parents had completed high school. Considering the highly educated sample population used for this study, it is not surprising that the parents had levels of education and positions within the occupational structure that were above average for their time. As pointed out by Guppy (1984), there is a strong correlation between parents' standing within the socio- economic hierarchy and children's levels of education. Using multiple analysis of variance, no significant differences in response patterns linked to respondent social class background were noted for the problem evaluation or for the client characteristics results. However, analysis of responses linked to client and respondent social class was impaired by the significant absence of respondents whose backgrounds were from either the semi/unskilled blue collar, or the semi/unskilled white collar groups. Respondents' Level of Education To examine possible effects of the combination of client social class and respondent level of education on client evaluations, I chose to use only those respondents holding either a master's or a doctoral degree. Categories excluded were undergraduate degrees (n = 7), 'other' category (» = 2) and missing data (n = 9). In all, 45 of the 49 BCPA members (18 masters degrees, 27 doctorate degrees) and 48 of the 62 CGCA members (36 masters degrees, 12 doctorate degrees) were included in the analysis. No significant interactions by client social class and respondent degree were found on the problem evaluation (See Appendix F). In examining results on the client  99 characteristics by client social class and respondent degree, five of the nineteen client characteristics produced significant results (See Table 14). Analyses of variance found significant interactions between client social class and respondent's degree on the following client characteristics: involved/withdrawn, dishonest/honest, incapable/capable, emotional/controlled, and loud/quiet. Friendly/hostile also showed a slight tendency towards an interaction at an alpha level of .085. (See analyses of variance for all client characteristics in Appendix F). To assist me in understanding and interpreting the data, I performed Mests on each of the six descriptor pairs separately, by client social class and by respondent degree. For the following results, middle class means and standard deviations are listed first. InvolvedAVithdrawn. For the descriptor pair involved/withdrawn, master's respondents rated the middle class client as significantly more withdrawn than the lower class client (Ms = 5.60, 4.14, SDs = 1.12, 2.17) f = 3.03,/? = .004. Doctoral respondents exhibited a tendency to rate the middle class client as less withdrawn than the lower class client, however, the results did not reach statistical significance (Ms = 4.41, 5.41, SDs = 1.89, 1.28) t = -1.88,/? = :069. Dishonest/Honest. On the descriptor pair dishonest/honest, master's respondents rated the middle class client significantly more honest than the lower class client (Ms = 4.60, 3.59, SDs = 1.04, 1.90) t = 2.38,p = .02. Doctoral respondents did not produce a statistically significant difference in ratings between the middle and lower class client (Ms = 3.68, 4.24, SDs = 1.67, 1.09) t = -1.18,/? = .25. Incapable/Capable. For the descriptor pair incapable/capable, master's respondents rated the middle class client significantly more capable than the lower class  100 Table 14 Client Characteristics Showing Significance By Client Social Class and Respondent Degree (N= 93. df= 1) Client Characteristic  SS  MS  F  P  involved/withdrawn by class by degree class by degree  1.18 .04 33.98  1.18 .04 33.98  .40 .01 11.51  .53 .91 .00  dishonest/honest by class by degree class by degree  1.19 .41 13.74  1.19 .41 13.74  .51 .18 5.97  .48 .68 .02  incapable/capable by class by degree class by degree  6.94 1.08 10.92  6.94 1.08 10.92  2.76 .43 4.34  .10 .51 .04  emotional/controlled by class by degree class by degree  19.64 .00 38.16  19.64 .00 38.16  5.30 .00 10.30  .02 1.00 .02  loud/quiet by class by degree class by degree  17.01 .10 13.93  17.01 .10 13.9  6.77 .04 5.54  .01 .84 .02  client (Ms = 4.60, 3.35, SDs = 1.32, 1.61) t = 3.10,/? = .003. Doctoral respondents produced no significant difference in their ratings of the middle and lower class client on this variable (Ms = 3.68, 3.82, SDs = 1.94, 1.38) t = -.26,p = .80. Emotional/Controlled. On the variable emotional/controlled, master's respondents rated the lower class client as significantly more emotional than the middle class client (Ms = 4.76, 2.52, SDs = 1.90, 1.86) t = 4.37, p = .000. Doctoral respondents produced no  101 significant difference in the rating of the middle and lower class client on this variable (Ms = 3.46, 3.82, SDs = 2.04, 1.91) t = -.58,/? = .57. Loud/Quiet. On the descriptor pair of loud/quiet, master's respondents rated the middle class client quieter than the lower class client. The difference was significant (Ms = 5.04, 3.38, SDs = 1.10, 1.92) t = 3.82,/? = .000. Doctoral respondents again produced no difference in their ratings on the loud/quiet scale (Ms = 4.32, 4.24, SDs = 1.96, .83, t = .16, p  = .87). Friendly/Hostile. On the descriptor pair friendly/hostile, master's respondents  rated the middle class client more hostile than the lower class client (Ms = 4.76, 3.83, SDs = .88, 1.79) t = 2.36,/? = .02. Doctoral respondents produced no significant difference linked to client social class on this variable (Ms = 4.59, 4.65, SDs = 1.37, .86) t = -.15,/? = .88. Ignorant/Knowledgeable. As with the total sample population, both associations and both genders, on the variable of ignorant/knowledgeable, masters degree respondents rated the lower class client as significantly less knowledgeable than the middle class client (Ms = 4.44, 3.00, SDs = 1.19, 1.49) t= 3.88,/? = .000. Doctoral respondents however, did not rate the lower class client as significantly less knowledgeable than the middle class client (Ms = 3.96, 3.53, SDs = 1.96, 1.23) f = .78,/? = .44. Clean/Dirty. By respondent degree, master's respondents produced no significant difference on the variable of clean/dirty (Ms = 3.08, 3.55, SDs = 1.28, 1.74) t = -1.11,/? = .27. Doctoral respondents however, rated the middle class client significantly cleaner than the lower class client (Ms = 3.05, 3.94, SDs = 1.46, .43) t = -2.44,/? = 02. Unintelligent/Intelligent. Both groups rated the lower class client as significantly  102  less intelligent than the middle class client. For the master's respondents results were Ms = 5.52, 3.38,  SDs = 1.09, 1.74, t = 5.32,/; = .00. For the doctoral respondents, results  were Ms = 4.86, 3.53, SDs = 1.86, 1.28, t = 2.53,/? = .02. Doctoral degree respondents also produced a tendency towards difference linked to client social class on the descriptor pair: impulsive/reliable (Ms = 2.23, 3.05, SDs = 1.19, 1.64, t = -1.84, p = .07).  The lower class client was rated as more reliable than the  middle class client. In all, master's degree respondents produced significant differences on eight of the opposing pairs of descriptors, and doctoral degree respondents produced significant differences on two (and a tendency towards difference on two other) of the opposing pairs of descriptors. Respondents' Years of Experience The impact of respondents' years of counselling experience on client evaluations was investigated using factorial analyses of variance (See Appendix G). Analyses were performed using the following five levels of counselling experience: 0 - 4 years (n = 16), 5 - 9 years (» = 27), 10 -14 years (n = 23), 15 -19 years (n = 20), and 20 or more years experience (n = 23). Within the problem evaluation scales, main effects linked to years of experience by client social class were noted for ratings of client motivation for change (F = 4, df= 4, p = .01) and for prognosis ( F = 3.21, df= 4,p = .02). On motivation for change, respondents with 0 - 4 years experience produced a mean score of 5.50 for the middle class client and 3.50 for the lower class client. This suggests that the difference produced on this variable is due predominantly to the spread of scores within this 0 - 4 years experience group  103 Figure 2.  (See Table 15). Both the 0 - 4 and the 15 - 19 years experiences groups rated the lower class client as having a stronger motivation for change than the middle class client. All three other groupings based on years of experience rated the middle class client as having a slightly higher motivation for change than the lower class client. On the variable of prognosis, as with motivation for change, scores do not appear to follow any linear pattern, making it difficult to draw any clear conclusions. In examining years of experience and evaluations of client characteristics as listed on the client characteristics scale, no significant differences linked to an interaction between respondents' years of experience and client social class were evident on any of the nineteen descriptor pairs. Although analyses of variance did not produce significant interactions, there were noteworthy differences evident in Table 16. However, because no consistent/linear pattern by experience is apparent, results are difficult to interpret.  104 Table 15 Rating Means For Motivation For Change and Prognosis Based On Respondents Years of Experience  Number of Years Experience:  1 -4 (n=\6)  5 -9 (n = 27)  10- 14 (n = 23)  15 - 19 (n = 20)  20+ (n = 23)  M  M  M  M  M  Class III  5.50  4.15  3.92  4.91  4.21  Class V  3.50  5.00  4.18  3.78  4.44  F=4.23  /? = .003  Motivation for change  Prognosis Class III  3.00  3.46  2.67  4.36  3.33  Class V  3.50  4.14  4.00  3.22  3.44  F=3.18  p = .0\l  105 Table 16 Mean Client Characteristic Scores by Respondents' Years of Experience Number of Years Experience:  1 -4 (ft =16)  5 -9 (ft = 27)  10- 14 (ft = 23)  15 - 19 (ft = 20)  20+ (ft = 23)  M  M  M  M  M  Class III  3.75  5.39  4.67  4.46  3.64  Class V  4.33  5.29  3.64  4.33  3.78  F=.40  /> = .81  expressive/inexpressive  pessimistic/optimistic Class III  1.50  2.31  2.17  1.73  2.14  Class V  2.58  3.00  1.46  1.67  2.56  F=1.09  p = 37  trustworthy/untrustworthy Class III  3.50  3.85  3.25  5.09  3.93  Class V  3.82  4.07  3.55  3.78  3.78  F=.93  p = A5  competent/incompetent Class III  3.00  4.31  3.58  4.55  3.54  Class V  4.42  5.00  3.36  4.33  3.67  F=.85  p=.50  unintelligent/intelligent Class III  4.00  5.77  4.67  5.46  5.42  Class V  3.83  3.36  3.20  4.00  2.78  F=1.80  p = A3  involved/withdrawn Class III  6.00  5.54  4.33  5.64  4.50  Class V  4.25  5.29  4.64  5.33  3.78  F=.77  p = .55  (table continues)  106  Table 16 (continued) Number of Years Experience:  1-4  5-9  1 0 - 14  15 - 19  (w=16)  (n = 27)  (n = 23)  (n = 20)  (n = 23)  20+  M  M  M  M  M  industrious/lazy Class III  4.00  3.15  3.83  4.27  3.21  Class V  3.75  4.36  3.73  3.78  3.22  F=1.60  p = AS  impulsive/reliable Class III  4.00  3.15  3.83  4.27  3.21  Class V  3.75  4.36  3.73  3.78  3.22  F=.56  p = .70  responsible/irresponsible Class III  3.25  4.77  4.50  5.27  4.07  Class V  4.58  4.50  3.70  5.11  3.89  F=.7\  p=.59  ignorant/knowledgeable Class III  3.50  4.62  3.42  4.73  4.50  Class V  3.67  3.43  3.18  3.89  2.78  F=1.19  p = .32  friendly/hostile Class III  5.00  4.92  4.50  4.73  4.79  Class V  4.67  4.79  3.55  4.22  3.44  F=.73  p = .57  loud/quiet Class III  4.25  4.46  4.33  5.09  4.79  Class V  4.33  4.21  3.36  4.22  3.56  F=.52  p=J2  (table continues)  107 Table 16 (continued) Number of Years Experience:  1 -4 (n = 16)  5 -9 (n = 27)  10- 14 (n = 23)  15 - 19 (n = 20)  20+ (n = 23)  M  M  M  M  M  Class III  2.75  3.15  3.00  2.64  3.21  Class V  3.75  4.14  3.18  3.78  3.55  F=.54  p = .l\  clean/dirty  emotional/controlled Class III  4.00  4.39  2.92  4.73  3.64  Class V  3.17  3.57  2.64  3.11  2.20  F=.31  p = .S3  moral/immoral Class III  4.50  3.46  2.33  3.91  3.36  Class V  3.67  3.64  3.27  3.56  2.67  F=1.49  p = .2l  incapable/capable Class III Class V  5.25  3.92  3.75  3.91  4.64  3.67  4.00  3.27  4.00  2.79  F=\.61  p = .16  defensive/receptive Class III  2.00  2.62  2.17  2.64  2.71  Class V  2.92  2.79  3.18  2.89  2.33  F=J5  p=.56  aggressive/peacefiil Class III Class V  2.00  3.15  2.33  2.18  2.71  2.42  2.86  1.91  2.89  2.67  F=.81  p = .52  (table continues)  108  Table 16 (continued) Number of Years Experience:  1 -4 (n = 16)  5 -9 (n = 27)  10- 14 (n = 23)  15 - 19 (n = 20)  20+ (n = 23)  M  A/  M  M  M  Class III  3.75  4.54  3.75  3.73  4.64  Class V  4.75  4.00  3.27  3.67  3.22  dishonest/honest  F=\36  p = .25  Summary While few differences were found in the problem evaluation scales used to partially replicate Sutton and Kessler's (1981) original research carried out in the U. S., significant differences arose in responses to the open-ended questions, and in the client characteristics ratings. Differences linked to client social class also occurred when results were examined by professional association and by gender. Significant interactions were also evident between client social class and respondent level of education. It was impossible to carry out response analyses based on respondents' race or ethnicity as the sample population was overwhelmingly Caucasian (95%). In addition, response differences linked to respondent social class, while investigated, were of little value because there were so few respondentsfromlower (semi - unskilled blue and white collar) class backgrounds (n = 7) using father's occupations and parents' levels of education as social class indicators. In the following chapter, the results will be discussed with consideration given to the relevant literature, and the implications for clinical practice and training.  109 Discussion  This study was designed to explore whether initial information about a client's social class would impact negatively on the therapist's perception, evaluation, and proposed treatment for the client. A review and discussion of the predominant findings, and implications of those results, appears below. Overall, this study lends support to previous psychological and sociological research into the effects of client socio-economic status (SES) on therapist perception, judgement, evaluation, and proposed treatment for the lower social class client. Since both hypothetical clients were identical except for information identifying social class and class background, it would appear that information identifying the one client as lower social class (education, occupation, family social class background, and manner of dress) had a negative impact upon respondents' perceptions, evaluations, and proposed treatment for that client. The implications of thesefindingsare serious in that most of the respondents reported having clients within all levels of social class occupations; and, in fact, the client population category with the highest levels of frequency (i.e., the respondent has clients who fall within that category) was welfare recipient (See Respondent's Personal Network, p. 94). I have chosen to review thefindingsbeginning with areas that I believe provide the most persuasive evidence of respondent bias linked to client social class. Client Characteristics Results on the client characteristics were significant when examined by total sample population, by association, by respondents' level of education, and by gender.  110 Findings bv Total Sample Population. Findings on the results of the client characteristics revealed that respondents receiving a description of a lower social class client provided significantly less positive evaluations of their client than did respondents receiving a description of a middle class client on 6 of the 19 pairs of opposing adjectives (p = .05). These were unintelligent/intelligent, ignorant/knowledgeable, loud/quiet, emotional/controlled, incapable/capable and clean/dirty. While it may be argued that the lower level of education attributed to the lower class client suggests a somewhat lower level of intelligence, and less knowledgeability and capability, it is imperative for counsellors to begin the counselling process with as little bias as possible. A variety of research studies from Canada and the United States have found that social class has a significant negative impact on the treatment of, and on the education received, by lower social class students (Baer & Lambert, 1982; Colclough & Beck, 1986; Gamoran, 1987; Guppy, Mikicich & Pendakur, 1984). This, in combination with the added stressors of childhood poverty, can produce higher dropout levels for lower social class students. To present for therapy, and to be initially perceived, evaluated and/or treated as less intelligent, capable or knowledgeable by a helping professional can in no way benefit a client from any social class background, let alone lower class individuals who interact in a society that already labels them as "losers". While some may make the claim that level of education is one valid reflection of intelligence, knowledgeability, or capability, the lower SES client was also evaluated as louder, more emotional, and less clean than the middle class client. There would appear to be no reason, based on the client information presented to the respondents, for these results except that these descriptors fit the commonly held stereotype of a lower class  Ill member, as described in both the sociological and psychological literature (Hollingshead & Redlich, 1958; Jones, 1982; Morris & Williamson, 1982). Interestingly, the middle class client was given a more negative rating on the one variable of friendly/hostile. Lower class individuals have historically been stereotyped in the psychological literature as hostile (Hollingshead & Redlich, 1958; Morris & Williamson, 1982). Therefore, this one result falls outside of the stereotypic expectation. Perhaps, although both clients' behaviour and communication was the same, respondents may have assumed that the middle class client would have a more difficult time opening up to the therapeutic experience due to the embarrassment of presenting oneself for therapy. Another possible explanation may the existence of a Type I error. Findings bv Association. The findings also indicated that, while the lower class client received more negative ratings than the middle class clientfromboth the Canadian Guidance and Counselling Association and the British Columbian Psychological Association respondents, BCPA respondents (N = 49) rated the lower class client more negatively on five of the variables in comparison with three of the variables for the CGCA respondents (N= 62). BCPA respondents rated the lower class client as less intelligent, less knowledgeable, louder, dirtier, and less capable than the middle class client. CGCA respondents rated the lower class client as less intelligent, less knowledgeable, and less clean. While at first glance, it would appear that the BCPA respondents exhibited more differential perception, two other variables within the CGCA respondent ratings also produced a tendency towards difference. These were hostile/friendly (p = .09) and more emotional/controlled (p - .08). The lower class client was rated as friendlier and more emotional than the middle class client. From these results, it is not possible to determine  112 that the BCPA responses produced more bias than the CGCA responses. However it is possible to state that both associations produced significant results that portray the lower class client in a more negative light, and that these differences fall within the societal stereotypes of lower social class members. Findings bv Respondent Level of Education. Some researchers (Baer & Lambert, 1982; Johnston & Ornstein, 1985) have suggested that higher levels of education are associated with more conservative socio-political viewpoints, although this may be somewhat mitigated by field of study. Longitudinal research (Guimond & Palmer, 1990) investigating the causal attributions of poverty found that social science students were more likely to endorse structural explanations for poverty over commerce or engineering students, who were more likely to endorse individualistic explanations. The respondent population's average level of education was a doctoral degree for the BCPA sample, in comparison with a master's degree among respondents from the CGCA. However, analysis of findings based on respondents' highest degree of education rather than association membership found that respondents with master's degrees produced more highly significant results on the client characteristics than did respondents with doctoral degrees. Respondents with doctoral degrees produced significant results on two of the descriptor pairs. These were: clean/dirty and unintelligent/intelligent. The lower class client was perceived to be dirtier and less intelligent than the middle class client. Master's degree respondents produced significant results on eight of the descriptor pairs. These were: ignorant/knowledgeable, friendly/hostile, loud/quiet, emotional/controlled, incapable/capable, dishonest/honest, unintelligent/intelligent, and  113 involved/withdrawn. The lower class client was perceived to be more ignorant, friendlier, louder, more emotional, less capable, less honest, less intelligent but more involved than his middle class counterpart. While respondents of both levels of education produced significant results that involved a predominantly negative perception of the lower class client, the group of respondents holding masters degrees produced bias on far more of the variables than the group of respondents holding doctoral degrees. It would appear that, contrary to one of my original hypotheses, higher levels of education within the general field of psychology had a mitigating effect on levels of biased perception. This would suggest that education positively impacted on the degree of negative stereotyping. However, since many masters level individuals will not continue on towards a doctoral degree, and doctoral respondents also produced significant bias in their responses, it would seem highly probable that providing training and education specifically on class and stereotyping would have a positive impact on both master's and doctoral students' ability to offer unbiased services to all social classes. Findings by Gender. The lower class client received more negative evaluations on the client characteristics than the middle class client when results were examined by respondent gender. Male respondents produced more negative evaluations of the lower class client on five of the descriptor pairs (unintelligent/intelligent, ignorant/ knowledgeable, loud/quiet, clean/dirty, emotional/controlled), and a strong tendency towards difference on one other (incapable/capable). Female respondents produced significant differences on three descriptors. These were unintelligent/ intelligent, ignorant/knowledgeable, and clean/dirty. While it is not possible to infer with certainty  114  that because the male respondents produced significant results on two more of the descriptors that they are, in fact, exhibiting more bias, it seems reasonable to assume that feminist attitudes in counselling have affected women more than men, and the feminist emphasis on taking into account the social contexts of a person's life may have had a modifying impact on female respondent ratings on the client characteristics. Findings bv Respondents' Years of Experience. In examining the data informally, an unusual pattern of response linked to respondents' level of experience was apparent. No consistent upward or downward pattern of evaluation linked to client social class and respondents' years of experience was evident; however, ratings varied dramatically at times, from one experience group to another. On those adjectives that had produced significance by social class for the total sample population (unintelligent/intelligent, ignorant/knowledgeable, friendly/hostile, loud/quiet, emotional/controlled, and incapable/capable), the 20+ years experience group produced the greatest spreads of differences linked to client social class, with the lower social class client receiving the poorer evaluations. Replicating the results found by Sutton (1983), therapists with the most years of counselling experience appear to have shown more negative clinical evaluations towards the lower social class client. It may be reasonable to assume that many of these respondents received their training at a time when it was believed that lower social class clients were not good candidates for psychotherapy, due to a variety of personal deficiencies such as lower levels of cognitive and verbal abilities and an inability to delay gratification (Hollingshead & Redlich, 1958). In addition, gender and cultural differences and other social context issues were not considered topics for therapeutic discussion, making recognition of biased perception more difficult. This may  115 have had an influence on ratings provided by the respondent population with 20+ years' experience. However, lack of statistically significantfindingsrequires caution in advancing this hypothesis. More research may be required into the specific effects of years of counselling experience, theoretical orientation, and number of years since attending training or graduate school. In all, when results on the client characteristics were examined by total sample population, by association, by educational degree, and by gender, all produced significant differences linked to client social class. Most of these differences produce a negative perception of the lower class client unrelated to the information provided to the respondents in the client information material. Explanations for Choices of Therapy Explanations for choices of therapy contained more negatively descriptive and evaluative statements of the lower class client (e.g. "I suspect his cognitive abilities are limited."). The most obvious explanation for this would appear to be the belief that lower class clients (regardless of whether they present in the same manner as middle class clients) are less able than their middle class counterparts to think in the abstract, less apt to progress with insight-oriented therapy, more apt to require a vocational therapeutic focus, and more apt to have learning disabilities. Statements made were reinforced when examining evaluations produced on the client characteristics. There appeared to be a tendency to view the lower class client as less intelligent, less capable, and less apt to progress if offered insight-oriented therapy. The impact of such beliefs on the lower class client could no doubt effect both the progress made and their choice of remaining in therapy. To attempt to secure assistance  116 for a marital problem only to have vocational, aptitude or intelligence testing suggested would appear to be disrespectful of the client's own choices for coming to therapy, let alone ring of biased judgement. Previous literature (Spengler et al., 1990) has suggested a vocational overshadowing when both vocational and personal issues are brought out in 1  the counselling setting. In this case, although both clients were unemployed, and neither verbalised vocational issues, only in the case of the lower class client was a vocational focus taken by some of the respondents. Rather than a vocational overshadowing, a personal overshadowing in favour of the vocational emerged for the lower class client. This vocational focus, in itself, does not necessarily prove respondent bias. It can be argued that because of the greater risks involved with poverty, respondents who chose to include a vocational focus were demonstrating an awareness of and concern for the socio-economic situation faced by the lower class client. However, the language used to explain the respondents' choice of therapy for the lower class client (e.g. "He's probably not too bright." "His personal information profile does not suggest that one would get very far with subtle.") leave one feeling that one is observing decisions influenced by biased thinking. In either case, it seems apparent that the lower class client would not be offered the equivalent therapy available to the middle class client. Issues/Presenting Problems Respondent differences linked to client social class also occurred in the area of presenting problems. The total number of problems generated by the respondents for the lower class client was slightly less than those generated for the middle class client. In  'Vocational overshadowing' occurs when a client presents with both personal and vocational issues, and a preference is shown on the part of the therapist to focus more on the personal issues. 1  117 addition, the issues of anxiety, family violence, and paranoia were generated significantly more frequently for the middle class client, while the issues of feelings/mood and vocation were generated significantly more frequently for the lower class client. A greater portion of these differences were due to responses from the CGCA sample population. Findings bv Association. CGCA respondents produced significant frequency differences on four issues. Family violence and paranoia were generated significantly more frequently for the middle class client while coping with feelings/mood and vocation were generated significantly more frequently for the lower class client. In addition, the CGCA respondents produced an overall frequency for presenting problems of 134 for the middle class client and 110 for the lower class client. BCPA respondents generated the one issue, anxiety, significantly more frequently for the middle class client than for the lower class client. Overallfrequenciesfor the middle and lower class client were virtually identical (f= 80 and 82 respectively). It appears that, on this question, BCPA respondents exhibited less difference in perception of the problem between the middle and lower class client than did respondents from the CGCA sample population. The average levels of education were a master's degree for the CGCA sample population, and a doctoral degree for the BCPA sample population. Significant differences on the Client Characteristics were linked to levels of education. This may have been the determining factor in significant differences in frequencies of presenting problems; however, statistical investigation of presenting problems was not carried out by respondent level of education. Findings by Gender. Female respondents generated a significantly higher frequency of the issue of family violence for the middle class client. The issue of paranoia  118 produced a tendency towards difference (p = 06), with a higher frequency generated for the middle class client. Female respondents generated the issue of unemployment significantly more frequently for the lower class client. Male respondents produced no significant frequency differences on any of the presenting problems. While one of the frequencies reached significance (anxiety,/? = .04), total frequencies were too low for chi square analysis. Initially, one might assume that the male respondents are exhibiting no difference between the middle and lower class client in issues generated, however, results are inconclusive because, on 15 out of 18 issues generated, cell frequencies were too low to carry out reliable analyses. Overall, the male respondents generated lower frequencies (f= 174) than the female respondents (f= 232) for all of the presenting problems. The most frequently generated issue by total sample population, by gender and by CGCA respondents was family violence. Family violence was generated significantly more frequently for the middle class client than for the lower class client. Recent studies (Davidovich, 1990; Peterson, 1980; Smith, 1990) have revealed an increase in family violence moving from the middle to lower social class. These studies also argue that the lack offinancesand certain forms of social supports increase the possibility of family violence. Economic factors tend to be the strongest reasons why women remain in violent situations (Ignagni et al., 1988). Why then, was family violence as an important issue, noted significantly less frequently for the lower class client? One possibility may be that counsellors/therapists were less likely to note family violence as an important issue for the lower class client because violence is more frequently expected (less shocking) when occurring within the context of poverty or  119 limited financial resources (Morris & Williamson, 1982). Counsellors may downplay family violence related to the lower class client because they implicitly recognize the violence as a result of the more difficult socio-economic situation the lower class family faces. While plausible, this explanation still appears weak in that recognition of social context should not blind one to the issue. An alternative explanation for the apparent lowered emphasis on the issue of family violence may be linked to schema theory and stereotyping. When faced with an individual from a social group other than one's own, one is likely to be less perceptive of a variety of particular aspects and characteristics of that individual than for individuals who fall within or close to one's own social group (Fiske & Taylor, 1984; Jones, 1988; Leyens et al, 1994; Morris & Williamson, 1988). The less one identifies with an individual, and the more one is affected by the stereotype, the less apt one is to take note of all of the specific issues or characteristics that make up that particular individual. Studies have shown that perceptions of out-group members show much less variability and complexity than perceptions of in-group members (Fiske & Taylor, 1984). While therapists are trained, more than most professionals, in acceptance of individuals different from themselves, research has shown that they are not immune to stereotypes or their immediate activation when facing out-group members (Smith, 1988). This being the case, therapists who interact with a lower social class client are faced with a stereotype; and, because of this, may be less apt to notice as many of the predominant issues. The lowered frequencies of issues generated for the lower social class client in this particular section of my research parallels results of previous out-group schema research (Fiske & Taylor, 1984).  120 Suggested Length of Stay in Therapy  No significant difference was measured in suggested length of stay in therapy when results were examined by total sample population, or by respondent gender. By total sample population, the lower class client was offered approximately 13 sessions and the middle class client was offered approximately 15 sessions. By gender, female respondents suggested approximately 13 sessions of therapy for the middle class client and 14 sessions of therapy for the lower class client. Although the male respondents produced noticeably different results in suggested length of stay in therapy linked to client social class (18 sessions for the middle class client and 12 sessions of therapy for the lower class client), results were not significant. This is, most probably, due to the wide range in responses for this question, producing large standard deviations, and indicating that, on this particular question, the male respondents were not a homogeneous group. Findings by Association. Differences were significant when results were examined by professional association. One might intuit that the lower class client would be determined to need approximately the same number of therapy sessions (if not more) as the middle class client. BCPA respondents suggested a nonsignificantly longer length of stay in therapy for the lower class client than for the middle class client (Ms = 14.79, 12.45 sessions respectively, p = .37). However, CGCA respondents suggested a statistically significant shorter length of stay in therapy for the lower class client than for the middle class client (Ms = 11.71, 17.68 sessions respectively, p = .05). One explanation could be that some respondents perceived the lower class client as a less appropriate candidate for long-term therapy. The lower class client was perceived by some respondents as less psychologically-minded, and therefore, less apt to respond  121 well to insight-oriented therapy. However, as noted in the Literature Review, when lower class clients have been offered long-term therapy in an accepting environment, dropout rates have not been significantly higher than those of middle class clients (Beutler, 1981; Lerner, 1972). Nearly all of the respondents fall within and originate from higher social class backgrounds. As pointed out by schema research (Fiske & Taylor, 1984; Leyens et al, 1994), seeing an individual as different from ourselves produces less of an attraction to that individual. This possible perceived difference between respondent and client could have produced lower motivation on the part of the respondents to provide long term therapy for the lower class client. However, this does not explain the differing results between the CGCA and BCPA respondents. Another possible explanation for the significant difference on the part of CGCA respondents could be that the client's ability to pay was taken into account in respondents' estimates of suggested length of stay in therapy. It may be argued that more BCPA members are able to charge fees for services directly through the provincial medical plan an option not available to most CGCA members. However, since only one CGCA respondent mentioned ability to pay, it is difficult to ascertain whether this had any significant impact in their decisions. Previous studies dating back to the 1950s (Hollingshead & Redlich, 1958) showed that, even with payment guaranteed, therapists displayed a lowered interest in treating lower social class clients. Both previous (Dohrenwend, 1973; Kessler & Geary, 1980) and more recent (Harder et al, 1990) longitudinal studies on levels of psychological distress and prognosis have revealed that lower class individuals develop greater levels of psychopathology and  122 take longer to recover. Virtually all health studies (Canadian Public Health Association, 1997) reveal that health is directly related to socio-economic status, and individuals from the lower socio-economic levels are more apt to fall ill and take longer to recoverfroma wide range of both physical and mental illnesses. This being the case, it would seem more logical and effective to offer the greater length of stay in therapy to the lower class client. Problem Evaluation Results In reviewing results of the problem evaluation, no differences linked to social class were found to be statistically significant when examined by total sample population or by association. Female respondents to the lower class client produced a significantly lower prognosis when compared with female respondents to the middle class client. While it is not possible to determine with confidence why female respondents rated the lower class client less positively on prognosis, there are several possible explanations. One explanation may be that female respondents were demonstrating more bias than male respondents. This seems less likely however, when one considers the rating results on the client characteristics. Female respondents' evaluations produced less significant differences linked to client social class on more of the variables than did male respondents' evaluations. A more plausible explanation for this difference may be that female respondents were somewhat more apt to take into account social contexts and therefore, provide a more realistic prognosis for the lower class client considering the added stressors that accompany poverty, social bias, and lower access to and availability of a variety of social supports. Since this particular evaluation was the only one to reach significance, one very  123 possible explanation may be the occurrence of a Type I error. Choice of Therapy No significant differences arose in respondent choice of therapy offered and client social class. BCPA respondents displayed a slightly higher tendency to offer cognitive therapy to the middle class client (middle class client = 70%, lower class client = 54%). Whether this tendency is linked to a belief that lower class clients would benefit less from an insight-oriented form of therapy is difficult to ascertain. Research carried out in the 1950s - 1970s suggested that lower class clients benefited less from psychodynamic psychotherapy (Hollingshead & Redlich, 1958; Lorion & Felner, 1986). However, Brill and Strorrow (1960) found that long-term psychoanalytic treatment was offered much morefrequentlyto middle and upper class clients, while drug therapy and inpatient services were offered morefrequentlyto lower class clients regardless of whether the presenting problems were alike. Beutler's (1981) study found no outcome differences linked to client social class, using cognitive-based therapy. While CGCA respondents offered cognitive therapy equally to both middle and lower class clients (middle class client = 50%, lower class client = 50%), behavioural therapy was suggested slightly morefrequentlyfor the lower class client (middle class client = 41%, lower class client = 50%). Behaviour therapies focus on producing a behavioural change. With the added stressors impacting on almost every aspect of life in the lower social class, a focus on effecting behaviour change may have been viewed by some as more of an imperative for the lower class client. Brill & Strorrow (1961) and Lorion & Felner (1986) found that lower class clients desired somewhat more direct intervention on the part of the therapist, and therapy aimed at symptom relief. Further  124  research in this area could help clarify whether, because of the more difficult social situation for many lower class clients, a behavioural approach might provide more options for short-term change. Summary It is evident in these findings that respondents demonstrated a differential perception, evaluation and proposed treatment of the lower social class client. Comparison by professional association produced inconclusive results. While BCPA respondents produced more negative evaluations of the lower class client on the client characteristics, CGCA respondents produced more significant differences in the frequencies and choices of presenting problems and in the suggested length of stay in therapy also linked to client social class. Findings on the client characteristics linked to gender do appear to lend limited support to my hypothesis that, due to a heightened awareness of gender biases and the inclusion of social context within feminist counselling, female respondents produced less negative evaluations of the lower class client than male respondents.  However, results  on the problem evaluation, presenting problems and suggested length of stay in therapy linked to respondent gender and client social class remain inconclusive. In comparing results by respondent levels of education, bias appeared more strongly among master's respondents than among doctoral respondents on the client characteristics. This finding is in contradiction to my original hypothesis that higher levels of education would produce more bias.  125 Implications Clinicians employ the same method of cognitive processing as other individuals. Initial intake contacts with a particular client, including client demographic information, presenting problem and physical appearance, may trigger schemas categorising the client as a member of a particular out-group (Smith, 1988). The findings suggest that therapists may use indicators of socio-economic status to evaluate a client's suitability for therapy as well as to evaluate a client's characteristics in terms that are linked to social class stereotypes. This can lead to the perpetuation of social class stereotyping and class bias in the clinical setting (Hertzberg & Eschbach, 1982). Under these circumstances, it is realistic to infer that the lower social class client is not offered as thorough or fair a therapeutic assessment or environment as is offered to the middle class client. Until recently, social context was given short shrift within the counselling setting. Individualistic explanations for a client's problems and life situation dominated the field. This atmosphere tends to be one that places responsibility as well as blame for most life situations on the individual. This neglect of the social context allowed for little understanding or empathy for the realities for lower class individuals within a society where there are, in fact, considerably more obstacles and less opportunities in nearly every aspect of their lives. Some may argue that lower and middle class clients, due to a variety of external and internal factors, are different and, therefore, therapists are evaluating the lower class client based on a correct judgement or evaluation. One might realistically expect certain client differences linked to client social class. However, research has been inconclusive (and/or disregarded) on exactly what many of these differences may be and how they  126 might be best handled in a counselling setting. If, as research suggests, some real differences linked to client social class do exist, then both research into the exact differences and the provision of appropriate academic training for counselling lower social class clients is significantly lacking. In view of the fact that, within the category of clients on the Personal Network Grid, the most frequently checked off category was welfare recipient, more effective and thorough treatment programs need to be designed and integrated into already existing programs. On the other hand, if, as suggested by Sutton and Kessler's (1986) study and in the results of this work, therapists are exhibiting negative evaluation linked to social class stereotypes, then academic as well as other training programs must actively participate in moderating and eliminating social class bias among its trainees and trainers. It is probable that both negative stereotyping and actual differences are in effect when counselling lower social class clients. The implication of both of these issues is that lower social class clients are evaluated more negatively, and may not be offered as positive or thorough a therapeutic environment as the middle class client. It is important for graduate programs to develop and offer courses and written material that educate graduates about social class and class stereotyping. Further, closer ties with departments that have a tradition of carrying out research on class issues and have already proven to be more responsive to social class need to be encouraged and cultivated. Non-university training programs, frequently attended by practicing professionals, also need to incorporate social class into their existing agendas. Cultural and gender training and the inclusion of culturally and gender relevant materials within university counselling programs serves to increase counsellors' awareness  127 of and sensitivity to the importance of culture and gender on one's life experiences. The lack of focus on social class as a predominant factor can serve to perpetuate class stereotypes, and maintain a lack of awareness of the effects of social class on psychological health and wellbeing. When one considers therapists' years of training, clinical supervision, and the constant need to demonstrate at least a moderate degree of compassion and acceptance of people dissimilar to themselves, thefindingthat ignorance or bias continues to persist within this group, suggests that social beliefs and stereotypes may be deeply ingrained. Research in schema theory and stereotyping has revealed that stereotypes are long lasting and are resistant, although not impervious, to change (Fiske & Taylor, 1984). For individuals needing and expecting unbiased assistance in a therapeutic environment, the likelihood that they will be faced with persistent social biases, as demonstrated in previous research and in this study, constitutes a severe indictment of the profession. Strengths and Limitations This study has several strengths. By providing all respondents with the same case history, with the only differences being in aspects of social class and class background, it was possible to clearly isolate the effects of the social class information for analysis. In addition, by provided a Caucasian male as the client, it was possible to avoid the confounds of gender and race effects. To my knowledge, there has never been a study of therapist and/or counsellor judgement differences based on client social class in Canada. Using members of both the CGCA and the BCPA in British Columbia, allowed for a representative sample of counsellors and therapists across the province, and crosscomparison based on a variety of respondent demographics (e.g. degree, level of  128 education, gender, association membership, etc.). Therefore, this study, while partially replicating a similar American study carried out in 1981, may be more representative of Canadian therapist and counsellor responses. Another strength is the return rate on the questionnaire mailout. More than onethird (N = 111) of the random sample (N = 300) returned completed questionnaires, providing a large sample size from which to carry out analyses and comparisons. Analogue studies also contain certain built-in weaknesses. As with all analogue studies, a major limitation of the current research lies in its generalizability to real life counselling practice. It is not always possible to infer that responses to a written case study are analogous to actual clinical evaluation. It is difficult to determine whether negative clinical perception, treatment and evaluation would be lessened or increased within an actual clinical setting with real clients. However, some studies suggest that individuals who display significant racial bias in responses to written questionnaires demonstrate higher levels of bias when tested in real life situations (Crosby et al., 1980). Many counsellors and therapists do rely on written summaries in client evaluation and therapist decision-making. By presenting the respondents with as much information as possible, in the form of a personal information sheet, results of psychological testing and the initial interview, I hoped to replicate a clinical evaluation as closely as possible. Another limitation is that this research does not extend into an understanding of potentially real differences between middle and lower class clients. The lines between actual differences and bias are not clearly deligneated. This is an important point because, if differences are real, therapists need to learn more about these differences in order to increase an understanding of and comfort for the client.  129 Other limitations include the fact that the hypothetical client was male and findings may not necessarily apply to lower class female clients. In addition, the results represent responses within the province of British Columbia only and may not be generalizable to other areas of the country. One further limitation was related to respondents' social class and class background. Studies have found that client/therapist similarity of background and values has produced positive treatment and outcome ratings (Sladen, 1982). However, the significantly low numbers of lower social class background respondents made it impossible to determine whether this would have had a positive impact on clinical evaluation. If the sample population is representative of the British Columbian general population of therapists and counsellors, it is reasonable to assume that very few comefromlower class backgrounds. One might assume that negative stereotyping might be lower among individuals whose class background was similar to those of lower class clients. On the other hand, receiving education in a predominantly middle class environment and value system, with material focused and based predominantly on middle class populations may impact on the perceptions of all students. Suggestions For Future Research  Recent published research in the area of therapist perceptions, evaluations and treatment of lower socio-economic status clients and their effects on outcome in therapy is significantly lacking both within Canada and the United States. A Canadian-wide study linked to client social class could help to shed light on whether differences noted in this study are particular to British Columbia or reflections of a nation-wide difference in therapists' perceptions, evaluations and treatment linked to  130 client social class. Since stereotypes tend to be enduring and difficult to change, it is also important to design research that examines ways to initiate stereotype change and incorporate this into training designed to educate students about social class. In conjunction with this is the need for studies of possible actual differences in clients from differing social class backgrounds, in what ways these differences affect the counselling experience, and how best to work with lower social class clients. Studies of the impact of differing counsellor and client value systems, and in what ways these impact on the counsellor/client relationship and counselling experience, might also provide insightful and useful information both for training and clinical purposes. A review of course materials and training programs to examine possible social class bias (either explicitly or by way of exclusion of class context) in both research and education could also be undertaken and prioritised. Few individualsfromlower socio-economic levels reach graduate levels of education. A study to explore lower and working class students' experiences of attending institutions that reflect and uphold middle class culture, values and ideology might be enlightening. Since few lower and working class students continue on into graduate programs, investigation of experiences of students, from a social class perspective, could shed light on the obstacles or hindrances they might face, and deterrencesfromentrance to and continuation in graduate school. Because social class is more invisible than culture and gender, and because North American society encourages a belief that a class system does not exist here, lower class students remain, to some extent, invisible. This can serve to deny or invalidate their experiences and values systems, and allows the assumption that  131 all students share similar histories, values and beliefs. Another possible area of research is a qualitative analysis and comparison of both lower, working and middle class individuals' experiences in counselling. Psychological research linked to the study of the lower social classes has been minimal. As described by Reid (1992), personal affiliation leads individuals to study populations more like themselves. For example, until women began participating in producing research, most studies involved male populations. In a similar manner, most research, including the testing of theories and standardized tests has been carried out on white, middle class populations. Lower class populations are then compared to this standard. Because few individualsfromthe lower social classes reach higher levels of academia (or have done so despite barriers associated with social class), little enthusiasm has been shown for extensive studies of lower social class populations. This in itself, has meant an inadequate focus on a significantly large portion of our entire population. Conclusion Over the past twenty years, a variety of cross-cultural and feminist counselling models have been developed, as well as guidelines for counselling women and ethnic groups. While some of these address the issue of counselling the poor, frequently this is done only in so much as the poor are members of an ethnic minority or single-parent women. The lack of training or focus on the specific needs and life-experiences of all individuals within the lower social classes would appear to perpetuate their invisibility and the notion that they are more responsible for their negative life situations. If therapists perceive lower class clients as less suitable for therapy, and as exhibiting less positive outcomes, do we then believe that the therapists' expectations and  132 beliefs have no effect on the course and outcome of therapy?  If an individual is already  uncertain about involvement in mental health treatment, the lower socio-economic status client's awareness of therapist messages may constitute a hindrance to the client's therapeutic process and outcome. Lower socio-economic status clients have limited access to mental health and other counselling services. In addition, the services available are frequently less culturally and socially relevant than for more privileged clients. The emphasis within our society and within counselling to focus on individual action as the prime determinant of success or failure adds an implicit negative judgement on those less economically successful. To see a person as separatefromthe contexts of his or her life devalues the experience of many individuals, handicaps the therapist's capacity to provide help and facilitate change, and in addition does not allow for examination and questioning of one's own class based beliefs and value structures. Clinicians employ the same method of cognitive processing as other individuals. 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Special report on the socially and economically disadvantaged. Health and Welfare Canada. Wright, E. O., Costello, C , Hachen, D. & Sprague, J. (1982). The American class structure. American Sociological Review, 47, 709-726.  140  Appendix A  THERAPIST DECISION-MAKING Directions; 1. 2. 3. 4. 5. 6.  Remove, read, and retain the letter of consent. Read the client Personal Information Form, Standardized Testing Results and Intake Interview on pages one and two of this questionnaire booklet. After reading all of the client information, complete the questionnaire in order. Please do not look ahead or go back to change your answers once you have completed them. If you wish to enter the prize drawing, fill in your name and address on the attached form and seal it in the small envelope. Return the questionnaire and sealed draw envelope to me in the large stamped and addressed envelope. If you would like to receive a synopsis of the results, mail in the Request For Synopsis of Results form in a separate envelope. Do not include this in the draw envelope or with your questionnaire.  This questionnaire will take approximately one-half hour of your time and contains a number of questions that ask for your impressions of a hypothetical client. We recognize that no client can be described in absolute terms with such limited information. However, for the purposes of this research, your best estimate of characteristics and probable results is requested. Thank You.  141 PERSONAL INFORMATION FORM This form is to help your counsellor become better acquainted with you Please fill in as much as you can Omit any item you do not want to answer. Name  / & ^ a J c " (First)  (Last) Aqe^V  Date of birth  Ethniclty/Raclal origin  S3  C^^i^LLa^ 3  Education: Number of years Occupation  (d)  (Initial) /  (m)  L  Manned  How many times have you been married  (y)  Oicrvui^  Presently. Employed  Separated  Divorced  Number of children: 3  2,  /  _  L*JLj>J  \*/  / (m)  Sex(M/F)_£2_ (y) Religious Preference  Degrees  r^^iL.T^y^  Marital Status: Single  /  .  Date (d)  :  Unemployed < / _  Widowed How many of them live with you? »3_  Family Background While y o u were growing up, were your parents: MarriecWiving together  Divorced ^  Father remarried Father's occupation Father's education  Separated  Mother remarried  ^o^JL  Deceased: Mother Mother's occupation  6>  ^sr^i^JU^  Number of brothers and sisters  #  Mother's education  Father  -^j^r^L^^Se^fu  <^/ui^*kes  How many were younger/older than you? Younger  —  Older  2-_  Physical Conditions and Characteristics  Heioht£>gl.  /jLu.  .  Weight  ZOQ^JL.  :  Physical disabilities or health problems? (Describe)  Any lengthy hospitalizations or severe injuries? (Describe)  UQ*  Presenting Problem^) W h y y o u have chosen to come for counselling?  Underline any of the following that apply t o y o u : Frequent h e a d a c h e s , b a c k a c h e s , drinking or drug problems, dizziness, overeating, poor appetite, vomiting, digestive problems, s l e e p l e s s n e s s , fainting spells,pension, continued tiredness, tearfulness, visual or hearing problems .  142  Name: Results of standard psychological testing showed elevations on the following scales: Anxiety: 80th percentile Depression: 82nd percentile Paranoia. 71st percentile  Intake Interview:  Robert -is a talZ, slightly stocky man, who arrived {or this {-Out sessio dressed in a T-shirt and jeans. Robert sat somewhat sti{{ly throughout the { meeting, and made. onZy intermittent eye.-contact. H-ii predominant mood app be somewhat agitated and anxious. Robert stated that he, tost kis job -in the, past year and -is currently su hti {amiZy on monthly wel{are cheque*, Robert haA concerns about being abl {orhts {amity. Hehashadmany bout* o{ unemployment over the years. Rob {other lc{t the family when Robert was quite young, leaving hi* mother to r £ive children on welfare. Robert shared that one week, previously, hi* wi{e had &sked him {or to Robert admitted to her that he had blown mo-it o{ h-is welfare cheque that w he stated he has problems stopping himsel{ {rom doing lately, H-is wi{e had angry at thts, and Robert lost his temper and broken several objects before sl hi* wile to stop her {rom "nagging " him. Robert also mentioned that one day this past week he had kept bis child {rom school, as he {eared he would never see them again. H-U wi{e was not his behavior and told him he needed to "get his act together ". He described his thoughts recently as racing all the time lately, includin night, preventing him {rom sleeping. He also stated that he {orgets things, an {eeli cu>i{heis going crazy. He holds tittle hope that counselling will be help Robert alio said that he has been drinking more than usual recently.  Now that you have read the client information, please answer the questions in each of the sections that follow. You will be asked questions about the client, his concerns, and possible choices for treatment  143 PART I: Case History Rating Scales:  Please circle one number on each of the bar graphs that best describes your impression of the client. 1. Severity of presenting problem: Very Severe 1 2  Very Mild  2. Perceived client motivation for change: Very Strong 1 2 3  _ 7  3. Perceived client self-concept: Excellent 1  Very Weak  Poor  4. Prognosis: Favourable  Bleak  5. Likelihood of referring this client for psychiatric assessment: Very High 1 2 3 4 5  7  Very Low  6. Your personal interest in treating this client: Very Strong 1 2 3  _ 7  Very Weak  Case History Questions:  1. Many counsellors modify their approachfromone client to another. Please describe the approach (e.g. structured vs open-ended, directive vs nondirective, cognitive vs behavioral vs affective, etc.) you would use with this client and why.  144  2. What problems and issues do you feel it would be important to address first with this client?  3. Recommended number of sessions in counselling/therapy:  PART H:  Client Characteristics:  Based on your brief first impression, please check to what extent each of the following characteristics might best describe the hypothetical client. Yourfirstresponse is best. Please do not refer back to the case history as you answer. very closely describes client  expressive pessimistic trustworthy competent unintelligent involve industrious impulsive responsible ignorant friendly loud clean emotional moral incapable defensive aggressive dishonest  closely describes client  only slightly describes client  not related  only slightly describes client  closely describes client  very closely describes client  inexpressive optimistic untrustworthy incompetent intelligent withdrawn lazy reliable irresponsible knowledgeable hostile quiet dirty controlled immoral capable receptive peaceful honest  145  PART HI:  Personal Network:  For this section, please indicate whether you know anyone in each of the occupations listed. Do not put more than one tick for any one person. Do not put more than one tick in any one box. Example of how to answer this section:  TYPE OF JOB: Do you know anyone who works in the following industries?  Example 1: secretary Example 2: counsellor  TYPE OF RELATIONSHIP: Acquaintance Close Friend Relative  Colleague  Client x  X X  X  x  Example 1, would indicate that you know an acquaintance and a client who are both secretaries. Example 2, would indicate that you know a close friend, a relative and several colleagues, all three of whom are counsellors.  TYPE OF JOB: Do you know anyone who works in the following industries?  business owners or managers university or college professors primary or secondary school teachers bankers accountants engineers bus drivers seasonal farm workers or fishers auto mechanics plumbers/electricians waiters/waitresses (nonsupervisory) police officers loggers/mill workers firefighters (non volunteer) provincial/federal politicians computer/electronic specialists biologists/botanists/chemists nurses/physiotherapists doctors architects lawyers unskilled construction workers janitorial/cleaning personnel gas station attendants unskilled factory workers longterm welfare recipients truck drivers (non owners) social workers  TYPE OF RE LATIONSHIP: Acquaintance Close Friend Relative  Colleague  Client  146  PART IV:  Demographic Information:  The following questions pertain to important background information to help ensure that a range of professionals have responded. Please answer as honestly as you can. Results are completely anonymous. Thank you for responding. 2. Your gender:  1. Your age:  D Female  • Male  3. Your ethnic/racial identification (Please circle only one.): 1 White 2 Aboriginal 3 Asian 4 East Indian 5 Black 6 Hispanic 7 Other - Please specify 4. Highest level of education your parents or significant adults you lived with completed while you were growing up: (If there are more than two important adults, please answer for the ones you lived with the longest.) Mother/Significant Adult  Father/Significant Adult  1 2 3 4 5  1 2 3 4 5  6  6  7 8 9 10 11  7 8 9 10 11  No formal education Some grade school Completed grade school Some high school Completed high school Some college Completed college Some university Completed undergraduate degree Some graduate work Completed graduate degree  5. Your father's/significant adult's occupation(s) while you were growing up: (If more than one occupation, list the two longest held starting with the more recent)  6. Your mother's/significant adult's occupation(s) while you were growing up: (If more than one occupation, list the two longest held starting with the more recent)  Please continue on to the last page  147  7. Did your father/mother/significant adult receive public assistance (e.g. welfare, unemployment insurance, disability, etc.) while you were growing up? •  Yes  •  No  If Yes, approximately how frequently?  Often  Sometimes  Rarely  8. Number of years of professional therapeutic practice after completing your training: 9. Your highest degree and the year it was completed: D Bachelor's  D Master's  D Doctorate  10. Programfromwhich you received your highest degree: 1 2 3 4 5 6  Counselling Psychology Clinical Psychology Educational Psychology Counsellor Education Social Work Other (Please Specify):  11. Where did you receive your highest degree? 1 2 3  within British Columbia outside of British Columbia, within Canada outside of Canada Please indicate which country:  12. Your usual work setting: (If more than one applies, please circle the two most frequent.) 1 2 3 4 5  University or college counselling centre Nonprofit community agency Government agency Private profit agency Private practice  13. Residential setting of the majority of your clients: 1 2 3 4  Rural Suburban Urban Mixed  THANK YOU AGAIN FOR PARTICIPATING!!  148  Appendix B Independent T-Test Results of Respondents' Years of Counselling Experience by Client Social Class  Variable Years Middle Class Exp. Lower Class Mean Difference = 1.78  Number of Cases  Mean  SD  SE of mean  56 54  13.50 11.72  7.72 7.72  1.03 1.05  Levene's test for Equality of Variances: F=091 P = .764  T-Test for Equality of Means  Variances  t-value  df  2-Tail Sign  1.208 1.208  108 107.855  .230 .230  Equal Unequal  Mean Diff  SE of Diff  95% CI for Diff  1.78 1.78  1.47 1.47  (-1.14, 4.96) (-1.14, 4.96)  Independent T-Test Results of Respondents' Years of Counselling Experience by Professional Association  Variable Years Exp.  Number of Cases  Mean  SD  SE of mean  62 48  10.37 15.54  7.00 7.72  .89 1.11  CGCA BCPA  Mean Difference = 5.17  Levene's test for Equality of Variances: F = .799  P = .337  T-Test for Equality of Means  Variances  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  Equal Unequal  -3.672 -3.626  108 95.895  .000 .000  -5.17 -5.17  1.41 1.43  95% CI for Diff (-7.96, -2.38) (-8.00, -2.34)  149  Appendix C independent /'-Tests on Respondents' Evaluations of the Problem Total Sample Population Presenting problem Number of Cases  Variable  middle c l a s s lower c l a s s  Mean  Mean D i f f e r e n c e Levene's Test  = -.2104  f o r E q u a l i t y of V a r i a n c e s : F= .030  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  -1.35 -1.35  . 109 .111  . 809 . 828  2 .2182 2 . 4286  55 56  SE of Mean  SD  109 109.00  P= .863  SE of D i f f  95% CI f o r D i f f  155 155  (-.519, .098) (-.519, .098)  . 179 . 179  Client self-concept Number of Cases  Variable  middle c l a s s lower c l a s s  55 54  Mean D i f f e r e n c e Levene's Test  .09 .10  SD  5.8545 5.8704  SE of Mean  .931 . 802  . 126 . 109  = -.0158  f o r E q u a l i t y o f V a r i a n c e s : F= .201  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail S i g Equal Unequal  Mean  107 105.22  . 925 .924  SE of D i f f . 167 .166  P= .655 95% CI f o r D i f f  (-.346, (-.34.6,  .315) .314)  Appendix C Independent T-Tests on Respondents' Evaluations of the Problem Total Sample Population Motivation for change  Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  . 54 . 54  SD  SE of Mean  4.3455 4 .2143  1.220 1.317  . 165 . 176  = .1312  f o r E q u a l i t y of Variances: F= .249  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  Mean  109 108.63  P= .619  SE of D i f f  95% CI f o r D i f f  .241 .241  (-.347, .609) (-.347, .609)  . 588 . 587  Personal interest in treating the client Number of Cases  Variable  middle c l a s s lower c l a s s  54 56  Mean D i f f e r e n c e Levene's T e s t  -.38 .38  SD  2.9074 3.0179  1. 444 1 . 601  SE of Mean  . 197 .214  = -.1104  f o r E q u a l i t y of V a r i a n c e s : F= .309  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  Mean  108 107.53  .705 . 705  P= .579  SE o f D i f f  95% CI f o r D i f f  .291 .291  (-.688, .467) (-.686, .466)  151  Appendix C Independent /'-Tests on Respondents'.Evaluations of the Problem Total Sample Population Prognosis Number of Cases  Variable  middle c l a s s lower c l a s s  53 56  Mean D i f f e r e n c e Levene's Test  Mean  3.4151 3.6964  -1.21 -1.20  SE of Mean  1.307 1.127  .180 .151  = -.2813  f o r E q u a l i t y o f V a r i a n c e s : F= 1.641  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail S i g Equal Unequal  SD  107 102.79  P= .203  SE of D i f f  95% CI f o r D i f f  .233 .234  (-.744, .181) (-.746, .184)  .231 .233  Likelihood of referring for psychiatric assessment Number o f Cases  Variable  middle c l a s s lower c l a s s  54 56  Mean D i f f e r e n c e Levene's Test  Mean  3.4630 3.8214  -1.04 -1.04  SE o f Mean  1.668 1.927  .227 .257  = -.3585  f o r E q u a l i t y o f V a r i a n c e s : F= 1.304  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  SD  108 106.78  .300 .299  SE o f D i f f .344 .343  P= .256 95% CI f o r D i f f  (-1.041, .324) (-1.039, .322)  152  Appendix C Independent T-Tests on Respondents' Evaluations of the Problem (BCPA only) Presenting problem Number of Cases  Variable  middle c l a s s lower c l a s s  Mean  23 26  Mean Difference Levene's Test  2.4783 2.5385  -.23 -.23  SE of Mean  .846 .948  .176 .186  = -.0602  f o r E q u a l i t y of Variances: F= .047  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  47 46.99  P= .830  SE of D i f f  95% CI f o r D i f f  .258 .256  (-.579, .459) (-.576, .455)  .817 .815  Client self-concept Number of Cases  Variable  middle c l a s s lower c l a s s  23 24  Mean Difference Levene's Test  Mean  5.8696 6.0417  -.82 -.81  SE of Mean  .757 .690  .158 .141  = -.1721  f o r E q u a l i t y of Variances: F= .867  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  45 44.19  .419 .420  P=  .3 57  SE of D i f f  95% CI f o r D i f f  .211 .212  (-.598, .253) (-.599, .254)  153  Appendix C independent 7-Tests on Respondents' Evaluations of the Problem (BCPA only) Motivation for change Number of Cases  Variable  middle c l a s s lower c l a s s  Mean  23 26  Mean D i f f e r e n c e Levene's Test  4.2174 4.2308  -.04 -.04  SE of Mean  1.166 1.177  .243 .231  = -.0134  f o r E q u a l i t y of Variances: F= .008  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  47 46.37  95% CI f o r D i f f  SE of D i f f  .968 .968  P= .928  .335 .335  (-.688, .662) (-.688, .662)  Personal interest in treating the client Number of Cases  Variable  middle c l a s s lower c l a s s  22 26  Mean D i f f e r e n c e Levene's Test  Mean  3.2727 3.8077  -1.09 -1.11  SE of Mean  1.518 1.833  .324 .360  = -.5350  f o r E q u a l i t y of V a r i a n c e s : F= 2.209  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  46 45.98  .282 .274  SE of D i f f .491 .484  P= .144  95% CI f o r D i f f (-1.524, .455) (-1.509, .439)  154  Appendix C Independent /-Tests on Respondents' Evaluations of the Problem (BCPA only) Prognosis Number of Cases  Variable  middle c l a s s lower c l a s s  23 26  Hean Difference Levene's Test  Mean  3.3478 3.8846  -1.54 -1.53  i.265 1.177  SE of Mean  .264 .22 1  = -.5368  f o r E q u a l i t y of Variances: F= .204  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  47 45.25  SE of D i f f  .131 .133  .349 .351  P= .653 95% CI f o r D i f f (-1.239, .166) (-1.243, .169)  Likelihood of referring for psychiatric assessment Number of Cases  Variable  middle c l a s s lower c l a s s  23 26  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  3.6087 3.8846  1.559 1.904  .325 .373  = -.2759  f o r E q u a l i t y of V a r i a n c e s : F= .411  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  -.55 -.56  47 46.74  .585 .580  SE of D i f f .501 .495  P= .524 95% CI f o r D i f f (-1.285, .733) (-1.272, .720)  155  Appendix C Independent T-Tests on Respondents' Evaluations of the Problem (CGCA only) Presenting problem Number of Cases  Variable  middle c l a s s lower c l a s s  32 30  Mean Difference Levene's Test  -1. 64 -1. 64  SE of Mean  740 711  2.0313 2 .3333  131 130  = -.3021  f o r E q u a l i t y of Variances: F= .083  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  Mean  60 59.96  P= .775  SE of D i f f  95% CI f o r D i f f  .185 .184  (-.671, .067) (-.671, .067)  . 107 . 106  Client self-concept Number of Cases  Variable  middle c l a s s lower c l a s s  32 30  Mean D i f f e r e n c e Levene's Test  Mean  5.8438 5.7333  .45 .45  1. 051 . 868  . 186 .159  = .1104  f o r E q u a l i t y of Variances: F= .004  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  SE of Mean  SD  60 59.10  .655 .653  P= .952  SE of D i f f  95% CI f o r D i f f  .246 .244  (-.381, .602) (-.378, .599)  156  Appendix C •Independent /'-Tests on Respondents' Evaluations of the Problem (CGCA only Motivation for change Number of Cases  Variable  middle c l a s s lower c l a s s  32 30  Mean Difference  Mean  SD  4.4375 4.2000  SE of Mean  1.268 1.448  .224 264  = .2375 . 480  Levene's Test  f o r E q u a l i t y of Variances:  t - t e s t t-value f o r E q u a l idf t y of2 -Means Variances Tail S i g Equal Unequal  .69 .69  60 57.77  F= .506  SE of D i f f  95% CI f o r D i f f  .345 .347  (-.453. .928) (-.457, .932)  .494 .496  Personal interest in treating the client Number of Cases  Variable  middle c l a s s lower c l a s s  32 30  Mean D i f f e r e n c e Levene's Test  Mean  2.6563 2.3333  1.07 1.09  SE of Mean  1.359 .959  .240 .175  = .3229  f o r E q u a l i t y o f Variances:  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  SD  60 55.84  .287 .282  F= 2.469  P= .121  SE of D i f f  95% CI f o r D i f f  .300 .297  (-.278, .924) (-.273, .918)  157  Appendix C Independent T-Tests on Respondents' Evaluations of the Problem (CGCA only) Prognosis Number of Cases  Variable  middle c l a s s lower c l a s s  30 30  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  3.4667 3.5333  1.358 1.074  .248 .196  = -.0667  f o r E q u a l i t y of V a r i a n c e s : F= 1.695  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  -.21 -.21  58 55.08  P= .198  SE of D i f f  95% CI f o r D i f f  .316 .316  (-.700, .566) (-.700, .567)  .834 .834  Likelihood of referring for psychiatric assessment Number o f Cases  Variable  middle c l a s s lower c l a s s  31 30  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE o f Mean  3.3548 3.7667  1.762 1.977  .316 .361  = -.4118  f o r E q u a l i t y o f V a r i a n c e s : F= 1.146  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  -.86 -.86  59 57.73  .393 .394  SE of D i f f .479 .480  P= .289 95% CI f o r D i f f  (-1.371, .547) (-1.373, .549)  158 Appendix C Independent T-Tests on Male Respondents' Evaluations of the Problem Presenting Problem Number Variable  of Cases  Mean  SD  SE of mean  25 28  2.28 2.46  .61 .74  .12 .14  middle class lower class  Mean Difference = .18 Levene's test for Equality of Variances: F = 2.266 P = .138 T-Test for Equality of Means Variances  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  Equal Unequal  -.976 -.987  51 50.700  .334 .328  -.18 -.18  .19 .19  (-.56,. 19) (-.56,.19)  Motivation for Change Number Variable  of Cases  Mean  SE)  SE of mean  25 28  4.32 4.00  1.07 1.19  .21 .22  middle class lower class  Mean Difference = .32 Levene's test for Equality of Variances: F= 040 P=842 T-Test for Equality of Means Variances  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  Equal Unequal  1.027 1.033  51 50.993  .309 .307  .32 .32  .31 .31  (-.31,.95) (-.30, .94)  159  Appendix C Independent T-Tests on Male Respondents' Evaluations of the Problem Client Self-Concept  Variable middle class lower class  Number of Cases  Mean  SD  SE of mean  25 27  5.68 5.78  1.03 .93  .21 .18  Mean Difference = .10 Levene's test for Equality of Variances: F = .063 P = .803 T-Test for Equality of Means  Variances  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  Equal Unequal  -.359 -358  50 48.506  .721 .722  -9.78E-02 -9.78E-02  .27 .27  (-.64, .45) (-.65, .45)  Prognosis Variable middle class lower class  Number of Cases  Mean  SD  SE of mean  24 28  3.58 3.36  1.32 1.03  .27 .19  Mean Difference = .22 Levene's test for Equality of Variances: F = 2.218 P = . 143 T-Test for Equality of Means  Variances Equal Unequal  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  .696 .683  50 43.219  .490 .498  .23 .23  .33 .33  (-.43, .88) (-.44, .89)  160 Appendix C Independent T-Tests on Male Respondents' Evaluations of the Problem Likelihood of Referring for Psychiatric Assessment  Variable  Number of Cases  Mean  SD  SE of mean  25 28  3.40 4.00  1.41 2.05  .28 .39  middle class lower class  Mean Difference =  Levene's test for Equality of Variances: F = 6.294 P = .015  T-Test for Equality of Means Variances  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  Equal Unequal  -1.233 -1.249  51 48.037  .227 .218  -.60 -.60  .49 .49  (-1.58, .38) (-1.57, .37)  Personal Interest in Treating the Client Number of Cases  Mean  SD  SE of mean  middle class lower class  25 28  2.92 2.64  1.53 1.39  .31 .26  Mean Difference = .28  Levene's test for Equality of Variances: F= 484 P = .490  Variable  T-Test for Equality of Means Variances Equal Unequal  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  .691 .688  51 48.939  .493 .495  .28 .28  .40 .40  95% CI for Diff (-.53, 1.08) (-.53, 1.09)  161 Appendix C Independent T-Tests on Male Respondents' Evaluations of the Problem Presenting Problem Number of Cases  Mean  SD  SE of mean  middle class lower class  25 28  2.28 2.46  .61 .74  .12 .14  Mean Difference = 1 8  Levene's test for Equality of Variances: F = 2.266 P = .138  Variable  T-Test for Equality of Means Variances Equal Unequal  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  -.976 -.987  51 50.700  .334 .328  -.18 -.18  .19 .19  (-.56, .19) (-.56, .19)  Motivation for Change Variable  Number of Cases  Mean  SD  SE of mean  25 28  4.32 4.00  1.07 1.19  .21 .22  middle class lower class  Mean Difference = .32 Levene's test for Equality of Variances: F = .040 P = .842 T-Test for Equality of Means Variances Equal Unequal  t-value  df  2-Tail Sign  1.027 1.033  51 50.993  .309 .307  Mean Diff  SE of Diff  95% CI for Diff  .32 .32  .31 .31  (-.31,.95) (-.30, .94)  162  Appendix C Independent T-Tests on Female Respondents' Evaluations of the Problem Client Self-Concept  Variable  Number of Cases  Mean  SD  SE of mean  31 26  5.97 6.00  .84 .63  .15 .12  middle class lower class  Mean Difference = .03 Levene's test for Equality of Variances: F = .572  P = .500  T-Test for Equality of Means 2-Tail Sign Variances Equal Unequal  t-value  df  -.162 -.166  55 54.474  .872 .869  Mean Diff  SE of Diff  95% CI for Diff  -3.23 -3.23  .20 .19  (-.43, .37) (-.42, .36)  Prognosis  Variable  Number of Cases  Mean  SD  SE of mean  30 27  3.30 4.04  1.29 1.16  .24 .22  middle class lower class  Mean Difference = .74 Levene's test for Equality of Variances: F = 1.208  P=277  T-Test for Equality of Means 2-Tail Sign Variances  t-value  df  Equal Unequal  -2.258 -2.271  55 55.000  Mean Diff .028 .027  -.74 -.74  SE of Diff .33  95% CI for Diff (-1 39,)  .32  (-L39,)  163  Appendix C Independent T-Tests on Female Respondents' Evaluations of the Problem Likelihood of Referring for Psychiatric Assessment Number of Cases  Mean  SD  SE of mean  middle class lower class  30 27  3.57 3.59  1.87 1.82  .34 .35  Mean Difference = .02  Levene's test for Equality of Variances: F = .461  Variable  P = .500  T-Test for Equality of Means 2-Tail Sign Variances Equal Unequal  t-value  df  .053 .053  55 54.626  .958 .958  Mean Diff  SE of Diff  95% CI for Diff  -2.59E-02 -2.59E-02  .49 .49  (-1.01, .96) (-1.01, .96)  Personal Interest in Treating the Client Number of Cases  Mean  SD  SE of mean  middle class lower class  30 27  2.93 3.37  1.39 1.76  .25 .34  Mean Difference = .44  Levene's test for Equality of Variances: F = 2.695 P = . 106  Variable  T-Test for Equality of Means 2-Tail Sign Variances  t-value  df  Equal Unequal  -1.047 -1.034  55 49.422  .300 .306  Mean Diff  SE of Diff  -.44 -.44  .42 .42  95% CI for Diff (-1.27, .40) (-1.29, .41)  164  Appendix D  Coding Instructions for Part I, Case History Question # 2 1. Assign a number to each of the questionnaires you have received. Do this in numeric order starting with # 1 (e.g. # 1, 2, 3, and so on). 2. Read the response to Part I, Case History Question #2 on thefirstquestionnaire. 3. In the left-hand row of the code sheet provided, list questionnaire by the assigned number. 4. Use one line per questionnaire. 5. For each response make checkmarks in the boxes under the prearranged categories. 6. As you go along, if certain responses do not appear appropriate to any of the prearranged categories, note any way that the categories might be rearranged, added to or refined to be more accurately descriptive of the issues noted by the respondents. Follow this procedure until you have coded each of the questionnaires. For example: if questionnaire # 1 listed 'refer for psychiatric assessment', 'money problems' and 'assess for suicidal ideation', as responses to the question, you would list the questionnaire number in the left hand row and check off the categories as follows:  suicide 1  /  children  family  mentalhe  genhealt  finance  165 Appendix D ANGER  anger or anger management  by  CL  CL  Count  middle  lower Row Total  ANGER . 00 no  41  mention 1.00 issue  important  Column Total  79 71 . 2  15  17  56 50.5  55 49.5  Chi-Square  111 100.0  Observations:  ANXIETY  by  CL  Signi ficance . 63157 .78719 .63151 .63311  15.856  Number of M i s s i n g anxiety  DF  .22993 . 07288 .23002 .22786  Minimum Expected Frequency -  0  class  CL  Count  |middle  lower Row Total  ANXIETY .00  40  1.00 issue  16  mention  important  32 28 . 8  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association  no  class  Column Total  48  23 20.7  56 50.5  55 49.5  Chi-Square  111 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number o f M i s s i n g  88 79 .3  4.24035 3.33069 4.33689 4.20215 -  Observations:  11.396 0  DF  Significance . 03947 .06800 . 03730 . 04037  166  Appendix D ALCOHOL  by  CL  class CL  Count  middle  2  33  33  66 59 . 5  1. 00 issue  23  22  45 40.5  Column Total  56 50.5  55 49.5  . 00  n mention  Chi-Square  Number of M i s s i n g  DF  . 01321 .00000 .01321 .01310  Minimum Expected Frequency  -  CL  class  Row Total  2  44  42  86 77.5  12  13  25 22.5  56 50.5  55 49.5  111 100.0  . 00 1.00 issue  Column Total  lower  1  FAMILY  Chi-Square  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g  by  CL middle  important  . 90848 1. 00000 . 90848 ' .90889  0  family or r e l a t i o n s h i p problems  mention  Significance  22.2 97  Observations:  Count  no  111 100 . 0  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association  FAMILY  Row Total  1  ALCOHOL no  lower  .07751 .00262 .07752 . 07681 -  Observations:  12.387 0  DF  Significance .78070 . 95918 .78069 .78167  167  Appendix D CHILDHOO  childhood issues  by  CL  class  CL I  Count  PUTT  no  middle  2  48  46  8  9  17 15.3  56 50.5  55 49.5  111 100.0  . 00 1. 00 issue  important  Column Total Chi-Square  94 84 . 7  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  by  CL  Significance .76118 . 96780 .76114 .76222  8.423  Number of M i s s i n g O b s e r v a t i o n s : depression  DF  .09238 . 00163 . 09240 , 09154  Minimum Expected Frequency -  DEPRESSI  Row Total  1  DHOO  mention  lower  0  class  CL Count  I  middle  mention  important  Row Total  1  2  .00  42  44  86 77.5  1.00 issue  14  11  25 22 . 5  56 50.5  55 49.5  DEPPE^^I no  lower  Column Total -Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency  111 100.0  •39753 .16263 .39838 .39395 -  Number o f M i s s i n g O b s e r v a t i o n s :  12.387 0  DF 1 1 1 1  Significance .52837 .68674 .52793 .53023  168  Appendix D FAMVIOL  family violence  by  CL  class  CL  Count  middle  lower Row Total  FAMVIOL . 00 no  25  39  64 57 . 7  31  16  47 42 . 3  56 50.5  55 49.5  mention  important  1. 00 issue Column Total  Chi-Square  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association  Number of M i s s i n g  -  . 00511 .00910 .00481 .00531  0  spending  by  CL  class  CL  Count  middle  lower Row Total  FINANCE .00 no  Signi ficance  23.288  Observations:  finances/money  DF  7.84136 6.80238 7.95040 7 . 77072  Minimum Expected Frequency  FINANCE  111 100.0  50  mention  49  1.00  12 10.8  important Column Total  56 50.5  55 49.5  Chi-Square  Number of M i s s i n g  111 100.0  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  99 89 .2  Frequency Observations:  . 00109 . 00000 .00109 .00108 5.946 0  DF  Significance .97364 1. 00000 . 97364 . 97376  169  Appendix D GENHEALT  general health  by  issues  CL  CL  Count  middle  lower Row Total  GENHEALT . 00  49  no mention  49  13 11.7  Column Total  56 50.5  55 49.5  Chi-Square  111 100.0  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g  DF  .06792 .00000 .06799 .06731 -  Significance . 79439 1. 00000 . 79429 . 79530  6.441  Observations:  mental h e a l t h  issues  0  by  CL  class  CL  Count  middle  lower Row Total  MENTALH . 00  49  no mention important  98 88 . 3  1.00 issue  important  MENTALH  class  1.00  issue Column Total  56 50.5  45  94 84.7  10  17 15.3  55 49.5  111 100.0  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Number of M i s s i n g  Frequency Observations:  .69067 .32206 .69345 . 68445 8.423 0  DF  Significance .40594 .57037 .40499 .40806  170 Appendix D MOOD  mood/coping w i t h Count  feelings  MOOD  important  . 00 1. 00 issue  Column Total  CL  class  CL middle  no mention  by  lower  1  2  54  47  2  8  56 50.5  55 49 . 5  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  101 91. 0 10 9. 0 111 100 . 0  Value  DF  4 . 07647 2 . 84766 4 . 33142 4.03975  Signi ficance . 04348 . 09151 . 03741 .04444 .04386 . 05263  Minimum Expected Frequency 4 . 955 C e l l s with Expected Frequency < 5 Number of M i s s i n g ' O b s e r v a t i o n s :  Row Total  0  1 OF  4 ( 25.0%)  171  Appendix D  OTHER  by  CL  class  Count  CL middle  OTHER  lower Row Total  1  2  48  45  93 83 . 8  1. 00  5  6  11 9. 9  2 . 00  2  3  5 4.5  . 00  3 . 00  1  4 . 00  1  Column Total  56 50.5  1 .9 1 .9  55 49.5  Chi-Square  111 100.0  Value  Pearson Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  2.37887 3.15276 . 10273  Minimum Expected Frequency -  .495  C e l l s with Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  0  DF  Significance . 66645 . 53259 .74858  6 OF  10 ( 60.0%)  172  Appendix D  PARAN10  fearfulness/paranoia  by  CL  class  CL Count middle PARANIO no  lower Row Total  . 00  36  46  mention  important  1. 00 issue  20  Column Total  56 50.5  29 26.1 55 49.5  Chi-Square  Number of M i s s i n g  111 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  82 73 . 9  Frequency Observations:  5.38335 4.42743 5 . 49226 5.33486 14.369 0  DF  Signi ficance .02033 . 03537 . 01910 . 02 09 0  173  Appendix D SELFDIR  self-directed Count  by  class  CL middle  n  CL  P T FDTT!L\  lower  1  2  50  51  6  4  Row Total  O 1—1 J_J 1. LJ J.  no mention important  . 00 1.00 issue  Column Total  56 50 . 5  55 49 . 5  Chi-Square  10 9. 0 111 100.0  Value.  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail Minimum Expected Frequency C e l l s w i t h Expected Frequency  101 91. 0  DF  Significance .52661 .76291 .52523 .52848  .40092 . 09100 .40360 .39731  .38260 . 74218 4.955 < 5 -  Number of M i s s i n g O b s e r v a t i o n s :  0  1 OF  4 ( 25.0%)  174  Appendix D SELFEST  self  esteem/worth/concept  by  CL  CL  Count  middle  lower Row Total  SELFEST . 00  41  43  84 75 . 7  15  12  27 24 . 3  56 50.5  55 49.5  no m e n t i o n 1. 00 issue  important  Column Total Chi-Square  111 100.0  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association  Number of M i s s i n g  DF  .37197 .15106 .37264 .36862  Minimum Expected Frequency -  SUICIDE  class  .54193 .69753 .54157 .54376  13.37E  Observations:  s u i c i d e / s e l f damage  Signi ficance  0  by  CL  class  Count middle ^UICIDE %w» J - !_/ i—J  W W -L-  no mention •important  .00  2  49  51  100 90 .1  7  4  11 9.9  55 49.5  111 100.0  56 50 . 5  Chi-Square  Value  Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g  Row Total  1  1.00 issue Column Total  lower  Observations:  .84924 .36466 .85963 .84159 5.450 0  DF 1 1 1 1  Significance .35677 .54593 .35384 .35894  i7H-a Appendix D UNEMPLOY  unemployment Count  by  CL  class  CL middle  lower'  . 00  45  41  86 77 . 5  1. 00 issue  11  14  25 22 . 5  Row Total  UNEMPLOY no m e n t i o n important  Column Total  56 50.5  55 49 . 5  Chi-Square  111 100 . 0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  DF  .53708 .25566 . 53797 . 53224  Signi ficance .46364 . 61312 .46327 .46567  Minimum Expected Frequency .12.387 Number of M i s s i n g O b s e r v a t i o n s : 0 VOCATION  vocational assistance Count  by  CL  CL middle  lower Row Total  VOCATION no mention important  class  .00  54  47  101 91. 0  1.00 issue Column Total  10 9.0 56 5 0.5  55 49 . 5  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t ' f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail Minimum Expected Frequency C e l l s w i t h Expected Frequency  111 100. 0 DF  4.07647 2 . 84766 4.33142 4.03975  Significance . 04348 . 09151 - 03741 . 04444 . 04386 .05263  4.955 < 5 -  Number of M i s s i n g O b s e r v a t i o n s :  0  1 OF  4 ( 25.0%)  175  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Alcohol Count  middle  lower Row Total  ALCOHOL no  CL  00  15  .15  30 61.2  11  19 38 . 8  mention  important  1.00 issue Column Total  23 46.9  26 53.1  Chi-Square  49 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  DF  .29110 . 06041 .29188 .28516  Minimum Expected Frequency -  Significance .58952 .80584 .58902 . 59334  8.918  Number of M i s s i n g O b s e r v a t i o n s :  0  Anger CL Count middle  lower Row Total  ANGER .00 no  16  mention  important  18  34 69.4  1.00 issue  15 30.6  Column Total  23 46.9  26 53.1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  49 100.0  Frequency  Number o f M i s s i n g O b s e r v a t i o n s :  .00064 .00000 .00064 .00063 7.041 0  DF  Significance .97978 1.00000 .97977 .97998  176  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Anxiety Count  CL middle  Row Total  ANXIETY no  lower  . 00  14  23  37 75.5  mention 1. 00 issue  important  12 24 . 5  Column Total  23 46.9  26 53 .1  Chi-Square  49 100 . 0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  DF  . 02499 .05630 .02302 . 02652  5 . 02435 3 . 64305 5 .16701 4 . 92181  Minimum Expected Frequency  -  Significance  5.633  Number of M i s s i n g O b s e r v a t i o n s :  0  Depression Count  CL middle  .00  17  mention  important  Row Total  1  DEPRESSI no  lower  19  1.00 issue Column Total  36 73 . 5 13 26.5  23 46.9  26 53.1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  .00438 .00000 . 00438 . 00429 6.102 0  DF  Significance . 94725 1.00000 . 94724 .94779  177 Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Childhood issues Count  CL middle  CHILDHOO no  Row Total . 00  mention  important  lower  21  24  45 91. 8  1. 00 issue Column Total  4 8.2 23 46.9  26 53 .1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  .01639 .00000 .01636 .01605  Significance .89814 1.00000 .89822 .89918 .64720 1.00000  Minimum Expected Frequency 1.878 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100 . 0  0  2 OF  4 ( 50.0%)  178  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Family or relationship problems CL Count middle  lower Row Total  1 FAMILY no  , 00  21  39 79.6  mention  important  1.00 issue Column Total  10 20.4 23 46.9  26 53.1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  Significance  .82788 1.00000 .82799 .82962  .04727 .00000 .04721 .04631  .55267 1.00000  Minimum Expected Frequency 4.694 C e l l s w i t h Expected Frequency < 5 Number o f M i s s i n g O b s e r v a t i o n s :  49 100.0  0  1 OF  4 ( 25.0%)  179  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Family violence CL  Count  middle  lower Row Total  FAMVIOL . 00  13  no mention 1.00 issue  important  19  32 65.3  10  Column Total  17 34.7  .23 46.9  26 53.1  Chi-Square  49 100 . 0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  DF  1.47627 .83600 1.48009 1.44614  Minimum Expected Frequency -  Significance .22436 .36054 .22376 .22915  7.980  Number of M i s s i n g Observations:  0  Mental health issues CL  Count  middle  lower Row Total  MENTALH .00  20  no mention important  1.00 issue  11 22 . 4  Column Total  23 46.9  26 53.1  Chi-Square  49 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  38 77 . 6  Frequency  Number o f M i s s i n g Observations:  .01255 .00000 . 01256 . 01229 5.163 0  DF  Significance .91082 1.00000 . 91077 .91173  180  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Finances/money spending Count  CL middle  FINANCE no  mention  important  lower Row Total  1 . 00  20  25  45 91.8  1. 00 Column Total  4 8.2 23 4 6.9  26 53.1  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact Test: One-Tail Two-Tail  Value  DF  1.37704 .42347 1.41941 1.34894  Significance .24061 . 51521 .23350 .24546 .25912 . 32968  Minimum Expected Frequency 1.878 C e l l s with Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  181 Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class General health issues Count  CL middle  GENHEALT  lower  . 00  19  no mention important  Row Total  1  42 85 . 7  23  1.00 issue Column Total  7 14.3 23 46.9  Chi-Square  26 53 .1 Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  Significance . 55901 . 86085 . 55920 .56305  .34142 .03073 .34109 .33445  . 42874 . 69178  Minimum Expected Frequency 3.286 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  182  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Mood Count  CL middle  Row Total  MOOD no  lower  . 00 mention  important  22  26  48 98.0  1. 00 issue Column Total  1 2.0 23 46.9  26 53 .1  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value  DF  1.15399 .00384 1.53623 1.13043  Significance .28272 .95058 .21518 .28768 .46939 .46939  Minimum Expected Frequency .469 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  183  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Other Count  CL middle  OTHER  lower Row Total  1  2  20  22  42 85.7  1. 00  2  2  4 8.2  2 . 00  1  1  2 4.1  1  1 2. 0  . 00  3 . 00 Column Total  23 46.9  26 53.1  Chi-Square Pearson Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  Value  DF  .91499 1.29778 .28721  Minimum Expected Frequency .469 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  Significance .82181 .72966 .59201  6 OF  8 ( 75.0%)  184  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Paranoia Count  CL middle  lower Row Total  PARAN10 no  00  40 81. 6  22  mention  important  1. 00 issue Column Total  9 18 . 4 23 4 6.9  26 53.1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  Signi ficance .56644 .83861 .56671 .57043  .32867 .04148 .32822 .32196  .41800 .71648  Minimum Expected Frequency 4.224 Cell.s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  185 Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Self-directed CL Count  middle  lower Row Total  1 SELFDIR no  , 00  22  47 95.9  25  mention  important  2 4. 1  1.00 issue Column Total  23 46.9  26 53.1  DF  Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Significance .92942 1.00000 . 92948 . 93014  .00785 .00000 .00783 .00769  .72364 1.00000  Minimum Expected Frequency .939 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  186  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Self-esteem CL Count  middle  lower Row Total  SELFEST no  . 00  18  22  40 81.6  mention  important  9 18 . 4  1. 00 issue Column Total  23 46.9  26 53 .1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  Significance .56644 . 83861 . 56671 . 57043  .32867 .04148 .32822 .32196  .41800 .71648  Minimum Expected Frequency 4.224 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100. 0  0  2 OF  4 ( 50.0%)  187 Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Suicide CL Count middle  Row Total  SUICIDE no  lower  .00  20  23  43 87.8  mention  important  6  1.00 issue Column Total  12 .2 23 46.9  26 53 .1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact Test: One-Tail Two-Tail  DF  Significance .87257 1.00000 .87267 .87387  .02573 .00000 .02568 .02520  .60486 1.00000  Minimum Expected Frequency 2.816 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  188 Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Vocation CL Count middle VOCATION  lower Row Total  1  2  . 00  22  24  46 93.9  1.00 issue  1  2  3 6.1  23 46.9  26 53.1  49 100.0  no mention important  Column Total  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail , Two-Tail  Significance . 62601 1.00000 .62205 .62956  .237 51 .00000 .24299 .23266  .54684 1.00000  Minimum Expected Frequency 1.408 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  Value  Chi-Square  0  2 OF  4 ( 50.0%)  189  Appendix D Chi Square Analyses of BCPA Respondents' Choices of Important Issues by Client Class Unemployment CL Count  middle  lower Row Total  1 UNEMPLOY  . 00  20  40 81.6  20  no mention important  1.00 issue Column Total  9 18.4 23 46.9  26 53.1  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r \ s Exact T e s t : One-Tail Two-Tail  DF  .81940 .28685 .83561 .80268  Significance .36536 .59225 .36066 .37029 .29848 .47162  Minimum Expected Frequency 4.224 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  49 100.0  0  2 OF  4 ( 50.0%)  190  Appendix D Chi Square Analyses of C G C A Respondents' Choices of Important Issues by Client Class Alcohol CL  Count  lower  middle  Row Total  1 ALCOHOL  36 58 .1  . 00  no m e n t i o n important  1. 00 issue Column Total  15  11  33 53.2  29 46.8  26 41 . 9 62 100.0 DF  Value  Chi-Square  Minimum Expected Frequency Number of M i s s i n g  . 54917 .73303 . 54873 .55240  .35881 .11635 .35959 .35303  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association -  Signi ficance  12.161  Observations:  0  Anger/anger management CL Count  middle  lower Row Total  1 ANGER  .00  25  45 72 . 6  20  no mention important  17 27.4  1.00 issue Column Total  33 53.2  Chi-Square  29 46.8  Value .35780 . 09790 .35732 .35203  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  62 100.0  Frequency  Number of M i s s i n g O b s e r v a t i o n s :  7.952 0  DF  Significance . 54973 .75437 . 55000 .55296  191 Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Anxiety Count  CL middle  lower 2  ANXIETY  26  . 00  Row j Total 51 82.3  25  no mention important  1. 00 issue  11 17.7  Column Total  33 53.2  29 46.8  Chi-Square  62 100.0  Value  DF  .58215 .18477 .59000 .57276  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency -  Significance .44547 .66730 .44242 .44916  5.145  Number o f M i s s i n g Observations:  0  Childhood issues CL Count middle  lower Row Total  1 CHILDHOO  27  .00  49 79.0  22  no mention important  13 21.0  1.00 issue Column Total  33 53 .2  29 46.8 Value  Chi-Square  .33044 .06875 .32985 .32511  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number o f M i s s i n g Observations:  62 100.0  6.081 0  DF  Significance . 56540 .79316 .56575 .56855  192  Appendix D Chi Square Analyses of.CGCA Respondents' Choices of Important Issues by Client Class Depression Count  CL middle  Row Total  1  2  . 00  25  25  1 . 00 issue  8  4  12 19 .4  Column Total  33 53 .2  29 46.8  62 100.0  PEPFESSI no mention important  lower  Chi-Square  50 80 . 6  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  DF  1. 07976 .51408 1.10095 1.06235  Minimum Expected Frequency -  Signi ficance .29875 .47338 .29406 .30268  5 . 613  Number o f M i s s i n g O b s e r v a t i o n s :  0  Family or relationship problems Count  CL middle  important  2  26  21  47 75.8  7  8  15 24 .2  33 53 .2  29 46.8  62 100.0  . 00 1.00 issue Column Total  Row Total  1  FAMILY no mention  lower  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number o f M i s s i n g O b s e r v a t i o n s :  .34194 .08271 .34140 .33643 7.016 0  DF  Significance .55871 .77366 . 55903 . 56190  193  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Finances/money spending CL Count middle  lower Row Total  1 FINANCE no  .00  30  24  54 87 .1  mention 1.00  12.9  important Column Total  33 53.2  29 46.8  Chi-Square  DF  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  .91240 .33128 .91514 .89768  Significance .33948 .56491 .33875 .34340 .28232 .45606  Minimum Expected Frequency 3.742 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  62 100.0  0  2 OF  4 ( 50.0%)  194  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Family violence  CL  Count middle  lower 2  FAMVIOL no  .00  12  1. 00 issue  21  mention  important  Column Total  Row ! Total  20  32 51. 6 30 48.4  33 53.2  29 46.8  Chi-Square  62 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  DF  6.56928 5 . 32870 6.70010 6.46332  Minimum Expected Frequency  -  Significance .01038 . 02098 . 00964 . 01101  14.032  Number of M i s s i n g O b s e r v a t i o n s :  0  Fearfulness/paranoia CL Count  PARANIO no  middle  lower  Row Total  1  2  ,00  18  24  42 67 .7  1.00 issue  15  5  20 32.3  33 53.2  29 46.8  62 100.0  mention  important  Column Total  Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g O b s e r v a t i o n s :  5.62248 4.40551 5.83432 5.53180 9.355 0  DF  Significance .01773 .03582 .01572 .01867  195 Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class General health issues CL Count  middle  lower  Row Total  1 GENHEALT no  . 00  26  30  mention  important  56 90.3 6 9.7  1.00 issue Column Total  33 53.2  29 46.8  Chi-Square  62 100.0 DF  Value  .86766 1.00000 .86778 .86872  . 02777 .00000 . 02771 .02732  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail  .59977 1.00000  Two-Tail  2.806 Minimum Expected Frequency C e l l s w i t h Expected Frequency < 5 Number o f M i s s i n g O b s e r v a t i o n s :  Significance  0  2 OF  4 ( 50.0%)  196 Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Mental health issues CL Count  middle  lower Row Total  1 MENTALH  31  . 00  56 90.3  25  no mention important  6 9.7  1. 00 issue Column Total  33 53 .2  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  29 46.8  DF  Value  Significance .30416 . 55045 .30198 .30810  1.05585 .35651 1. 06545 1.03882  .27547 .40545  Minimum Expected Frequency 2.806 C e l l s with Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  62 100.0  0  2 OF  4 ( 50.0%)  197  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Mood CL Count  middle  lower Row Total  MOOD  . 00  32  53 85 . 5  21  no mention important  9 14 . 5  1.00 issue Column Total  33 53.2  29 46.8  Significance  . 00617 .01743 .00410 .00660  7.50062 5.65225 8.23913 7.37964  .00748 .00938  Minimum Expected Frequency 4.210 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  62 100.0  0  2 OF  4 ( 50.0%)  198  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Other Count  CL middle  lower Row Total  1  2  28  23  51 82.3  1. 00  3  4  7 11. 3  2 . 00  1  2  3 4.8  4.00  1 •  OTHER . 00  Column Total  33 53.2  1 1.6 29 46.8  Chi-Square Pearson Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  Value  DF  1.71546 2 .10218 . 00030  Minimum Expected Frequency .468 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  62 100.0  0  6 OF  Significance . 63350 .55147 .98607  8 ( 75.0%)  199  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Self-directed CL Count middle  lower Row Total  SELFDIR no  , 00  28  54 87 . 1  26  mention  important  1. 00 issue Column Total  12 . 9 33 53.2  29 46.8 Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  Significance .57322 . 85426 . 57089 .57633  .31733 .03374 .32119 .31221  .43024 .71255  Minimum Expected Frequency 3.742 C e l l s with Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  62 100.0  0  2 OF  4 ( 50.0%)  200  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Self-esteem CL  Count  middle  lower Row Total  1 SELFEST  00  23  1. 00 issue  10  44 71 . 0  21  no mention important  18 29 . 0  33 53.2  Column Total  29 46.8  Chi-Square  62 100.0  Value . 05530 .00000 .05538 .05441  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency  DF  -  Significance . 81409 1.00000 .81396 .81557  8.419  Number of M i s s i n g O b s e r v a t i o n s :  0  Unemployment CL  Count  UNEMPLOY  middle  lower  21  25  .00  Row Total  no mention important  16 25.8  1.00 issue Column Total  33 53.2  29 46.8  62 100. 0  Value  Chi-Square  .09014 .00009 . 09002 .08868  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  46 74.2  Frequency  Number of M i s s i n g O b s e r v a t i o n s :  7.484 0  DF  Significance .76400 .99251 .76415 .76586  201  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Suicide CL Count middle  lower Row Total  1 SUICIDE  . 00  29  57 91.9  28  no mention important  1 . 00 issue Column Total  5 8 .1 33 53 .2  29 46. 8  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value  DF  1.56600 .61467 1.68675 1.54074  Significance .21079 .43304 . 19403 .21451 .22006 .35954  Minimum Expected Frequency 2.339 C e l l s with Expected Frequency < 5 Number of M i s s i n g Observations:  62 100.0  0  2 OF  4 ( 50.0%)  202  Appendix D Chi Square Analyses of CGCA Respondents' Choices of Important Issues by Client Class Vocation CL Count middle  lower Row Total  VOCATION no  32  . 00  23  55 88 .7  mention  important  7 11.3  1.00 issue Column Total  33 53 .2  29 46.8  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value  DF  Significance  4.80610 3 .20462 5.18356 4.72858  .02836 .07343 . 02280 . 02967 .03505 .04373  Minimum Expected Frequency 3.274 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  62 100.0  0  2 OF  4 ( 50.0%)  203  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Alcohol CL Count  ALCOHOL  middle  . 00 1.00 Column Total  lower  1  2  Row Total  15  19  34 64.2  10  9  19 35.8  25 47.2  28 52.8  53 100.0  Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel test for linear association  DF  .35454 .09520 .35443 .34785  Minimum Expected Frequency -  Significance .55155 .75767 .55161 .55533  8.962  Number of Missing Observations:  0  Anger Count  ANGER  CL middle  lower  1  2  Row Total  .00  19  23  42 79.2  1.00  6  5  11 20.8  25 47.2  28 52.8  53 100.0  Column Total Chi-Square  Value .30302 .04462 .30266 .29730  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel test for linear association Minimum Expected Frequency Number of Missing Observations:  5.189 0  DF  Significance .58199 .83271 .58222 .58558  204  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Anxiety CL Count middle  lower Row Total  1  2  .00  18  26  44 83 . 0  1.00  7  2  9 17.0  25 47 . 2  28 52.8  53 100.0  ANXIETY  Column Total Chi-Square  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value  Significance  .04351 .09846 .03961 . 04554  4.07557 2.73035 4 .23470 3 . 99867  .04830 .06739  Minimum Expected Frequency 4.245 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  0  2 OF  4 ( 50.0%)  205  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Childhood issues CL  Count  lower  middle CHILDHOO  2  23  24  47 88.7  2  4  6 11.3  25 47.2  28 52.8  53 100.0  . 00 1.00 Column Total  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  ,39099 ,67179  Number of M i s s i n g O b s e r v a t i o n s : by  Significance .47093 .77430 .46620 .47514  .51980 .08223 .53097 .50999  Minimum Expected Frequency 2.830 C e l l s w i t h Expected Frequency < 5 -  depression  DF  Value  Chi-Square  DEPRESSI  Row Total  1  CL  0  class  2 OF  4 ( 50.0%)  206  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Depression  Count  CL middle  DEPRESSI  . 00  lower  1  2  21  24  4  4  1.00  Row Total 45 84.9 15.1  Column Total  25 47.2  28 52.8  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  .03029 .00000 .03025 .02971  Significance .86184 1. 00000 .86193 .86314 .58054 1.00000  Minimum Expected Frequency 3.774 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  53 100.0  0  2 OF  4 ( 50.0%)  207  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Family or relationship issues CL Count  RELFAM  middle  lower  1  2  .00  20  23  1.00  5  5  Column Total  25 47 .2  Chi-Square  28 52 . 8  43 81.1 10 18 . 9 53 100 . 0 DF  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Significance . 84223 1.00000 .84232 . 84371  .03962 .00000 .03957 .03887  . 55858 1.00000  Minimum Expected Frequency 4.717 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  Row Total  0  1 OF  4 ( 25.0%)  208  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Family violence CL Count  FAMVIOL  middle  Row Total  1  2  11  19  30 56.6  14  9  23 43.4  25 47.2  28 52.8  53 100.0  . 00 1. 00 Column Total  lower  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g O b s e r v a t i o n s :  Value 3 . 06028 2.16611 3 . 08515 3 . 00254 10.849 0  DF  Significance . 08023 . 14108 .07901 .08313  209  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Finances/money spending Count  CL middle  lower 2  .00  21  25  46 86.8  1.00  4  3  7 13.2  25 47.2  28 52.8  53 100.0  FINANCE  Column Total Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Number of M i s s i n g O b s e r v a t i o n s :  DF  Significance  .57047 .87209 .57058 .57412  .32190 .02592 .32171 .31583  .43443 .69449  Minimum Expected Frequency 3.302 C e l l s w i t h Expected Frequency < 5 -  6  Row Total  1  0  2 OF  4 ( 50.0%)  210 Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class General health issues CL Count  GENHEALT  .00  middle  Row Total  1  2  21  25  4  3  7 13.2  25 47.2  28 52.8  53 100.0  51  1.00 Column Total  lower  Chi-Square  DF  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Significance . 57047 .87209 .57058 .57412  .32190 .02592 .32171 .31583  .43443 .69449  Minimum Expected Frequency 3.302 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  46 86 . 8  0  2 OF  4 ( 50.0%)  211  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Mood Count  CL middle  lower Row Total  1  2  .00  24  25  49 92 . 5  1.00  1  3  4 7. 5  25 47.2  28 52.8  MOOD  Column Total Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  DF  .85333 .16234 .89700 .83723  Significance .35561 . 68701 .34359 .36019 .34961 . 61274  Minimum Expected Frequency 1.887 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  53 100.0  0  2 OF  4 ( 50.0%)  212  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Mental health issues Count  CL middle  MENTALH  lower Row Total  1  2  .00  21  23  44 83 . 0  1.00  4  5  9 17 . 0  25 47.2  28 52.8  Column Total Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail Minimum Expected Frequency C e l l s w i t h Expected Frequency  53 100.0 DF  .03231 .00000 .03238 .03170  Significance . 85734 1.00000 . 85720 .85868 . 57531 1. 00000  4.245 < 5 -  Number of M i s s i n g O b s e r v a t i o n s :  0  2 OF  4 ( 50.0%)  213  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Paranoia CL Count middle PARANOIA  Row Total  1  2  19  25  44 83 . 0  6  3  9 17 . 0  25 47.2  28 52.8  . 00 1. 00 Column Total  lower  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value  DF  Significance .19846 .35782 .19623 .20275  1.65367 .84552 1.67023 1.62247  . 17921 .27846  Minimum Expected Frequency 4.245 C e l l s w i t h Expected Frequency < 5 Number o f M i s s i n g O b s e r v a t i o n s :  53 100.0  0  2 OF  4 ( 50.0%)  214  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Self-directed CL Count  middle  SELFDIR . 00  1.00  Column Total  lower  1  2  21  27  Row Total 48 90.6  4  1  5 9.4  25  28  53  52.8  100.0  47.2  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  2 .38784 1.15472 2.50951 2 . 34279  . 12228 .28256 . 11316 .12586  .14194 . 17619  Minimum Expected Frequency 2.35c C e l l s w i t h Expected Frequency < 5 Number o f M i s s i n g Observations:  Significance  DF  Value  0  2  OF  4  (  50.0%)  215  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Self-esteem CL Count middle SELFEST  Row Total  1  2  19  20  6  8  14 26.4  25 47.2  28 52.8  53 100.0  . 00 1.00 Column Total  lower  Chi-Square  Value .14200 .00419 . 14244 .13932  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g O b s e r v a t i o n s :  39 73 . 6  6.604 0  DF  Significance .70630 .94836 .70587 .70896  216 Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Suicide CL Count middle SUICIDE  Row Total  1  2  21  27  48 90.6  4  1  5 9.4  25 47 .2  28 52.8  . 00 1.00 Column Total  lower  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value  DF  2.38784 1.15472 2.50951 2 . 34279  Significance .12228 .28256 .11316 .12586 .14194 . 17619  Minimum Expected Frequency 2.358 C e l l s w i t h Expected Frequency < 5 Number o f M i s s i n g O b s e r v a t i o n s :  53 100 . 0  0  2 OF  4 ( 50.0%)  217  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Unemployment CL Count middle UNEMPLOY  . 00  Row Total  1  2  19  24  43 81.1  6  4  10 18.9  25 47.2  28 52.8  53 100.0  1.00 Column Total  lower  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  .81419 .30325 .81552 .79883  Signi ficance .36688 . 58185 .36649 .37144 .29079 .48780  Minimum Expected Frequency 4.717 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  0  1 OF  4 ( 25.0%)  218  Appendix D Chi Square Analyses of Male Respondents' Choices of Important Issues by Client Class Vocation CL Count  middle  lower 2  1 VOCATION  . 00  25  48 90.6  2  3  5 9.4  25 47.2  28 52.8  53 100.0  23  1. 00 Column Total  Row Total  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  .11389 .00000 .11481 .11174  1 1 1 1  Significance .73576 1.00000 .73473 .73817 .55510 1.00000  Minimum Expected Frequency 2.358 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  Value  0  2 OF  4 ( 50.0%)  219  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Alcohol CL Count  lower  middle ALCOHOL  2  18  14  32 55.2  13  13  26 44 . 8  31 53.4  27 46.6  . 00 1. 00 Column Total  Row Total  1  Chi-Square  58 100.0  Value  DF  .22521 .04406 .22523 .22133  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  Significance .63510 . 83374 . 63508 . 63803  Minimum Expected Frequency 12.103 Number o f M i s s i n g O b s e r v a t i o n s : 0  Anger Count  CL middle  lower 2  23  15  38 65.5  8  12  20 34.5  31 53.4  27 46.6  58 100.0  ANGER . 00 1.00 Column Total  Row Total  1  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number o f M i s s i n g O b s e r v a t i o n s :  Value 2 .21890 1.47061 2 .22622 2.18065 9.310 0  DF  Significance .13633 .22525 .13569 .13976  220  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Anxiety CL  Count  middle ANXIETY  1  2  22  22  9  5  31 53.4  27 46.6  . 00 1.00 Column Total  lower  Chi-Square  Row Total 44 75.9 14 24 . 1 58 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association  D F  .87114 .39158 .88286 .85612  Minimum Expected Frequency  -  Significance .35064 .53147 . 34742 .35483  6.517  Number of M i s s i n g O b s e r v a t i o n s :  0  Childhood issues CL  Count  middle CHILDHOO  lower Row Total  1  2  .00  25  22  1.00  6  5  11 19 . 0  31 53.4  27 46.6  58 100 . 0  Column Total Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  47 81. 0  Frequency  Number of M i s s i n g O b s e r v a t i o n s :  .00657 . 00000 .00657 .00645 5 .121 0  DF  Significance .93541 1. 00000 .93538 .93597  221 Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Depression Count  CL middle  lower  1  2  .00  21  20  1.00  10  7  31 53.4  27 46.6  DEPRESSI  Column Total Chi-Square  Number of M i s s i n g O b s e r v a t i o n s :  41 70.7 17 29 . 3 58 100.0  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency  Row Total  .27927 .05727 .28051 .27445 7.914 0  DF  Significance .59718 . 81087 .59637 . 60036  222  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Family or relationship problems CL Count middle RELFAM  lower Row Total  1  2  .00  24  19  1. 00  7  8  15 25.9  31 53.4  27 46.6  58 100.0  Column Total  Value  Chi-Square  . 37398 . 09669 .37335 . 36753  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number of M i s s i n g  43 74 . 1  Observations:  6.983 0  DF  Signi ficance .54084 .75584 .54119 . 54435  223  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Family violence CL Count  FAMVIOL  middle  lower  Row Total  1  2  . 00  14  20  34 58.6  1. 00  17  7  24 41.4  31 53.4  27 46.6  Column Total  Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel test f o r linear association Minimum E x p e c t e d Number o f M i s s i n g  58 100 . 0  Frequency Observations:  4. 3. 5. 4.  97328 85276 08478 88754  11.172 0  DF  Signi ficance . 02574 . 04966 . 02414 . 02705  224  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Finances/money spending Count  CL middle  FINANCE  . 00  Row Total  1  2  29  24  53 91.4  2  3  5 8.6  31 53.4  27 46.6  58 100.0  1. 00 Column Total  lower  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  .39773 .02615 .39767 .39087  Significance  1 1 1 1  . 52827 .87154 .52829 . 53184 .43319 , 65567  Minimum Expected Frequency 2.328 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  0  2 OF  4 ( 50.0%)  225  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class General health issues CL Count  GENHEALT  middle  lower  1  2  .00  27  23  1.00  4  4  31 53.4  27 46.6  Column Total  50 86.2 13 .1 58 100.0 DF  Value  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Significance .83321 1.00000 . 83337 . 83463  .04435 .00000 .04426 .04358  .56474 1.00000  Minimum Expected Frequency 3 . 724 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  Row Total  0  2 OF  4 ( 50.0%)  226  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Mental health issues CL Count middle MENTALH  1  2  29  23  2  4  31 53.4  27 46.6  . 00 1. 00 Column Total  lower  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  52 89.7 6 10 . 3 58 100.0  Value  DF  1.08829 . 37335 1.09737 1.06952  Significance .29685 . 54118 .29484 .30105 .27077 .40230  Minimum Expected Frequency 2.793 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  Row Total  0  2 OF  4 ( 50.0%)  227 Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Mood Count  CL middle  Row Total  1  2  30  22  52 89 .7  1  5  6 10.3  31 53.4  27 46.6  58 100.0  MOOD . 00 1. 00 Column Total  lower  Chi-Square Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Value 3 . 63888 2 .17680 3.87062 3.57614  Significance .05644 . 14011 .04914 . 05862 .06914 . 08734  Minimum Expected Frequency 2.793 C e l l s w i t h Expected Frequency < 5 Number o f M i s s i n g O b s e r v a t i o n s :  DF  0  2 OF  4 ( 50.0%)  228  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Paranoia Count  CL middle  PARANOIA  1  2  17  21  14  6  31 53.4  27 46.6  . 00 1. 00 Column Total  lower  Chi-Square Pearson Continuity Correction L i k e l i h o o d Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency Number o f M i s s i n g O b s e r v a t i o n s :  Row Total 38 65.5 20 34 . 5 58 100.0  Value 3 .36118 2 .42250 3.43707 3 . 30323 9.310 0  DF  Significance . 06675 .11960 . 06375 . 06914  229 Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Self-directed CL  Count  middle  lower  Row Total  1  2  .00  29  24  53 91.4  1.00  2  3  5 8.6  31 5 3.4  27 46.6  58 100.0  SELFDIR  Column Total Chi-Square  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  Significance .52827 .87154 .52829 .53184  .39773 .02615 .39767 .39087  .43319 .65567  Minimum Expected Frequency 2.328 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  Value  0  2 OF  4 ( 50.0%)  230  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Self-esteem CL  Count  SELFEST  lower  middle  2  21  23  44 75.9  10  4  14 24 .1  31 53 .4  27 46.6  58 100.0  . 00 1.00 Column Total  Row Total  1  Chi-Square  Value  DF  2 .39788 1.53990 2.47143 2.35654  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected Frequency  -  Significance .12150 .21463 .11593 .12476  6.517  Number of M i s s i n g O b s e r v a t i o n s :  0  Unemployment CL  Count  middle UNEMPLOY  2  26  16  42 72 . 4  5  11  16 27.6  31 53.4  27  58  46.6  100.0  1.00  Chi-Square  Value  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association Minimum Expected  Row Total  1 . 00  Column Total  lower  Frequency  Number of M i s s i n g O b s e r v a t i o n s :  4.37590 3 .23057 4.43384 4.30046 7 .448 0  DF  Significance . 03645 . 07228 . 03523 .03810  231  Appendix D  Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Suicide CL Count middle SUICIDE  lower Row Total  1  2  .00  28  24  52 89.7  1.00  3  3  6 10.3  31 53.4  27 46.6  58 100.0  Column Total  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  .03198 .00000 .03192 .03143  Significance .85807 1.00000 .85821 .85928 .59560 1.00000  Minimum Expected Frequency 2.793 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  Value  Chi-Square  0  2 OF  4 ( 50.0%)  232  Appendix D Chi Square Analyses of Female Respondents' Choices of Important Issues by Client Class Vocation CL Count  VOCATION  middle  lower Row Total  1  2  .00  30  23  53 91.4  1.00  1  4  5 8.6  31 53.4  27 46.6  58 100.0  Column Total Chi-Square  Pearson Continuity Correction Likelihood Ratio Mantel-Haenszel t e s t f o r linear association F i s h e r ' s Exact T e s t : One-Tail Two-Tail  2.46037 1.20913 2.57860 2.41795  Significance  1 1 1 1  .11675 .27150 .10832 . 11995 .13635 .17343  Minimum Expected Frequency 2.328 C e l l s w i t h Expected Frequency < 5 Number of M i s s i n g O b s e r v a t i o n s :  DF  Value  0  2 OF  4 ( 50.0%)  233 Appendix DI Independent Samples T-Tests for Proposed Length of Therapy by Respondent Gender Female Respondents  Variable  Number of Cases  Mean  SD  SE of mean  24 20  13.04 14.40  7.80 8.43  1.59 1.89  middle class lower class  Mean Difference = 1.36  Levene's test for Equality of Variances: F = .026  P = .873  T-Test for Equality of Means  Variances Equal Unequal  t-value  df  2-Tail Sign  Mean Diff  SE of Diff  95% CI for Diff  -.554 -.550  42 39.263  .582 .585  -1.36 -1.36  2.45 2.47  (-6.30, 3.59) (-6.35, 3.63)  Male Respondents  Variable  Number of Cases  Mean  SD  SE of mean  23 20  17.52 11.95  12.76 7.61  2.66 1.70  middle class lower class  Mean Difference = 5.57 Levene's test for Equality of Variances: F = 3.457  P = .070  T-Test for Equality of Means  Variances Equal Unequal  t-value  df  2-Tail Sign  1.706 1.765  41 3.579  .096 .086  Mean Diff  SE of Diff  5.57 5.57  3.27 3.16  95% CI for Diff (-1.03, 12.17) (-.83, 11.97)  234 Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) CI: Expressive/Inexpressive Number o f Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  4.4364 4.3750  1 873 2.171  253 .290  = .0614  f o r E q u a l i t y of Variances: F= 2.579  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  .16 .16  109 107.24  P= .111  SE of D i f f  95% CI f o r D i f f  .385 .385  (-.702, .825) (-.701, .824)  .874 .874  C2: Pessimistic/Optimistic Number o f Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  Mean  2.0364 2.2857  -.89 -.89  SE of Mean  1.319 1.615  .178 .216  = -.2494  f o r E q u a l i t y o f V a r i a n c e s : F= 3.430  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  SD  109 105.51  .375 .375  P= .067  SE of D i f f  95% CI f o r D i f f  .280 .280  (-.805, .306) (-.804, .305)  235  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C3: Trustworthy/Untrustworthy Number of Cases  Variable  middle c l a s s lower c l a s s  Mean  3.9273 3 .8000  55 55  Mean D i f f e r e n c e Levene's Test  . 42 . 42  1 . 665 1 . 532  . 225 .207  = .1273  f o r E q u a l i t y of V a r i a n c e s : F= .442  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SE of Mean  SD  108 107.26  P= .508  SE of D i f f  95% CI f o r D i f f  .305 .305  (-.478, .732) (-.478, .732)  . 677 . 677  C4: Competent/Incompetent Number of Cases  Variable  middle c l a s s lower c l a s s  54 56  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  3.8889 4.2321  1.436 1.640  .195 .219  = -.3433  f o r E q u a l i t y of V a r i a n c e s : F= .279  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  -1.17 -1.17  108 107.02  .246 .245  P= .598  SE of D i f f  95% CI f o r D i f f  .294 .294  (-.927, .240) (-.926, .239)  236  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C5: Unintelligent/Intelligent Number of Cases  Variable  middle c l a s s lower c l a s s  55 55  Mean  SD  5.2545 3.4545  SE of Mean  1.443 1.525  .195 .206  Mean D i f f e r e n c e = 1.8000 Levene's Test  f o r E q u a l i t y of V a r i a n c e s : F= .099  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  6.36 6.36  108 107.67  95% CI f o r D i f f  SE of D i f f  .000 .000  P= .754  .283 .283  (1.239, 2.361) (1.239, 2.361)  C6: Involved/Withdrawn  Variable  Number of Cases  Mean  SjD  SE of mean  56 55  5.04 4.67  1.66 1.88  .22 .25  middle class lower class Mean Difference = .37  Levene's test for Equality of Variances: F = 1.567 t-test for Equality of Means Variances t-value Equal Unequal  1.079 1.078  P = .213  df  2-Tail Sign  Mean Diff  109 106.942  .283 .283  .36 .36  237  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C7: Industrious/Lazy Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  Mean  3.5818 3.8214  -.97 -.97  SE of Mean  1.410 1.177  .190 .157  = -.2396  f o r E q u a l i t y of V a r i a n c e s : F= 2.723  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  109 104.95  95% CI f o r D i f f  SE o f D i f f  .333 .334  P= .102  .246 .247  (-.728, .249) (-.729, .250)  C8: Impulsive/Reliable Number of Cases  Variable  middle c l a s s lower c l a s s  55 55  Mean D i f f e r e n c e Levene's Test  Mean  2.2364 2 .4909  -.94 -.94  SE o f Mean  1 .261 1. 550  . 170 .209  = -.2545  f o r E q u a l i t y o f V a r i a n c e s : F= 3.412  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail Sig Equal Unequal  SD  108 103.72  .347 .347  SE o f D i f f .269 .269  P=  067  95% CI f o r D i f f (-.789, (-.789,  .280) .280)  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C9: Responsible/Irresponsible Number of Cases  Variable  middle c l a s s lower c l a s s  55 55  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  4.4909 4.3818  1.814 1.748  .245 .236  = .1091  f o r E q u a l i t y of Variances: F= .075  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  .32 .32-  108 107.85  P= .785  SE of D i f f  95% CI f o r D i f f  .340 .340  (-.'564, .783) (-.564, .783)  .749 .749  C10: Ignorant/Knowledgeable Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  4.2909 3.3929  1.560 1.397  .210 .187  = .8981  f o r E q u a l i t y of V a r i a n c e s : F= .498  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  3.20 3.19  109 107.25  .002 .002  P= .482  SE of D i f f  95% CI f o r D i f f  .281 .281  (.341, 1.455) (.340, 1.456)  239  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) CI 1: Friendly/Hostile Number of C a s e s  Variable  middle c l a s s lower c l a s s  Mean  55 56  SD  4.7636 4.2143  SE o f Mean  1.201 1.486  .162 .199  Mean D i f f e r e n c e = .5494 Levene's Test f o r E q u a l i t y  o f V a r i a n c e s : F= .906  t - t e s t f o r E q u a l i t y o f Means Variances t-value df 2-Tail S i g Equal Unequal  2.14 2.14  109 105.14  .035 .034  95% CI f o r D i f f  SE o f D i f f  ( . 0 4 0 1 058) (.041, 1.058)  .257 .256  '  P= .343  C12: Loud/Quiet Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean  SD  4.6545 3.9643  SE o f Mean  1.506 1.629  203 '.218  Mean D i f f e r e n c e = .6903 . Levene's T e s t f o r E q u a l i t y o f V a r i a n c e s : F= .088 t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  2.32 2.32  109 108.61  .022 .022  P= .767  SE of D i f f  95% CI f o r D i f f  .298 .298  (.100, 1.281) (.100, 1.280)  240  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C13: Clean/Dirty Number of Cases  Variable  middle c l a s s lower c l a s s  Mean  55 56  Mean D i f f e r e n c e Levene's Test  2.9818 3.7143  -2 . 89 -2 . 89  SE of Mean  1 .367 1.303  . 184 . 174  = -.7325  f o r E q u a l i t y of V a r i a n c e s : F= 5.188  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SD  109 108.52  95% CI f o r D i f f  SE of D i f f  . 005 . 005  .254 .254  P= .025  (-1.235, -.230) (-1.235, -.230)  C14: Emotional/Controlled Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  2.43 2.43  SD  3.8909 2 . 9464  SE of Mean  2 . 096 2 . 004  .283 .268  = .9445  f o r E q u a l i t y o f V a r i a n c e s : F= 2.676  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  Mean  109 108.56  . 017 . 017  P= .105  SE of D i f f  95% CI f o r D i f f  . 389 .389  (.173, 1.716) (.173, 1.716)  241 Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C15: Moral/Immoral Number of Cases  Variable  middle c l a s s lower c l a s s  Levene's Test  - . 04 -.04  SE of Mean  193 186  = -.0120  f o r E q u a l i t y of V a r i a n c e s : F= .177  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  1 .428 1.392  3 . 3273 3.3393  55 56  Mean D i f f e r e n c e  SD  Mean  109 108.79  P= .675  SE of D i f f  95% CI f o r D i f f  .268 .268  (-.543, .519) (-.543, .519)  . 964 . 964  C16: Incapable/Capable Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  Mean  SD  4 .2000 3 . 5536  1.660 1.560  2.11 2.11  .224 . 208  = .6464  f o r E q u a l i t y o f V a r i a n c e s : F= .383  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  SE o f Mean  109 108.30  . 037 . 037  P= .537  SE of D i f f  95% CI f o r D i f f  . 306 .306  (.040, 1.252) (.040, 1.253)  242  Appendix E  Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C17: Defensive/Receptive Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  -1.12 -1.12  SD  SE of Mean  2 .4727 2.7857  1.317 1. 615  . 178 .216  = -.3130  f o r E q u a l i t y of Variances: F= 2.608  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  Mean  109 105.47  P= .109  SE of D i f f  95% CI f o r D i f f  .280 . 279  (-.868, .242) (-.867, .241)  .266 .265  C18: Aggressive/Peaceful Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  .03 .03  SD  SE o f Mean  2 . 5636 2.5714  1.229 1.189  .166 .159  = -.0078  f o r E q u a l i t y of V a r i a n c e s : F= .030  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  Mean  109 108.71  .973 .973  P= .863  SE of D i f f  95% CI f o r D i f f  .229 .230  (-.463, .447) (-.463, .447)  243  Appendix E Client Characteristics: T-Tests for Independent Samples of Social Class (N = 111) C19: Dishonest/Honest Number of Cases  Variable  middle c l a s s lower c l a s s  55 56  Mean D i f f e r e n c e Levene's Test  Mean  SD  SE of Mean  4.2182 3.8393  1.524 1.558  .205 .208  = .3789  f o r E q u a l i t y of V a r i a n c e s : F= .272  t - t e s t f o r E q u a l i t y of Means Variances t-value df 2-Tail Sig Equal Unequal  1.29 1.30  109 109.00  . 198 . 198  SE of D i f f .293 .293  P= .603  ci  95% for Diff  (-.201, (-.201,  .959) .959)  244 Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) C I : Expressive/inexpressive Tests of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C I u s i n g UNIQUE sums o f s q u a r e s DF SS MS  WITHIN+RESIDUAL CL DEG CL BY DEG  391 83 58 12 7 55  89 1 1 1  4 40 58 12 7 55  (Model) (Total)  9 20 401 03  3 92  3 07 4 36  R-Squared = A d j u s t e d R-Squared =  F  Sig of F  . 13 . 03 1 . 72  .717 . 872 . 194  . 70  . 557  .023 .000  C2: Pessimistic/optimistic T e s t s of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C2 u s i n g UNIQUE sums of squares SS DF MS  WITHIN+RESIDUAL CL DEG CL BY DEG  202 .55 .11 4 .05 3 . 51  89 1 1 1  2 28 11 4 05 3 51  (Model) (Total)  7 .96 210 . 52  3 92  2 . 65 2 29  R-Squared = A d j u s t e d R-Squared =  F  S i g of  . 05 1.78 1 . 54  . 827 . 186 .217  1.17  . 327  C3 u s i n g UNIQUE sums of squares SS DF F MS  S i g of F  .038 .005  C3: Trustworthy/untrustworthy T e s t s of S i g n i f i c a n c e for Source of V a r i a t i o n WITHIN+RESIDUAL CL DEG CL BY DEG  242 72 99 1 65 00  89 1 1 1  2 73 99 1 65 00  (Model) (Total)  2 .98 245. 70  3 92  99 2 67  R-Squared = A d j u s t e d R-Squared -  .012 .000  . 36 . 60 . 00  . 549 . 439 .966  .36  . 779  245  Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) C4: Competent/incompetent T e s t s o f S i g n i f i c a n c e f o r C4 u s i n g UNIQUE sums Of s q u a r e s Source of V a r i a t i o n DF F SS MS WITHIN+RESIDUAL CL DEG CL BY DEG  228 41 1 49 3 10 62  89 1 1 1  2 57 1 49 3 10 62  (Model) (Total)  4 49 232 90  3 92  1 50 2 53  R-Squared = Adjusted R-Squared =  Sig of F  . 58 1 .21 . 24  . 448 . 274 . 623  . 58  . 627  .019 .000  C5: Unintelligent/intelligent Tests of S i g n i f i c a n c e f o r C5 u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS F WITHIN+RESIDUAL CL DEG CL BY DEG  211 67 1 3  89 55 43 64  89 1 1 1  2 67 1 3  (Model) (Total)  78 77 290 67  3 92  26 26 3 16  R-Squared = Adjusted R-Squared =  38 55 43 64  S i g of F  28.37 . 60 1.53  . 000 .440 .220  11.03  .000  .271 .246  C6: involved/withdrawn Tests of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C6 u s i n g UNIQUE sums o f squares DF SS. MS  WITHIN+RESIDUAL CL DEG CL BY DEG  262 88 1 18 04 33 98  89 1 1 1  2 95 1 18 04 33 98  (Model) (Total)  38 36 301 25  3 92  12 79 3 27  R-Squared = Adjusted R-Squared- =  . 127 . 098  F  S i g of F  40 01 11 51  . 529 .909 . 001  4 33  . 007  246 Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) C7: Industrious/lazy T e s t s of S i g n i f i c a n c e f o r C7 using UNIQUE sums of squares Source of V a r i a t i o n SS DF MS F WITHIN+RESIDUAL CL DEG CL BY DEG  149 84 1 86 63 3 37  89 1 1 1  1 68 1 86 63 3 37  (Model) (Total)  4 89 154 73  3 92  1 63 1 68  R-Squared = A d j u s t e d R-Squared =  1 .11 . 37 2 . 00 . 97  S i g of F .296 . 542 . 161 .411  .032 .000  C8: Impulsive/reliable T e s t s of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C8 u s i n g UNIQUE sums o f s SS DF MS  WITHIN+RESIDUAL CL DEG CL BY DEG  179.96 5.02 4.04 2.87  89 1 1 1  2.02 5.02 4.04 2.87  (Model) (Total)  9.87 189.83  3 92  3.29 2.06  R-Squared = A d j u s t e d R-Squared =  F  S i g of F  2.48 2.00 1.42  .119 ' .161 .237  1.63  .189  . 052 020  C9: Responsible/irresponsible  Source o f V a r i a t i o n  r C9 u s i n g UNIQUE sums of squares SS DF MS F  WITHIN+RESIDUAL CL DEG CL BY DEG  285 20 17 5 59 3 23  89 1 1 1  3 20 17 5 59 3 23  (Model) (Total)  9 44 294. 65  3 92  3 15 3 .20  R-Squared = A d j u s t e d R-Squared =  . 032 . 000  S i g of F  . 05 1.74 1.01  .821 . 190 . 318  .98  . 405  Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) CIO: Ignorant/knowledgeable T e s t s of S i g n i f i c a n c e f o r CIO u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS F WITHIN+RESIDUAL CL DEG CL BY DEG  201 .35 19 .46 01 5 .76  89 1 1 1  2 . 26 19.46 . 01 5 . 76  (Model) (Total)  29 .81 231 .16  3 92  9 . 94 2 .51  R-Squared = A d j u s t e d R-Squared =  S i g of F  8 . 60 . 00 2 . 55  . 004 . 945 . 114  4 . 39  . 006  .129 .100  CI 1: Friendly/hostile T e s t s o f S i g n i f i c a n c e f o r C l l u s i n g UNIQUE sums of squares Source o f V a r i a t i o n SS DF MS F WITHIN+RESIDUAL CL DEG CL BY DEG  159.90 4 . 30 2 .37 5.47  89 1 1 1  1. 80 4 . 30 2 .37 5.47  (Model) (Total)  14.57 174.47  3 92  4.86 1.90  R-Squared = A d j u s t e d R-Squared =  S i g of F  2 . 39 1 . 32 3 . 04  . 126 .254 . 085  2.70  . 050  .084 .053  C12: Loud/quiet T e s t s o f S i g n i f i c a n c e f o r C12 u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS F WITHIN+RESIDUAL CL DEG CL BY DEG  223.62 17.01 . 10 13 . 93  89 1 1 1  2 . 51 17.01 . 10 13 . 93  (Model) (Total)  37 . 50 261.12  3 92  12.50 2 . 84  R-Squared = A d j u s t e d R-Squared =  . 144 .115  S i g of F  6 . 77 . 04 5 . 54  . 011 . 842 . 021  4 . 97  . 003  248  Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) C13: Clean/dirty Tests of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C13 u s i n g UNIQUE sums o f squares SS DF MS F  WITHIN+RESIDUAL CL DEG CL BY DEG  172 91 10 46 70 1 01  89 1 1 1  (Model) (Total)  10. 92 183 .83  3 92  R-Squared = Adjusted R-Squared =  1 94 10 46 70 1 01 .  3 64 2 .00  S i g of F  5 38 36 52  . 023 . 549 . 474  1 87  . 140  .059 .028  C14: Emotional/controlled Tests of S i g n i f i c a n c e source of V a r i a t i o n  f o r C14 u s i n g UNIQUE sums o f squares SS DF MS F  WITHIN+RESIDUAL CL DEG CL BY DEG  329 .73 19 . 64 . 00 38 . 16  89 1 1 1  3 .70 19 64 00 38 16  (Model) (Total)  68 92 398 65  3 92  22 97 4. 33  R-Squared = Adjusted R-Squared =  S i g of F  5 .30 00 10 30  . 024 .999 . 002  6 20  . 001  .173 .145  C15: Moral/immoral Tests of S i g n i f i c a n c e f o r C15 C15 uussii n g UNIQUE sums of Source of V a r i a t i o n SS DF MS WITHIN+RESIDUAL CL DEG CL BY DEG  178 .28 05 08 5 46  89 1 1 1  2 00 05 08 5 46  (Model) (Total)  5. 53 183 .81  3 92  1. 84 2 .00  R-Squared = Adjusted R-Squared =  . 030 .000  S i g of F .03 .04 2.73  .871 .843 .102  .92  .435  249  Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) C16: Incapable/capable Tests of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C16 u s i n g UNIQUE sums o f s q u a r e s SS DF MS F  WITHIN+RESIDUAL CL DEG CL BY DEG  223 6 1 10  80 94 08 92  89 1 1 1  (Model) (Total)  22. 10 245. 89  3 92  R-Squared = A d j u s t e d R-Squared  2 6 1 10  51 94 08 92  7 37 2. 67  Sig of F  2 76 43 4 34  . 100 . 514 . 040  2 93  . 038  .090 .059  =  C17: Defensive/receptive T e s t s of S i g n i f i c a n c e Source of V a r i a t i o n  f o r C17 using UNIQUE sums of squares SS DF MS F  WITHIN+RESIDUAL CL DEG CL BY DEG  162 . 17 2 .46 06 1 08  89 1 1 1  1 82 2 46 06 1 08  (Model) (Total)  3 _,. 08 165.2S 165. 25  j 3 Q -5 92  ±.US 1. 03 i1. 80  uo  R-Squared = A d j u s t e d R-Squared =  1.35 . 03 .59 ..56 56  Sig of F . 249 . 855 .444 .640  .019 .000  C18: Aggressive/peaceful T e s t s of S i g n i f i c a n c e f o r CI 8 u Source of V a r i a t i o n SS  UNIQUE sums of squares DF MS F  WITHIN+RESIDUAL CL DEG CL BY DEG  136 . 43 09 42 3 31  89 1 1 1  1 .53 . 09 42 3 31  (Model) (Total)  3 .85 140. 28  3 92  1 28 1 52  R-Squared = A d j u s t e d R-Squared =  .027 .000  Sig of F  . 06 .27 2.16  . 814 . 602 . 145  ' .84  . 477  Appendix F Client Characteristics: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) C19: Dishonest/honest T e s t s o f S i g n i f i c a n c e f o r C19 u s i n g UNIQUE sums o f s q u a r e s Source of V a r i a t i o n SS DF MS F WITHIN+RESIDUAL CL DEG CL BY DEG  204 87 1 . 19 41 13 . 74  89 1 1 1  2.30 1 . 19 .41 13 .74  (Model) (Total)  17 . 13 222 . 00  3 92  5.71 2 .41  R-Squared = A d j u s t e d R-Squared =  . 077 . 046  Sig of F  . 51 .18 5 . 97  .475 . 676 .017  2.48  . 066  251 Appendix F Problem Evaluation: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) Perceived Client Self-Concept Tests of S i g n i f i c a n c e f o r T u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS WITHIN+RESIDUAL CL DEG CL BY DEG  68 . 63 .33 . 33 . 80  87 1 1 1  .79 .33 . 33 .80  (Model) (Total)  1 .48 70 . 11  3 90  .49 .78  R-Squared = Adjusted R-Squared =  F  S i g of F  42 42 1 02  . 518 . 518 .316  62  . 602  .021 .000  Prognosis Tests of S i g n i f i c a n c e Source of V a r i a t i o n  f o r I u s i n g UNIQUE sums o f squares SS DF MS  WITHIN+RESIDUAL CL DEG CL BY DEG  121.74 .71 2.58 .41  88 1 1 1  (Model) (Total)  3.94 125.68  3 91  R-Squared = Adjusted R-Squared =  .031 .000  1.38 .71 2.58 .41  1  3  1  1.38  F  S i g of F  .52 1.86 .30  .475 .176 .587  .95  4  2  o  252  Appendix F Problem Evaluation: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) Likelihood of Referring for Psychiatric Assessment Tests of S i g n i f i c a n c e f o r PSYC2 u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS F S i g of F WITHIN+RESIDUAL CL DEG CL BY DEG  296 15 66 1 31 1 52  88 1 1 1  3 37 66 1 31 1 52  (Model) (Total)  4 05 300 21  3 91  1 35 3 30  R-Squared = Adjusted R-Squared =  .20 .39 .45  . 660 . 535 .504  . 40  .752  .014 .000  Personal Interest in Treating This Client Tests of S i g n i f i c a n c e f o r G u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS WITHIN+RESIDUAL CL DEG CL BY DEG  193 1 20 7  06 19 62 96  88 1 1 1  (Model) (Total)  27 85 220 91  3 91  R-Squared = Adjusted R-Squared =  .12 6 .096  2 1 20 7  19 19 62 96  9 28 2 43  F  S i g of F  54 9 40 3 63  .464 . 003 . 060  4 23  . 008  Appendix F Problem Evaluation: Analyses of Variance by Client Social Class and Respondent Level of Education (N = 89) Severity of Presenting Problem Tests of S i g n i f i c a n c e f o r PRESPR2 using UNIQUE sums of Source of V a r i a t i o n SS DF MS  squares F S i g of F  WITHIN+RESIDUAL CL DEG CL BY DEG  59 . . . .  72 98 57 04  89 1 1 1  . 67 .98 . 57 . 04  1. 47 . 85 . 06  . 229 .359 . 800  (Model) (Total)  1 .. 57 61 .29 .  3 92  . 52 . 67  .78  . 508  F  S i g of F  R-Squared = A d j u s t e d R-Squared =  .026 .000  Perceived Client Motivation for Change T e s t s o f S i g n i f i c a n c e f o r A u s i n g UNIQUE sums of squares Source of V a r i a t i o n SS DF MS WITHIN+RESIDUAL CL DEG CL BY DEG  132 . 13 1 . 97 4 . 01 1 .41  89 1 1 1  1 .48 1 . 97 4 . 01 1 .41  (Model) (Total)  7 . 67 139 .81  3 92  2 . 56 1 . 52  R-Squared = A d j u s t e d R-Squared =  . 055 . 023  1..33 2..70 .95  .253 . 104 .332  1..72  . 168  254  Appendix G Problem Evaluation: Analyses of Variance by Respondents' Years of Experience and Client Social Class (N = 99) Severity of Presenting Problem: Source o f V a r i a t i o n  SS  DF  MS  84 04 63 93  99 4 1 4  .65 .26 . 63 .73  9 108  DF  WITHIN+RESIDUAL EXPERYRS CL EXPERYRS BY CL  64 . 1. . 2.  (Model) (Total)  4 93 69 76  R-Squared = A d j u s t e d R-Squared =  F  S i g of F  .40 . 97 1 . 12  .811 . 328 .352  .55 . 65  . 84  . 585  MS  F  071 000  Client Motivation for Chan ge: Source of V a r i a t i o n  SS  WITHIN+RESIDUAL EXPERYRS CL EXPERYRS BY CL  145 .29 3 . 74 3 . 08 23 . 48  99 4 1 4  (Model) (Total)  29 . 32 174 . 61  9 108  3.26 1. 62  SS  DF  MS  WITHIN+RESIDUAL EXPERYRS CL EXPERYRS BY CL  71 . 44 2 .01 14 5 .12  97 4 1 4  . 74 . 50 . 14 1 .28  (Model) (Total)  8 .73 80. 17  9 106  . 97 .76  R-Squared = A d j u s t e d R-Squared =  1 . 47 . 94 3 . 08 5 . 87  S i g of F  .'64 2 . 10 4 .00  . 637 . 151 . 005  2 .22  . 027  . 168 . 092  Client Self-Concept: Source o f V a r i a t i o n  R-Squared = A d j u s t e d R-Squared =  .109 .026  F  S i g of F  68 20 1. 74  . 607 . 658 . 148  1. 32  .238  255 Appendix G Problem Evaluation: Analyses of Variance by Respondents' Years of Experience and Client Social Class (N = 99) Prognosis: Source of V a r i a t i o n  SS  DF .  WITHIN+RESIDUAL EXPERYRS CL EXPERYRS BY CL  133 5 2 17  60 57 09 66  97 4 1 4  (Model) (Total)  26 75 160 36  9 106  R-Squared = Adjusted R-Squared =  1 1 2 4  MS  F  38 39 09 41  1 01 1 52 3 21  .405 . 221 .016  2 16  . 032  2 97 1 51  Sig of F  .167 .090  Likelihood of Referring Client for Psychiatric Assessment: Source of V a r i a t i o n  SS  DF  MS  F  S i g of F  WITHIN+RESIDUAL EXPERYRS CL EXPERYRS BY CL  334 2 3 10  90 32 48 57  98 4 1 4  3 . 42 . 58 3 .48 2 . 64  (Model) (Total)  19 42 .354 32  9 107  2 . 16 3 .31  . 63  DF  MS  F  98 4 1 4  2 30 3 24 54 3 30  1 41 24 1 43  .238 . 628 .229  9 • 107  2 81 2 35  1 22  .292  R-Squared = Adjusted R-Squared =  . 17 1 . 02 . 77  .953 .315 . 545 .768  .055 .000  Personal Interest in Treating the Client: Source of V a r i a t i o n  SS  WITHIN+RESIDUAL EXPERYRS CL EXPERYRS BY CL  225 . 64 12 95 ' 54 13 20  (Model) (Total)  25 28 250 92  R-Squared = Adjusted R-Squared =  . 101 . 018  S i g of F  

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