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Multicultural counselling self-efficacy among school counsellors in British Columbia Adams, Cynthia 2015

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MULTICULTURAL COUNSELLING SELF-EFFICACY AMONG SCHOOL COUNSELLORS IN BRITISH COLUMBIA by  Cynthia Adams B.A., Simon Fraser University, 1999 B.Ed., The University of British Columbia, 2001    A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF ARTS in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Counselling Psychology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  July 2015  © Cynthia Adams, 2015  ii Abstract Across Canada, schools are serving an increasingly multicultural student population, one with diverse and sometimes unfamiliar experiences and worldviews. Despite this fact, very little research has been conducted on school counsellor multicultural self-efficacy in Canada. To address this gap, a survey research design was used to assess the level of multicultural self-efficacy among a sample of school counsellors (N = 226) in British Columbia. This study also sought to identify the demographic and workplace variables that contribute to higher levels of multicultural counselling self-efficacy among school counsellors in British Columbia.  In addition, the study examined the relative contribution of years of experience versus caseload diversity, and the impact of high levels of multicultural training on the relationship between self-efficacy and years of experience. The School Counselor Multicultural Self-Efficacy Scale (SCMES; Holcomb-McCoy, Harris, Hines, & Johnston, 2008) measured self-efficacy across six factors. Results suggest that BC school counsellors have moderate to high levels of multicultural counselling self-efficacy across all six factors of the SCMES. Hierarchical regression analyses were used to identify the unique contributions of specific predictor variables to specific SCMES factors. Three distinct patterns emerged. In Pattern #1, graduate-level multicultural training courses, and frequency of cross-cultural sessions were the most influential predictors. In Pattern #2, multicultural training alone exerted the greatest influence. However, in Pattern #3, teaching experience and community setting combined with graduate-level multicultural training as significant contributors to a single factor: Factor 3 (Developing Cross-Cultural Relationships). Factor 3 plays an important and unique role in subsequent analyses. The implications of these findings for counsellor training and practice, and suggestions for further research are discussed.   iii Preface This thesis is an original, unpublished, independent work by the author, Cynthia Adams.  This project required the approval of the University of British Columbia Behavioral Research Ethics Board. The project, entitled “Multicultural Counselling Self-Efficacy Among School Counsellors in British Columbia,” received ethics approval on October 2, 2014 (Certificate Number H14-02534).   iv Table of Contents  Abstract .......................................................................................................................................... ii	  Preface ........................................................................................................................................... iii	  Table of Contents ......................................................................................................................... iv	  List of Tables ............................................................................................................................... vii	  Acknowledgements ...................................................................................................................... ix	  Chapter 1: Introduction ................................................................................................................1	  Research Questions ..................................................................................................................... 3	  Chapter 2: Literature Review .......................................................................................................5	  Theoretical Underpinnings – Self-Efficacy ................................................................................ 5	  Theoretical Underpinnings – Multicultural Counselling Theory ................................................ 9	  Review of Research – MCC and MCSE ................................................................................... 13	  Chapter 3: Method .......................................................................................................................33	  Research Design: ...................................................................................................................... 33	  Sample / Participants ................................................................................................................. 33	  Procedures ................................................................................................................................. 33	  Instruments ................................................................................................................................ 36	  School Counsellor Multicultural Self-Efficacy Scale (SCMES) .......................................... 36	  Demographic and Workplace Questionnaire ........................................................................ 37	  Chapter 4: Results ........................................................................................................................38	  Response Rate ........................................................................................................................... 38	  Participant Characteristics ........................................................................................................ 38	   v Workplace Characteristics ........................................................................................................ 39	  School and Caseload Diversity Characteristics ........................................................................ 41	  SCMES Factors – Normality of Distribution and Outliers ....................................................... 43	  Research Question 1 ................................................................................................................. 44	  Research Question 2 ................................................................................................................. 46	  Demographic Hypotheses: .................................................................................................... 46	  Workplace Hypotheses: ........................................................................................................ 47	  School and Caseload Diversity Hypotheses: ........................................................................ 48	  Preliminary Analysis ............................................................................................................. 49	  Secondary Analysis ................................................................................................................... 52	  Rationale for Using Hierarchical Multiple Linear Regression Analysis .............................. 52	  Research Question 3 ................................................................................................................. 62	  Research Question 4 ................................................................................................................. 64	  Chapter 5: Discussion ..................................................................................................................71	  Research Question 1 ................................................................................................................. 71	  Research Question 2 ................................................................................................................. 73	  Preliminary Results: Hypotheses that Retained the Null ...................................................... 73	  Preliminary Results: Hypotheses that Rejected the Null ...................................................... 75	  Secondary Results: Regression Analyses ................................................................................. 79	  Pattern 1: Factors with Two Contributing Variables:  MC Training and Frequency of Cross Cultural Sessions ...................................................... 80	  Pattern 2: Factors with One Contributing Variable: MC Training ....................................... 82	    vi Pattern 3: Factors with Three Contributing Variables:  Teaching Experience, MC Training, and Community Setting ............................................. 84	  Research Question 3 ................................................................................................................. 86	  Research Question 4 ................................................................................................................. 87	  Limitations ................................................................................................................................ 89	  Implications for School Counsellor Training and Practice ....................................................... 91	  Suggestions for Future Research .............................................................................................. 92	  References .....................................................................................................................................94	  Appendices ..................................................................................................................................104	  Appendix A: Survey Instruments ........................................................................................... 104	  Appendix B: Preliminary Results of Demographic Hypotheses ............................................ 111	  Appendix C: Preliminary Results of Workplace Hypotheses ................................................ 115	  Appendix D: Preliminary Results of School and Caseload Diversity Hypotheses ................ 117	  Appendix E: Inter-correlations among Predictor Variables and Criterion Variables ............ 120	  Appendix F: Hierarchical Multiple Regression Tables	  for Factors 1 through 6 and the Total Scale ............................................................................ 122	    vii List of Tables Table 1: Prevalence of Cultural Groups in Participant Caseloads ............................................... 42	  Table 2: Prevalence of Majority Cultures in Participant Caseloads ............................................. 42	  Table 3: Correlations and Alphas Among Scales of SCMES ...................................................... 45	  Table 4: Descriptive Statistics for SCMES .................................................................................. 45	  Table 5: Graduate MC Training: Correlations, Significance  and Variance with SCMES Factors .............................................................................................. 50	  Table 6: In-Service MC Training: Correlations, Significance  and Variance with SCMES Factors .............................................................................................. 50	  Table 7: Frequency of Cross Cultural Counselling Sessions  and Correlations, Significance and Variance with SCMES Factors ............................................. 52	  Table 8: Inter-correlations Among Regression Predictor Variables ............................................ 55	  Table 9: Hierarchical Regression Analysis - SCMES Factor 1  - Knowledge of Multicultural Concepts (N = 212) ....................................................................... 56	  Table 10: Hierarchical Regression Analysis - SCMES Factor 2  - Using Data and Understanding Systemic Change (N = 212) ..................................................... 57	  Table 11: Hierarchical Regression Analysis - SCMES Factor 3  - Developing Cross Cultural Relationships (N = 212) .................................................................. 58	  Table 12: Hierarchical Regression Analysis - SCMES Factor 4  - Multicultural Counselling Awareness (N = 212) ...................................................................... 59	  Table 13: Hierarchical Regression Analysis - SCMES Factor 5  - Multicultural Assessment (N = 212) .......................................................................................... 60	    viii Table 14: Hierarchical Regression Analysis - SCMES Factor 6  - Application of Racial and Cultural Knowledge to Practice (N = 212) ....................................... 61	  Table 15: Hierarchical Regression Analysis - SCMES Total Score (N = 212) ........................... 62	  Table 16: Correlations between SCMES Factors and Years of Experience  and Frequency of Cross Cultural Sessions (N = 226) ................................................................... 63	  Table 17: Hierarchical Regression Analysis Results for Years of Experience  and Caseload Diversity (N = 212) ................................................................................................ 64	  Table 18: Correlation of Teaching Experience with Self-Efficacy  at Increasing Levels of Multicultural Counselling Graduate Training ......................................... 67	  Table 19: Correlation of Counselling Experience with Self-Efficacy  at Increasing Levels of Multicultural Counselling Graduate Training ......................................... 68	  Table 20: Correlation of Teaching Experience with Self-Efficacy  at Increasing Levels of Multicultural In-Service Training ........................................................... 69	  Table 21: Correlation of Counselling Experience with Self-Efficacy  at Increasing Levels of Multicultural In-Service Training ........................................................... 70	  Table 22: Means and Standard Deviations for SCMES Items 7, 16, 40 and 49  Sorted by Counsellor Grade Level ................................................................................................ 72	  Table 23: Contributions to Variance in SCMES Factors and Total Scale:  Teaching Experience, MC Graduate -Level Training, Community Setting  and Frequency of Cross Cultural Sessions .................................................................................... 80	     ix Acknowledgements  I would like to express my deepest thanks to the members of my supervisory team: Dr. Buchanan for advising on the overall design and staging of the study, Dr. Ishiyama for helping to select and critique the survey instruments, and Dr. Cox for guiding the analysis and interpretation of the survey data.  I would also like to thank the staff and students (past and present) of Guildford Park Secondary, who astonish me daily with their dedication, courage and humility. You are the inspiration for this project. Finally, I would like to thank my partner, Jan, for her encouragement and endless good humour throughout this long journey.    1 Chapter 1: Introduction Schools are microcosms of the societies to which they belong.  In recent years, schools have been swept up in the rising tide of multiculturalism.  This reflects a trend both national and local in scope. For example, Census data reveals British Columbia as having very high levels of diversity: cultural and linguistic. In the Lower Mainland, approximately 40.2% of residents belong to a visible minority (Statistics BC, 2006).  Cutting across visible majority and minority cultures are invisible minorities: those defined by class, religion and sexual orientation, among others.  Canada prides itself on its policies of inclusiveness.  Unfortunately, not everyone is at ease in our diverse society.   As many as 8% of Canadians feel unwelcome, or out of place in their communities (Collins & Arthur, 2007).  At the same time, minority populations typically underutilize mental health services, and those that do seek help frequently terminate prematurely (Cheung & Snowden, 1990; Echemendia & Nunez, 2004; McCabe, 2002; Sue & Sue, 2013; Zane, Enonmoto, & Chun, 1994).  This dual sense of disconnection has two significant implications for counsellors.  First and foremost, disconnection is detrimental to individual mental health, as it fosters isolation and distrust.  Secondly, disconnection suggests that conventional mental health services are unable to meet the needs of some minority clients.  This, in turn, indicates the very important role of cultural literacy in helping counsellors build effective therapeutic relationships with their clients.  However, awareness is not enough. If counsellors are to work across cultures, they must feel confident in their ability to apply their knowledge and skill across cultures.  In other words, they require a foundation of multicultural counselling self-efficacy.  2 Multicultural counselling self-efficacy is a specialized form of self-efficacy.  As such it heralds from social cognitive theory. According to Bandura (1990), “ . . . perceived self-efficacy is concerned with people’s beliefs in their capabilities to mobilize the motivation, cognitive resources, and courses of action needed to exercise control over task demands” (p. 316).  It is not a substitute for ability, but it can contribute mightily to task performance.  Although it is often used interchangeably with confidence, self-efficacy is a much more precise word. It communicates both the strength of belief, and the object of that certainty. Multicultural self-efficacy refers to the “ . . . self-perceived capability to counsel diverse clients” (Sheu & Lent, 2007, p. 31). Nowhere is this diversity more apparent than in the school system. Here, intersecting waves of identity – visible and invisible -- bring complex opportunities and challenges to school counsellors. Unfortunately, not all counsellors are equally equipped to work across cultures. At first glance, this may be difficult to understand.  Certainly the counselling profession has been evolving to incorporate multicultural awareness and skill into its discourse of theory, ethics and practice.  The paradigm of multicultural counselling itself has a well established, if recent, history. Referred to as the “Fourth Force” (Pedersen, 1991) of counselling psychology, it posits that all encounters with clients should be regarded as multicultural experiences.  This spirit of awareness is reflected in the codes of ethics that guide the counselling profession. For example, the American School Counselor Association designates an entire section (article E.2) of its Ethical Standards to the issue of diversity. Among its many recommendations, it states: “The professional counselor acquires educational, consultation, and training experiences to improve awareness, knowledge, skills, and effectiveness in working with diverse populations . . . ” (ASCA, p. 4). The Canadian Counselling and Psychotherapy Association similarly directs  3 “Counsellors [to] actively work to understand the diverse cultural background of the clients with whom they work . . . ” (CCPA, p. 9).  These are weighty directives, with significant consequences for students in multicultural settings.   In a similar vein, multicultural scholarship has provided guidelines for competent practice.  A great deal of debate has centered on the improvement of multicultural competence among counsellors (Collins & Arthur, 2007; Hays, 2009).  School counsellors have not escaped this scrutiny, and scales have been developed to measure both multicultural “competence” and “self-efficacy” among practitioners (Holcomb-McCoy, 2003; Holcomb-McCoy, 2004; Holcomb-McCoy, Harris, Hines, & Johnston, 2008; Robinson & Bradely, 2005).  Clearly, the development of skill and the confidence to use one’s skill, are central concerns in multicultural counselling. Poised against these pressures for reform, however, are the bureaucratic realities of the K to 12 Education System.  Schools are unique settings for counselling services, because schools already embody so many roles. Dual relationships and competing agendas are common in the school system, and school counsellors must consciously recalibrate themselves to give priority to the perspectives of their clients (Welfel, 2010).  To complicate matters somewhat, there is considerable variation among districts, schools, and professionals, in terms of the methods, theoretical orientation, and level of training of school counsellors.  Not all school counsellors share the vision of multicultural counselling, and some are simply unaware of it. Research Questions Given this context, I am interested in identifying the factors that enhance effective school counselling in multicultural settings.  More specifically, my study asks:   1. What is the level of self-reported multicultural self-efficacy among a sample of school counsellors in British Columbia?  4 2. What personal (demographic) and workplace variables are correlated with multicultural self-efficacy? 3. Does diversity of caseload have a stronger relationship with multicultural counselling self-efficacy than years of experience? 4. Among school counsellors with higher levels of training, do years of experience have a significantly stronger relationship with multicultural counselling self-efficacy, when compared to counsellors with less training? My research is premised on the notion that school counsellors are ethically and professionally invested in the issue, and that there are methods for measuring multicultural counselling self-efficacy (Holcomb-McCoy, Harris, Hines, & Johnston, 2008).  The answers to the questions would be of interest to the school counselling profession, and to the many communities that employ school counsellors. Furthermore, this research could help to guide the professional development and supervision of counsellors in schools.  It would promote the provision of equitable service to all students, and it might help preserve the integrity and relevance of the profession as a whole.    5 Chapter 2: Literature Review Theoretical Underpinnings – Self-Efficacy Self-efficacy offers some insight into how school counsellors adapt to the challenges posed by multiculturalism. Self-efficacy is a component of Albert Bandura’s (1986) Social Cognitive Theory. This theory affirms society’s contribution to peoples’ thoughts and actions, and it recognizes the importance of cognitive processes to emotions, motivations and actions. It has, as its basis, the tripartite model of Emergent Interactive Agency, in which environment, behavior, and personal factors influence one another reciprocally. As a cognitive construct, self-efficacy represents a very task-specific measure of confidence.  Self-efficacy determines whether a person will pursue a goal, how much effort they will expend, and whether or not they will persevere in the face of failures and setbacks (Bandura, 1997). As such, “Efficacy beliefs are the foundation of human agency” (Bandura, 2001, p. 10) or intentional, self-directed action. Self-efficacy is a unique concept. It cannot simply be equated to task competency. “Perceived self-efficacy is not a measure of the skills one has, but a belief about what one can do under different sets of conditions with whatever skills one possesses” (Bandura, 1997, p. 37). Similarly, self-efficacy is distinct from self-concept. While self-concept is stable and transcends specific situations and behaviors, self-efficacy varies from task to task, and is responsive to changes in perceived task difficulty. In fact, this responsiveness is an important defining quality.  It is necessary to reappraise self-efficacy when task demands change or when adaptation is required. This distinguishes informed confidence from recklessness, pointless persistence, or delusions of grandeur (Riggio, 2012). However, as Bandura explains, “The most functional efficacy judgments are those which slightly exceed what is possible at any given moment” (Colledge, p. 224).  Thus, while seemingly inflated self-efficacy scores may indicate exaggerated  6 self-confidence or a failure to accurately appraise task demands, higher self-efficacy also allows people to take measured risks: risks that enhance performance and bring forth new opportunities. Self-efficacy influences behavior directly and through a number of mediating processes: cognitive, motivational, affective and selective. These operate together in concert, not in isolation (Bandura, 1997). As a result, individuals with high self-efficacy are typically more optimistic, persistent and academically successful, and less anxious and depressed (Bandura, Barbaranelli, Caprara, & Pastorelli, 1996). They have greater interpersonal competence, personal control, and feelings of self-esteem and coping (Bandura, 1997). Thus, directly and indirectly, self-efficacy exerts considerable influence on task performance.  Fortunately, self-efficacy can be enhanced through a variety of avenues: direct experience, vicarious experience, social persuasion and physical or emotional states. Together, these variables affect self-efficacy across the life span. It is important to note that self-efficacy beliefs are unique to different areas of skill and task settings. For this reason, direct experience, or enactive mastery of skills, is the strongest predictor of self-efficacy (Bandura, 1986; Chen & Zimmerman, 2007). Prior successes build confidence, while prior failures erode it.  Vicarious experience is slightly different; it involves witnessing the behavior of others as they pursue goals with greater or lesser success. It is more common, but not as strong as direct experience. Vicarious experience is associated with modeling, role-playing and training generally. Social comparison is involved in this process (Bandura, 1997), and the more similar the model is to the observer (in terms of factors such as age, gender or task experience), the stronger the impact on the observer’s self-efficacy (Schunk & Zimmerman, 2007).  Social Persuasion is also a powerful force: messages from others can enhance or debilitate self-efficacy. Positive messages about capabilities and skills raise self-efficacy (Hattie &  7 Timperly, 2007), while disparagement and negative criticism reduce it (Pajares, 2006).  Again, as with vicarious experience, personal identification with the source of persuasion is key (Bussey & Bandura, 1999; Mellor, Bulger, & Kath, 2006), but the credibility of the source is also important (Riggio, 2012). In the counselling milieu, supervision makes good use of verbal persuasion, especially among trainees.   Finally, an individual’s physiological and emotional state can play a major role in their judgments of self-efficacy. Physical sensations are subject to attribution (Cioffi, 1991). These attributions, and their subsequent interpretation, influence self-efficacy and behavior. When sensations are attributed to fear, anxiety, or low mood, self-efficacy is reduced (Pajares, Johnson, & Usher, 2007). For this reason, reducing stress and negative emotions actually alters and improves self-efficacy beliefs (Bandura, 1997).  The enhancement of self-efficacy is important, because it has been implicated in so many areas of human endeavor, from the academic performance of children and young adults (Pajares & Graham, 1999) to enhanced athletic performance (Nicholls, Polman, & Levy, 2010).  Self-efficacy is also associated with counselling: general, school, and multicultural.  Since self-efficacy beliefs are unique to different areas of skill and to task settings, it is logical that research has yielded both general and specific factors that influence counselling self-efficacy, depending on the counselling environment and diversity of clients. Larson and Daniels (1998) examined the impact of various factors on general counselling self-efficacy, which they defined as, “ . . . one’s beliefs or judgments about one’s capabilities to effectively counsel a client in the near future,” (p. 180). In their review of 32 research studies, ranging from 1983 to 1998, the authors found that self-efficacy correlated most strongly with training, supervision and experience, although the developmental process was not clear. Similarly, while developing and testing the Counselor  8 Activity Self-Efficacy Scale (CASES), Lent, Hill, and Hoffman (2003) found that trainees with higher levels of experience had significantly higher counselling self-efficacy scores. These results support self-efficacy theory, which stresses the importance of direct experience, vicarious experience and social persuasion.   Shifting the focus from general counselling to school counselling, the importance of task demands and setting become more apparent. School counsellors have many unique duties – collaboration, consultation, assessment, advocacy (Holcomb-McCoy, Harris, Hines, & Johnston, 2008; Tadlock-Marlo, 2012) – and these are reflected in the factors that emerge in assessing self-efficacy. Here, general factors, such as experience, training and supervision, are tailored to suit the school setting. This is seen in the work of Sutton and Fall (1995), who developed the first self-efficacy scale for school counsellors, the Counselor Self-Efficacy Scale (CSS). In their research with the scale, they found that counsellor “efficacy expectancy” (self-efficacy) was affected by social persuasion, through the support of fellow teachers and administrators. Self-efficacy was also associated with caseload and non-counselling duties, the stresses of which may have diminished the counsellors’ physiological and emotional states. Gündüz (2012) detected similar patterns in his study of self-efficacy and burnout among school counsellors in Turkey. There, self-efficacy was enhanced by colleague support, and lowered by high caseloads. Experience is also an important factor, as Bodenhorn and Skaggs (2005) discovered while designing and testing the School Counselor Self-Efficacy Scale (SCSE). They found that self-efficacy was higher for individuals with direct experience, as school counsellors or teachers, and for women, who benefitted from the modeling (vicarious experience) provided by predominantly female peers.  9 Clearly, school counsellor self-efficacy is influenced by direct experience, vicarious experience, social persuasion and physiological and emotional states.  These in turn are uniquely shaped by task demands.  This rule of specificity is important, since it applies not only to counsellors who work in school settings, but also to counsellors who work with multicultural clients. Theoretical Underpinnings – Multicultural Counselling Theory Multicultural counselling theory is actually a meta-theory: a theory about theories. It provides an organizational framework for counselling philosophies and strategies. As such, it has motivated counsellors of all stripes to re-evaluate both their methods and the very nature of their relationship with clients. It has broadened the notion of diversity, and encouraged counsellors to become more aware and more educated about cultural differences.  And it has inspired a wide spectrum of new research, ranging from ethics and training, to supervision and competency, and the study of specialized populations and settings (Ridley & Kleiner, 2003).  Multicultural counselling theory has number of defining premises, as outlined by Sue, Ivey and Pedersen (1996). First, it acknowledges that clients and counsellors have multiple levels of experience that affect treatment, and that cultural identity is an important consideration in the therapeutic relationship. Secondly, it asserts that counsellors should use treatment goals and modalities that are both culturally consistent and mutually agreed upon (Collins & Arthur, 2007).  Finally, it directs counsellors to expand their role to include advocacy and systemic intervention, thus making counselling a route to social transformation (Bemak & Chung, 2008; Lee, Blando, Mizelle & Orozco, 2007). Its scope is wide, and its aspirations are revolutionary. Multicultural theory recognizes that cultural differences are not value-neutral: a hierarchy is enshrined in all our institutions, including counselling, and this hierarchy can be oppressive to  10 clients. Indeed, clients may come to counselling with histories of discrimination that compound mental health issues (D. Hays, 2008), and provoke mistrust. Some scholars have argued that the profession is “culturally encapsulated” (Hobson & Kanitz, 1996; Welfel, 2010), with counsellors holding a position of relative privilege (P. Hays, 2008).  From this position, it is possible for value conflicts, micro-aggressions, and color-blindness to rupture the therapeutic alliance (Arthur & Januszkowski 2001; Chao, Wei, Good & Flores, 2011). To prevent this, counsellors must work to develop multicultural competence. Sue and Sue (2013) describe multicultural competence (MCC) as superordinate to general counselling competence, because it recognizes the diversity inherent in all people.  This is supported by Constantine (2002), who found in her research that MCC is distinguishable from general counselling competence, and is associated with higher levels of counselling satisfaction among clients of color. The basic features of MCC – awareness, knowledge, and skills -- were first outlined by Sue and colleagues in 1982. According to Sue and Sue’s (2013) more recent definition: … a culturally competent helping professional is one who is actively in the process of  becoming aware of his or her own assumptions about human behavior, values, biases,  preconceived notions, personal limitations and so forth, … who actively attempts to  understand the worldview of his or her culturally different client, … [and] who is in the  process of actively developing and practicing appropriate, relevant, and sensitive  intervention strategies and skills in working with his or her culturally different client  (p. 47-48).   It is clear that the development of multicultural competence is an ongoing and aspirational process. From these three simple dimensions, increasingly detailed and complex models have emerged. For example, Sue, Arredondo, and McDavis (1992) expanded the number of competencies to 31, and organized them dimensionally along a continuum of increasing MCC.  These competencies were endorsed by the Association for Multicultural Counseling  11 Development (AMCD), and later operationalized by Arredondo and colleagues (1996). Then, in a bid for even greater MCC specificity, D. W. Sue (2001) conceptualized a multidimensional model of cultural competence (MDCC).  Here, awareness, knowledge and skills constitute just one dimension in a three-dimensional matrix: the other two dimensions are culture-specific attributes, and degrees of social complexity.  Meanwhile, counselling specialties were developing their own MCC models.  In her exploration of school MCC, Holcomb-McCoy (2004) used a theme analysis of the literature to identify 51 competencies. From this, she created a checklist for self-assessment and training purposes. This very small sample of models reveals some of the complexity of multicultural competence. It also foreshadows the complexity of MCC assessment. Multicultural theory has generated a great deal of research into the measurement of MCC, for both general and school settings (D. Hays, 2008; Lee, Blando, Mizelle, & Orzoco, 2007; Ridley & Kleiner, 2003). These scales are based roughly on the Sue et al. (1982) model of awareness, knowledge and skills, although there are notable variations.  Two of the instruments most commonly used to measure general MCC are the Multicultural Counselling Inventory (MCI; Sodowsky, Taffe, Gutkin, & Wise, 1994), and the Multicultural Counseling Competence and Training Survey (MCCTS; Holcomb & Meyers, 1999). For the specialty of school counselling there is the Multicultural Counseling Competence and Training Survey, Revised (MCCTS-R; Holcomb-McCoy & Day-Vines, 2004), and One School, Many Differences (OSMD; Tadlock-Marlo, Zyromski, Asner-Self, & Sheng, 2013).   MCC instruments have been subjected to considerable scholarly scrutiny, and their utility has been questioned. D. Hays (2008) asserts that there is a tendency for respondents to overestimate self-reports of MCC, and test results are biased by a number of confounding  12 factors, including social desirability. Most MCC scales use a self-report format. Yet, research by Cartwright, Daniels and Zhang (2008) demonstrates that self-rated MCC is significantly inflated when compared to observed MCC. In addition, Guzmán, Calfa, Van Horn Kerne and McCarthy (2013) have found that self-rated and observed MCC respond differently to training and experience.  Given this apparent disconnect, Worthington, Soth-McNett and Moreno (2007) recommend that MCC assessment should be based on observed behavior. This is especially true of MCC skills, which cannot be captured well in a written test.   In fact, MCC may not be captured in these tests at all. Both D. Hays (2008) and Worthington et al. (2007) suggest that these self-rated scales are indirectly assessing multicultural counselling self-efficacy (MCSE) instead of MCC.  This echoes the observations of Constantine and Ladany (2000), who recommend re-conceptualizing self-perceived MCC skills within the context of self-efficacy theory.  Certainly, recent research indicates that a relationship exists between MCC and MCSE. In her research with counsellor trainees, Constantine (2001) found that general MCC and MCSE were significantly correlated (r=0.51, p<0.001). Similarly, in a study of school counsellors, Owens, Bodenhorn and Bryant (2010) found that one scale of the SCSE (Bodenhorn & Skaggs, 2005) significantly predicted all scales of MCC on the MCCTS-R (Holcomb-McCoy & Day-Vines, 2004). For Worthington et al., the use of MCSE reduces the issue of confounding variables:  … whereas the measurement of self-efficacy by definition is inherently amenable to a  self-report format (e.g. it is reasonable for a person to self-report his or her confidence  in carrying out a specific action), the self-report measurement of competencies has  been described as susceptible to inherent biases that are difficult to control (p. 359).    Through the use of MCSE measures, a more accurate picture of counsellor potential emerges: one that reflects the confidence to perform multicultural tasks, and one that is responsive to the  13 interventions outlined in self-efficacy theory.  Given these advantages, Worthington and his team suggests that MCSE scales should supplement or even replace traditional measures of MCC. Review of Research – MCC and MCSE Since MCC and MCSE scales are measuring, however imperfectly, a similar phenomenon, they will be considered together in the review of the research literature. The literature shows that research in both areas is preoccupied with measuring MCC/MCSE and determining the demographic and professional factors that enhance it.  Not surprisingly, given the high degree of overlap between these two constructs, many of the factors that affect MCC also affect MCSE. In fact, much of the literature deals with the impact of training, supervision and experience.  These are self-efficacy constructs: vicarious experience, social persuasion and direct experience.  For this reason, all of the research will be viewed through the lens of self-efficacy theory. Multicultural training and supervision (when measured) are consistent contributors to self-rated MCC and MCSE. In most cases, more of each is better.  However, a less consistent picture emerges for experience.  In the literature reviewed, experience is mediated by multicultural specificity, frequency of contact with diverse cultures, and interactions with training.  Arthur and Januszkowski (2001) demonstrate the interplay of these forces. Their Canadian study is unique among the MCC literature: it uses quantitative and qualitative research methods. The authors explored self-rated general MCC and the associated demographic and professional variables among practicing counsellors, using quantitative means.  In addition, they identified which multicultural issues counsellors believe they are managing effectively or ineffectively.  This information is best captured qualitatively. To explore these questions, a sample of 181 members of the Canadian Guidance and Counselling Association (CGCA) was drawn by random selection, stratified by province.   14 A package of three questionnaires was mailed to the selected counsellors, with a response rate of 33%. There were two quantitative measures: the Multicultural Counseling Inventory, (MCI; Sodowsky, Taffe, Gutlin, & Wise, 1994), and a demographic questionnaire. The MCI is a 40-item scale that measures MCC along four dimensions: Awareness, Knowledge, Skills and Cross-Cultural Relationships. The scale as a whole has an internal consistency of α = 0.90. The questionnaire measured age, level of education, professional experience, and most importantly, multicultural casework, and multicultural caseload. In addition, a qualitative measure, the Critical Incidents Questionnaire (adapted from Ottavi, Pope-Davis, & Dings, 1994), asked subjects to recall two cross-cultural counselling sessions: one that went particularly well, and one that did not proceed as well as it could have. Subjects then described the presenting issues and the MCCs (awareness, knowledge, skills) that either contributed to the positive session, or which they would have liked to assist them.  The qualitative and quantitative data revealed the importance of specialized training and experience. Theme analysis was used to detect patterns among the critical incidents. This process revealed that the “keys to success” were multicultural awareness, multicultural knowledge, and general counselling skills, including consultation with and referral to outside specialist resources. Failure was predicated on: a lack of outside resources, client issues that fell outside the counsellor’s range of competence, and irreconcilable conflicts of values. Multivariate analysis of variance (MANOVA) was used to compare the professional and demographic variables of counsellors with high and low MCC.  It found that counsellors with high MCC had more multicultural coursework, F(1,155) = 8.9, p<0.01, and a higher percentage of client diversity in their caseload, F(1,155) = 9.5, p<0.01.   15 Finally, regression analysis was performed to determine which counsellor characteristics best predicted MCC. It found that the strongest predictors were a culturally diverse caseload, and the completion of professional seminars on multicultural counselling. The second-strongest predictors were graduate level multicultural coursework, and experience in case consultation. Here again, specific counselling experience – frequent contact with multicultural clients – combined with training and supervision to enhance MCC. The issue of specificity is key, because the terrain of multicultural counselling is so complex (Shen & Lowinger, 2007). In reflecting on the qualitative data, Arthur and Januszkowski (2001) note, “Although many of the presenting issues are concerns expressed by a general client population, counsellors reported confounding influences of culture for understanding the nature of client issues, the potential for value conflicts, and the need to design culturally appropriate interventions” (p. 40). Under these circumstances, general counselling experience does not suffice. The mixed-methods design of this study allowed Arthur and Januszkowski to measure with great sensitivity the dimensions of experience that best enhance MCC: specificity and frequency of client contact.  This was not the case for Holcomb-McCoy (2005), and perhaps for this reason experience had no significant effect on school counsellor MCC.  Here, comparatively insensitive measurement failed to capture the contribution of experience to MCC. In a quantitative study, Holcomb-McCoy (2005) sought to fill a gap in the literature by examining differences in perceived MCC across various school counsellor characteristics. She drew a geographically stratified sample of 510 professional school counsellors from the membership of the American School Counselors Association (ASCA). Two hundred and nine (209) school counsellors completed the measures by mail, for a response rate of 41%.  16 The survey packages contained a demographic questionnaire and the Multicultural Counseling Competence and Training Survey - Revised (MCCTS-R; Holcomb-McCoy & Day-Vines, 2004). The questionnaire recorded each counsellor’s gender, years of experience, work setting (school type), and amount of multicultural coursework. Significantly, unlike Arthur and Januszkowski (2001), it did not ask for information about specific dimensions of experience, such as caseload diversity. The 32-item MCCTS-R measured school counsellor MCC across three behaviorally based dimensions: Terminology (α=0.97), Awareness (α=0.85), and Knowledge (α=0.95).  Training was conceptualized as taking at least one multicultural course. As such, it was a significant influence on two of the MCCTS-R scales. Multivariate analysis of variance (MANOVA) determined that coursework was related to Knowledge, F(19,184)=2.81, p<0.01, and Terminology, F(4,203)=2.42, p=0.05. Further, training accounted for 22% of variance in Knowledge and 5% of the variance in Terminology.  However, no effect was found on any of the scales for gender, school type, or most significantly, years of experience. This is quite contrary to self-efficacy theory and it requires some explanation. The criteria, “years of experience” is perhaps too general; it does not include the specificity or frequency of contact required for experience to influence MCC.  As a result, it is possible that some of the counsellors sampled do not have many cross-cultural clients, or they see them rarely, and this has reduced the impact of their “years of experience” on MCC. Holcomb-McCoy (2005) acknowledges that, “it is possible that participants’ perceived multicultural counseling competence is related to their exposure or lack of exposure to culturally diverse student populations” (p. 8). Since this study does not ask for specific information about  17 caseload diversity, the picture of school counsellor MCC, as rendered by Holcomb-McCoy is incomplete. The notion of experience is complicated somewhat by race and age, as is demonstrated by Guzmán, Calfa, Van Horn Kerne, and McCarthy (2013). Guzmán’s team promotes a novel interpretation of race and age. For Guzmán et al., these constructs embody unique lived experience: something that is necessarily multicultural, and something that is encountered daily. As such, race and age are factors that affect MCC.  Guzmán’s team was conducting two projects. They examined not only the differences between self-reported and observed MCC, but also the extent to which these two measures of MCC are affected by training, age, race and experience.  The results are complex and unexpected, but ultimately reinforce the precepts of self-efficacy theory.   Central to the design of this study are the hypothetical counselling scenarios or Multicultural Critical Incident Vignettes (MCIV; authors of this study). These provide a means for assessing demonstrated MCC. They consist of 4 brief written stories: (1) Frequent Fights, (2) Ethnic Heritage Month, (3) HIV Myths and (4) Counsellor/Student Racial or Ethnic Similarity. For each story counsellors are asked, “How would you respond?” and they are encouraged to write with as much detail as possible.  The written responses are observer-scored to generate ratings of observed MCC. Reported inter-rater reliability was high: 99.8% consensus.  Meanwhile, self-rated MCC was measured through the Multicultural Counseling Competence and Training Survey-Revised (MCCTS-R; Holcomb-McCoy & Day-Vines, 2004), described earlier. A demographic survey collected information on: gender, race/ethnicity, years of teaching experience, years of counselling experience, work setting (school type), and number and types of multicultural training experiences. Finally, the Marlowe-Crowne Social Desirability  18 Scale (M-C SDS; Strahan & Gerbasi, 1972) was used to account for social desirability during regression analysis.  The authors recruited a convenience sample of 227 Texan school counsellors from private and public schools.  Participants were directed to a webpage to complete the surveys, questionnaires and vignettes online. Multiple regression analysis, controlling for social desirability, was used to explore both the relationship between self-rated and observed MCC, and the relationship between various forms of training and both ratings of MCC. As expected from previous research (Cartwright et al., 2008), self-rated MCC did not predict MCIV (observed MCC) scores. There was one exception, the vignette Frequent Fights, where it predicted 5% of the variability.  Also consistent with the literature, self-rated MCC was affected by training. Training had a significant relationship to all dimensions of the self-rated MCCTS-R (Terminology F(4,183)=2.99, p=0.02; Awareness F(4,192)=2.85, p=0.03; and Knowledge F(4,193)=6.27, p<0.01).  Years of experience, meanwhile, showed no influence on self-rated MCC (consistent with Holcomb-McCoy, 2005).  However, experience manifested itself in unconventional ways, and found expression in terms of race and age. Analysis of variance (ANOVA and MANOVA) was used to tease out the relationship between MCC and race, age and experience. It found that counsellors belonging to racial/ethnic minorities had higher self-ratings across all scales of the MCCTS-R: F(3,193)=6.9, p=0.001  This trend exists in other research (Crook, 2010; Holcomb-McCoy et al., 2008; Sheu & Lent, 2007), and it is explained in part by Chao, Wei, Good, and Flores (2011).  This team argues that members of racial or ethnic minority groups encounter a form of sustained multicultural experience: one developed through continual contact with the  19 more dominant culture(s). In their research, they found that minority race and ethnicity raise some dimensions of MCC (Awareness) as compared to whites. Only through additional training, could white counselling students catch up to the level of MCC demonstrated by their peers. Thus, in this study we see an influence for both training and race: expressed here as a very specific and frequently encountered kind of lived experience.  Lived experience has limits however, and these limits explain the low-performance of racial/ethnic minority counsellors on the MCIV vignettes. Whereas non-white counsellors showed higher self-rated MCC, race/ethnicity had no effect on observed MCC, except in the HIV Myth vignette, where white counsellors had higher ratings F(1,151)=4.3, p=0.05. The authors suggest that all of the participants had difficulty translating knowledge into practice, and assert, more controversially, that minority counsellors may simply have less lived experience in working with HIV-specific issues (Brooks, Etzel, Hinojos, Henry, & Perez, 2005). This acknowledges that diversity is not limited to race/ethnicity, and that experience in one area (even lived experience) does not necessarily confer MCC for all issues and populations. It demonstrates once again the importance of specific experience in developing MCC.   Guzmán et al. (2013) use the concept of lived experience to explain the puzzling relationship between MCC and age. Age produced no significant differences in self-reported MCCTS-R scores. However, younger counsellors did have higher observed scores for two of the vignettes: Ethnic Heritage Month F(2,140)=3.35, p=.04 and Counselor/Student Racial or Ethnic Similarity F(2,145)=8.01, p=0.001. Thus, age is a determiner of demonstrated skill, but is not necessarily linked to self-reported MCC. Certainly, younger counsellors may have access to more opportunities for multicultural training, but this advantage is not reflected in the self-rated MCC.  The authors counter that formal training may be less important to MCC than immersion in a  20 diverse environment. Younger counsellors would have the advantage of having lived most of their lives at a time of increased multiculturalism. This lived experience enhances their observed MCC. In fact, Guzmán’s team (2013) privileges lived experience over more conventional and institutional experience. For this reason, they surmise, years of teaching experience produced no differences in the self-rated MCCTS-R scores, contrary to the findings of Bodenhorn and Skaggs (2005).  Yet, counsellors with less teaching experience had higher observed scores for two of the vignettes: Ethnic Heritage Month, F(3,140)=4.17, p=0.01, and Counselor/Student Racial or Ethnic Similarity, F(3,145)=4.16, p=0.01. Similarly, years of counselling experience had no affect on self-rated MCCTS-R scores. However, counsellors with less counselling experience had higher scores for the Ethnic Heritage Month vignette, F(2,91)=3.62, p=0.03. At first glance, these results seem counter to self-efficacy theory. However, they are comparable to the findings on race and age. The lived experience of younger, less experienced counsellors simply has a greater impact on observed MCC. In this study, self-reported and observed MCC seem, at best, tenuously related. As in Cartwright et al. (2008), “These results raise an important question about what research on self-reported competency can really tell us about how well counselors will manage diversity situations on the job” (p. 17). However, this discrepancy is quite in accordance with self-efficacy theory.  Self-reported MCC (or self-efficacy) is not the same as demonstrated skill. Similarly, the contradictory findings on training, age, race and experience can be explained in terms of specificity and frequency of client contact: factors central to our discussion self-efficacy theory in the literature. The authors recommend, “… recalling that a variety of types of training were not found to be related to demonstrated MCC, while age (younger) and experience (less) did  21 have a significant relationship, [there is a] possibility that a more sustained exposure to interacting with diverse groups is needed rather than isolated trainings” (p. 20). Thus, for Guzmán et al., conventional training and experience are over-rated as influences on MCC. Tadlock-Marlo (2012) takes issue with this view of formal training and experience.  She interprets formal training in an entirely different way: one that emphasizes its interaction with experience as a means of enhancing MCC. Tadlock-Marlo developed a unique instrument for measuring school counsellor MCC, entitled One School Many Differences (OSMD; Tadlock-Marlo, Zyromski, Asner-Self, & Sheng, 2013).  This scale is unusual because it is based on the updated professional standards of the ASCA (2010, E.2) and the AMCD (Arredondo et al., 1996), as well as existing MCC scales. After working with her team to develop the scale, Tadlock-Marlo (2012) tested its validity. In the process, she hoped to determine the psychometric properties of the OSMD, and determine the influence of various demographic variables, including training and experience, on MCC. A convenience sample of 871 school counsellors participated in the online study. Three measures were used: a demographic questionnaire, the OSMD, and the Multicultural Awareness-Knowledge-Skills Scale-Revised (MAKSS-R; Kim, Cartwright, Asay, & D’Andrea, 2003). The demographic questionnaire was extremely detailed. It collected information on gender, multicultural training, race/ethnicity, socio-economic status, experience working with multicultural populations and personal multicultural experiences. The OSMD was a four-factor scale with 37 items that accounted for 37.2% of the scale’s variance. It had an internal of α=0.87. Its four factors revealed the extent to which “school counselors’ roles vary greatly from those of community health professionals” (Tadlock-Marlo et al., 2013, p. 235): (1) Assessment of School Environment, (2) Reflection of Personal Culture, (3) Interpersonal Relationships, and (4)  22 Collaboration. The authors argued that the three basic competencies – awareness, knowledge, and skills – are woven into the four scales, but are insufficient to capture the complexity of school counsellor MCC. Finally, the MAKSS-R is a 33-item scale, which measures general MCC along three dimensions, and it has an internal consistency of α=0.81.   Factor analysis of OSMD confirmed the original four scales, but reduced the number of items to 31, which together accounted for 47.1% of the variance.  Internal reliability of the revised scale was α=0.86 to 0.87. Construct validity was established by a strong correlation with the MAKSS-R of r=0.51, p=0.000.  This indicates a relationship exists between general MCC and school counsellor MCC.   In addition, multivariate analysis of variance (MANOVA) showed a significant relationship between training and MCC.  Graduate-level coursework and continuing education coursework were each significantly related to OSMD full-scale, at F(1,870)=1.35, p=0.05, and F(1,870)=2.76, p=0.05, respectively.  This is consistent with the role of training in the literature. However, experience was only weakly correlated to the OSMD full-scale, with r=0.21, p=0.05. While this pattern has been noted previously, it is unexpected in this study. Indeed, whereas Holcomb (2005) and Guzmán et al. (2013) measured counselling experience generally in terms of “years, ” Tadlock-Marlo (2012) measured it with much greater sensitivity.  Her questionnaire was extremely detailed and took into account work with multicultural populations and personal multicultural experiences. Clearly, specificity and caseload diversity were included in this view of experience.  The low correlation between specific experience and MCC is quite unlike that found by Arthur and Janszkowski (2001), and is quite contrary to the expectations of self-efficacy theory.  It requires some explanation.   23 Tadlock-Marlo (2012) attributes this low result to the intertwined nature of training and experience.  Without training, multicultural experience does not benefit from framing, interpretation, or adjustment, and it is less likely to enhance competency levels. She explains:  … if an individual has not had proper training in areas of multicultural competence  specific to school counseling, then it is difficult to improve in that area despite years of  practice. However if training specific to school counselor multicultural competence is  provided for the professional, then awareness may be brought forward in areas that  need improvement. Practicing ineffective multicultural counseling with insufficient  training leads to a school counselor who is not as effective or efficient as he or she  could be, despite the years of experience the individual may have practiced (p. 157).   In this way, the quality of counselling experience can be seen as dependent on training. Without MC training, the connection of experience to actual competence remains quite loose.  Thus training affects MCC both directly, and indirectly by enhancing experience. This may explain why experience is so strongly related to MCC and multicultural self-efficacy (MCSE) among trainees. Perhaps the accumulation of experience in a training-enriched environment produces stronger effects for experience on the development of MCC or MCSE. Turning now to general counselling MCSE, Tadlock-Marlo’s view of training provides a fresh perspective on the research of Sheu and Lent (2007) and Sheu, Rigali-Oiler and Lent (2012).  Both research teams worked with graduate-level counselling trainees. Since these participants were immersed in coursework, their counselling experiences were mediated -- shaped and interpreted -- by training and supervision. And the impact of their experience on MCSE was much more apparent. Sheu and Lent’s (2007) Multicultural Counseling Self-Efficacy Scale – Racial Diversity Form (MCSE-RD), is designed to measure general MCSE, or “… a therapist’s perceived ability to successfully perform various counseling tasks when working with racially diverse clients in the context of individual therapy” (p. 32). Since their study involved the creation of a new scale, its scope is quite broad, and includes test, test-retest, and pretest-posttest methods to map out the  24 scale’s factor structure, reliability and validity. It also tests the scale’s relationship to various demographic variables, including those known to influence self-efficacy, such as training, supervision and experience. The test sample consisted of 375 graduate students, in the later stages of masters or doctoral programs, from 8 public universities in the United States. 181 completed the study, for a response rate of 48%.  The pretest-posttest sample consisted of 22 graduate students in a pre-practicum course in a large mid-Atlantic university. Five instruments were used with all 181 test-participants. The preliminary version of the MCSE-RD consisted of 60 items, derived from extensive literature review and expert panels. A demographic questionnaire recorded age, gender, race/ethnicity, education level, multicultural training and experience, and counselling interest and intention levels. Convergent validity was determined through the use of the Multicultural Counseling Inventory (MCI; Sodowsky, Taffe, Gutkin, & Wise, 1994), and the Counselor Activity Self-Efficacy Scale (CASES; Lent, Hill & Hoffman, 2003). Discriminant validity was established through the use of the Multicultural Social Desirability Index (MCDS; Sodowsky, Kuo-Jakson, Richardson & Corey, 1998). For the pretest-posttest study, graduate students were tested using the final version (37 items) of the MCSE-RD at the beginning and end of their 15-week practicum. All participants used the MCSE-RD as a self-report instrument. Exploratory factor analysis showed three factors, which accounted for 37 items and 71% of the variance. These factors are: Multicultural Intervention; Multicultural Assessment; and Multicultural Session Management. The total scale had a strong test-retest reliability: r= 0.77 (p<0.001), and total internal consistency for the instrument was very high: α=0.98. Convergent and discriminant validity results were also very encouraging.  25 The influence of demographic variables was measured using general linear models. Consistent with the literature, these indicated small effects for race/ethnicity, gender, age, and interest, and much larger effects for level and specificity of education, and amount of specific training. Many of the smaller effects could be attributed to unique attributes of the sample. For example, members of racial/ethnic minorities had higher self-efficacy in all three factors, F(1,179) = 12.15 p<0.01 with an effect size of η2=0.064. These results support the observations of Guzmán et al., (2013). Perhaps lived experience increased MCSE. In addition, follow-up contact with participants confirmed that these individuals had more multicultural client contact (10.9 vs. 8.6 hours, p<0.05) and more multicultural training (2.2 vs. 1.1 workshops, p<0.05).  Meanwhile, training was a major contributor to MCSE. Students with higher degrees, those who were enrolled in counselling psychology programs, and those who were more advanced in their programs had higher self-efficacy. For example, the impact of tenure in graduate programs ranged from F = 12.56 to 16.26, p<0.001, with effect sizes of η2=0.124 to 0.154. (medium to large). This is significant since it reinforces the idea that specific training builds self-efficacy over time. Indeed, MCSE-RD correlated positively with training: courses, workshops and supervision.   Significantly, as suggested by Tadlock-Marlo (2012), experience is interwoven in this process. The strongest correlations were found in direct contact hours with racially different clients (r=0.42 to 0.48 across the scales, p not reported). As additional support, results from the pretest-posttest study indicated that total scores and subscale scores on MCSE-RD were higher after the 15-week practicum: t(21) = 6.05, p<0.001 full scale, with d = 0.81 (differences were large in magnitude). Clearly, supervised training experiences enhanced MCSE.  26 Finally, hierarchical regression analysis determined the biggest predictors of multicultural self-efficacy. The strongest contributors were the trainee’s highest earned degree and year of program (15% of variance), number of multicultural courses and workshops taken (6%) and direct counselling experience and supervision (8%). Direct contact hours with culturally different clients produced the highest β (0.35). Of course, these hours are accumulated during training. Sheu, Rigali-Oiler and Lent (2012) then strengthened the link between training and experience. This team conducted additional research using the MCSE-RD, hoping to confirm its factor structure, and connect it to constructs from Social Cognitive Theory (SCT). In the process, they found that multicultural self-efficacy could be predicted by prior cross-racial contact hours (r = 0.37, p<0.05), and perceptions of the multicultural training environment (r=0.16, p<0.05). Since these cross-racial sessions occurred in the context of training and supervision, they represent a condensation of training and experience. Together they exert a significant influence on MCSE. The results of these MCSE studies reinforce the observations of Tadlock-Marlo (2012).  Here, specific training and experience, along with relevant supervision, predict higher levels of MCSE. Unlike previous research, which shows little (or no) effect for experience, Sheu and Lent (2007) and Sheu et al. (2012) demonstrate the value of training on experience.  Through training, the impact of experience on MCSE is enriched and amplified. MCSE research with trainees sheds some light on MCSE research with practicing school counsellors. Here the same principles of specific experience, frequency of contact, and training interaction apply.  However, as Tadlock-Marlo (2012) observed, professional school counsellors are no longer trainees; they do not benefit from the same degree of concurrent training.  Thus for counsellors with less multicultural training, the influence of years of experience on school  27 counselling MCSE may be diminished.  This is seen quite clearly in the research of Holcomb-McCoy, Harris, Hines and Johnston (2008), and Crook (2010). Holcomb-McCoy et al. (2008) developed and tested the School Counselor Multicultural Self-Efficacy Scale (SCMES). In the process, they examined the relationship of the SCMES to a host of demographic factors, and confirmed the importance of training and experience. Only two measures were used: the SCMES and a demographic questionnaire. The SCMES consisted of 90 items generated through extensive literature review, then vetted by professional school counsellors. The demographic questionnaire collected information on counsellor gender, race/ethnicity, years of experience, number of multicultural courses taken, highest degree completed, and professional identity or role.  The authors had some difficulty in recruiting participants. Using a combination of mail-out and electronic survey techniques, 181 randomly selected members of the ASCA participated in the study (an overall response rate of 24%).  Exploratory factor analysis found six factors and 52 items that together accounted for 59.49% of the variance in the SCMES. The six dimensions are (1) Knowledge of Multicultural Counseling Concepts, (2) Using Data and Understanding Systemic Change, (3) Developing Cross-Cultural Relationships, (4) Multicultural Awareness, (5) Multicultural Assessment, and (6) Applying Racial Concepts to Practice. It is significant that these factors are somewhat different from those identified in Sheu and Lent’s (2007) MCSE-RD. These differences are indicative of the unique tasks and roles of school counsellors. The total scale has a coefficient alpha of 0.93. A series of multivariate analyses of variance (MANOVA) demonstrated relationships between SCMES and training and experience that are consistent with the literature reviewed. Multicultural training had a pronounced influence. It was linked most significantly to  28 Multicultural Knowledge (Factor 1), Using Data and Understanding Systemic Change (Factor 2), Multicultural Awareness (Factor 4) and Multicultural Assessment (Factor 5). Effect sizes were moderate (η2=0.062 to 0.097), and differences were significant (p<0.05 to p<0.01). However, these findings must be interpreted with caution, since the number of subjects with extensive training was quite small (for example, only five subjects had taken 5 to 7 MC courses and only six subjects had taken more than 8 courses). Training was not linked to Developing Cross-Cultural Relationships (Factor 3) or Applying Racial Concepts to Practice (Factor 6).  The authors suggest that these scales may be more affected by counsellor personality, and that multicultural training may not include enough specific skills to affect them.  By contrast, “years of experience” had no significant effect on self-efficacy. This is consistent with the findings of Holcomb-McCoy (2005), and it may be the result of similarly insensitive scales of measurement. As in Holcomb-McCoy (2005), experience is measured roughly in this study, and no exploration is made into diversity of caseload or frequency of sessions.  As a result, experience seems to be an insignificant factor. Or possibly, as Tadlock-Marlo (2012) suggests, these years are not sufficiently informed by training to have much impact on MCSE. The more specific measure of lived experience did have an influence, however. Members of racial/ethnic minorities had higher scores for all factors of SCMES except Developing Cross-Cultural Relationships (Factor 3). The authors suggest that relationship-building may simply be an area of relative strength for most counsellors, regardless of race or ethnicity. Effect sizes for these differences were smaller than those for training (η2=0.021 to 0.048), but the differences were significant (p<0.05 to p<0.01). The team argues that, in addition to having lived experience, counsellors of minority status may have higher MCSE because they prefer to take more  29 multicultural training, and have more multicultural clients. Recall that Sheu and Lent (2007) found this to be the case. Thus Holcomb-McCoy at el. (2008) demonstrate once more the importance of specific experience, and by extension training and caseload diversity, in developing MCSE. Crook (2010) tackles the role of caseload diversity more directly in his investigation of the School Counselor Multicultural Self-Efficacy Scale (SCMES; Holcomb-McCoy, Harris, Hines & Johnston, 2008). Following recommendations by the scale’s authors, Crook explores the relationship between general counselling self-efficacy (CSE) and MCSE, while taking another look at the school counsellor variables that may affect MCSE. Participants were recruited through the 2009/2010 ASCA Online Directory and through six personal contacts. Of the 4024 contacts made, 173 school counsellors completed online survey packages (for a rather low response rate of 4%).  Three measures were used in the study: the SCMES (Holcomb-McCoy, Harris, Hines & Johnston, 2008); The School Counselor Concept Scale (SCCS; Bodenhorn, 2009; Bodenhorn & Skaggs, 2005), and a demographic questionnaire.  The SCCS is an adapted version of the School Counselor Self-efficacy Scale (SCSE; Bodenhorn & Skaggs), consisting of 43 items with an internal reliability of α=0.963. It is used in this study as a full-scale instrument because its factor structure was deemed unstable. The questionnaire collected data on race/ethnicity, gender, years of experience, and school setting (rural, urban, suburban).  The SCMES and SCCS were moderately to strongly correlated: Pearson’s coefficient ranged from 0.596 to 0.675 (p<0.01, two tailed) across all 6 factors of the SCMES. This significant correlation provides some convergent validity for the SCMES.  30 Multivariate analysis of variance (MANOVA) showed no effect for training.  This is unusual in the literature reviewed, and contrary to Holcomb-McCoy et al. (2008), but it can be explained. Unfortunately, training was not measured sensitively in this study: participants were asked merely if they had taken at least one multicultural counselling course. Since 95.6% of all participants had done so, this prevented training from being used meaningfully in the analysis.  By contrast, MANOVA did reveal significant effects for experience, race/ethnicity and school setting. “Years of experience” affected Factor 2, Using Data and Understanding Systemic Change: F(6,166) = 2.67, p<0.05, p=0.017. These differences were most pronounced between counsellors that had 11-14 or 15-19 years of experience and those with less. This is consistent with self-efficacy theory; certainly using data and navigating workplace systems could be enhanced by experience. However, it is notable that only one factor was affected by experience: by all accounts a very powerful force in self-efficacy theory. Perhaps once again, “years of experience” is not a sufficiently sensitive measure (Holcomb-McCoy, 2005; Holcomb-McCoy et al., 2008) or it is simply uninformed by training (Tadlock-Marlo, 2012). In any case, consistent with the literature reviewed, Crook (2010) shows that specific (lived) experience and a diverse caseload affect MCSE. In fact, race/ethnicity influenced four factors of the SCMES: Using Data and Understanding Systemic Change (Factor 2), Developing Cross-Cultural Relationships (Factor 3), Multicultural Awareness (Factor 4), and Applying Racial Concepts to Practice (Factor 6). Results ranged from F(3,165)=2.71 to 3.41, p<0.05. These results diverge slightly from those of Holcomb-McCoy et al. (2008), who found no effect on Factor 3. Here again, lived experience may combine with unique counsellor training and caseload preferences, to contribute to higher levels of MCSE.  31  Finally, Crook’s (2010) research is unique, because he collects information on school setting. Like ethnicity/race, school setting provides a much more specific and sensitive measurement of experience, insofar as urban schools may evidence more visible multiculturalism. This variable affected all six dimensions of the SCMES. Factors 1 and 3 (Knowledge of Multicultural Counseling Concepts and Developing Cross-Cultural Relationships) were affected more by urban than by suburban or rural settings: F(2,170)=7.46 and 7.03, p<0.05 respectively. The remaining factors were affected more by urban than rural settings: F(2,170)=3.47 to 4.14, p<0.05. These results are contrary to Bodenhorn and Skaggs (2005), but they make sense in terms of population diversity. School counsellors in urban settings encounter greater caseload diversity, and their MCSE is correspondingly higher. Here, Crook is tapping into a dimension of experience that is meaningful to its measurement, and it reveals that experience does indeed influence MCSE.  This brief review of the literature shows that training and supervision (when measured) exert a consistent influence on MCC and MCSE.  By contrast, experience varies along a number of dimensions that render it more or less influential. Stand-alone discrete training sessions and generic counselling experience are not enough. To be meaningful, experience needs to be specific, frequent, and informed by relevant training and supervision. Several important issues are raised in the Literature Review, and these have shaped the direction of my research.  First and foremost, multicultural counselling self-efficacy has emerged as a construct distinct from competence, and it is worthy of research in its own right.  Secondly, practicing school counsellors, particularly Canadian ones, are rarely used as participants in studies of multicultural competence or self-efficacy. This is clearly a gap in the research that needs to be filled, and numerous authors (Holcomb-McCoy, Harris, Hines, & Johnston, 2008;  32 Sheu, Rigali-Oiler, & Lent, 2012; Worthington, Soth-McNett, & Moreno, 2007) acknowledge this.  Finally, the complex relationship between multicultural counselling self-efficacy and counselling experience deserves further exploration.  33 Chapter 3: Method Research Design: This is a quantitative study of practicing school counsellors. It looks for patterns that link school counsellor multicultural self-efficacy with specific counsellor-based and school-based variables. It is hoped that results from the present study will serve as the foundation for future qualitative research. With this in mind, survey research serves as the basis of the research methodology.   Sample / Participants This study used a self-selected sample of 300 British Columbia school counsellors. These counsellors work with elementary, middle, or high school aged students, in different community settings (such as urban, suburban or rural) across the various geographic regions of the province.  Some of the school counsellors are members of the British Columbia School Counsellors Association (BCSCA). BCSCA members work in a variety of school environments, including public, private secular, and private religious settings. However, it should be noted that not all school counsellors in British Columbia are members of the BCSCA. Procedures  Participants were recruited using two different procedures, entitled conference, and mail-out distribution.  Conference procedures were used to recruit participants during the British Columbia School Counsellors Association Conference (BCSCA; October 22 to 24, 2014). Prospective participants first learned about the study through the BCSCA email list-serve.  The goals and general structure of the study were formally announced via the list-serve, thus alerting members to the possibility of participating during the conference.  During the conference, the study was  34 promoted through announcements, flyers and posters. Conference organizers made scripted announcements at the end of presentations and seminars. Flyers were placed in conference packages and on resource tables in seminar rooms. Posters were displayed on bulletin boards and flip charts. The survey was administered in the Exhibition Area of the conference, where publishers, businesses, and community agencies had displays. The survey could be completed in the Exhibition Area on tables or kiosks provided, or it could be completed elsewhere and returned. Survey packages consisted of informed consent forms, the Demographic and Workplace Questionnaire and the School Counselor Multicultural Self-Efficacy Scale (SCMSE; Holcomb-McCoy, Harris, Hines & Johnson, 2008). These two instruments are discussed more fully in the next section. Informed consent forms were attached to the front of the survey package and all contents of the package were coded numerically.  The numerical coding serves several purposes: tracking the number of surveys distributed and received; ensuring that multiple surveys are not completed by a single counsellor; and conducting an incentive raffle (described below).  When the survey package was handed in, the participant detached the informed consent form from the survey package, and placed each in a separate sealed box. These boxes remained under direct visual supervision during the conference and were removed from the conference site at the end of each day. As an incentive to participate in the study, a $25 gift card was raffled, for every 25 consent forms received.  Participants did not need to complete the survey package (only the consent form) to participate in the raffle. The code from the completed consent form was entered into the raffle at the time the form was returned.  Raffle winners were contacted based on the information they provided on the consent forms.  Mail-out distribution was used to recruit additional participants from public schools throughout the province. This method had some benefits, since it afforded participants the luxury  35 of time and privacy to respond to a longer, more in-depth set of questions (Andres, 2012). This was a three-stage process. In the first stage, potential participants were identified. Of the 59 public school districts, 55 had Internet sites with links to school websites and staff email lists.  Using these public records, a list of potential counsellor-participants was drawn up for each district. These potential participants were contacted by email with a brief letter of introduction, explaining the purpose of the research and inviting their participation in the survey. If counsellors responded with interest, a survey package was then mailed to their school. Following the procedures of Arvay and Uhlemann (1996), the mail-out packages contained: an explanatory cover letter, a consent form, two stamped self-addressed return envelopes, and the two questionnaires.  The cover letter explained the goals and general structure of the study, invited the counsellor to participate, and outlined the procedures for completing the surveys and returning the consent form and package.   The consent forms and the questionnaires were mailed back separately: the consent form in one self-addressed envelope and the questionnaires in the other.  Each participant was issued a numeric code to ensure anonymity, and the consent forms were cross-referenced against the mailing list to allow for follow-up with non-respondents.  Mailing lists, consent forms, and questionnaire data were stored and processed separately to maintain anonymity.   In the third stage, non-responding participants were contacted. Two weeks after the initial mailing, a reminder email was sent to non-responding participants. To ensure a representative and statistically useful sample, it was hoped that at least 30% of the randomly selected participants would complete the mail-out survey (Andres, 2012; Arvay & Uhlemann, 1996).  The raffle system, described earlier, was continued as an incentive to complete the survey.  In  36 addition, all participants could request, as part of their informed consent form, to receive a copy of the findings of the study. Instruments The study consists of two questionnaires, which are included together in Appendix A.   School Counsellor Multicultural Self-Efficacy Scale (SCMES) The most promising multicultural self-efficacy scale is the School Counselor Multicultural Self-Efficacy Scale (SCMSE), designed and piloted by Holcomb-McCoy, Harris, Hines, and Johnson (2008).  This self-administered instrument consists of 52 items, each phrased as a positive statement, and each associated with a seven-point Likert scale.  “Respondents are asked to rate how well they can perform the tasks by circling the appropriate number of a scale from 1 (not well at all) to 7 (very well)” (Holcomb-McCoy et al., 2008, p. 168).  This scale has identified six factors (or subscales): (1) Knowledge of Multicultural Counselling, (2) Using Data and Understanding Systemic Change, (3) Developing Cross Cultural Relationships, (4) Multicultural Awareness, (5) Multicultural Assessment, and (6) Application of Racial and Cultural Knowledge to Practice.  The internal consistency of the scale as a whole, and for each factor and factor are significant: all have p values of less than 0.01.  According to the test authors, the scale “… yielded a coefficient alpha of 0.93. Examination of each factor yielded a coefficient alpha of 0.95 for Factor 1, 0.91 for Factor 2, 0.89 for Factor 3, 0.93 for Factor 4, 0.89 for Factor 5, and 0.88 for Factor 6” (Holcomb-McCoy et al., 2008, p. 169).  At this time, there are no studies of the reliability of the scale items. Although this questionnaire is lengthy, it was hoped that the higher literacy level of participants, combined with the conference, and mail-out methods of recruitment would help to promote completion of the scale.    37 Demographic and Workplace Questionnaire The second questionnaire is designed to capture demographic and work setting information, and it is also self-administered. It has been developed specifically for this study. The content of the 19-item Demographic and Workplace Questionnaire is very much influenced by trends already identified in the literature, and it seeks to confirm and expand on these trends.  For example, at the practitioner’s level, counsellor self-efficacy has been associated with gender and level of teaching experience (Bodenhorn & Skaggs, 2005), and multicultural counselling self-efficacy has been linked to counsellor race or ethnicity (Crook, 2010; Holcomb-McCoy, Harris, Hines, & Johnston, 2008), amount and specificity of training (Holcomb-McCoy et al., 2008; Sheu & Lent, 2007), and years of counselling experience (Crook, 2010). At the level of the workplace, counsellor self-efficacy has been connected to caseload diversity (Sheu & Lent, 2007; Sheu, Rigali-Oiler, & Lent, 2012), and community setting (Crook, 2010).   With this in mind, the second questionnaire measures counsellor-variables, such as level of education, years of experience, and additional multicultural training.  It also measures workplace variables, such as the number of languages spoken in the school, the estimated percentage of visible minority students, caseload diversity, and the perceived availability of school district supervision or consultation.  For most instrument items, the data collected will take the form of discrete numerical responses (such as the counsellor’s age or years of experience).  In four items, Likert scale data is used (to measure perceived diversity of caseload, for example). Two items are open-ended, and ask participants to describe both their race / ethnicity and the resources they use for multicultural consultation and supervision. Together, these two questionnaires constitute the survey portion of the study. The data that they generated were analyzed separately and together to detect patterns and relationships.  38 Chapter 4: Results The main purpose of this study was to assess the level of multicultural counselling self-efficacy (MCSE) among a sample of school counsellors in British Columbia. A second objective was to identify those demographic and workplace variables that are significantly related to MCSE.  The third purpose was to determine if MCSE is more strongly related to diversity of caseload, than it is to years of experience. The final goal was to determine if high levels of multicultural training enhance the relationship of experience and MCSE: causing years of experience to be more strongly related to MCSE, among school counsellors with higher levels of training. In this chapter, the findings from the analysis of the survey data are presented in descriptive and tabular format. Response Rate  There were 300 survey packages distributed: 121 at the British Columbia School Counsellors Conference (October 22 to 24, 2014), and 179 as part of a systematic mail-out.  A total of 232 surveys (77%) were returned: 74 directly from conference attendees, and 158 by mail. Of these, 6 surveys (2%) were excluded from data analysis, because more than 10% of the SCMES was incomplete (6 or more items were not answered).  The 226 survey packages included in data analysis yielded a final response rate of 75%. Participant Characteristics  The ages of participants ranged from 26 to 69 years, with a mean of 46.5 years (SD = 9.88). Fifty percent of participants were between the ages of 39 and 53.  179 of the participants were women (79.2%) and 47 were men (20.8%).  The majority of participants were Caucasian or White (n = 190, 84%): with either English as their first language (n = 189, 83.6%) or English as their second language (n = 1, 0.4%). The remaining participants by race / ethnicity included:  39 Aboriginal (n = 1, 0.4%), Asian (n = 9, 4%), Metis (n = 3, 1.3%), and South Asian (n = 6, 2.7%). Three participants (1.3%) described their race / ethnicity as Other, and one participant (0.4%) did not report their race / ethnicity. Interestingly, 13 participants (5.8%) identified their race / ethnicity as Canadian.  For most participants, their highest level of education was a master’s degree (n = 196, 86.7%). However, 27 participants (11.9%) had a bachelor degree alone, and 3 (1.3%) held a doctorate.  Most participants had specific counselling training (n = 194, 85.8%): 9 (4%) had diploma-level training, and 185 (81.9%) had graduate-level training.    Teaching experience among participants ranged from 0 to 40 years, with a mean of 17.11 years (SD = 9.27). Fifty percent of the sample had between 10 and 24 years of teaching experience. Similarly, counselling experience ranged from 0 to 37 years, with a mean of 9.32 years (SD = 7.86). Fifty percent of the sample had between 3 and 14 years of counselling experience.    Specific multicultural training showed a great deal of variability.  Graduate level multicultural training ranged from 0 to 10 courses, with a mean of 1.41 courses (SD = 1.65). Fifty percent of the sample had 0 to 2 courses, and of these 67 participants (29.6%) had 0 courses.  Similarly, in-service multicultural training ranged from 0 to 20 courses, with a mean of 3.12 (SD = 3.67).  Fifty percent of the sample had 0 to 4 courses, and of these 56 participants (24.8%) had 0 courses.   Workplace Characteristics  Most participants work in the Metro Region of the Lower Mainland (n = 105, 46.5%). However, participants were drawn from all regions of British Columbia, including Central BC (n = 14, 6.2%), Fraser Valley (n = 20, 8.8%), Kootenay (n = 5, 2.2%), North (n = 13, 5.8%),  40 Okanagan (n = 22, 9.7%), and Vancouver Island / Sunshine Coast (n = 47, 20.8%). Participants work primarily in public schools (n = 216, 94.2%), but a few are employed in private or independent schools (n = 10, 5.8%).   Participants identified as practicing in the following community settings: urban (n = 105, 46.5%), suburban (n = 60, 26.5%), rural (n = 30; 13.3%), and mixed (n = 31, 13.7%).  Seventy-two participants (31.9%) classified their schools as Inner City, while 154 (68.1%) did not.  Participants reported working at the following grade levels: elementary (n = 50, 22.1%), middle (n = 14, 6.2%), high school (n = 133, 58.8%), and mixed grade assignments (n = 28, 12.4%). One participant (0.4%) did not indicate a grade level of work.   In these workplaces, the availability of multicultural training and supervision varied a great deal. Participants were asked if “the school or district provides professional development in-services that address the counselling of students that are culturally different,” on a seven-point scale, where 1 = never, 4 = sometimes, and 7 = always.  Responses ranged from 1 to 7, with a mean of 2.83 (SD = 1.33) indicating a response of less than “sometimes.”  Fifty percent of the sample rated training availability between 2 and 4.  Availability of supervision was reported as slightly higher. Participants responded to the statement, “When I require additional guidance / information in counselling students that are culturally different from myself, the school or district provides resources.”  Here, responses once again ranged from 1 to 7, but the mean of 3.55 (SD = 1.70) indicates a response of only slightly less than “sometimes.” Fifty percent of the sample rated supervision availability between 2 and 5.  41 School and Caseload Diversity Characteristics  Student diversity was measured for two populations: the school as a whole, and the specific students with which counsellors work.  Here, counsellor caseloads are a subset of the school population. Participants reported the racial / ethnic diversity of their school(s) in two ways: perceived multiculturalism and number of languages. Participants rated the extent to which students in their school varied by “race, ethnicity, language and/or religion.”  Participants were asked to classify the population of their school(s), on a seven-point scale, where 1 = not at all multicultural, 4 = somewhat multicultural, and 7 = extremely multicultural.  Responses ranged from 1.5 to 7, with a mean of 4.84 (SD = 1.48) indicating a response of slightly more than “somewhat multicultural.”  Fifty percent of the sample rated the cultural diversity of their school between 4 and 6.  In addition, participants estimated the number of languages spoken in their school.  Estimates ranged from 1 to 100, with a median of 10 and mode of 10.  Fifty percent of the sample reported between 5 and 21 languages spoken in their school.  Caseload diversity was measured along three dimensions: number of cultural groups, percentage of various cultural groups in caseload, and frequency of cross-cultural counselling sessions. The number of cultural groups ranged from 1 to 11, with a median of 6 and a mode of 9. Fifty percent of participants reported that their caseloads consisted of 4 to 8 cultural groups. The percent-composition of caseloads reveals great variability from counsellor to counsellor. Table 1 provides percentage estimates of specific cultural groups in participant caseloads.      42 Table 1: Prevalence of Cultural Groups in Participant Caseloads Cultural Group Prevalence in Participant Caseloads   Median (%) Mode (%) Range (%)  Aboriginal 10 10 0 to 98 African 0.5 0 0 to 15 Arab 0.2 0 0 to 30 Asian (not South Asian) 5 0 0 to 100 Caucasian (English as First Language) 50 40 0 to 100 Caucasian (English as Second Language) 1 0 0 to 75 Latina / Latino 1 0 0 to 30 Metis 0 0 0 to 30 South Asian 2 0 0 to 88 Note: caseload percentages were reported by 219 participants.  Some participants reported that their caseloads were comprised of one single, large, majority culture.  Caucasian majorities were more common than non-Caucasian majorities, as indicated in Table 2. Table 2: Prevalence of Majority Cultures in Participant Caseloads  Caucasian Majority  Single Non-Caucasian Majority Size of Cultural Group in Caseload N Percentage of Sample N Percentage of Sample 50% or higher 116 51.3% 50 22.8% 75% or higher 52 23.7% 17 7.8% 90% or higher 22 10% 3 1.4% Note: caseload percentages were reported by 219 participants.  Cross-cultural counselling sessions, for the purposes of this study, occur whenever the counsellor and student differ in terms of “race, ethnicity, language, and/or religion.” Participants rated the frequency of cross-cultural sessions, on a seven-point scale, where 1 = never, 4 = sometimes, and 7 = always.  Responses ranged from 1 to 7, with a mean of 4.64 (SD = 1.50) indicating a response of slightly more than “sometimes.” Fifty percent of the sample rated the frequency of cross-cultural counselling sessions between 4 and 6.  43 SCMES Factors – Normality of Distribution and Outliers Visual examination of the normal Q-Q plots for SCMES factors revealed that all six factors and the Total Score were normally distributed.  However, all SCMES factors and the Total Score were negatively skewed, as evidenced by visual examination of their histograms and box plots.  Skewedness and kurtosis scores, respectively, ranged between  -1.0 and 1.0 for all factors (including the Total Score), with one exception: Factor 3. Factor 3 (Developing Cross-Cultural Relationships) had a heavy-tailed distribution, with a skewedness of -1.163 (SE = .162) and kurtosis of 1.656 (SE = .322).    To remedy this, we examined the distribution for outliers. Z-scores were calculated for all Factor 3 scores. Two outliers were identified as being significantly below the cutoff (Z-score < -3.29). These values (raw scores 3.57 and 3.71) were replaced with the next highest value in the distribution (4.0) through the process of Winsorizing. Thus, Winsorizing affected 0.9% of the distribution (or 2 of 226 scores). Replacement of these scores adjusted the skewedness to -1.044 (SE = .162) and kurtosis to -1.048 (SE = .322). To further improve normality, the scores for Factor 3 were reflected (to make the skew positive) and then subjected to the square-root transformation. Transformation reduced skewedness to .646 (SE = .162) and kurtosis to .055 (SE = .322).   When we used the transformed scores of Factor 3 to analyze the data, the pattern of results for the t-tests, Pearson Product-Moment correlations, and regression analysis was identical to that found using the Winsorized data set scores.  For this reason, the Winsorized data set for Factor 3 was used in the present analyses, because the results of analyses using the non-transformed Factor 3 scores are more readily interpretable.   44 Research Question 1 Research Question 1 asked, “What is the level of self-reported multicultural self-efficacy among a sample of school counsellors in British Columbia?”  To assess the level of multicultural self-efficacy among school counsellors, participants completed the School Counseling Multicultural Efficacy Scale (SCMES; Holcomb-McCoy, Harris, Hines & Johnston, 2008). The SCMES consists of six distinct scales: Factor 1 = Knowledge of Multicultural Concepts, Factor 2 = Using Data and Understanding Systemic Change, Factor 3 = Developing Cross-Cultural Relationships, Factor 4 = Multicultural Counseling Awareness, Factor 5 = Multicultural Assessment, and Factor 6 = Application of Racial and Cultural Knowledge to Practice.  Participants indicated their ability to perform tasks related to multicultural school counselling, using a seven-point scale, where 1 = not well at all, 3 = not too well, 5 = pretty well, and 7 = very well. The scales of the SCMES are highly inter-correlated, indicating that they are measuring related constructs. As shown in Table 3, Pearson Product-Moment Coefficients range from .425 (p < 0.001) to .858 (p < 0.001). However, the scales themselves are distinct. Internal consistency was measured for the SCMES by computing Cronbach’s coefficient of reliability for each factor and for the total scale. These values were significant, and ranged from α = 0.78 for Factor 6 to α	  =	  0.96	  for	  the	  Total	  Scale.	  The results are summarized in greater detail in Table 3.       45 Table 3: Correlations and Alphas Among Scales of SCMES Scale 1 2 3 4 5 6 Total Scale 1 --       2 .672*** --      3 .596*** .425*** --     4 .735*** .576*** .610*** --    5 .613*** .762*** .515*** .657*** --   6 .616*** .525*** .577*** .686*** .588*** --  Total Scale .857*** .829*** .727*** .854*** .858*** .797*** -- α .90   .81   .83   .87   .85   .78 .96 Note: N = 266. Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001  Overall, the data indicate that participants feel “pretty well,” across all six factors, about their ability to perform tasks related to multicultural school counselling. As shown in Table 4, participants report less self-efficacy in Factor 2 (Using Data and Understanding Systemic Change, M = 4.27, SD = .946) and Factor 5 (Multicultural Assessment, M = 4.77, SD =  .953), while they report greater self-efficacy in Factor 3 (Developing Cross-Cultural Relationships, M = 6.14, SD = .640).  Table 4: Descriptive Statistics for SCMES SCMES Factors  N Minimum Maximum Mean SD 1 226 2.21 6.79 5.07 .816 2 226 1.44 6.44 4.27 .946 3 226 4.00 7.00 6.14 .640 4 226 2.67 6.89 5.20 .729 5 226 1.57 6.71 4.77 .953 6 226 3.33 7.00 5.42 .743 Total Scale 226 2.77 6.48 5.14 .665 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice.  46 Research Question 2  Research Question 2 asked, “ What personal (demographic) and workplace variables are correlated with multicultural self-efficacy? This general question was broken down into a series of 14 hypotheses. Each hypothesis was then tested systematically, using preliminary and, where appropriate, secondary data analyses. Preliminary data analysis consisted of independent t-tests and Pearson Product-Moment correlation tests, while secondary data analysis consisted of hierarchical multiple regression analyses. Demographic Hypotheses: 1. H0: Age will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Age will have a significant effect on school counsellors’ multicultural counselling self-efficacy. 2. H0: Gender will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Gender will have a significant effect on school counsellors’ multicultural counselling self-efficacy. 3. H0: Race / ethnicity will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: School counsellors who are from minority racial / ethnic backgrounds will have higher levels of multicultural counselling self-efficacy than those who are not. 4. H0: Specific graduate-level training in counselling will not have a significant effect on school counsellors’ multicultural counselling self-efficacy.  47 H1: School counsellors with specific graduate-level training in counselling will have higher levels of multicultural counselling self-efficacy. 5. H0: Years of teaching experience will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Counsellors with more years of teaching experience will have higher levels of multicultural counselling self-efficacy than those with less teaching experience. 6. H0: Years of counselling experience will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Counsellors with more years of counselling experience will have higher levels of multicultural counselling self-efficacy than those with less counselling experience. 7. H0: Taking graduate-level multicultural courses will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Counsellors with more graduate-level multicultural coursework will have higher levels of multicultural counselling self-efficacy than those with less coursework. 8. H0: Taking in-service multicultural courses will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Counsellors with more in-service multicultural coursework will have higher levels of multicultural counselling self-efficacy than those with less coursework. Workplace Hypotheses: 9. H0: Community setting (urban, suburban, rural or mixed) will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: Counsellors working in urban settings will have higher levels of multicultural counselling self-efficacy than those who work in other community settings.  48 10. H0: The provision of professional development (Pro-D) training in multicultural issues will not have a significant effect on multicultural counselling self-efficacy. H1: School counsellors who work in schools that provide higher levels of multicultural Pro-D training will have higher levels of multicultural counselling self-efficacy than counsellors who work in other settings. 11. H0: The provision of supervision and consultation in multicultural issues will not have a significant effect on multicultural counselling self-efficacy. H1: School counsellors who work in schools that provide higher levels of multicultural supervision and consultation will have higher levels of multicultural counselling self-efficacy than counsellors who work in other settings. School and Caseload Diversity Hypotheses: 12. H0: The racial /ethnic composition of the school will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: School counsellors working in more racially / ethnically diverse schools will have higher levels of multicultural counselling self-efficacy. 13. H0: The racial /ethnic composition of the school counsellor’s caseload will not have a significant effect on school counsellors’ multicultural counselling self-efficacy. H1: School counsellors with more racially / ethnically diverse caseloads will have higher levels of multicultural counselling self-efficacy. 14. H0: The frequency of cross-cultural counselling sessions will not have a significant effect of school counsellors’ multicultural counselling self-efficacy. H1: School counsellors with more frequent cross-cultural counselling sessions will have higher levels of multicultural counselling self-efficacy.  49 Preliminary Analysis The null hypotheses were retained for the following eight hypotheses: 1, 2, 3, 4, 5, 6, 11 and 12. A summary of the results of the preliminary analyses can be found in Appendices B, C, and D. There was no significant correlational relationship between any of the SCMES factors and the following independent variables: age (Hypothesis 1), years of teaching experience (Hypothesis 5), years of counselling experience (Hypothesis 6), the provision of supervision and consultation (Hypothesis 11), and the racial/ethnic composition of the school population (Hypothesis 12). Similarly, when examining the scores of the SCMES factors, there was no significant mean difference between groups for the following independent variables: gender (Hypothesis 2), counsellor race/ethnicity (Hypothesis 3), and specific graduate-level training in counselling (Hypothesis 4).  The null hypotheses were rejected for the following six hypotheses: 7, 8, 9, 10, 13 and 14.  As mentioned above, a summary of the results of the preliminary analyses can be found in Appendices B, C, and D.  In addition, preliminary results will be discussed briefly below for each hypothesis.  7. Hypothesis 7: Graduate School Multicultural Training. Number of graduate-level multicultural counselling courses taken was significantly correlated to all factors and to the total score of the SCMES (see Table 5).       50 Table 5: Graduate MC Training: Correlations, Significance and Variance with SCMES Factors SCMES Factors  N r  p r2 1 226    .251***    .0001 .063 2 226    .248***    .0002 .062 3 226 .140*  .036 .020 4 226   .203**  .002 .041 5 226   .195**  .003 .038 6 226 .156*  .019 .024 Total Scale 226    .246***    .0002 .061 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001  8. Hypothesis 8: In-Service Multicultural Training. Number of in-service multicultural counselling courses taken was significantly correlated to Factor 1 (Knowledge of Multicultural Concepts), Factor 2 (Using Data and Understanding Systemic Change), Factor 5 (Multicultural Assessment), Factor 6 (Application of Racial and Cultural Knowledge to Practice), and to the Total Scale of the SCMES (see Table 6). Table 6: In-Service MC Training: Correlations, Significance and Variance with SCMES Factors SCMES Factors  N r  p r2 1 226     .217**  .001 .047 2 226     .191**  .004 .036 3 226  .045  .503 .002 4 226 .111  .097 .012 5 226   .139*  .036 .019 6 226   .146*  .028 .021 Total Scale 226     .178**  .007 .032 Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001  51 9. Hypothesis 9: Community Setting. Counsellors working in rural settings had higher scores (N = 30, Mean = 6.35) for Factor 3 (Developing Cross-Cultural Relationships) than counsellors working in all other settings combined (N = 196, Mean = 6.10). An independent t-test showed that the difference between the conditions was statistically significant (t = -1.981, df = 224, p < .05, two-tailed). The magnitude of the difference in the means (mean difference = -0.25, 95% CI: -0.4926 to -0.0013) was small (d = 0.39). 10. Hypothesis 10: Provision of Training. There was a significant positive correlation between provision of training and Factor 1: Knowledge of Multicultural Concepts  (r = .156, N = 226, p < 0.05, two-tailed).  It was a weak correlation: 2.4% of the variation was explained (r2 = 0.024). 13. Hypothesis 13: Caseload Diversity. Counsellors whose caseloads consist of a single Non-Caucasian majority of 75% (or higher) had significantly higher scores (Mean = 5.44) for Factor 4 (Multicultural Counselling Awareness) than counsellors whose caseloads did not consist of such a majority (Mean = 5.19).  An independent t-test showed that the difference between the conditions was statistically significant (t = -2.078, df = 23.734,  p < .05, two-tailed). The magnitude of the difference of means (mean difference = -0.25, 95% CI: -0.4983 to -0.0015) was small (d = 0.35). Please note: in this test, only 17 counsellors have caseloads with Non-Caucasian majorities of 75% or higher, while 202 counsellors have other types of caseloads. Equality of variance does not exist between the two conditions (Levene’s p = 0.031). This test relies on calculations that assume the variances are unequal. 14. Hypothesis 14: Frequency of Cross-Cultural Counselling Sessions. Frequency of cross-cultural counselling sessions was significantly correlated to Factor 1 (Knowledge of  52 Multicultural Concepts), Factor 4 (Multicultural Counselling Awareness), Factor 5 (Multicultural Assessment), and the total score of the SCMES (see Table 7). Table 7: Frequency of Cross Cultural Counselling Sessions and Correlations, Significance and Variance with SCMES Factors  SCMES Factors  N r  p r2 1 226   .157*  .018 .025 2 226 .043  .523 .002 3 226 .055  .408 .003 4 226   .170*  .010 .029 5 226   .158*  .017 .025 6 226           .074  .268 .005 Total Scale 226   .134*  .044 .018 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001  Secondary Analysis  Rationale for Using Hierarchical Multiple Linear Regression Analysis  Multiple regression analysis is the method of choice, when dealing with relationships that are highly complex, particularly when these relationships are not readily subject to experimental control (Dickson & Jepsen, 2007; Licht, 2004). In this study, five types of predictors interacted to influence multicultural self-efficacy among school counsellors. These predictors – demographic variables, experience variables, training variables, workplace variables, and caseload diversity variables – contributed collectively and individually to variance in self-efficacy.  Given this complexity, hierarchical multiple regression was used to tease out the relative contributions of these predictors, and to identify specific variables that are statistically  53 significant contributors. Each of the six SCMES factors, and the Total Scale, was examined separately.  Preliminary analyses were used to identify promising predictor variables. Three variables -- multicultural graduate-level training, multicultural in-service training, and frequency of cross-cultural counselling sessions -- were significantly related to a number of factors. The remaining variables – provision of training, community setting, and non-Caucasian majority – had smaller and more localized effects. Two were excluded from secondary analysis. Provision of training was removed, because it was significantly correlated with in-service training (r = .177, p = .008), and appeared to measure a complimentary phenomenon.  Similarly, non-Caucasian majority (75% or higher) was removed because (1) it was significantly correlated to frequency of cross-cultural sessions (r = .220, p = .001),  (2) it was based on a very small sub-group (N = 17), and (3) its preliminary t-test results did not adhere to the assumption of equality of variance. Community setting was retained as a predictor because it presented no such concerns.  The final selection of predictor variables was informed by both preliminary analyses and the remaining research questions of this study.  As a result, Step 1, Demographics, consists of four variables that are not statistically significant in preliminary analysis: participant age, gender, race/ethnicity, and level of post-secondary education (graduate-level training in counselling).  These items provide a baseline or point-of-comparison for the steps that follow.  Graduate-level training in counselling is particularly important, because it allows variance from general counselling training to be distinguished from variance contributed specifically by multicultural training.  In a similar vein, Step 2, Experience, consists of teaching experience and counselling experience. Neither factor is statistically significant, but both are related to Research Questions 3  54 and 4. By contrast, the variables included in Steps 3, 4 and 5 – Training, Workplace, and Caseload Diversity – were all identified as significant in the preliminary analyses above.  The order of entry into the regression was dictated by primacy. In other words, those factors or experiences occurring earlier and lasting longer were entered in the first steps, and those occurring later and lasting for a shorter duration were entered in the later steps.  For the results of these analyses to be meaningful, the data must conform to a number of conditions, as outlined below. First, the number of participants must be large.  The present regression uses ten predictor variables and is based on 212 participants. (Although results were obtained from 226 participants, 14 did not report their ethnicity/race and were excluded from the regression analysis). Tabachnick and Fidell (2007) prescribe that the number of participants should be (1) at least 8 times the number of predictor variables plus 50 (in our study, 10 x 8 + 50 = 130), or (2) the number of predictors plus 104 (in our study, 10 + 104 = 114). Based on these criteria, our study exceeds the minimum number of participants recommended.  Secondly, data must be screened for outliers and normality. These conditions were addressed, and Factor 3 was remedied, as described earlier. Thirdly, all predictors should be independent, as evidenced by low inter-correlations and high collinearity tolerance statistics during multiple regression. Table 8 reveals the patterns of predictor inter-correlations. To view the inter-correlations between all predictor and criterion variables, please consult Appendix E.         55 Table 8: Inter-correlations Among Regression Predictor Variables Predictor Variables  1 2 3 4 5 6 7 8 9 10 1. --          2. -.145* --         3. .060 -.111 --        4. -.043 .079 -.088 --       5. -.026 .714*** -.142* -.049 --      6. -.123 .578*** -.078 .096 .463*** --     7. .038 -.015 .066 .075 -.049 -.060 --    8. .141* .167* .090 -.023 .149* .170* .400*** --   9. .008 .009 -.041 -.120 .017 -.045 .077 .133* --  10. .064 -.119 .109 -.021 -.067 -.149* .042 .087 -.165* -- Note: 1 = Age; 2 = Gender; 3 = Race / Ethnicity; 4 = Counselling Graduate Degree;  5 = Teaching Experience; 6 = Counselling Experience; 7 = Graduate-level Multicultural Training; 8 = In-Service Multicultural Training; 9 = Community Setting; 10 = Frequency of Cross-Cultural Sessions. Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Masters in Counselling, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001   Predictably, age is strongly correlated with teaching experience (r = .714, p < .001) and counselling experience (r = .578, p < .001). Similarly, teaching experience is strongly correlated with counselling experience (r = .463, p < .001), and multicultural graduate-level training is strongly correlated with multicultural in-service training (r = .400, p < .001). All other variables are correlated at lower levels of strength and significance. In addition, tolerance statistics calculated during standard multiple regression, ranged from .396 to .953, and were well above the threshold of 0 for collinearity. Finally, residual scores should be screened for outliers, normality and homoscedasticity. Residuals were screened for each factor and the Total Score, during multiple regression.  Visual examination of Normal P-P plots of expected-versus-observed scores showed a normal (linear) distribution of residuals for each regression.  In  56 addition, visual examination of scatterplots of regression standardized residuals-versus-regression standardized predicted values, indicated homoscedastic distributions (a roughly rectangular spread) for each factor.  The results of hierarchical multiple regression analysis for each factor and the Total Score are given below in Tables 9 through 15.  In each table, the results are drawn from the fifth model (or fifth step), which includes all ten individual predictor variables. A more detailed summary of the results can be found in Appendix F. Table 9: Hierarchical Regression Analysis - SCMES Factor 1 - Knowledge of Multicultural Concepts (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Factor 1; R2 = .135; ƒ2 = .16 Step 1: Demographic Variables   .012 .012 Step 2: Experience Variables   .019 .007      Teaching Experience .117 .009        Counselling Experience .004 .009   Step 3: Training Variables   .104 .085***      Graduate-level Multicultural Training .199** .035        In-service Multicultural Training .124 .017   Step 4: Community Setting .104 .165 .110 .005 Step 5: Frequency of Cross Cultural Sessions .165* .037 .135 .025* Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001   Model 5 explains 13.5% of the variance in Factor 1 (R2 = .135) and was significant (F(10, 201) = 3.132, p < .001). The effect size (ƒ2 = .16) was small, when applying Cohen’s (1988) interpretive language. Training variables accounted for significant incremental variance in predicting scores on the Factor 1 subscale, ΔR2 = .085, p < .001, after controlling for demographic and experience effects. Graduate-level multicultural training (β = .199, p < .01) made a unique contribution to  57 predicting scores on the Factor 1 subscale. Frequency of cross cultural sessions also accounted for significant incremental variance in predicting scores on the Factor 1 subscale, ΔR2 = .025, p < .05, after controlling for demographic, experience, training, and workplace effects. This variable made a unique contribution (β = .165, p < .05) to predicting scores on the Factor 1 subscale. Table 10: Hierarchical Regression Analysis - SCMES Factor 2 - Using Data and Understanding Systemic Change (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Factor 2; R2 = .108; ƒ2 = .12 Step 1: Demographic Variables   .010 .010 Step 2: Experience Variables   .015 .005      Teaching Experience .103 .010        Counselling Experience .021 .010   Step 3: Training Variables   .100 .085***      Graduate-level Multicultural Training .202** .041        In-service Multicultural Training .132 .019   Step 4: Community Setting .085 .196 .106 .006 Step 5: Frequency of Cross Cultural Sessions .048 .044 .108 .002 Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001   Model 5 explains 10.8% of the variance in Factor 2 (R2 = .135) and was significant (F(10, 201) = 2.437, p < .01). The effect size (ƒ2 = .12) was small, when applying Cohen’s (1988) interpretive language. Training variables accounted for significant incremental variance in predicting scores on the Factor 2 subscale, ΔR2 = .085, p < .001, after controlling for demographic and experience effects. Graduate-level multicultural training (β = .202, p < .01) made a unique contribution to predicting scores on the Factor 2 subscale.    58 Table 11: Hierarchical Regression Analysis - SCMES Factor 3 - Developing Cross Cultural Relationships (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Factor 3; R2 = .085; ƒ2 = .09 Step 1: Demographic Variables   .010 .010 Step 2: Experience Variables   .033 .023      Teaching Experience  .201* .007        Counselling Experience -.060 .007   Step 3: Training Variables   .061 .028*      Graduate-level Multicultural Training  .164* .028        In-service Multicultural Training -.024 .019   Step 4: Community Setting .151* .131 .079 .018* Step 5: Frequency of Cross Cultural Sessions .079 .030 .085 .006 Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001   Model 5 explains 8.5% of the variance in Factor 3 (R2 = .085), but was not statistically significant (F(10, 201) = 1.862, p = .052). The effect size (ƒ2 = .09) was small, when applying Cohen’s (1988) interpretive language. Experience variables accounted for non-significant incremental variance in predicting scores on the Factor 3 subscale, ΔR2 = .023, p = .088, after controlling for demographic effects. Teaching experience (β = .201, p < .05) made a unique contribution to predicting scores on the Factor 3 subscale. Training variables also accounted for significant incremental variance in predicting scores on the Factor 3 subscale, ΔR2 = .028, p < .05, after controlling for demographic and experience effects. Graduate-level multicultural training (β = .164, p < .05) made a unique contribution to predicting scores on the Factor 3 subscale. Finally, community setting accounted for significant incremental variance in predicting scores on the Factor 3 subscale, ΔR2 = .018, p < .05, after controlling for demographic,  59 experience and training effects. This variable made a unique contribution (β = .151, p < .05) to predicting scores on the Factor 3 subscale. Table 12: Hierarchical Regression Analysis - SCMES Factor 4 - Multicultural Counselling Awareness (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Factor 4; R2 = .096; ƒ2 = .11 Step 1: Demographic Variables   .013 .013 Step 2: Experience Variables   .017 .004      Teaching Experience  .041 .008        Counselling Experience  .080 .008   Step 3: Training Variables   .064 .048**      Graduate-level Multicultural Training  .202** .032        In-service Multicultural Training  .037 .015   Step 4: Community Setting -.040 .152 .069 .005 Step 5: Frequency of Cross Cultural Sessions .171* .034 .096 .027* Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001   Model 5 explains 9.6% of the variance in Factor 4 (R2 = .096) and was significant (F(10, 201) = 2.145, p < .05). The effect size (ƒ2 = .11) was small, when applying Cohen’s (1988) interpretive language. Training variables accounted for significant incremental variance in predicting scores on the Factor 4 subscale, ΔR2 = .048, p < .01, after controlling for demographic and experience effects. Graduate-level multicultural training (β = .202, p < .01) made a unique contribution to predicting scores on the Factor 4 subscale. Frequency of cross cultural sessions also accounted for significant incremental variance in predicting scores on the Factor 4 subscale, ΔR2 = .027, p < .05, after controlling for demographic, experience, training, and workplace effects. This variable made a unique contribution (β = .171, p < .05) to predicting scores on the Factor 4 subscale.  60 Table 13: Hierarchical Regression Analysis - SCMES Factor 5 - Multicultural Assessment  (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Factor 5; R2 = .083; ƒ2 = .09 Step 1: Demographic Variables   .006 .006 Step 2: Experience Variables   .008 .002      Teaching Experience  .001 .010        Counselling Experience -.038 .011   Step 3: Training Variables   .059 .050**      Graduate-level Multicultural Training  .167* .042        In-service Multicultural Training  .081 .020   Step 4: Community Setting .055 .197 .060 .001 Step 5: Frequency of Cross Cultural Sessions .159* .044 .083 .024* Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001   Model 5 explains 8.3% of the variance in Factor 5 (R2 = .083), but was not statistically significant (F(10, 201) = 31.824, p = .058). The effect size (ƒ2 = .09) was small, when applying Cohen’s (1988) interpretive language. Training variables accounted for significant incremental variance in predicting scores on the Factor 5 subscale, ΔR2 = .050, p < .01, after controlling for demographic and experience effects. Graduate-level multicultural training (β = .167, p < .05) made a unique contribution to predicting scores on the Factor 5 subscale. Caseload variables also accounted for significant incremental variance in predicting scores on the Factor 5 subscale, ΔR2 = .024, p < .05, after controlling for demographic, experience, training, and workplace effects. This variable made a unique contribution (β = .159, p < .05) to predicting scores on the Factor 5 subscale.    61 Table 14: Hierarchical Regression Analysis - SCMES Factor 6 - Application of Racial and Cultural Knowledge to Practice (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Factor 6; R2 = .078; ƒ2 = .08 Step 1: Demographic Variables   .012 .012 Step 2: Experience Variables   .021 .009      Teaching Experience .105 .008        Counselling Experience .068 .008   Step 3: Training Variables   .064 .043*      Graduate-level Multicultural Training .128 .033        In-service Multicultural Training .103 .016   Step 4: Community Setting .092 .154 .070 .005 Step 5: Frequency of Cross Cultural Sessions .093 .035 .078 .008 Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001   Model 5 explains 7.8% of the variance in Factor 6 (R2 = .078), but was not statistically significant (F(10, 201) = 1.697, p = .083). The effect size (ƒ2 = .08) was small, when applying Cohen’s (1988) interpretive language. Training variables accounted for significant incremental variance in predicting scores on the Factor 6 subscale, ΔR2 = .043, p < .05, after controlling for demographic and experience effects.          62 Table 15: Hierarchical Regression Analysis - SCMES Total Score (N = 212)  Predictor  β SE R2 ΔR2 Criterion: SCMES Total Scale; R2 = .119; ƒ2 = .14 Step 1: Demographic Variables   .010 .010 Step 2: Experience Variables   .016 .006      Teaching Experience .107 .007        Counselling Experience .014 .007   Step 3: Training Variables   .096 .081***      Graduate-level Multicultural Training .215** .029        In-service Multicultural Training .098 .014   Step 4: Community Setting .088 .136 .100 .004 Step 5: Frequency of Cross Cultural Sessions .144* .031 .119 .018* Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Effect size is computed from (ƒ2 = R2 / 1 – R2) (Cohen, 1988, p. 410) Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001  Model 5 explains 11.9% of the variance in the Total Scale (R2 = .119) and was significant (F(10, 201) = 2.718, p < .01). The effect size (ƒ2 = .14) was small, when applying Cohen’s (1988) interpretive language. Training variables accounted for significant incremental variance in predicting scores on the Total Scale, ΔR2 = .081, p < .001, after controlling for demographic and experience effects. Graduate-level multicultural training (β = .215, p < .01) made a unique contribution to predicting scores on the Total Scale. Frequency of cross cultural sessions also accounted for significant incremental variance in predicting scores on the Total Scale, ΔR2 = .018, p < .05, after controlling for demographic, experience, training, and workplace effects. This variable made a unique contribution (β = .144, p < .05) to predicting scores on the Total Scale.  Research Question 3 Research Question 3 asked, “Does diversity of caseload have a stronger relationship to multicultural counselling self-efficacy than does years of experience?”  63 The preliminary and secondary analyses for Research Question 2 suggest that these two variables are related to different scales of the SCMES.   In preliminary analysis, years of experience, teaching and counselling, is not significantly correlated to any of the scales of the SCMES. By contrast, caseload diversity, in the form of frequency of cross-cultural sessions, is significantly correlated with four scales: Factors 1, 4, 5 and the Total Scale. See Table 16 below. Table 16: Correlations between SCMES Factors and Years of Experience and Frequency of Cross Cultural Sessions (N = 226)  Factor N Years of Experience Caseload Diversity  Teaching (r) Counselling (r) Frequency of Cross-Cultural Sessions (r) 1 226  .023  .005   .157* 2 226 -.007 -.016 .043 3 226  .079 -.008 .055 4 226 -.021  .028   .170* 5 226 -.037 -.060   .158* 6 226  .048  .057 .074 Total Scale 226  .011 -.004   .134* Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01 (2-tailed)  In secondary analysis, the general category, years of experience, is not a significant predictor of any SCMES factors. However, teaching experience, specifically, emerges as a significant predictor of Factor 3 – Developing Cross-Cultural Relationships.  Caseload diversity is not a significant predictor for this factor.  Similarly, while caseload diversity, in the form of frequency of cross-cultural sessions, is a significant predictor of Factors 1, 4, 5 and the Total Scale, years of experience is not a significant predictor of any of these factors. See Table 17 below.  64 Table 17: Hierarchical Regression Analysis Results for Years of Experience and Caseload Diversity (N = 212)  Factor N Years of Experience Caseload Diversity  Predictor Contribution (ΔR2) Teaching (β) Predictor Contribution (ΔR2) Frequency of Cross-Cultural Sessions (β) 1 212 .007 .117   .025*   .165* 2 212 .005 .103 .002 .048 3 212 .023   .201* .006 .079 4 212 .004 .041   .027*   .171* 5 212 .002 .001   .024*   .159* 6 212 .009 .105 .008 .093 Total Scale 212 .006 .107   .018*   .144* Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001  These results indicate that caseload diversity predicts a larger number of factors (and different factors) than does years of experience, in the form of teaching experience.   Research Question 4 Research Question 4 asked, “Among school counsellors with high levels of training, do years of experience have a significantly stronger relationship with multicultural counselling self-efficacy, when compared to counsellors with lower levels of training?”  Since this study measures two types of training (graduate and in-service) and two types of experience (counselling and teaching), this general question was broken down into a series of 4 hypotheses, numbered 15 to 18.   65 15. H0: Taking a larger number of graduate-level multicultural counselling courses will have no significant effect on the relationship between years of teaching experience and multicultural counselling self-efficacy. H1: School counsellors with a higher number of graduate-level multicultural courses will show a stronger relationship between years of teaching experience and multicultural counselling self-efficacy. 16. H0: Taking a larger number of graduate-level multicultural counselling courses will have no significant effect on the relationship between years of counselling experience and multicultural counselling self-efficacy. H1: School counsellors with a larger number of graduate-level multicultural courses will show a stronger relationship between years of counselling experience and multicultural counselling self-efficacy. 17. H0: Taking a larger number of in-service multicultural counselling courses will have no significant effect on the relationship between years of teaching experience and multicultural counselling self-efficacy. H1: School counsellors with a larger number of in-service multicultural courses will show a stronger relationship between years of teaching experience and multicultural counselling self-efficacy. 18. H0: Taking a larger number of in-service multicultural counselling courses will have no significant effect on the relationship between years of counselling experience and multicultural counselling self-efficacy.  66 H1: School counsellors with a larger number of in-service multicultural courses will show a stronger relationship between years of counselling experience and multicultural counselling self-efficacy. To test these hypotheses, the variables number of graduate courses and number of in-service courses were each coded into 4 levels. These levels corresponded with natural breaks in the data distributions and with inter-quartile ranges. Number of graduate courses broke into four levels: 1 = zero courses, 2 = 1 course, 3 = 2 courses, and 4 = 3 to 10 courses.  Since the range of level 4 (3 to 10 courses) was so large, this level was further divided: level 4 = 3 to 4 courses, and level 5 = 5 to 10 courses (2 standard deviations above the mean). A similar process was used to code the number of in-service courses into five levels:  1 = zero courses, 2 = 1 to 2 courses, 3 = 3 to 4 courses, 4 = 5 to 10 courses, and 5 = 11 to 20 courses (again, 2 standard deviations above the mean).   Once these training levels were determined, it was possible to test the relationship between experience and self-efficacy at each training level, using Pearson Product-Moment correlation. Results for all training levels are shown below, and significant results are summarized. 15. Hypothesis 15: High Grad MC Courses - Correlation of Teaching Experience and Self-Efficacy. The null hypothesis is rejected for Factor 3. Among school counsellors with 5 to 10 graduate level multicultural counselling courses, years of teaching experience was significantly correlated to Factor 3 (Developing Cross-Cultural Relationships), r = 0.619, N = 10, p < 0.05, one tailed. It is a moderately strong correlation: 38.3% of the variation is explained (r2 = 0.3832). See Table 18 below.    67 Table 18: Correlation of Teaching Experience with Self-Efficacy at Increasing Levels of Multicultural Counselling Graduate Training  SCMES Factors Correlation of Teaching Experience with Self-Efficacy (r)  Zero Courses (N = 67) 1 Course (N = 81) 2 Courses (N = 48) 3 to 4 Courses (N = 20) 5 to 10 Courses (N = 10) 1 .058 -.088 .131 .157 .217 2 .049 -.123 .021 .160 .464 3 .081 .044 .089 .103 .619* 4 .001 -.051 .009 .305 -.082 5 -.019 -.163 .048 -.168 .467 6 .094 -.166 .175 .296 .452 Total Scale .046 -.126 .093 .207 .476 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01 (1-tailed)  16. Hypothesis 16: High Grad MC Courses - Correlation of Counselling Experience and Self-Efficacy. The null hypothesis is retained for all factors and for the Total Scale. Regardless of training level, no significant correlations were found between years of counselling experience and multicultural counselling self-efficacy. See Table 19 below.          68 Table 19: Correlation of Counselling Experience with Self-Efficacy at Increasing Levels of Multicultural Counselling Graduate Training  SCMES Factors Correlation of Counselling Experience with Self-Efficacy (r)  Zero Courses (N = 67) 1 Course (N = 81) 2 Courses (N = 48) 3 to 4 Courses (N = 20) 5 to 10 Courses (N = 10) 1 .052 .104 -.018 .117 .012 2 .126 -.035 -.147 .073 .400 3 .048 .081 -.165 .207 .411 4 .133 .089 -.102 .157 -.286 5 .086 -.100 -.206 .015 .158 6 .199 .029 -.151 .226 .185 Total Scale .121 .022 -.166 .186 .213 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01 (1-tailed)  17. Hypothesis 17: High In-Service MC Courses - Correlation of Teaching Experience and Self-Efficacy. The null hypothesis is rejected for Factor 3. Among school counsellors with 5 to 10 in-service multicultural counselling courses, years of teaching experience was significantly correlated to Factor 3 (Developing Cross-Cultural Relationships), r = 0.281, N = 43, p < 0.05, one tailed. It is a small correlation: 7.9% of the variation is explained (r2 = 0.0789). See Table 20 below.        69 Table 20: Correlation of Teaching Experience with Self-Efficacy at Increasing Levels of Multicultural In-Service Training  SCMES Factors Correlation of Teaching Experience with Self-Efficacy (r)  Zero Courses  (N = 56) 1 to 2 Courses (N = 72) 3 to 4 Courses (N = 48) 5 to 10 Courses (N = 43) 11 to 20 Courses (N = 7) 1 .047 -.148 -.110 .223 .566 2 .091 -.123 -.176 .109 .066 3 .218 -.023 -.228   .281* .591 4 .108 -.212* -.260* .254 .151 5 .051 -.154 -.162 .024 .343 6 .008 -.032 -.145 .243 .284 Total Scale .098 -.148 -.208 .214 .392 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01 (1-tailed)  Hypothesis 18: High In-Service MC Courses - Correlation of Counselling Experience and Self-Efficacy. The null hypothesis is retained for all factors and for the Total Scale. At higher training levels, no significant correlations were found between years of counselling experience and multicultural counselling self-efficacy. See Table 21 below.           70 Table 21: Correlation of Counselling Experience with Self-Efficacy at Increasing Levels of Multicultural In-Service Training  SCMES Factors Correlation of Counselling Experience with Self-Efficacy (r)  Zero Courses  (N = 56) 1 to 2 Courses (N = 72) 3 to 4 Courses (N = 48) 5 to 10 Courses (N = 43) 11 to 20 Courses (N = 7) 1 .007 -.247* .184 -.054 .472 2 .161 -.309** .196 -.138 .326 3 .180 -.228* .041 -.149 616 4 .159 -.178 .003 .068 .173 5 .118 -.335** .126 -.203 .397 6   .241* -.141 .000 -.027 .329 Total Scale .173 -.298** .123 -.113 .449 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01 (1-tailed)  These results indicate that, at very high levels of multicultural graduate-level and in-service training, the relationship between years of teaching experience and self-efficacy is stronger. This trend exists only for Factor 3 (Developing Cross Cultural Relationships).   71 Chapter 5: Discussion Research Question 1 The first research question examined British Columbian school counsellors’ levels of multicultural counselling self-efficacy, using the School Counseling Multicultural Self-Efficacy Scale (SCMES; Holcomb-McCoy, Harris, Hines, and Johnson, 2008). Findings across all six factors, and the Total Scale, suggest that school counsellors feel “pretty well” (4 to 6 on a 7-point scale) about their ability to perform tasks associated with multicultural school counselling.  These findings are consistent with the results obtained by Holcomb-McCoy et al. (2008) and Crook (2010).  Notably, participants in this study report less self-efficacy in Factor 2 (Using Data and Understanding Systemic Change, M = 4.27, SD = .946) and Factor 5 (Multicultural Assessment, M = 4.77, SD =  .953), while they reported greater self-efficacy in Factor 3 (Developing Cross-Cultural Relationships, M = 6.14, SD = .640).  The lower results for Factors 2 and 5 may be attributed in part to two biases that are built into this instrument: (1) school level and (2) regional availability of culturally sensitive assessment.  First, the SCMES contains several items that are geared primarily to high school counsellors.  These items – Numbers 7, 16, 40 and 49 – are all drawn from Factor 2, and they are all related to post-secondary or career planning.  Sixty-four (64) participants identified themselves as elementary or middle school counsellors. Elementary and middle school counsellors, do not emphasize such planning, and their scores for these items were correspondingly lower than those of their high school colleagues. These lower individual scores depressed the overall score for Factor 2.  See Table 20 below.    72 Table 22: Means and Standard Deviations for SCMES Items 7, 16, 40 and 49 Sorted by Counsellor Grade Level  Items Elementary and Middle School Counsellors High School Counsellors  N Mean SD N Mean SD 7 64 3.71 1.64 133 4.49 1.33 16 64 2.98 1.50 133 3.85 1.61 40 64 4.32 1.53 133 4.98 1.38 49 64 3.46 1.46 133 4.15 1.39  The second instrument bias concerns the availability of culturally sensitive assessment in British Columbia (BC) versus the United States. The contentious item –Number 52 – is drawn from Factor 5. It states, “I can use culturally appropriate instruments when I assess students.” Many participants commented on the rarity of such instruments, and asked how they could be acquired.  It is possible that culturally appropriate instruments are more plentiful in the United States, where a much larger population provides greater opportunities for test development and marketing.  Scores for this item were lower (Mean = 4.00, SD = 1.33), and reduced the overall score for Factor 5 (Mean = 4.77, SD = 0.95).  By contrast, the higher results for Factor 3 may be due in part to ceiling effects in its seven constituent items.  Factor 3 is the only scale in which the range of reported combined-item-scores extends to the upper limit of seven (7) on a 7-point scale. In fact, twelve (12) respondents report perfect scores (7) for this Factor.  This skewedness in the distribution suggests that the scale itself is not capturing the true variability in the data at the upper extreme.  A limit of 7 on this scale may be constraining participants to report a maximum value, whereas a higher limit could provide a more accurate profile of participants’ ability to develop cross-cultural relationships.  73 Research Question 2  The second research question examined the demographic and workplace variables that contribute to school counsellors’ multicultural counselling self-efficacy. Since two levels of analysis were used, this discussion will address the results of each level separately. Preliminary Results: Hypotheses that Retained the Null During preliminary analyses, eight of the fourteen hypotheses retained the null hypothesis. No significant effects were found for gender or for age.  This is quite consistent with most of the literature (Arthur & Januszkowski, 2001; Crook, 2010; Holcomb-McCoy, 2005; Holcomb-McCoy et al., 2008; Tadlock-Marlo, 2012). In terms of gender, two notable exceptions include Bodenhorn and Skaggs (2005), who found that female school counsellors reported greater school counsellor self-efficacy, and Sheu and Lent (2007), who found that male counsellors reported more general counselling self-efficacy. Age also registered small effects for Sheu and Lent (2007), with older counsellors having slightly higher general counselling self-efficacy.  A different picture emerges for race/ethnicity. Here again, no effect was found in the present study, despite widespread reports of its significance in the literature (Crook, 2010; Guzman, Calf, Van Horn Kerne, & McCarthy, 2013; Holcomb-McCoy et al., 2008; Sheu & Lent, 2007). Our results do not support the concept of race/ethnicity as significant lived experience, as described by Guzmán and colleagues (2013). A number of factors may account for the non-significance of this variable. Perhaps our sample of counsellors did not contain enough members of racial/ethnic minorities -- just 22 participants, or 9.7% of the sample -- to make a meaningful comparison. Furthermore, we pooled minority counsellors into a single category to obtain a significantly large sub-group for purposes of comparison.  In the process, important distinctions between the different racial/ethnic groups were almost certainly lost (Ridley & Shaw-Ridley,  74 2011).  Finally, during regression analysis, our sample was further reduced to 212 counsellors. Fourteen participants were excluded: 13 had reported themselves as Canadian and one did not report his/her race.  As a result, the regression did not include their data in its analysis.  If this variable is to be meaningfully examined in future studies, greater care will need to be taken to capture the ethnic/racial data of participants. Less controversially, graduate training in general counselling had no effect.  This variable is not widely studied in the literature, but Sheu and Lent (2007) did find that it had a significant effect on general counselling self-efficacy. For the purposes of regression analyses in the present study, this variable makes a very useful distinction between graduate-level counsellor training and graduate-level multicultural training. Similarly, years of experience – teaching and counselling – were not significantly related to any of the factors of the SCMES.  These findings are entirely consistent with the literature (Guzmán et al, 2013; Holcombe-McCoy, 2005; Holcomb-McCoy et al., 2008; Tadlock-Marlo, 2012).  Crook (2010), who found a positive relationship between years of counselling experience and Factor 2 of the SCMES, is the only exception.  However, few of the studies, cited above, report on teaching experience separately. Bodenhorn and Skaggs (2005) did measure teaching experience, and found that it was positively related to school counsellor self-efficacy. This perhaps foreshadows the significance of teaching experience during regression analysis in the present study. No significant effects were detected for school diversity, consistent with Tadlock-Marlo (2012). This variable is very useful, because it distinguishes between diversity in the school population and the diversity of the particular students the counsellor works with. It is significantly correlated with frequency of cross-cultural sessions (r = .528, p < 0.001), but it is not correlated with self-efficacy. These results suggest that mere exposure to a diverse  75 population is not sufficient to develop multicultural self-efficacy: interaction is needed. Finally, provision of supervision was not related to any scales of the SCMES. This calls into question the relationship of supervision to practicing school counsellors’ self-efficacy.  Most research on this relationship has been carried out with trainees (Constantine, 2001; Sheu & Lent, 2012), and it may not apply to seasoned school counsellors. Arthur and Januszkowski (2001) provide a notable exception.  In a qualitative study, they found that peer consultation contributed to higher MCC among general counsellors. Perhaps this variable needs to be measured differently to capture such a relationship among school counsellors. Preliminary Results: Hypotheses that Rejected the Null  During preliminary analyses, six of the fourteen hypotheses rejected the null hypothesis. Graduate-level multicultural (MC) training was significantly correlated to all of the factors and the Total Scale. It is the most widely influential variable of all those examined in this study. This result corresponds well to the idea that training enhances self-efficacy. However, it should be remembered that these results are correlational. Thus, it is also possible that MC self-efficacy motivates counsellors to seek MC training, or that another variable, such as MC interest, affects training and self-efficacy.  This finding is generally supported by the literature (Arthur & Januszkowski, 2001; Guzmán et al., 2013; Holcomb-McCoy, 2005; Holcomb-McCoy et al., 2008; Sheu & Lent, 2007; Tadlock-Marlo, 2012). Significantly however, Holcomb-McCoy and colleagues (2008) had a much more constrained view of training in any form; it was not related to Factor 3 or Factor 6 of the SCMES. Our results are furthermore contrary to Crook (2010) who measured MC training as taking at least one graduate-level MC course (not sufficiently sensitive) and found no effects at all.   76  In-service multicultural (MC) training was significantly correlated across fewer factors: 1, 2, 5, 6, and the Total Scale.  Despite its more limited scope, this variable, too, provides evidence of the importance of training to self-efficacy (though the alternate interpretations, described above, also apply here). Our results for in-service MC training find general support in the literature (Arthur & Januszkowski, 2001; Holcomb-McCoy, 2005; Holcomb-McCoy et al., 2008; Tadlock-Marlo, 2012). Furthermore, our finding that in-service training is unrelated to Factor 3, echoes in part the results of Holcomb-McCoy and colleagues (2008), described above, for Factors 3 and 6.  It is possible that its effects are more limited in scope, because in-service training occurs within the context of practice, and may be less consistent in its availability, content, and delivery. Certainly, it merits further investigation.   Given these results, it makes sense that provision of training is significantly related to Factor 1 (Knowledge of Multicultural Concepts). This variable is significantly correlated to in-service training (r = .177, p < .01) and provides a measure of convergent validity for in-service MC training. These results could be interpreted in two ways: (1) much of the in-service training provided in work settings is related to developing MC knowledge, or (2) counsellors with high levels of MC knowledge seek additional in-service MC training.    The results for community setting require more explanation, because they are counter-intuitive and contrary to the findings of the only other study that has reported on the effect of community setting (Crook, 2010). In the present study, community setting is significantly related to Factor 3 (Developing Cross Cultural Relationships), with counsellors in rural schools having higher levels of MC self-efficacy than counsellors in urban, suburban or mixed settings. By contrast, Crook (2010) found that counsellors working in urban settings had higher SCMES scores across all six factors. At first glance, Crook’s (2010) results make more sense: typically,  77 urban populations have higher levels of cultural diversity than rural populations.  Thus, counsellors in urban settings may have more experience with diverse students and families in and out of the workplace, and higher resulting self-efficacy.  If this is true, then there are at least two interpretations for our results.  First, rural counsellors, having a limited range of cross-cultural experiences, may have simply over-estimated their ability to form relationships with diverse students.  Alternatively, rural counsellors may have based their self-estimates on a greater sense of mastery and depth of experience, afforded by the experience of working with one or two minority populations.    The latter interpretation is supported by other evidence in our study. For example, we found that schools in rural settings have significantly higher Causcasian populations. In the present study, the percentage of Caucasian students on caseloads is higher in rural settings (mean = 60.46) than in non-rural settings (mean = 47.53). This difference is significant (p = .022), and the effect size is moderate (d = 0.48). Not surprisingly therefore, counsellors in rural settings report significantly less contact with non-Causcasian students. The frequency of cross-cultural sessions is lower in rural settings (mean = 4.02) than in non-rural settings (mean = 4.74). This difference is also statistically significant (p = .013), and the effect size is moderate (d = 0.49).  However, rural counsellors do have more contact with Aboriginal students. The percentage of Aboriginal students on caseloads is higher in rural settings (mean = 24.85) than non-rural settings (mean = 12.75). This difference is significant (p = .005), and the effect size is moderate (d = 0.66). (Note, the variability of these two groups is not equal: Levene’s coefficient p = 0.045). It is possible that school counsellors in rural settings report higher self-efficacy for Factor 3 because they work primarily with Caucasian and Aboriginal cultures, and develop greater skill in forming relationships with students from these cultures. Rural school counsellors may experience higher  78 self-efficacy, despite having less frequent contact with minority members, because they are able to reflect more on their interactions, and work to develop a greater depth of connection.  This pattern is not limited to counsellors who work in rural settings.  Generally, school counsellors with caseloads consisting of only two racial/ethnic groups (N = 8), report higher scores for Factor 3 (mean = 6.56) than counsellors having caseloads of only one, or greater than two, groups (N = 218, mean = 6.12). This difference is statistically significant (p = .001) with a moderate effect size (d = 0.49). (Again note, the variability of these two groups is not equal: Levene’s coefficient p = 0.039).  This suggests that Factor 3 may be related to a different dimension of experience: one that is measured more by depth of contact, rather than range or frequency of contact.  This would make Factor 3 somewhat unique among the SCMES scales.  By comparison, frequency of cross-cultural sessions is significantly related to completely different SCMES scales: factors 1, 4, 5 and the Total Scale.  Once again, there are at least two possible interpretations. Perhaps frequent, specifically cross-cultural counselling experiences contribute to the development of MC self-efficacy. Or perhaps school counsellors with high MC self-efficacy attract or seek out more diverse caseloads.  These results are supported by the literature on general counselling MCC and self-efficacy (Arthur & Januszkowski, 2001; Sheu & Lent, 2007; Sheu et al., 2012). However, they are not supported by Tadlock-Marlo (2012) whose detailed methods of measuring specific experience yielded no effect, surprisingly, for school counsellor MCC.  After graduate-level and in-service MC training, frequency of cross-cultural counselling sessions is the most widely influential variable of those included in this study. Finally, counsellors with caseloads consisting of a single large non-Causcasian majority (75% or higher) have significantly higher scores for Factor 4 (Multicultural Awareness). This variable offers a different measure of specific cross-cultural counselling experience. As a result,  79 this finding provides convergent validity for the frequency of cross-cultural session findings, described above. Its link to Factor 4 is logical: one’s awareness of a specific minority group may be heightened by virtue of its large size and one’s experience working with the group over time. Secondary Results: Regression Analyses Hierarchical regression analysis was used to identify the most significant predictors of variance in school counsellor MC self-efficacy, as measured by the SCMES. Across the factors, variance ranged from R2 = 7.8% (for Factor 6) to R2 = 13.5% (for Factor 1), while the effect sizes were consistently small, ranging from ƒ2  =  .09 (for Factor 6) to ƒ2  =  .16 (for Factor 1).  These small values suggest that there may be other variables, not included in this study, that contribute much more to variance in school counsellor self-efficacy. This is a topic for future research. Multicultural (MC) training emerged as a significant predictor for all six factors and the Total Scale. And, for every factor (except Factor 6), graduate-level MC training made a statistically significant, unique contribution to variance. Although it is not possible to assign a causal relationship to MC training and MC self-efficacy, it is clear that a positive, mutually enhancing relationship does exist.  Certainly, this result supports the continued provision of MC training, both in graduate-level and in-service settings. Aside from MC training, there are no other predictors that contributed universally to the SCMES factors.  Instead, three distinct patterns of contribution were found. These can be seen in Table 21, below. The first pattern consists of two predictors, namely MC training and frequency of cross-cultural sessions. It is present in Factors 1, 4, 5 and the Total Scale. The second pattern is defined by a single predictor: MC training.  It is found in Factors 2 and 6. The third pattern includes MC training, teaching experience and community setting. It is found in Factor 3 alone.  80 Given the distinctive nature of each of the six SCMES factors, it is not surprising that, through hierarchical regression, distinctive patterns of contribution arose. Each pattern will be discussed in turn, with reference to the appropriate scales. Table 23: Contributions to Variance in SCMES Factors and Total Scale: Teaching Experience, MC Graduate -Level Training, Community Setting and Frequency of Cross Cultural Sessions  Factor  Predictors  Teaching Experience (β) MC Training (ΔR2) Community Setting (ΔR2) Frequency of Cross Cultural Sessions (ΔR2) 1     .085***  .025* 2      .085***   3 .201*  .0.28* .018*  4    .048**  .027* 5    .050**  .024* 6  .043*   Total Scale     .081***  .018* Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: Beta weights and ΔR2 are significant at: *p < .05, **p < .01, ***p < .001  Pattern 1: Factors with Two Contributing Variables: MC Training and Frequency of Cross Cultural Sessions These factors include knowledge, awareness and skills that are significantly influenced by MC training and frequency of cross-cultural counselling sessions: itself a very specific form of experience.  In each factor, MC Training is a much stronger contributor, providing approximately twice as much variance to each factor, when compared to frequency of cross-cultural sessions. This pattern is consistent throughout the four scales that constitute the group.   Factor 1 (Knowledge of Multicultural Concepts) was equated by Holcomb-McCoy and colleagues (2008) with the knowledge scale of Sue’s (2001) tri-part model of MCC. According to Holcomb-McCoy and her team (2008), Factor 1 measures the school counsellor’s ability “…to  81 discuss multicultural concepts such as the influence of racism on counseling, societal issues that affect students’ development, students’ interaction patterns, and culturally appropriate and inappropriate counseling interventions” (p. 172). MC Training accounts for 8.5% (ΔR2 = .085, p < .001) of the variance in Factor 1, with MC graduate-level training as the strongest contributor (β = .199, p < .01). Frequency of cross-cultural sessions accounted for much less of the variance -- 2.5% (ΔR2 = 0.025, p < 0.05) -- with this variable also making a unique contribution (β = .165, p < .05). Clearly, specific training and, to a lesser degree, specific counselling experience are important predictors of this self-efficacy scale. A similar pattern is apparent in Factor 4 (Multicultural Awareness). Sue and colleagues compare this factor to the awareness scale of Sue’s (2001) tri-part model of MCC. This factor includes items that capture a school counsellor’s “… multicultural self-awareness and capability to understand oneself and how one’s culture may affect his or her interactions and interventions with students” (Holcomb-McCoy et al., 2008, p. 173). Here, MC Training accounts for 4.8% (ΔR2 = .048, p < .01) of the variance, with MC graduate-level training as the strongest contributor (β = .202, p < .01). Frequency of cross-cultural counselling sessions accounted for less of the variance -- 2.7% (ΔR2 = 0.027, p < 0.05) -- with this variable making a unique contribution (β = .171, p < .05). Once more, specific training and specific counselling experience are the most significant contributors, with specific training outweighing specific counselling experience. Factor 5 (Multicultural Assessment) is entirely unique. Like Factors 2 and 3, it has no specific link to Sue’s (2001) MCC model. According to Holcomb-McCoy and colleagues (2008), it “… covers culturally appropriate and fair testing in schools” (Holcomb-McCoy et al., 2008, p. 173). In Factor 5, MC Training accounts for 5.0% (ΔR2 = .05, p < .01) of the variance, with MC  82 graduate-level training as the strongest contributor (β = .167, p < .05). Frequency of cross-cultural sessions accounts for approximately half of this level of variance -- 2.4% (ΔR2 = 0.024, p < 0.05) -- with this variable making a unique contribution (β = .159, p < .05). Here again, MC training and specific counselling experience play out a familiar pattern, with MC training accounting for more variance. Together, factors 1, 4 and 5 contain 36 of the 52 items in the SCMES.  It is therefore not surprising that the Total Scale reflects the same pattern of predictors shown in the previous three factors. However, the discrepancy between the two main contributors is much greater in the Total Scale.  MC Training accounts for 8.1% (ΔR2 = .081, p < .001) of the variance, with MC graduate training as the strongest contributor (β = .215, p < .01). Meanwhile, frequency of cross-cultural sessions accounted for much less of the variance -- 1.8% (ΔR2 = 0.018, p < 0.05) -- with this variable still making a unique contribution (β = .144, p < .05).  Clearly, this pattern indicates that, as a whole, variance in the SCMES is significantly influenced by MC training and, to a lesser extent, caseload diversity. Nevertheless, care should be taken in using the Total Scale alone as a measure of school counsellor self-efficacy. As we shall see, it does not share the same predictor pattern as the remaining three factors.  Pattern 2: Factors with One Contributing Variable – MC Training These factors are influenced by MC training alone. No other variable even approaches the same degree of significance. However, unlike the predictors discussed in Group 1, MC training does not show the same consistent pattern of contribution from factor to factor. This difference becomes apparent when we compare Factors 2 and 6.  83 Factor 2 (Using Data and Understanding Systemic Change), like Factors 3 and 5, is a scale unique to the SCMES. Holcomb-McCoy and colleagues (2008) described Factor 2 as measuring a school counsellor’s “…perceived capabilities to address equity and to use data as an advocacy and equity tool” (p. 173). In this scale, MC training accounts for 8.5% (ΔR2 = .085, p < .001) of the variance, with MC graduate-level training acting as the strongest contributor (β = .202, p < .01). This is the only statistically significant contributor.  Perhaps the skills inherent in Factor 2 can only be developed through training. Without such training, exposure to a diverse student caseload might not enhance self-efficacy.  Thus, for the purposes of this study, Factor 2 is strongly related to a single variable. By contrast, Factor 6 (Applying Racial and Cultural Knowledge to Practice) seems to be only loosely predicted by the variables included in this study. Holcomb-McCoy and colleagues (2008) identify this factor as encompassing the multicultural skills component of the Sue’s (2001) model. As such, it “… addresses professional school counsellors’ capability to integrate and apply racial concepts (e.g., racism, discrimination) into their actual practice” (p. 173). During their research of the SCMES, Holcomb-McCoy’s team found no significant relationship between Factor 6 and MC training. They concluded that perhaps MC self-efficacy skills are not strongly influenced by training. However, the present study finds quite the opposite result: MC training is the only variable that contributes significantly to Factor 6. MC training accounts for 4.3% (ΔR2 = 0.042, p < 0.01) of the variance. MC graduate-level training is the strongest non-significant contributor (β = .128, p > .05), but MC in-service training also makes a comparable contribution (β = .103, p > .05). No other variable approached the same level of statistically significant contribution.  Although the overall pattern is similar to that of Factor 2, there are some significant differences. For example, MC training in Factor 6 accounts for roughly half of  84 the variance it explained in Factor 2.  In addition, no specific training variable (graduate-level or in-service) emerges as a statistically significant contributor in Factor 6.  Finally, Regression Model 5 accounts for only 7.8% of the total variance in Factor 6. This suggests that, while Factor 6 shares some features with Factor 2, it is not well described by the variables currently under study. Perhaps there are other variables that are more powerful contributors to its variance. Certainly, frequency of cross-cultural counselling sessions is not a variable that enhances the ability to apply racial and cultural knowledge to practice.  Pattern 3: Factors with Three Contributing Variables – Teaching Experience, MC Training, and Community Setting A completely different pattern emerges for Factor 3 (Developing Cross Cultural Relationships). According to Holcomb-McCoy and colleagues (2008), this factor “… consists of items that address the counselor’s perceived capabilities to develop relationships (i.e., friendships) with culturally diverse people” (p. 173). Like Factors 2 and 5, it is unique to the SCMES. Here, three variables are involved, and each one contributes roughly equivalent amounts of variance to the factor. Years of teaching experience was the strongest individual contributor (β = .201, p < .05).  (General years of experience did account for 2.3% of the variance in this factor, but it was not statistically significant). This was an unexpected result, since experience – counselling or teaching – did not emerge as significantly correlated to Factor 3 during Preliminary Analyses. It is possible that, in the “struggle for variance” that occurs during regression, teaching experience was able to reclaim some of the influence it exerts over this factor. Certainly, there is an intuitive appeal to the idea that teaching experience enhances cross-cultural relationships.  Indeed, some of the skills required for teachers to work with diverse  85 students may be applied to building a counselling relationship with the same students. More puzzling is the non-effect of counselling experience. Perhaps this is the result of: (1) duration of experience, since most school counsellors have much more teaching experience than counselling experience, or (2) the different specific skills used in the two relationships.  Less surprising is the part played by MC training.  Unlike Holcomb-McCoy and colleagues (2008), who reported no effect for training on Factor 3, the present study found that MC training accounts for 2.8% (ΔR2 = 0.028, p < 0.05) of the variance in this factor, with MC graduate-level training as its second strongest contributor (β = .164, p < .05). The amount of variance contributed by MC training is comparable to the (statistically non-significant) variance contributed by general years of experience (2.3%). Weighing in at a similar level, community setting accounts for 1.8% (ΔR2 = 0.018, p < 0.01) of the variance, and provides the third strongest contribution (β = .151, p < .05) to the model. As discussed earlier, rural settings, by virtue of their lower levels of racial/ethnic diversity, may in fact enhance the development of cross-cultural relationships, by affording school counsellors the opportunity to develop a richer understanding of, and deeper connections with, diverse students. In this regard, Factor 3 is unique among the six factors. Holcomb-McCoy and her team acknowledge, “… the ability to develop cross-cultural relationships might be more of a reflection of one’s personality and personal experiences rather than an academic or learned type of skill that is taught in a course” (p. 175). Clearly, the impact of MC training is balanced by teaching experience and community setting, variables that are specific to each counsellor. To sum up, regression analyses have uncovered three patterns of variance among the six factors and Total Scale.  MC training is the most common contributor to variance, followed by frequency of cross-cultural sessions (a measure of specific experience).  However, just as the  86 SCMES factors describe unique dimensions of MC self-efficacy, so too are they related to different combinations and strengths of predictors. Future research might focus on the structural commonalities that tie certain factors together and exclude others. The Total Score of the SCMES obscures some of these differences; it would therefore be advisable to measure and analyze each factor’s score separately when administering the SCMES.  Research Question 3 Years of experience as a general category, does not contribute significantly to variance in any of the SCMES factors.  It is not a sufficiently sensitive measure. However, when experience is described or measured in a more specific way, it does become a significant contributor to some factors.  It is important to remember that teaching experience and caseload diversity are both specific types of experience. One is measured in terms of teaching time, the other in terms of frequency of a specific type of contact. For this reason, in hierarchical regression analysis, years of teaching experience does contribute significantly to Factor 3, even though the more general category – years of experience -- does not contribute. Similarly, caseload diversity, as measured through frequency of cross-cultural counselling sessions, does contribute significantly to Factors 1, 4, 5, and the Total Scale. These results indicate that caseload diversity predicts a larger number of factors (and different factors) than does years of experience, in the form of teaching experience. However, these two variables appear to influence different factors in a mutually exclusive way. It is possible that Factor 3 measures a different phenomenon than the rest of the factors: something that may be influenced more by depth of diverse experience rather than range or frequency of diverse experience.  In addition, it is possible that the skills defined by Factor 3 are more universal, or less culture-specific, than the skills described by the other factors. For this reason,  87 teaching experience, regardless of students’ race/ethnicity, may allow counsellors to develop relationship-building skills that transfer into cross-cultural counselling sessions.  By contrast, the other factors (1, 4, 5 and Total Scale) are more influenced by the specificity of experience developed through frequent cross-cultural counselling sessions.  Importantly, these experiences do not affect Factor 3. Further, it should be noted that experience in any form is not a significant contributor to Factors 2 and 6. For these factors, no distinction is made between years of experience or diversity of caseload. Research Question 4 For Factor 3 (Developing Cross-Cultural Relationships) the completion of five to ten graduate-level or in-service courses is significantly and positively correlated to the relationship between years of teaching experience and self-efficacy.  This is to be expected, based on the regression analysis of Factor 3.  If training were to have any impact on the interaction of experience and self-efficacy, it would be most apparent in Factor 3, where teaching experience plays a unique role in the variance of self-efficacy.  Since this strong relationship, between teaching experience and self-efficacy, is not observed significantly elsewhere, we do not see the impact of training on it elsewhere, either.   These results support the notion that specific MC training actually frames experience and enhances its relationship with MC self-efficacy (Tadlock-Marlo, 2012).  Specificity characterizes these results: the type of training (MC graduate-level and MC in-service), the type of experience (teaching), and the type of self-efficacy (relationship-building) are all highly specific. However, this dynamic is only seen in Factor 3.  88 It should be noted, furthermore, that the number of training courses required to produce these effects is very high, and that these effects are not necessarily caused by the training. Another interpretation is possible.  For example, an unmeasured factor, such as interest in MC topics, may cause a counsellor to pursue above-average levels of training, and this interest may also make the counsellor more capable of developing cross-cultural relationships, particularly as he or she accrues teaching experience. So, while these results are intriguing, they are still correlational, and as such, they do not conclusively demonstrate that training per se enhances the relationship between teaching experience and self-efficacy.  By contrast, the relationship between counselling experience and self-efficacy is not significantly correlated to graduate MC training or in-service MC training.  Higher levels of these types of training do not produce stronger relationships between counselling experience and self-efficacy for any of the factors of the SCMES. In some ways, this is a surprising result; one might expect counsellor MC training to interact more with counselling experience. As mentioned earlier, the different effects of teaching experience and counselling experience may be the result of (1) length of experience, since most school counsellors have much more teaching experience than counselling experience, (2) the different types of skills used in the two relationships, and (3) the timing of MC training in the counsellor’s career. Most school counsellors are teachers first, and this experience may actually frame and enhance the relevance of MC courses taken later in their career. Thus, high levels of MC training are associated with a stronger relationship between teaching experience and school counsellor self-efficacy for Factor 3 only.   89 Limitations This study is subject to a number of limitations, which touch on both overall research and survey design, and on patterns of sampling and response. Perhaps the single greatest limitation of this study is its design: a self-report survey.  As such, none of the controls or manipulation used in experimental designs are employed here. For this reason, it is not possible to assign causation to any of the observations made in this study.  Relationships are correlational, and while it is tempting to assign directionality to these relationships, this would be misleading. In addition, data were collected through self-report, with no controls in place for measuring social desirability.  Self-report has already been identified as problematic for measuring MCC, but it has been described as acceptable for assessing MC self-efficacy (Holcomb-McCoy, Harris, Hines & Johnston, 2008; Worthington, Soth-McNett & Moreno, 2007).  Nevertheless, in this study, it is not possible to determine the extent to which social desirability contributes to the variance of the School Counseling Multicultural Self-Efficacy Scale (SCMES; Holcomb-McCoy et al., 2008), nor is it possible to measure the potential interaction effects of social desirability on any of the identified significant predictors (such as MC graduate-level training).  Social desirability is not the only limitation of the instruments used in this study. The SCMES itself has some built-in biases. First, it was designed for use in American research on American counsellors. As discussed earlier, this scale includes individual items that may not apply to all counsellors in British Columbia, and this in turn may influence the results for certain sub-scales, such as Factor 2 – Using Data and Understanding Systemic Change.  Secondly, the SCMES uses anchor phrases in its Likert-scale that may inflate its scores.  The seven-point scale has four anchor phrases that range from 1 = not well at all, and 3 = not too well, to 5 = pretty well, and 7 = very well.  It is possible that “very well” is not a sufficiently  90 extreme descriptor: it fails to distinguish between high self-efficacy and extremely high self-efficacy. As a result, participants may be over-estimating their self-efficacy, simply by adhering to the reference points of the scale itself.  Different concerns apply to the Demographic and Workplace Questionnaire. Although this instrument was designed for use in British Columbia, it is not possible to be sure that all participants interpreted its questions in the same way, and used the same criteria for responding. This is one of the limitations inherent in all survey research (Andres, 2012; Creswell, 2009). Two examples of this ambiguity were apparent in the feedback provided by participants. Multicultural training – graduate-level and in-service – was difficult to quantify. Some participants counted only individual courses, while others included any course or workshop that integrated some measure of multicultural counselling content.  Race/ethnicity was another significant stumbling block. Some participants were unsure how best to define the race/ethnicity of themselves and their students, and referred to the confounding issues of nationality, cultural integration and cultural salience. Thus, the results for the Demographic and Workplace Questionnaire must be interpreted with this ambiguity in mind.  In a similar vein, data may have been lost through biased sampling methods and response patterns. Counsellors were recruited through the 2014 BCSCA Conference and through systematic mail-outs. However, some counsellors could not be reached through these means. Among those counsellors who could be reached, 74 (or 25%) did not submit a completed survey package, or returned a package with more than five items left blank. In addition, those participants who did not report their race / ethnicity (1), or identified their race/ethnicity as “Canadian” (13) were excluded from the regression analyses. These counsellors may share common features, significant to the results of this study, but their data is simply not available.  91  Finally, despite efforts to capture a wide cross section of counsellors in British Columbia, this sample was not very culturally or geographically diverse.  Of 226 respondents, only 22 participants identified themselves as belonging to a racial or ethnic minority group, and only 30 participants reported working in a rural setting. It is therefore difficult to make general statements about the self-efficacy levels of all counsellors in British Columbia.  Implications for School Counsellor Training and Practice  Despite these limitations, the results of this study clearly demonstrate the value of multicultural training, both at the graduate and in-service levels. Multicultural training generally is a significant contributor to the variance of all six factors of the SCMES and to the Total Scale. While graduate-level training has the most widespread influence, in-service training is also significantly related to a number of factors.  These results reinforce the importance of multicultural training, both in counsellor preparation and in ongoing professional development.  A second important variable in multicultural counselling self-efficacy is experience working with diverse students.  Interestingly, in this study, specific experience takes two forms: years of teaching experience for Factor 3 (Developing Cross Cultural Relationships), and frequency of cross-cultural counselling sessions for Factors 1 (Knowledge of Multicultural Concepts), 4 (Multicultural Counselling Awareness), 5 (Multicultural Assessment) and the Total Scale. Given these results, it would be wise for school counsellor trainees and professionals alike to examine the racial / ethnic profile of their caseloads, and consciously expand their caseloads to include a greater range of clients.  Cultivating this type of experience will help school counsellors in British Columbia better serve all of the students in their care (Sue & Sue, 2013).   92 Suggestions for Future Research The present study is unique in two regards. It is the first of its kind to study MC self-efficacy among school counsellors in British Columbia. It is also the first study to use hierarchical regression analyses to identify specific patterns of predictors for each sub-scale and Total Scale of the SCMES. However, these regression analyses have accounted for only a small portion of the variance in the SCMES, ranging from 7.8% for Factor 6 (Developing Cross Cultural Relationships) to 13.5% for Factor 1 (Knowledge of Multicultural Concepts). Future research should aim to identify other variables, including social desirability, counsellor openness, counsellor extraversion, and pivotal life experiences (Guzmán, Calfa, Van Horn Kerne, & McCarthy, 2013), which may be stronger contributors of variance to multicultural self-efficacy among school counsellors.  The three patterns of contributors, identified thus far, provide a hint of the unity and complexity that underlie the six factors of the SCMES. Future research could examine these patterns more extensively, or study each factor individually and in greater detail.  Qualitative research could play an important role in providing such case-specific analyses, and may enrich the “aerial perspective” provided by the present quantitative study. This suggestion echoes the call of many previous researchers, who recommend a qualitative approach to this topic (D. Hays, 2008; Larson and Daniels, 1998; Worthington, Soth-McNett & Moreno, 2007). The present study highlights the value generally of multicultural training and frequent cross-cultural counselling sessions. Yet the content of this training and the format of these sessions remain unexamined.  Factor 3 (Developing Cross Cultural Relationships), with its emphasis on teaching experience and community setting, demonstrates that different facets of self-efficacy are associated with different predictors.  Future qualitative research could work to identify the most beneficial forms of multicultural training for school counsellors. Similarly, an in-depth study of  93 the timing, therapeutic style, and topics addressed during cross-cultural counselling sessions – career, academic, personal, social – may shed some light on the self-efficacy building process among school counsellors: a process which could be emulated by others, or even included in school counsellor training.  Multicultural training and specific experience are clearly correlated with multicultural counselling self-efficacy, but they may not be the causes of it. Indeed, Research Question #4 showed that only very high levels of training are associated with stronger relationships between teaching experience and self-efficacy (for Factor 3). Yet a large percentage of participants (roughly 25%) had no multicultural training courses of either graduate or in-service type.  Perhaps a broader, more all-encompassing variable, such as interest or life experience or curiosity, underlies the relationship between training, experience and self-efficacy.  Future research should expand beyond the all-too-familiar demographic and workplace variables, to examine the role of school counsellor-specific variables in enhancing multicultural counselling self-efficacy.       94 References American School Counselor Association (ASCA). (2010). Ethical standards for school counselors. Alexandria, VA: Author. 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I have completed the following number of graduate-level academic courses related to multiculturalism and/or diversity: __________  8. I have completed the following number of workshops and/or seminars related to multiculturalism and/or diversity: __________   Workplace Information:  9. The geographical region in which I currently work:  Central BC (eg. Prince George, Kamloops)  Fraser Valley (eg. Chilliwack, Mission)  Kootenay (eg. Arrow Lakes, Boundary)  Metro (eg. Vancouver, Richmond)  North (eg. Haida Gwaii, Peace River)  Okanagan (eg. Revelstoke, Vernon) ☐ Vancouver Island / Sunshine Coast (eg. Campbell River, Gulf Islands)  105  10. The type of school(s) in which I currently work (please check all that apply):  Public   District Number: _________  Private  Aboriginal or First Nations  Faith-Based (eg. Catholic or Muslim)  French Language (eg, Conseil Scolaire Francophone de la C-B – CSF)  Other (please specify): ______________  11. The community setting of the school(s) in which I currently work (please check all that apply):  Inner City  Urban  Suburban  Rural  Other (please specify): ______________  12. The grade level of the students with which I currently work as a counsellor (please check all that apply):  Elementary  Middle  High School (Grades 8 – 12)  Junior Secondary (Grades 8 – 10 only)  Senior Secondary (Grades 11 – 12 only)  13. Cultural diversity of the school(s) in which I work:  A multicultural population has individuals that vary by race, ethnicity, language, and/or religion.  Based on this definition of multicultural, I would classify the school(s) that I currently work in as (circle one):   ß   0 ---------- 1 ---------- 2 ---------- 3 ---------- 4 ---------- 5 ---------- 6 à  Not at all                    Somewhat      Extremely Multicultural        Multicultural            Multicultural  14. Please estimate the number of languages spoken in your school(s): ____   106  15. Cultural diversity of your caseload:  Please estimate, using approximate percentages, the proportion of students of each of the following races / ethnicities on your counselling caseload.  Please feel free to add any other groups that you work with, that have not been included. (Percentages should add up to 100%).  Race / Ethnicity % of Caseload Race / Ethnicity  % of Caseload 1. Aboriginal or First Nations  8. Metis   2. African or Caribbean  9. South Asian   3. Arabic  Additional:   4. Asian (not South Asian)  Additional:   5. Caucasian (English as first language)  Additional:  6. Caucasian (English as a second language)  Additional:  7. Latino / Latina  Additional:     16. Frequency of cross-cultural counselling sessions:  People that are culturally different may differ in terms of race, ethnicity, language, and/or religion.  Based on this definition of culturally different, I regularly counsel students that are culturally different from myself:   ß   0 ---------- 1 ---------- 2 ---------- 3 ---------- 4 ---------- 5 ---------- 6 à   Never    Sometimes    Always      107 17. Training:  The school or district provides professional development in-services that address the counselling of students that are culturally different.  ß   0 ---------- 1 ---------- 2 ---------- 3 ---------- 4 ---------- 5 ---------- 6 à   Never    Sometimes    Always   18. Consultation and Supervision:  When I require additional guidance / information in counselling students that are culturally different from myself, the school or district provides resources.  ß   0 ---------- 1 ---------- 2 ---------- 3 ---------- 4 ---------- 5 ---------- 6 à   Never    Sometimes    Always   19. Open-ended Question: When you require additional guidance in counselling students that are culturally different from yourself, where do you get additional support or information? Please write down your most reliable source(s) of help.             Thank-you!     108  School Counselling Multicultural Efficacy Scale (SCMES) Developed by Cheryl Holcomb-McCoy, Ph.D. John Hopkins University – School of Education  Directions: The following scale is designed to assess your ability to do the following tasks related to multicultural school counselling. Please rate how well you can do the things described below by circling the appropriate number.    1  2  3  4  5  6  7 Not well at all                    Not too well                    Pretty well                    Very well   Item Scale 1. I can challenge others’ racist and/or prejudiced beliefs and behaviours. 1    2    3    4    5    6    7 2. I can discuss the relationship between student resistance and racism. 1    2    3    4    5    6    7 3. I can assess my own racial/ethnic identity development in order to enhance my counselling. 1    2    3    4    5    6    7 4. I can discuss how interaction patterns (student-to-student, student-to-faculty) might influence ethnic minority students’ perceptions of the school community. 1    2    3    4    5    6    7 5. I can discuss how culture affects the help-seeking behaviours of students. 1    2    3    4    5    6    7 6. I can use data to advocate for students.  1    2    3    4    5    6    7 7. I can develop culturally sensitive interventions that promote post-secondary planning for minority students. 1    2    3    4    5    6    7 8. I can identify when a counselling approach is culturally inappropriate for a specific student. 1    2    3    4    5    6    7 9. I can develop a close, personal relationship with someone of another race. 1    2    3    4    5    6    7 10. I can verbally communicate my acceptance of culturally different students. 1    2    3    4    5    6    7 11. I can discuss how culture influences parents’ discipline and parenting practices. 1    2    3    4    5    6    7 12. I can evaluate assessment instruments for bias against culturally diverse students. 1    2    3    4    5    6    7 13. I can identify when my helping style is inappropriate for a culturally different student. 1    2    3    4    5    6    7 14. I can give examples of how stereotypical beliefs about culturally different persons impact the counselling process. 1    2    3    4    5    6    7    109 Item Scale 15. I can nonverbally communicate my acceptance of culturally different students. 1    2    3    4    5    6    7 16. I can analyze and present data that highlights inequities in course enrollment patterns and post-secondary decisions among student groups. 1    2    3    4    5    6    7 17. I can discuss the influence of self-efficacy on ethnic minority students’ achievement. 1    2    3    4    5    6    7 18. When counselling, I can address societal issues that affect the development of ethnic minority students. 1    2    3    4    5    6    7 19. I can work with community leaders and other community members to assist with student (and family) concerns. 1    2    3    4    5    6    7 20. I can use culturally appropriate counselling interventions. 1    2    3    4    5    6    7 21. I can discuss the influence of racism on the counselling process. 1    2    3    4    5    6    7 22. I can discuss how school-family-community partnerships are linked to student achievement. 1    2    3    4    5    6    7 23. I can assess how my speech and tone influence my relationship with culturally different students. 1    2    3    4    5    6    7 24. I can discuss how school-family-community partnerships influence minority student achievement. 1    2    3    4    5    6    7 25. I can identify when the race and/or culture of a student is a problem for a teacher. 1    2    3    4    5    6    7 26. I can recognize when my beliefs and values are interfering with providing the best services to my students. 1    2    3    4    5    6    7 27. I can identify when specific cultural beliefs influence students’ response to counselling. 1    2    3    4    5    6    7 28. I can identify whether or not the assessment process is culturally sensitive. 1    2    3    4    5    6    7 29. I can live comfortably with culturally diverse people.  1    2    3    4    5    6    7 30. I can explain test information to culturally diverse parents. 1    2    3    4    5    6    7 31. I can discuss how environmental factors, such as poverty, can influence the academic achievement of students. 1    2    3    4    5    6    7 32. I can help students determine whether a problem stems from racism or biases in others. 1    2    3    4    5    6    7 33. I can identify when my helping style is appropriate for a culturally different student. 1    2    3    4    5    6    7 34.  I can discuss what it means to take an “activist” approach to counselling. 1    2    3    4    5    6    7 35. I can develop friendships with people from other ethnic groups. 1    2    3    4    5    6    7    110 Item Scale 36. I can challenge my colleagues when they discriminate against students. 1    2    3    4    5    6    7 37. When implementing small-group counselling, I can challenge students’ biased and prejudiced beliefs. 1    2    3    4    5    6    7 38. I can develop interventions that are focused on “systemic change” rather than “individual student change.” 1    2    3    4    5    6    7 39. I can identify racist and/or biased practices in schools.  1    2    3    4    5    6    7 40. I can integrate family and religious issues in the career counselling process. 1    2    3    4    5    6    7 41. I can identify when my own biases negatively influence my services to students. 1    2    3    4    5    6    7 42. I can identify when my helping style is inappropriate for a culturally different parent or guardian. 1    2    3    4    5    6    7 43. I can define and discuss racism.  1    2    3    4    5    6    7 44. I can advocate for fair testing, and the appropriate use of testing of children from diverse backgrounds. 1    2    3    4    5    6    7 45. I can discuss how assessment can lead to inequitable opportunities for students. 1    2    3    4    5    6    7 46. I can identify when a teacher’s cultural background is affecting his/her perceptions of students. 1    2    3    4    5    6    7 47. I can identify unfair policies that discriminate against students of culturally different backgrounds. 1    2    3    4    5    6    7 48. I can adjust my helping style when it is inappropriate for a culturally different student. 1    2    3    4    5    6    7 49. I can utilize career assessment instruments that are sensitive to students’ cultural differences. 1    2    3    4    5    6    7 50. I can develop positive relationships with parents who are culturally different. 1    2    3    4    5    6    7 51. I can identify when to use data as an advocacy tool.  1    2    3    4    5    6    7 52. I can use culturally appropriate instruments when I assess students. 1    2    3    4    5    6    7   Thank-you for your participation!   The space below is set aside for your comments:     111 Appendix B  Preliminary Results of Demographic Hypotheses  1. Hypothesis 1 – Age  Table A-1:  Age: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226 -.038  .573 .001 2 226 -.071  .290 .005 3 226 .010  .876 .000 4 226 -.056  .401 .003 5 226 -.046  .488 .002 6 226 -.001  .994 .000 Total Scale 226 -.045  .498 .002 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001  2. Hypothesis 2 – Gender  Table A-2:  Gender: Means, Standard Deviations and t-Tests with SCMES Factors  Item Males (N = 47) Females (N = 179) t p  Mean SD Mean SD   1 5.11 .683 5.07 .848 .317 .751 2 4.31 .865 4.22 .967 .606 .545 3 6.23 .547 6.11 .661 1.20 .232 4 5.22 .555 5.20 .769 .181 .856 5 4.77 .892 4.77 .971 -.005 .996 6 5.50 .626 5.41 .772 .764 .445 Total Scale 5.19 .560 5.13 .691 .580 .562 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: difference between means is significant at: *p < .05, **p < .01, ***p < .001        112 3. Hypothesis 3 – Race / Ethnicity  Table A-3:  Race / Ethnicity: Means, Standard Deviations and t-Tests with SCMES Factors  Item Non-Caucasians (N = 22) Caucasians (N = 190) t p  Mean SD Mean SD   1 5.25 .928 5.06 .810 -1.017 .310 2 4.38 1.104 4.21 .943 -.759 .449 3 6.09 .676 6.15 .632 .411 .682 4 5.31 .651 5.18 .751 -.726 .469 5 4.94 .937 4.74 .958 -.934 .352 6 5.40 .793 5.41 .742 .050 .960 Total Scale 5.23 .731 5.13 .668 -.671 .503 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: difference between means is significant at: *p < .05, **p < .01, ***p < .001   4. Hypothesis 4 – Specific Graduate-level Training in Counselling  Table A-4:  Counsellor Training: Means, Standard Deviations and t-Tests with SCMES Factors  Item Graduate-level Counsellor Training (N = 185) Other Training  (N = 41) t p  Mean SD Mean SD   1 5.08 .805 5.03 .871 -.373 .709 2 4.22 .941 4.32 .975  .636 .525 3 6.15 .619 6.07 .732 -.748 .455 4 5.21 .700 5.16 .856 -.430 .667 5 4.76 .942 4.82 1.015 .330 .742 6 5.44 .713 5.34 .872 -.746 .459 Total Scale 5.14 .646 5.12 .757 -.197 .844 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: difference between means is significant at: *p < .05, **p < .01, ***p < .001         113 5. Hypothesis 5 – Teaching Experience  Table A-5:  Teaching Experience: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226  .023  .773 .000 2 226 -.007  .921 .000 3 226 .079  .238 .006 4 226 -.021  .751 .000 5 226 -.037  .577 .001 6 226  .048  .474 .002 Total Scale 226  .011  .867 .000 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001   6. Hypothesis 6 – Counselling Experience  Table A-6:  Counselling Experience: Correlations, Significance and Variance with SCMES Factors  SCMES Factors  N r  p r2 1 226  .005  .942 .000 2 226 -.016  .816 .000 3 226 -.008  .909 .000 4 226  .028  .677 .001 5 226 -.060  .367 .004 6 226  .057  .396 .003 Total Scale 226 -.004  .958 .000 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001        114 7. Hypothesis 7 – Graduate-level Multicultural Training  Table A-7: Graduate MC Training: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226    .251***    .0001 .063 2 226    .248***    .0002 .062 3 226 .140*  .036 .020 4 226   .203**  .002 .041 5 226   .195**  .003 .038 6 226 .156*  .019 .024 Total Scale 226    .246***    .0002 .061 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001   8. Hypothesis 8 – In-Service Multicultural Training  Table A-8: In-Service MC Training: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226     .217**  .001 .047 2 226     .191**  .004 .036 3 226  .045  .503 .002 4 226 .111  .097 .012 5 226   .139*  .036 .019 6 226   .146*  .028 .021 Total Scale 226     .178**  .007 .032 Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001     115 Appendix C  Preliminary Results of Workplace Hypotheses  9. Hypothesis 9 – Community Setting  Table B-9:  Community Setting: Means, Standard Deviations and t-Tests with SCMES Factors  Item Rural (N = 30) Suburban, Urban or Mixed (N = 196) t p  Mean SD Mean SD   1 5.33 .862 5.03 .803 -1.863 .064 2 4.50 .943 4.20 .942 -1.647 .101 3 6.35 .521 6.10 .651   -1.981* .049 4 5.13 .796 5.21 .720 .557 .578 5 4.91 1.04 4.75 .940 -.863 .389 6 5.62 .778 5.39 .735 -1.592 .113 Total Scale 5.31 .686 5.11 .660 -1.492 .137 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: difference between means is significant at: *p < .05, **p < .01, ***p < .001   10. Hypothesis 10 – Provision of Professional Development Training  Table B-10:  Provision of Training: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226    .156*  .019 .024 2 226  .099  .136 .010 3 226  .104  .118 .011 4 226  .046  .491 .002 5 226  .104  .120 .011 6 226 -.018  .793 .000 Total Scale 226  .102  .127 .010 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001     116 11. Hypothesis 11 – Provision of Supervision and Consultation  Table B-11:  Provision of Supervision: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226  .078  .224 .006 2 226  .065  .329 .004 3 226  .009  .891 .000 4 226 -.024  .717 .001 5 226  .051  .450 .003 6 226 -.055  .412 .003 Total Scale 226  .030  .658 .001 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001                117 Appendix D  Preliminary Results of School and Caseload Diversity Hypotheses  12. Hypothesis 12 – School Cultural Diversity  Table D-12a:  School Cultural Diversity: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226 .033  .619 .001 2 226 .057  .397 .003 3 226 .071  .289 .005 4 226 .067  .319 .004 5 226 .115  .085 .013 6 226 -.032  .630 .001 Total Scale 226 .066  .326 .004 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001   Table D-12b:  Number of Languages Spoken in School: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226  .069  .301 .005 2 226 -.004  .954 .000 3 226  .057  .391 .003 4 226  .027  .685 .001 5 226  .039  .563 .002 6 226 -.013  .849 .000 Total Scale 226  .034  .611 .001 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001       118 13. Hypothesis 13 – Caseload Cultural Diversity  Table D-13a:  Number of Cultural Groups on Caseload: Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226 .015  .823 .000 2 226 .046  .493 .002 3 226 .053  .429 .003 4 226 .018  .785 .000 5 226 .042  .533 .002 6 226 -.011  .871 .000 Total Scale 226 .033  .619 .001 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001   Table D-13b:  Single Non-Caucasian Majority (75% or Higher): Means, Standard Deviations and t-Tests with SCMES Factors  Item Single Non-Caucasian Majority (N = 17) All Other Caseloads  (N = 202) t p  Mean SD Mean SD   1 5.29 .619 5.07 .812 -1.074 .284 2 4.45 1.055 4.23 .936 -.905 .366 3 5.98 .651 6.16 .615 1.140 .246 4 5.44 .449 5.19 .726 -2.078* .049 5 4.97 .746 4.75 .967 -.947 .345 6 5.49 .751 5.43 .735 -.289 .773 Total Scale 5.27 .590 5.14 .657 -.797 .426 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: difference between means is significant at: *p < .05, **p < .01, ***p < .001 Note: equality of variance is not assumed for Factor 4 (Levene’s p = .031)        119 14. Hypothesis 14 – Frequency of Cross-Cultural Counselling Sessions  Table D-14: Frequency of Cross Cultural Counselling Sessions and Correlations, Significance and Variance with SCMES Factors  SCMES Factors N r  p r2 1 226   .157*  .018 .025 2 226 .043  .523 .002 3 226 .055  .408 .003 4 226   .170*  .010 .029 5 226   .158*  .017 .025 6 226           .074  .268 .005 Total Scale 226   .134*  .044 .018 Note: Factor 1 = Knowledge of Multicultural Concepts; Factor 2 = Using Data and Understanding Systemic Change; Factor 3 = Developing Cross Cultural Relationships; Factor 4 = Multicultural Counselling Awareness; Factor 5 = Multicultural Assessment; Factor 6 = Application of Racial and Cultural Knowledge to Practice. Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001                120 Appendix E  Inter-correlations among Predictor Variables and Criterion Variables Used in Hierarchical Multiple Regression Analysis   Var.  1 2 3 4 5 6 7 8 1. --        2. -.145* --       3.  .060 -.111 --      4. -.043  .079 -.088 --     5. -.026  .714*** -.142* -.049 --    6. -.123  .578*** -.078  .096  .463*** --   7.  .038 -.015  .066  .075 -.049 -.060 --  8.  .141*  .167*  .090 -.023  .149* .170* .400*** -- 9.  .008  .009 -.041 -.120  .017 -.045 .077 .133* 10.  .064 -.119  .109 -.021 -.067 -.149* .042 .087 11. -.021 -.038  .070 .025  .023  .005 .215*** .217** 12. -.040 -.071  .052 -.042 -.007 -.016 .248*** .191** 13. -.080  .010 -.028 .050  .079 -.008 .140* .045 14. -.012 -.056  .050 .029 -.021  .028 .203** .111 15.  .000 -.046  .064 -.022 -.037 -.060 .195** .139* 16. -.051 -.001 -.003 .057  .048  .057 .156* .146* 17. -.039 -.045  .046 .013  .013 -.004 .246** .178** Note: 1 = Age; 2 = Gender; 3 = Race / Ethnicity; 4 = Masters in Counselling;  5 = Teaching Experience; 6 = Counselling Experience; 7 = Graduate-level Multicultural  Training; 8 = In-Service Multicultural Training; 9 = Community Setting; 10 = Frequency  of Cross-Cultural Sessions; 11 = Factor 1; 12 = Factor 2; 13 = Factor 3; 14 = Factor 4;  15 = Factor 5; 16 = Factor 6; 17 = SCMES Total Scale Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity,  Caucasian = 1, non-Caucasian = 2; Masters in Counselling, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001         121 Inter-correlations among Predictor Variables and Criterion Variables Used in Hierarchical Multiple Regression Analysis (Continued)   Var.  9 10 11 12 13 14 15 16 17 1.          2.          3.          4.          5.          6.          7.          8.          9. --         10. -.165* --        11.  .124 .157* --       12.  .109 .043 .672*** --      13.  .131* .055 .596*** .425*** --     14. -.037 .170* .735*** .576*** .610*** --    15.  .058 .158* .613*** .762*** .515*** .657*** --   16.  .106 .074 .616*** .525*** .577*** .686*** .588*** --  17.  .099 .134* .857*** .829*** .727*** .854*** .858*** .797*** -- Note: 1 = Age; 2 = Gender; 3 = Race / Ethnicity; 4 = Masters in Counselling;  5 = Teaching Experience; 6 = Counselling Experience; 7 = Graduate-level Multicultural Training; 8 = In-Service Multicultural Training; 9 = Community Setting; 10 = Frequency  of Cross-Cultural Sessions; 11 = Factor 1; 12 = Factor 2; 13 = Factor 3; 14 = Factor 4; 15 = Factor 5; 16 = Factor 6; 17 = SCMES Total Scale Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity,  Caucasian = 1, non-Caucasian = 2; Masters in Counselling, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: correlation between variables is significant at: *p < .05, **p < .01, ***p < .001          122  Appendix F  Hierarchical Multiple Regression Tables  for Factors 1 through 6 and the Total Scale   Factor 1 – Knowledge of Multicultural Concepts  – Hierarchical Multiple Regression          Step 1     Step 2    Step 3       Step 4       Step 5     β SE β SE β SE  β SE β SE   Step 1: Demographic Vars. Gender   -.007 .142 -.020 .143 -.051 .139 -.051 .139 -.052 .137   Age   -.042 .006 -.124 .009 -.154 .009 -.159 .009 -.147 .009  Race or Ethnicity    .073 .188 .082 .189  .052 .183 .057 .183 .044 .182  Counselling Grad Deg.  .077 .151 .091 .154 .083 .149 .089 .149 .093 .147    Step 2: Experience Variables Teaching Experience   .125 .009 .126 .009 .126 .009 .117 .009   Counselling Experience   -.016 .009 -.027 .009 -.018 .009 .004 .009    Step 3: Education Variables Graduate MCC Training     .198** .036 .196** .036 .199** .035   In-Service MCC Training     .155* .017 .145 .017 .124 .017    Step 4: Workplace Variables Community Setting       .075 .164  .104 .165    Step 5: Caseload Variables Frequency of Cross          .165* .037   Cultural Sessions  Model Summary       Model F   .626  .674  2.951**  2.760**  3.132*** df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  4.987  5.135  5.257  4.931  4.444 R2   .012  .019  .104  .110  .135 ΔR2     .007  .085  .005  .025   Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2; Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001          123 Factor 2 – Using Data and Understanding Systemic Change  – Hierarchical Multiple Regression         Step 1      Step 2       Step 3       Step 4       Step 5     β SE β SE β SE  β SE β SE  Step 1: Demographic Vars. Gender   -.039 .165 -.049 .167 -.080 .163 -.080 .163 -.080 .163  Age   -.081 .007 -.164 .011 -.194 .010 -.200 .010 -.196 .010 Race or Ethnicity  .046 .219  .054 .221  .024 .214   .029 .214  .025 .215 Counselling Grad. Deg. -.001 .176  .009 .180  .001 .174   .006 .174  .007 .174  Step 2: Experience Variables Teaching Experience    .104 .011  .105 .010  .106 .010  .103 .010 Counselling Experience   .015 .011  .005 .010  .014 .010  .021 .010  Step 3: Education Variables Graduate MCC Training      .204** .042  .201** .042  .202** .041 In-Service MCC Training      .149 .020  .138 .020  .132 .019  Step 4: Workplace Variables Community Setting        .076 .192  .085 .196  Step 5: Caseload Variables Frequency of Cross           .048 .044 Cultural Sessions  Model Summary       Model F   .520  .531  2.830**  2.660**  2.437** df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  4.601  4.745  4.868  4.605  4.427 R2   .010  .015  .100  .106  .108 ΔR2     .005  .085  .006  .002  Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001                  124 Factor 3 – Developing Cross Cultural Relationships  – Hierarchical Multiple Regression        Step 1       Step 2       Step 3       Step 4       Step 5     β SE β SE β SE  β SE β SE  Step 1: Demographic Vars. Gender   -.072 .109 -.091 .110 -.098 .110 -.099 .109 -.099 .109  Age   -.018 .004 -.107 .007 -.118 .007 -.127 .007 -.121 .007 Race or Ethnicity  -.021 .145 -.007 .145 -.018 .144 -.009 .144 -.016 .144 Counselling Grad. Deg.  .056 .117  .085 .118  .073 .117   .083 .117   .085 .117  Step 2: Experience Variables Teaching Experience    .198 .007  .204 .007   .205* .007  .201* .007 Counselling Experience   -.096 .007 -.088 .007  -.071 .007 -.060 .007  Step 3: Education Variables Graduate MCC Training     .168  .028  .163*  .028  .164*  .028 In-Service MCC Training      .005 .013 -.014 .013 -.024 .013  Step 4: Workplace Variables Community Setting       .136* .129  .151* .131          Step 5: Caseload Variables Frequency of Cross           .079 .030 Cultural Sessions  Model Summary       Model F   .497  1.154  1.652  1.923  1.862 df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  6.268  6.308  6.318  6.008  5.814 R2   .010  .033  .061  .079  .085 ΔR2     .023  .028  .018  .006  Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001                  125 Factor 4 – Multicultural Counselling Awareness  – Hierarchical Multiple Regression         Step 1       Step 2     Step 3     Step 4      Step 5     β SE β SE β SE  β SE β SE  Step 1: Demographic Vars. Gender   -.007 .127 -.012 .129 -.027 .128 -.026 .129 -.027 .126  Age   -.069 .005 -.137 .008 -.156 .008 -.151 .009 -.137 .008 Race or Ethnicity    .050 .169  .054 .171  .036 .168   .031 .172   .017 .167 Counselling Grad. Deg.  .080 .136  .080 .139  .068 .137   .063 .140   .068 .135  Step 2: Experience Variables Teaching Experience    .046 .008  .051 .008   .051 .008   .041 .008 Counselling Experience    .063 .008  .066 .008   .057 .008   .080 .008  Step 3: Education Variables Graduate MCC Training      .197** .033  .199**  .034  .202** .032 In-Service MCC Training      .049 .015  .059 .016  .037 .015  Step 4: Workplace Variables Community Setting       -.071 .151 -.040 .152  Step 5: Caseload Variables Frequency of Cross           .171* .034 Cultural Sessions  Model Summary       Model F   .661  .573  1.746  1.668  2.145* df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  5.037  5.161  5.199  5.386  4.898 R2   .013  .017  .064  .069  .096 ΔR2     .004  .048  .005  .027   Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001                  126 Factor 5 – Multicultural Assessment  – Hierarchical Multiple Regression        Step 1      Step 2      Step 3       Step 4       Step 5     β SE β SE β SE  β SE β SE  Step 1: Demographic Vars. Gender   -.007 .165 -.007 .167 -.030 .166 -.030 .166 -.031 .164  Age   -.046 .007 -.021 .011 -.043 .010 -.045 .010 -.033 .010 Race or Ethnicity    .061 .219  .061 .221  .039 .218   .041 .222   .028 .217 Counselling Grad. Deg.  .015 .176  .021 .180  .014 .177   .015 .182   .020 .176  Step 2: Experience Variables Teaching Experience    .008 .011  .010 .010   .010 .010  .001 .010 Counselling Experience   -.056 .011 -.062 .011  -.059 .011  -.038 .011  Step 3: Education Variables Graduate MCC Training      .165* .043  .164*  .044  .167* .042 In-Service MCC Training      .105 .020  .101 .020  .081 .020  Step 4: Workplace Variables Community Setting        .027 .196  .055 .197  Step 5: Caseload Variables Frequency of Cross           .159* .044 Cultural Sessions  Model Summary       Model F   .329  .289  1.587  1.421  1.824 df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  4.717  4.630  4.718  4.627  4.040 R2   .006  .008  .059  .060  .083 ΔR2     .002  .050  .001  .024  Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001                  127 Factor 6 – Application of Racial and Cultural Knowledge to Practice  – Hierarchical Multiple Regression        Step 1       Step 2      Step 3       Step 4       Step 5     β SE β SE β SE  β SE β SE  Step 1: Demographic Vars. Gender   -.043 .128 -.054 .130 -.079 .129 -.079 .129 -.079 .129  Age   -.025 .005 -.137 .008 -.160 .008 -.165 .008 -.158 .008 Race or Ethnicity    .005 .170  .014 .171 -.008 .169 -.003 .170 -.010 .177 Counselling Grad. Deg.  .101 .137  .107 .139  .103 .138 .109 .138   .111 .138  Step 2: Experience Variables Teaching Experience    .111 .008  .110 .008   .111 .008   .105 .008 Counselling Experience    .058 .008  .047 .008   .056 .008   .068 .008  Step 3: Education Variables Graduate MCC Training      .129 .033  .126  .033  .128 .033 In-Service MCC Training      .125 .015  .115 .016  .103 .016  Step 4: Workplace Variables Community Setting        .075 .152  .092 .154  Step 5: Caseload Variables Frequency of Cross           .093 .035 Cultural Sessions  Model Summary       Model F   .655  .735  1.748  1.686  1.697 df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  5.264  5.439  5.518  5.317  5.051 R2   .012  .021  .064  .070  .078 ΔR2     .009  .043  .005  .008  Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001                  128 SCMES Total Scale  – Hierarchical Multiple Regression       Step 1       Step 2       Step 3       Step 4       Step 5     β SE β SE β SE  β SE β SE  Step 1: Demographic Vars. Gender   -.033 .116 -.044 .117 -.072 .114 -.072 .115 -.073 .114  Age   -.059 .005 -.138 .007 -.166 .007 -.170 .007 -.159 .007 Race or Ethnicity    .047 .154  .055 .155  .028 .150   .032 .151   .021 .150 Counselling Grad. Deg.  .061 .124  .073 .126  .063 .122   .067 .123   .071 .122  Step 2: Experience Variables Teaching Experience    .112 .007  .115 .007   .116 .007   .107 .007 Counselling Experience   -.006 .007 -.013 .007  -.005 .007   .014 .007  Step 3: Education Variables Graduate MCC Training      .215** .029  .212** .029  .215** .029 In-Service MCC Training      .125 .014  .116 .014  .098 .014  Step 4: Workplace Variables Community Setting        .062 .135  .088 .136  Step 5: Caseload Variables Frequency of Cross           .144* .031 Cultural Sessions  Model Summary       Model F   .503  .540  2.699**  2.490*  2.718** df   4, 207  6, 205  8, 203  9, 202  10, 201 Intercept  5.112  5.195  5.269  5.119  4.745 R2   .010  .016  .096  .100  .119 ΔR2     .006  .081  .004  .018  Note: dichotomous variables are coded as Gender, male = 1, female = 2; Race / Ethnicity, Caucasian = 1, non-Caucasian = 2; Counselling Graduate Degree, no = 1, yes = 2;  Community Setting, urban, suburban and mixed = 1; rural = 2 Note: Beta weights are significant at: *p < .05, **p < .01, ***p < .001 

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