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Patterns of research utilization on patient care units Estabrooks, Carole A; Scott, Shannon; Squires, Janet E; Stevens, Bonnie; O'Brien-Pallas, Linda; Watt-Watson, Judy; Profetto-McGrath, Joanne; McGilton, Kathy; Golden-Biddle, Karen; Lander, Janice; Donner, Gail; Boschma, Geertje; Humphrey, Charles K; Williams, Jack Jun 2, 2008

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ralssBioMed CentImplementation ScienceOpen AcceResearch articlePatterns of research utilization on patient care unitsCarole A Estabrooks*1, Shannon Scott1, Janet E Squires1, Bonnie Stevens2, Linda O'Brien-Pallas3, Judy Watt-Watson3, Joanne Profetto-McGrath1, Kathy McGilton4, Karen Golden-Biddle5, Janice Lander1, Gail Donner3, Geertje Boschma6, Charles K Humphrey7 and Jack Williams8Address: 1Faculty of Nursing, University of Alberta, Edmonton, Canada, 2Faculty of Nursing, University of Toronto and Hospital for Sick Children, Toronto, Canada, 3Faculty of Nursing, University of Toronto, Toronto, Canada, 4Toronto Rehabilitation Institute, Toronto, Canada, 5School of Management, Boston University, Boston, USA, 6Faculty of Nursing, University of British Columbia, Vancouver, Canada, 7Data Library, University of Alberta, Edmonton, Canada and 8Institute of Clinical Evaluative Sciences & Clinical Epidemiology and Health Services Research Program, Sunnybrook Health Sciences Centre, Toronto, CanadaEmail: Carole A Estabrooks* - carole.estabrooks@ualberta.ca; Shannon Scott - shannon.scott@ualberta.ca; Janet E Squires - janet.squires@ualberta.ca; Bonnie Stevens - b.stevens@utoronto.ca; Linda O'Brien-Pallas - l.obrien.pallas@utoronto.ca; Judy Watt-Watson - j.watt.watson@utoronto.ca; Joanne Profetto-McGrath - joanne.profetto-mcgrath@ualberta.ca; Kathy McGilton - McGilton.Kathy@TorontoRehab.on.ca; Karen Golden-Biddle - kgbiddle@bu.edu; Janice Lander - janice.lander@ualberta.ca; Gail Donner - g.donner@utoronto.ca; Geertje Boschma - boschma@nursing.ubc.ca; Charles K Humphrey - humphrey@datalib.library.ualberta.ca; Jack Williams - ji.williams@sympatico.ca* Corresponding author    AbstractBackground: Organizational context plays a central role in shaping the use of research byhealthcare professionals. The largest group of professionals employed in healthcare organizationsis nurses, putting them in a position to influence patient and system outcomes significantly.However, investigators have often limited their study on the determinants of research use toindividual factors over organizational or contextual factors.Methods: The purpose of this study was to examine the determinants of research use amongnurses working in acute care hospitals, with an emphasis on identifying contextual determinants ofresearch use. A comparative ethnographic case study design was used to examine seven patientcare units (two adult and five pediatric units) in four hospitals in two Canadian provinces (Ontarioand Alberta). Data were collected over a six-month period by means of quantitative and qualitativeapproaches using an array of instruments and extensive fieldwork. The patient care unit was theunit of analysis. Drawing on the quantitative data and using correspondence analysis, relationshipsbetween various factors were mapped using the coefficient of variation.Results: Units with the highest mean research utilization scores clustered together on factors suchas nurse critical thinking dispositions, unit culture (as measured by work creativity, work efficiency,questioning behavior, co-worker support, and the importance nurses place on access to continuingeducation), environmental complexity (as measured by changing patient acuity and re-sequencingof work), and nurses' attitudes towards research. Units with moderate research utilizationPublished: 2 June 2008Implementation Science 2008, 3:31 doi:10.1186/1748-5908-3-31Received: 11 August 2007Accepted: 2 June 2008This article is available from: http://www.implementationscience.com/content/3/1/31© 2008 Estabrooks et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 16(page number not for citation purposes)clustered on organizational support, belief suspension, and intent to use research. Higher nursingImplementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31workloads and lack of people support clustered more closely to units with the lowest researchutilization scores.Conclusion: Modifiable characteristics of organizational context at the patient care unit levelinfluences research utilization by nurses. These findings have implications for patient care unitstructures and offer beginning direction for the development of interventions to enhance researchuse by nurses.BackgroundInvestigators have described the difficulties and complex-ities of implementing change in practice [1], and increas-ingly we see calls for the design of more theory-informedinterventions [2-4]. While calls to make nursing practicemore research-based are common, research utilizationinvestigators in nursing have argued that the use ofresearch evidence is often not reflected in the delivery ofnursing care despite the benefits of adopting research-based practices, and the increased availability of researchto health professionals [5-7]. As a result, patients often donot receive optimal or effective nursing care. In responseto this, we have seen accelerated efforts to develop inter-ventions to increase the use of research in practice. How-ever, relatively few reports exist about intervention studiesin the area of research utilization for nurses, and thoseavailable have often not yielded positive results [8,9].(One reason for this, we argue, is a failure to systemati-cally account for the factors that influence nurses' use ofresearch, or stated another way, to systematically accountfor the determinants of research utilization behaviourwithin the work context (i.e., organizational setting) ofnurses.Various individual, organizational, and most recently,contextual, factors have been argued as influencing theuse of research by healthcare providers. Traditionally, thefactors studied in nursing have tended to be determinantsof research use that could be characterized as individual –such as age [10,11], attitude [11-13], clinical area [12,14],education [14-17], prior knowledge [15], employmentstatus [10,16,17], experience [11,14,15], journals read[18,19], and recently, critical thinking dispositions [20].In a systematic review of the literature on the individualdeterminants of research utilization by nurses, Estabrooksand colleagues identified a positive attitude towardresearch as both the most frequently studied individualdeterminant and the only one with a consistently positiveeffect [21]. Findings for all other individual determinantsin that review were equivocal.Less attention has been paid to the role of organizationsand context in promoting research use [21-23]. Histori-cally, a number of organizational factors thought to influ-innovation adoption include: organizational complexity[24], centralization [25], size [25,26], presence of aresearch champion [27,28], traditionalism [29,30],organizational slack [31], access to and amount ofresources [19,29,32,33], constraints on time [34-36] andstaffing [15,36], professional autonomy [35,37,38], geo-graphic location (i.e., urban versus rural) [39], and organ-izational support [11,12,35,40,41].Over the past decade, nurse investigators in the UnitedKingdom (UK) have called for more attention to contex-tual factors in promoting research use by healthcare pro-viders [42-44]. They define context as 'the environment orsetting in which the proposed change is to be imple-mented' and understand it to be comprised of three coredimensions: culture, leadership, and evaluation [42].McCormack et al., in a concept analysis of context in rela-tion to research implementation, define culture as thedefining prevailing beliefs and values, consistency in val-ues, and receptivity to change, among members of anorganization or group [45]. Organizational culture, atleast theoretically, affects clinician behaviors such as theadoption of research findings in practice. While positiveeffects of culture on research utilization have been sug-gested by several scholars in the field [42,46-49], to date,we have relatively little empirical evidence to supportthese assertions.Leadership refers to the 'nature of human relationships'with effective leadership being proposed to give rise toclear roles, effective teamwork and effective organiza-tional structures, as well as staff involvement in decision-making and approach to learning [45]. The effect of lead-ership has received much attention. Previous research hasshown that leadership is instrumental for cultural changeand has a strong effect on overall organizational perform-ance [45,50,51]. There is also evidence that leadership iscritical to nurses' decision-making processes [15,52]. andto creating a culture for evidence-based practice [6]. Addi-tionally, research conducted in magnet hospitals in theUnited States (US) indicate that nurse leaders play a criti-cal role in developing environments (i.e., contextual set-tings) that support nursing excellence and improvedPage 2 of 16(page number not for citation purposes)ence innovation adoption in industry and health serviceshave been studied. Those shown to have an influence onpatient outcomes [53-55].Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31Evaluation, the third proposed core dimension of context,refers to feedback mechanisms (individual and systemlevel), sources, and methods for evaluation [45]. Auditcoupled with a feedback mechanism, where data is fedback to a unit's providers in the form of some kind ofreport, is one of the most commonly applied evaluationmechanisms used in healthcare to implement the adop-tion of research-based practices, and has been shown tohave modest effects with physicians [56]. While its effecton nurses has been relatively untested, in one trial inves-tigators reported that audit and feedback together witheducational outreach and printed materials results inmoderate improvements in nursing care [57], lendingsupport to the importance of evaluation as a contextualpredictor.Additional support for investigating the role of context inresearch utilization comes from studies correlating spe-cific contextual factors with research utilization behaviorsof nurses. A number of investigators have correlated theimpact of organizational structures, roles, and policiesdesigned to promote research use with the actual use ofspecific research-based practices by nurses [13,14,26,58-60]. Studies examining the impact of context on researchimplementation in both the nursing [e.g., [52,61,62]] andorganizational behaviour literature [e.g., [63]] also sup-port the importance of contextual factors to research utili-zation, while stressing the interactivity among differentcontextual factors.Despite growing support for the importance of organiza-tional context to research utilization, little is known aboutwhich contextual factors are important for research utili-zation by nurses and how these factors operate. This lackof certainty was evident in the findings from a Cochranesystematic review [64] on organizational infrastructuresfor promoting research-based nursing interventions. Theauthors were not able to identify any studies meetingCochrane standards.A more recent review [65] that was not restricted to rand-omized control trials also assessed contextual factors andresearch utilization in nursing staff. These investigatorsreported that contextual factors (e.g., role, access toresearch, a favorable organizational climate towardsresearch use, material support to attend conferences, timeto read research, and organizational educational activitiessuch as mini-courses) had statistically significant butinconsistent associations with research use. These findingssuggest that while the contexts in which nurses work maybe important to research use, further study in this area isneeded.display. However, magnet hospital research in the USdoes give us some idea of what such an ideal unit wouldlook like from staff retention and quality patient care per-spectives. Consistently reported contextual and individualnurse characteristics of magnet hospitals include effectiveleadership (i.e., leaders who are visionary, enthusiastic,supportive, value education and professional develop-ment, maintain open lines of communication with staffnurses), the ability of staff nurses to establish and main-tain therapeutic nurse-patient relationships, nurse auton-omy and control, and collaborative nurse-physicianrelationships at the unit level [54,66,67]. The 'ideal nurs-ing unit' for research utilization may exhibit similar indi-vidual and contextual characteristics, although this is yetto be empirically tested.In summary, while an understanding of research utiliza-tion in nursing is growing, there are gaps in what is knownabout the factors that predict nurses' use of research.Knowledge of those factors would inform the develop-ment of interventions to increase the use of research in theservice of improved patient care. Individual determinantsof research use have been studied most frequently butfindings are equivocal, making it difficult to plan inter-ventions to facilitate research use, even at the individuallevel. Organizational determinants have been studied inindustries beyond health; relatively few studies have beenconducted in hospital settings or with nurses. Further,within healthcare organizations, nursing work is com-monly organized at the patient care unit level, indicatinga need to understand contextual factors at sub-levels (i.e.,patient care units) within the organization. Few reportsexamine work at the patient care unit level. Before inter-ventions to increase research use among nurses workingin hospitals can be optimally designed, investigators needto identify and understand factors at both the hospitaland the unit-levels [68]. In the study reported here, wefocused at the patient care unit level.PurposeThe purpose of this study was to identify and examineindividual and contextual factors at the unit level thatinfluence research utilization among nurses working inacute care hospitals, and to identify any differencesbetween adult and pediatric units. The specific purpose ofthe analyses reported in this paper was to conceptuallymodel an ideal patient care unit, i.e., a patient care unitdisplaying features optimal for research use. We used adescriptive approach to develop an organizational arche-type to examine determinants of research utilization at thepatient care unit level. Using this approach, a frameworkfor unit level research utilization was constructed basedon our understanding of a model nursing environment.Page 3 of 16(page number not for citation purposes)Little consensus exists among researchers on the featuresthat an 'ideal nursing unit' for research utilization wouldImplementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31Theoretical framingRogers' diffusion of innovations theory [29,69]. has pro-vided valuable insight into the field of research utiliza-tion. This theory explains the spread of new ideas usingfour main elements: the innovation, communicationchannels, time, and a social system. That is to say, diffu-sion is a process by which an innovation is communicatedthrough certain channels over a period of time amongmembers of a social system. It is not a single all-encom-passing theory; rather it consists of four theoretical per-spectives that relate to the overall concept of diffusion:innovation-decision process theory, the individual inno-vativeness theory, the rate of adoption theory, and the the-ory of perceived attributes.While the study reported here does not represent anempirical test of the diffusion of innovation theory, wedid use selected components of Rogers' [29] classical Dif-fusion of Innovation work (i.e., characteristics of the adopterand characteristics of the environment) to guide the selec-tion of variables for the original survey [70] of which anabbreviated form was used in this study. For example,characteristics of the adopter included individual varia-bles such as age and experience while characteristics of theenvironment included organizational and contextual var-iables such as unit culture and workload levels. See Addi-tional File 1 for a complete listing of all variables includedin the abbreviated version of the survey utilized in thisstudy.MethodsDesign and SampleTwo adult surgical units (units one and two) and fivepediatric surgical and specialty units (units three to seven)embedded in four metropolitan, tertiary level hospitals intwo Canadian provinces, Alberta and Ontario, partici-pated in the study. Ethical approval for the study wasobtained from the Universities of Alberta and Torontohuman research ethics committees and relevant univer-sity-affiliated institutional research ethics boards.Data CollectionConsistent with an ethnographic approach, both qualita-tive and quantitative data were collected. On each unit,fieldwork (participant observation, interviews, and focusgroups) was conducted over a six-month period yieldingqualitative data on nurses, physicians, other health pro-fessionals, patients and their families. Selected findings ofthe qualitative analysis have been reported elsewhere[71,72].In months one and six of observations on each unit, twoone-week periods of quantitative data collection occurred.tions, unit workload, unit environmental complexity, andunit culture. The only inclusion criterion for participantswas to be a registered nurse employed in one of the sevenparticipating units. Sealed questionnaire packages weresent to all nurses working in the seven units, with two tothree weeks allowed for completion. Participation wasvoluntary and anonymity was maintained. Posters, pam-phlets, and informal communication with on-site datacollectors during observation work were used as remind-ers to complete the questionnaires and return them to acentrally established location on the unit. Response ratesvaried with each instrument according to the time (i.e.,month one or month six) of data collection (see Addi-tional File 2). Across the seven units, 176 nurses partici-pated at month one and 117 at month six. Analysis wasperformed on a sample of N = 235 [i.e. time one (N = 176)+ time two (N = 117) minus nurses at time two whoalready filled out a survey at time one (N = 58)]. Weexcluded nurses at time two who already replied at timeone so not to bias the findings by placing a greater weighton the responses from individuals responding twice. Dueto the short time frame (six months) between times oneand two, we also elected to combine responses from bothperiods. Further, our qualitative analyses during this sixmonth interval did not show any evidence that the con-text of the units had changed and thus supported combin-ing time one and time two responses. Table 1 provides thedemographic profile of the nurses who participated in thestudy, and Table 2, a demographic profile of participatingunits.InstrumentsSix instruments were used to collect the quantitative data:A Demographic (DEM) Inventory, a Research UtilizationSurvey, the Environmental Complexity Scale (ECS), theNursing Unit Cultural Assessment Tool (NUCAT) Version3, the Project Research in Nursing (PRN) 80, and the Cal-ifornia Critical Thinking Disposition Inventory (CCTDI).These are described briefly in sections that follow. TheECS and PRN were both completed by research associateson the unit during the two separate week-long quantita-tive data collection periods, while the remainder of theinstruments were self-administered by the nurses. A sam-ple of the items and scales used to measure the study var-iables and corresponding reliability coefficients for scalesare shown in Additional File 1.Demographic (DEM) inventoryThe DEM developed for this study, included questions ongender, age, education, hours of work per week, length ofshift, years working in nursing, membership in nursingorganizations or groups, and the number of years workedon the unit.Page 4 of 16(page number not for citation purposes)Using survey instruments, data were collected on researchuse, organizational measures, critical thinking disposi-Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31Research utilization surveyThe Research Utilization Survey was first developed andreported by Estabrooks [70,73]. A shortened version ofthe original research utilization survey was used in thisstudy. The shortened version consisted of 22 questionsdivided into three sections: research utilization, kinds andsources of knowledge for practice, and organizationalcharacteristics.Environmental complexity scale (ECS)The ECS [74-76] was designed to assess the amount anddegree of work disruption experienced by nurses over thecourse of a shift. Since its original publication in 1997, thescale has undergone several pilot tests, reviews, and mod-ifications. The version used in this study consisted of 23items divided into three subscales: unanticipated changesin patient acuity, re-sequencing planned in nursing workto accommodate others, and influence of students. Indi-vidual items on each subscale were coded 0–10 (highincrease to high decrease) and summated to obtain finalsubscale scores.Nursing unit cultural assessment tool v3 (NUCAT3)The NUCAT3 was developed by Coeling [77,78]. The pri-mary purpose of this tool is to describe and understandnurses' immediate work group in a unit setting. A list of 50items in the form of questions, representing variousbehaviours is listed mid-page in the questionnaire. A five-point scale on the left and right of each item allows nursesto indicate how important the behaviour is to them per-Table 1: Demographic characteristics of participant nurses by unit (N = 235)Variables Unit 1 Unit 2 Unit 3 Unit 4 Unit 5 Unit 6 Unit 7 Overall (N = 37) (N = 45) (N = 15) (N = 20) (N = 19) (N = 77) (N = 22) (N = 235)Gender (%) Female 91.9 88.9 93.3 95.0 89.5 98.7 95.5 94.0Male 8.1 11.1 6.7 5.0 10.5 1.3 4.6 6.0Education (%)a LPN 14.3 0 13.3 10.0 5.3 0.0 0.0 4.3RN Diploma 57.1 44.2 66.7 80.0 47.4 39.0 40.9 48.9Bachelor's Degree 28.6 53.5 20.0 10.0 47.4 50.6 50.0 42.0Master's Degree 0.0 2.3 0.0 0.0 0.0 9.2 9.1 4.3Age (years) Mean (SD) 39.1 (10.6) 35.5 (8.8) 47.5 (9.3) 45.5 (7.6) 38.1 (9.6) 37.5 (8.4) 35.1 (7.8) 38.7 (9.5)Years in Nursing Mean (SD) 12.9 (9.8) 10.5 (9.1) 20.9 (8.6) 20.6 (8.4) 13.1 (7.9) 12.8 (8.9) 10.0 (8.1) 13.4 (9.4)Usual Shift Length (hours)Mean (SD) 10.6 (1.9) 11.6 (1.0) 11.1 (1.6) 8.0 (0.0) 11.4 (1.4) 11.8 (0.8) 11.2 (1.7) 11.1 (1.6)aNumbers may not add up to 100% due to missing values.SD = standard deviationTable 2: Hospital (N = 4) and unit (N = 7) profile.Unit ProfileUnit 1 There were 37 RNs, including 17 full time and 14 part time RNs. The nurse manager was in charge of the unit. The majority of patients was older than 50 years and stayed on average 4–5 days.(adult)Unit 2 There were 39 full time RNs, 17 part time RNs, and 10 casual RNs. The nurse manager was the leader on the unit. The patients stayed 1–3 weeks on average.(adult)Unit 3 (pediatric) Weekdays 4 nurses and 2 support staff worked the day shift. On nights and weekends, staff consisted of 2 nurses with support people. The clinical supervisor was the clinical leader on the unit; the unit manager took care of the managerial responsibilities for the unit.Unit 4 (pediatric) There were 17 full time RNs, 6 part time RNs, 2 LPNs and 11RNs relief in this unit. At the time of the study, the unit did not have a manager which was partly compensated for by the senior operating officer and the patient care director. The majority of the patients were discharged at that same day.Unit 5 (pediatric) Altogether there were 29 permanent nurses on this unit including 1 nurse educator and 2 LPNs. Local clinical leadership was provided by the clinical supervisor, while the unit manager performed the general administrative and leadership role, with some guidance from the senior operating officer. The average length of patient stay was 3 days.Unit 6 (pediatric) There was over 100 nursing staff in this unit, including 65 full time staff nurses, 25 part time staff nurses, 23 special assignment staff, 12 resource persons and 9 nurse specialists. The unit was administered by the unit manager working collaboratively with the medical clinical directors and the child health services manager.Unit 7 (pediatric) There was 37 nursing staff including the unit manager and the child health services manager. The average daily admissions were 4–5.The seven pediatric and adult acute care units were embedded in four urban, tertiary level hospitals in two cities, each affiliated with a university. Of Page 5 of 16(page number not for citation purposes)the four hospitals: one was a dedicated pediatric center, one had adult and pediatric units, and two were dedicated adult care hospitals. The seven units included five pediatric units and two adult surgical units.Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31sonally (left) and to the group as a whole (right). Based onthe responses to the 50 items, five subscales were concep-tually created to reflect specific cultural indicators reflec-tive of the behaviours for the nurses in this study. Thesesubscales were co-worker support, questioning behaviour,continuing education, work values-creativity, and workvalues-efficiency.Project research in nursing 80 workload measurement tool (PRN)The PRN is a Canadian classification system used to meas-ure the level of nursing care required by patients in hospi-tals and nursing homes [79]. It consists of seven majorcategories: respiration, feeding and hydration, elimina-tion, hygiene and comfort, communication, treatments,and diagnostic procedures. Each category provides a list ofpatient related needs, which are assigned a point valuebased on frequency and complexity. The total score, deter-mined by summing up the points from each of the sevencategories, is multiplied by five minutes to determine thedirect care time estimate for each patient. The higher thepoint value the greater the amount of direct care required.The PRN method of measuring care required has beentested extensively and has undergone several iterationssince its development in 1972. In 1978, Chagnon,Audette, Lebrun, and Tilquin reported its construct andpredictive validity [80].Critical thinking dispositions inventory (CCTDI)The CCTDI is a 75-question, six-point 'agree/disagree' Lik-ert-type scale. There are seven subscales to the inventory:truth-seeking, open-mindedness, inquisitiveness, system-aticity, maturity, self-confidence, and analyticity. Themaximum overall score attainable on this tool is 420, witheach subscale contributing a maximum of 60 points. Thestandard scores for each subscale and all scales combinedare 40 and 280 respectively. A score less than 40 on anysubscale or less than 280 overall indicates limitations orweakness, whereas subscale scores of 50 or higher andoverall scores at 350 or higher indicate a strength in criti-cal thinking dispositions [81].AnalysisWhile research utilization and possible explanatory varia-bles were measured at the individual level, the unit ofanalysis in this study was the patient care unit. To createunit scores, data collected at the level of the individualnurse were aggregated to the level of the patient care unitby calculating group means. When Cronbach alpha wasassessed, this was done at the individual level. One-wayanalysis of variance (ANOVA) was performed for each var-iable using the unit as the group variable. The source tablefrom the one-way ANOVA was used to calculate the fol-group mean square, WMS is the within-group meansquare, and K is the number of subjects per group. Theaverage K for unequal group size was calculated as K = (1/[N - 1]) (ΣK - [ΣK2/ΣK]); 2) interclass correlation ICC (2)= (BMS - WMS)/BMS; 3) η2 = SSB/SST, where SSB is thesum of squares between groups and SST is the sum ofsquares total; and 4) ω2 = (SSB - [N - 1]WMS)/(SST +WMS). For each nursing characteristic analyzed, there wasstrong agreement among nurses in each given unit whenICC(1) was greater than 0.1. Aggregated data were consid-ered reliable when the F statistic from the ANOVA tablewas statistically significant (p < 0.05) and/or ICC(2) wasgreater than 0.60 [82]. An indicator of effect size was η2,which was the proportion of variance in the individualfactor accounted for by group membership [83], and ω2was a measure of the relative strength of the aggregatedvariable at the group level [84]. Table 3 contains the relia-bility and validity values of the data aggregated at the unitlevel. Both η2 and ω2 are measures of validity of the aggre-gated data at the patient care unit level.To index diversity across units, a coefficient of variationwas computed and used in a correspondence analysis. Acoefficient of variation is a quotient of standard deviationover the mean, and allows distributions among differentunits to be compared [85]. It is expressed as a percentage,which constitutes a relative measure of dispersion. Inorder to assess the relationship between various factorsacross the seven units, the coefficient of variation wascomputed and the resulting quotient was multiplied by100 and denoted in the variation index. Variation indicesare commonly used in research for making comparisons[86-88]. In this study, the variation index matrix was thenanalyzed using correspondence analysis, which is a statis-tical visualization method for picturing the associationsamong the variables of a two-way contingency table. Theobject of a correspondence analysis is to obtain a graphi-cal display in the form of a spatial map of rows (units) andcolumns (factors), not only with respect to their marginalprofile, but also among each other. Here, we used corre-spondence analysis to explore the association between thepattern of factors (or determinants) and units. It shouldbe noted however that correspondence analysis is anexploratory technique, based on a philosophical orienta-tion that emphasizes the development of models that fitthe data, rather than the rejection of hypotheses based onthe lack of fit (Benzecri's 'second principle'). Therefore,statistical significance tests are not customarily applied tothe results of a correspondence analysis, and are notneeded for the clustering of factors produced in a corre-spondence analysis [89,90].Page 6 of 16(page number not for citation purposes)lowing indices: 1) interclass correlation ICC (1) = (BMS -WMS)/(BMS + [K - 1] WMS), where BMS is the between-Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31ResultsReliability of aggregated nursing measuresThe reliability properties of the aggregated nursing data atthe unit level are shown in Table 3. These properties sup-ported the reliability of the aggregated data at the unitlevel for over half of the variables: overall research utiliza-tion, authority, intent, belief, people support, organiza-tional support, re-sequencing, acuity, co-worker support,and total PRN. Statistically significant (p < .05) F statisticsand/or ICC(2) values greater than 0.60 indicate greaterreliability and justification for aggregating the variables atthe unit level. The ICC(1) values greater than 0.00 indi-cate some degree of perceptual agreement of nurses aboutthe mean values within each unit. That is, the nurses' per-ceptions about their own unit were highly similar. How-ever, the relative effect sizes for both η2and ω2 values weresmaller, with η2 indices ranging from 0.02 to 0.54 and ω2indices ranging from 0.00 to 0.48. Negative ω2 indices arereported as 0.00 [84,91]. The smaller η2and ω2 indicessuggest that, as we aggregated data, our ability to assignthe same meaning for a variable at the unit level that wehad at the individual level lessened considerably.Research utilizationAdjusted overall research utilization scores were used.Overall research utilization was assessed with a singlequestion asked at three different points in the question-naire: 'Overall, in the past year, how often have you usedoverall research utilization scores increased significantlyfrom the first to the second question (p < 0.001), and fromthe second to the third question (p < 0.05). Adjusted over-all research utilization scores were obtained by taking aweighted average of the score obtained from the threetimes. The first inquiry was given a weight of 1/6, the sec-ond was given a weight of 2/6, and the third was given aweight of 3/6. We assigned higher weights to the researchutilization question each time it appeared in the question-naire because participants learned more about researchutilization over the course of questionnaire completion.We reasoned that their answers were more reflective oftheir true scores each time they encountered the question,thus requiring a greater weight be placed on later inquir-ies. Figure 1 shows the adjusted overall research utiliza-tion scores with 'used research on about half the shifts'(five on the seven-point scale) as a reference line acrossthe seven units. Analysis of variance indicated that statis-tically significant differences existed among units on theoverall research utilization score (p < 0.001).As illustrated in Figure 1, the seven units fell into threemain groupings with respect to research utilization whichwe categorized as low (units one and four), moderate(units three and five), and high (units two, six, and seven)research utilization units. Units seven (pediatric), two(adult) and six (pediatric) had the highest mean scores ofresearch utilization with means of 5.55 (SD = 1.31), 5.77Table 3: Reliability and validity of data aggregated at the unit levelVariable ANOVA Degrees of Freedom ICC(1) ICC(2) η2 ω2 AlphaOverall RU 5.83** 6,264 0.11 0.83 0.12 0.00 --Authority 2.85* 6,303 0.04 0.65 0.05 0.00 --Attitude 1.08 6,303 0.00 0.07 0.02 0.00 --Intent 2.34* 6,298 0.03 0.57 0.05 0.00 --Belief 2.43* 6,285 0.03 0.59 0.05 0.00 0.85People support 4.60** 6,181 0.09 0.78 0.14 0.00 0.89Organizational support 21.56** 6,204 0.34 0.95 0.40 0.28 0.85Re-sequencing 12.21** 6,359 0.19 0.92 0.17 0.06 0.81Students 1.57 6,133 0.02 0.36 0.07 0.00 0.75Acuity 16.15** 6,364 0.24 0.94 0.21 0.11 0.84Coworker support 2.36* 6,149 0.06 0.58 0.09 0.03 0.72Education 1.46 6,144 0.02 0.32 0.06 0.00 0.64Behavior 1.62 6,152 0.03 0.38 0.06 0.00 --Creativity 0.86 6,155 0.01 0.11 0.03 0.00 --Efficiency 0.92 6,154 0.01 0.12 0.04 0.00 --Total PRN 260.32** 6,1334 0.59 1.00 0.54 0.48 --Total CT 1.54 6,140 0.03 0.36 0.06 0.00 --(a) Analysis of variance (ANOVA): Measure used to compare differences in mean scores across seven units;(b) p value for ANOVA F-statistics:* p < .05; **p < .01. The denominator, degree of freedom, differs for some variables owing to different instruments;(c) ICC = interclass correlation;(d) η2: proportion of total information in a given factor at the individual level, which is captured by aggregated data;(e) ω2: provides a relative measure of the strength of an independent variable, small effect < 0.06; medium effect, 0.06–0.15; large effect > 0.15Page 7 of 16(page number not for citation purposes)research in some aspect of your nursing practice?'Repeated measures analysis of variance revealed that the(SD = 1.22) and 5.78 (SD = 1.10) respectively. We foundno statistically significant difference between units two,Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31six, and seven however on research utilization scores(ANOVA, p > 0.05). In contrast, units one (adult) and four(pediatric) were the only units with mean scores ofresearch utilization less than 5. Again, there was also nostatistically significant difference between units one andfour on research utilization scores (ANOVA, p > 0.05).Factors influencing research utilizationTable 4 displays the mean scores of selected variables fromthe Research Utilization Survey, Environmental Complex-ity Scale (ECS), Nursing Unit Cultural Assessment Tool v3(NUCAT3), as well as total scores for the Project Researchin Nursing (PRN) 80, and the Critical Thinking Disposi-tions Inventory (CCTDI).Research Utilization SurveyWith respect to the Research Utilization Survey, unit six(pediatric) had the highest aggregated mean scores forthree of the six subscales: people support, belief suspen-sion, and organizational support. In contrast, unit four(pediatric) had the lowest aggregated mean scores for fourof the six subscales: people support, attitude, intent, andorganizational support. Comparisons of research utiliza-tion measures showed that adult and pediatric units didnot differ significantly.Environmental complexity scale (ECS)There are three subscales on the ECS: re-sequencing ofwork, influence of students, and changing patient acuity.Statistically significant differences were noted between theseven units on the three subscales (re-sequencing of work– ANOVA F-test statistic = 13.352, p < 0.001; influence ofp < 0.001). Generally speaking, adult units scored higherthan pediatric units (see Table 4). The overall mean scorefor re-sequencing of work was 29.45 (SD = 7.94). Unittwo (adult) scored the highest (mean = 35.39, SD = 7.96)and unit five (pediatric) scored the lowest (mean = 24.78,SD = 5.75). The overall mean score for influence of stu-dents was 11.77 (SD = 3.35). Unit one (adult) scored thehighest (mean = 14.33, SD = 5.30) and unit four (pediat-ric) scored the lowest (mean = 10.00, SD = 0.00). Theoverall mean score for changing patient acuity was 55.76(SD = 13.72). Unit two (adult) scored the highest (mean= 67.30, SD = 11.93) and unit three (pediatric) scored thelowest (mean = 48.01, SD = 9.95).Unit cultureThe NUCAT3 assesses and describes unit culture on fivesubscales: co-worker support, questioning behavior, con-tinuing education, work values – creativity, and work val-ues – efficiency. Units two (adult) and six (pediatric) hadthe highest aggregated mean scores on three of thesedimensions of group behavior: work values – creativity,work values -efficiency, and continuing education. Unitsthree (pediatric) and five (pediatric) had the highestaggregated mean scores on questioning behavior and co-worker support respectively. Differences between adultand pediatric units were not noted to be statistically signif-icant.WorkloadThe overall PRN aggregated mean score for each unitranged from 149.69 (unit four – pediatric) to 592.04 (unitsix – pediatric). Statistically significant differencesbetween adult and pediatric units were noted for the totalscore (p < 0.001).Critical thinkingThe overall aggregated mean scores of critical thinking dis-positions (CCTDI) for the seven units ranged from 256.71(unit three – pediatric) to 291.00 (unit seven – pediatric).Comparisons of critical thinking dispositions showed thatadult and pediatric units did not differ significantly withrespect to overall aggregated mean critical thinking scores.Correspondence analysisThe full set of variables (except individual nurse demo-graphic variables) was entered into a correspondenceanalysis, revealing a space (see Figure 2) structured alongtwo dimensions, which captured two thirds of the varia-bility (65.99%). As illustrated in Figure 2, critical thinkingdispositions and unit culture (as measured by work values– creativity, work values – efficiency and questioningbehavior) were found to be close to unit two (adult), ahigh research utilization score unit with a research utiliza-Research utilization scores by unitFigure 1Research utilization scores by unit. Note: reference line = "half of the shifts" = 5 on the 7-point likert scale.  Note: reference line = “half of the shifts” = 5 on the 7-point likert scale. Page 8 of 16(page number not for citation purposes)students – ANOVA F-test statistic = 2.615, p = 0.020,changing patient acuity – ANOVA F-test statistic = 16.575,tion mean of 5.77, indicating an association betweenthese factors and this unit. Unit culture (as measured byImplementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31Page 9 of 16(page number not for citation purposes)Table 4: Mean scores and standard deviations by unitUnit 1 (Adult)Unit 2 (Adult)Unit 3 (Pediatric)Unit 4 (Pediatric)Unit 5 (Pediatric)Unit 6 (Pediatric)Unit 7 (Pediatric)OverallResearch Utilization SurveyPeople Support (Max score = 30)17.94 (7.05) 20.70 (6.51) 18.79 (6.32) 16.44 (7.97) 20.29 (7.87) 21.18 (6.47) 20.30 (6.31) 19.94 (6.87)Autonomy/Authority (Range is 0–4)2.52 (0.81) 2.86 (0.95) 3.11 (0.81) 2.53 (1.01) 2.96 (0.74) 2.59 (0.82) 2.96 (0.74) 2.72 (0.86)Attitude (Range is 0–4) 2.91 (0.92) 3.19 (0.83) 3.00 (0.75) 2.72 (0.96) 2.92 (0.95) 3.02 (0.82) 2.93 (0.92) 3.00 (0.87)Intent (Range is 0–2)1.78 (0.42) 1.76 (0.43) 1.53 (0.51) 1.44 (0.51) 1.52 (0.51) 1.67 (0.49) 1.70 (0.47) 1.68 (0.48)Belief Suspension (Range is 0–4)2.13 (0.99) 2.37 (0.95) 2.47 (1.15) 2.29 (1.13) 2.37 (1.13) 2.50 (0.87) 2.11 (0.87) 2.34 (0.97)Organizational Support (Max. Score = 25)11.70 (4.23) 13.61 (5.15) 11.94 (5.32) 7.89 (2.65) 11.13 (2.85) 15.28 (4.14) 14.89 (2.36) 13.30 (4.61)Overall Research Utilization #13.94 (1.78) 5.43 (1.50) 4.47 (1.99) 3.59 (1.54) 4.43 (1.99) 5.18 (1.61) 5.16 (4.41) 4.80 (1.75)Overall Research Utilization #24.67 (1.85) 5.51 (1.61) 5.21 (1.89) 4.12 (1.87) 5.24 (1.81) 5.69 (1.39) 5.59 (1.60) 5.30 (1.68)Overall Research Utilization #34.83 (1.91) 5.83 (1.25) 5.06 (1.82) 5.19 (1.72) 5.56 (1.78) 5.93 (1.30) 5.59 (1.42) 5.56 (1.57)Adjusted (weighted) Overall research Utilization Score4.62 (1.62) 5.77 (1.22) 5.05 (1.82) 4.63 (1.34) 5.28 (1.63) 5.78 (1.10) 5.55 (1.31) 5.24 (1.43)Environmental Complexity ScaleRe-sequencing of work (Range is 0–50)28.50 (9.66) 35.39 (7.96) 28.24 (6.53) 30.0 (8.98) 24.78 (5.75) 27.21 (6.03) 30.72 (7.94) 29.45 (7.94)Influence of Students (Range is 0–20)14.33 (5.30) 12.18 (1.78) 11.37 (3.13) 10.00 (0.00) 10.91 (2.79) 12.61 (3.72) 11.00 (2.61) 11.77 (3.35)Changing patient acuity (Range is 0–90)54.77 (18.68) 67.30 (11.93) 48.01 (9.95) 52.35 (13.70) 50.70 (10.53) 53.27 (12.27) 57.05 (11.74) 55.76 (13.72)Nursing Unit Cultural Assessment Tool (Group's Behavior)Co-worker support (Range is 0–10)7.56 (2.20) 8.42 (1.69) 7.83 (1.75) 8.00 (1.25) 9.00 (1.07) 7.15 (1.74) 7.71 (1.49) 7.78 (1.78)Questioning behavior (Range is 0–5)4.04 (0.82) 4.21 (0.83) 4.58 (0.52) 4.36 (0.67) 4.47 (0.64) 4.23 (0.84) 3.83 (0.92) 4.21 (0.81)Continuing education (Range is 0–20)14.39 (2.74) 15.65 (2.98) 14.83 (2.67) 14.44 (2.60) 15.73 (2.21) 15.96 (2.27) 14.94 (2.07) 15.32 (2.52)Work values (creativity) (Range is 0–5)3.62 (0.98) 3.96 (0.89) 3.58 (0.79) 3.27 (0.79) 3.93 (0.70) 3.60 (0.92) 3.53 (0.91) 3.66 (0.89)Work values (efficiency) (Range is 0–5)4.31 (0.84) 4.36 (1.00) 4.08 (1.00) 4.10 (0.74) 4.13 (0.35) 4.24 (0.72) 3.78 (0.94) 4.19 (0.82)Project Research in Nursing 80Total PRN 255.42 (108.15)248.37 (82.98)188.54 (81.70)149.69 (24.59)217.41 (83.17)592.04 (157.84)307.94 (124.86)303.84 (184.41)Critical Thinking Dispositions InventoryTotal CCTDI (Max score = 420)286.26 (28.39)281.65 (31.38)256.71 (15.96)283.86 (25.63)288.60 (25.57)279.61 (25.54)291.00 (29.33)281.78 (27.58)Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31co-worker support) appeared to have a close relationshipwith units six (pediatric) and seven (pediatric), also highresearch utilization units. Another cluster includedauthority to use research, unit culture (as measured byimportance of access to continuing education), environ-mental complexity (as measured by work re-sequencing,changing patient acuity), attitude toward research, peoplesupport, belief suspension, and intent to use research, sug-gesting this cluster of factors are consistently associatedwith each other. An additional factor, influence of stu-dents, was far from all of the other factors, reflecting dis-similarity with the other factors across the seven units.Unit four (pediatric) was also far from other units, butclose to the factor of people support. We also observedthat nursing workload (i.e., total PRN score) was moreassociated with unit one (adult), and organizational sup-port with unit five (pediatric).Superimposing the research utilization scores onto the correspondence analysis mapSuperimposing findings from the research utilizationscores onto the correspondence map revealed interestingresults. Using the results from the overall research utiliza-tion scores, the units cluster in three distinct groups: low(units one and four), medium (units three and five) andhigh (units two, six, and seven). These are summarized inTable 5.When the research utilization scores in the high group(adult unit two, pediatric units six and seven) are superim-posed onto the correspondence analysis map they appearclose to one another in physical proximity (see Figure 2)suggesting they share similar characteristics. Howeverunits six and seven were closer to each other than to unittwo indicating there may be subtle differences betweenfactors that determine research use in adult compared topediatric units. The following factors clustered around thethree high research utilization units: changing patient acu-ity, re-sequencing of work, attitude toward research, criti-cal thinking dispositions, importance of access tocontinuing education, work values (creativity and effi-ciency), authority, questioning behavior, and co-workersupport, indicating an association between high researchutilization units and these factors. Some of these factorsclustered more closely around the units than others indi-cating a possible stronger relationship with research use:unit culture [as measured by work values (creativity andefficiency), authority, questioning behavior], and criticalthinking dispositions.After superimposing the research utilization scores ontothe correspondence analysis map we also realized that theunits in the low group (units one and four) were unlikethe other units. Units one and four had the lowest levelsof overall research utilization scores and subsequentlyplotted farther away from the other units (and each other)Overall correspondence analysis map illustrating unit clustering with contextual factorsFigure 2 Page 10 of 16(page number not for citation purposes)Overall correspondence analysis map illustrating unit clustering with contextual factors.Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31in the correspondence analysis map. Nursing workload(i.e., total PRN) and people support clustered close to unitone and unit four, respectively, indicating these two fac-tors may be associated with lower research utilizationunits.When units in the medium research utilization group(units three – pediatric and five – pediatric) were superim-posed onto the correspondence analysis plot we discov-ered a third clustering. In particular, we saw that theseunits are not like the units in the two other groups. Organ-izational support, belief suspension, and intent to useresearch clustered more proximally to the medium groupthan the other two cluster patterns, indicating an associa-tion between units with moderate research utilization andthese three factors.DiscussionThis discussion focuses on individual and contextual fac-tors and their role in research utilization by nurses. Thisstudy was exploratory in nature. Data were collected fromnurses employed on seven units. The unit of analysis wasthe patient care unit and our sample size was thus seven.Findings and interpretations must therefore be inter-preted cautiously and premature generalizations avoided.Other research utilization investigators have explored sev-eral of the factors that we studied in this project. In partic-ular, links between research utilization and attitudestoward and beliefs about research [11,60,92], continuinghave been previously investigated. However, our unit ofanalysis was the patient care unit, and therefore, the com-parisons described between the findings of this study andpast research where the individual nurse was the unit ofanalysis should be interpreted with caution.Some of our findings are consistent with previous work inthe field. For instance, our finding that patient care unitswith high and moderate levels of research use had thehighest levels of co-worker and organizational supportrespectively is not new. Champion and Leach [11] foundsupport from the unit director, chairperson, and directorof nursing to be positively correlated with nurses' use ofresearch in their practice nearly 20 years ago. Hatcher andTranmer [40] also reported small positive significant asso-ciations between the amount of organizational supportnurses perceived and their use of research in practice. Inaddition, Varcoe and Hilton [60] demonstrated that theuse of specific research-based practices was correlated withorganizational support.Our finding that patient care units with the highest levelsof research utilization had, on aggregate, nurses withmore positive attitudes about research use is also not new.Nurses' positive attitude towards research has been con-sistently shown to be associated at statistically significantlevels with research use [21].Authority to use research was also associated with higherlevels of research utilization. While there is no literatureTable 5: Mapping of correspondence analysis results onto unit groups based on research utilization scoresFACTORS Low Group Medium Group High GroupUnits 1 and 4 Units 3 and 5 Units 2, 6, and 7Influence of students (ECS) XPeople support (RU) XTotal PRN score (PRN80) XOrganizational support (RU) XBelief suspension (RU) XIntent (RU) XChanging patient acuity (ECS) XRe-sequencing of work (ECS) XAttitude (RU) XContinuing education (NUCAT3) XCritical thinking (CCTDI) XWork values: Creativity (NUCAT3) XWork values: Efficiency (NUCAT3) XAuthority (RU) XQuestioning behavior (NUCAT3) XCoworker support (NUCAT3) XThe three groupings (low, medium, high) were based on the aggregated research utilization scores for each unit'X' means that the factor sat closest to the respective unit groupPage 11 of 16(page number not for citation purposes)education [10,19,93], critical thinking [20], and supportfor research use [11,40,60] at the individual nurse levelthat directly associates authority and research utilization,there is support for this concept in the 'barriers to researchImplementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31utilization' literature in nursing. Several investigators havenoted that one of the most consistently reported barriersto using research in practice for nurses is 'lack the author-ity to implement change based on research findings' [94-102].Our findings run counter to the work of some investiga-tors. For example, Profetto-McGrath et al. [20] reported astatistically significant positive correlation between criti-cal thinking dispositions and research utilization. Giventhe work by Profetto-McGrath and colleagues, we wouldexpect to see high critical thinking dispositions scores fornurses on units two, six, and seven (i.e., high research uti-lization units) in comparison to the nurses on the otherstudy units. However, there were no statistically signifi-cant differences between nurses on total critical thinkingdispositions scores even though critical thinking disposi-tions did cluster around the 'high' research utilizationunits in the correspondence analysis. The Profetto-McGrath, et al. work was conducted on a subset of the dataused for this study. However, their unit of analysis was atthe level of the individual nurse, possibly accounting fordifferences. It may be that critical thinking dispositionsare most productively studied as an individual level phe-nomenon, as suggested by our non-significant ANOVA F-statistic and ICC(2) of < 0.60 for the total critical thinkingdispositions aggregated mean scores (see Table 3).The culture of a unit defines the behavior of nursesthrough observable artifacts, values (i.e., norms, socialprinciples and ideologies), beliefs, and attitudes [46,103].As such, it constitutes a potential contextual determinantof research utilization. In this study, 'high' research utili-zation units had the highest aggregated mean unit culturescores (as measured by importance of access to continuingeducation, work values – creativity, work values – effi-ciency, questioning behavior, and co-worker support)indicating that variables associated with unit culturereflect the vitality with which research utilization can bepromoted within patient care units. Positive effects of cul-ture on research utilization have been suggested by severalscholars in the field [42,46,47] but, to date, we have rela-tively little empirical evidence to support these assertions.For example, while several previous studies have exam-ined continuing education, an element of unit culture asmeasured by the NUCAT3, in relation to nurse researchutilization behavior, findings have been equivocal.McCleary and Brown [104] found taking a course aboutresearch design was positively associated with researchutilization. Rodgers [36] found that the number of studydays attended was associated with using more research inpractice. However, other investigators, have not foundsimilar associations [10,36,105]. Further research examin-definitive statement on its value as an intervention toincrease research use in practice can be made. In additionto continuing education, recent work by Belkhodja et al.[48] found specific aspects of unit culture, such as theunit's research culture (i.e., research as the preferredsource of information) and the intensity of use of researchsources by the unit's members to also be positively corre-lated (p < 0.05) with research utilization by healthcareprofessionals on hospital units.Pepler et al. [49] in a multiple case-study of research utili-zation on eight acute care units also found unit culture tobe a principal factor linked to patterns of research utiliza-tion. However, while Pepler and colleagues identified sev-eral aspects of unit culture that were important to researchutilization (e.g., harmony of research perspectives, moti-vation to learn, goal orientation, creativity, criticalinquiry, mutual respect, and maximization of resources)they also reported that the components of unit culturewere tightly intertwined resulting in a complexity whichrepresents a distinctive culture for each unit. While thisrepresents early support for unit culture as a factor inresearch utilization behaviours of nurses, further empiri-cal support is needed before a statement regarding theassociation between unit culture and research use can beconfidently made.In addition to the factors discussed above, we reported anumber of other factors that have not been previouslystudied with respect to nurses' research utilization behav-ior. For example, links between research utilization andnursing workload, patient acuity, and re-sequencing ofwork have not been previously explored, suggesting fruit-ful new avenues of inquiry. While we located no reports ofthese concepts having been studied in relation to researchutilization, there are many studies reporting on nurse per-ceived barriers to using research. Among these, investiga-tors consistently report a lack of time to read research andimplement findings as one of the most frequently identi-fied barriers [37,97,99]. Little clarification of what ismeant by time has been offered in these studies, althoughan implicit assumption is that nurses' lack of time pre-vents research use. Our findings suggest this may not bethe case. Two of the units with the highest workloads inthe study reported here were units one and two (bothadult units). Unit one was classified as a 'low' research uti-lization unit and unit two, a 'high' research utilizationunit, making it difficult to ascertain the direction of therelationship between workload and research use. How-ever, these findings do lead us to propose that there maybe contextual differences between units (e.g., primary ver-sus team nursing models, patient case mix, patient careacuity, healthcare team composition) that influencePage 12 of 16(page number not for citation purposes)ing the link between nurse research utilization and con-tinuing education will be necessary before a morenurses' research use.Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31In addition to the unit contextual and individual factorsidentified in the correspondence analysis as important toresearch use, the 'high' research utilization units (i.e.,units two, six, and seven) also had the highest proportionsof baccalaureate and master prepared nurses and theyoungest nurses (see Table 1). Education and age havebeen investigated in numerous previous research utiliza-tion studies and investigators have reported equivocaleffects, at best, on nurse research utilization behaviours.For example, several studies showed no statistically signif-icant association between education and research use[60,92,106]. while others showed the use of research inpractice to be higher among nurses with baccalaureate/masters degrees compared to those with registered nursediplomas [10,36,105]. Similarly, age has not been dem-onstrated to predict research use [10,19,92]. For this rea-son, and because we were interested in identifyingmodifiable, or at least more readily modifiable, factorsinfluencing research use, we chose not to enter age andeducation into our correspondence analysis. Other indi-vidual characteristics such as questioning behaviours andbelief suspension were entered in the correspondenceanalysis because we postulated they would be modifiablethrough continuing education. Age is not modifiable andeducation, while modifiable, would require long-termcommitment.The archetypical unitThe specific purpose of the analyses presented in thispaper was to model an ideal patient care unit. In such anideal or archetypical patient care unit factors would beoptimized to facilitate research use. We identified anumber of such modifiable factors or characteristics thatwere associated in this study with patient care units thatreported greater research use (see Table 5). In such units,these characteristics included unit culture, (specifically:co-worker support, questioning behavior, importance ofaccess to continuing education, work values – creativity,work values – efficiency), environmental complexity,workload, authority to use research, positive attitudestowards research, and stronger critical thinking disposi-tions. These findings illustrate both the complex nature ofresearch utilization and the shortcomings of models thataddress only individual or unit level dimensions. Either ofthese dimensions (individual, unit/contextual), whilenecessary, is insufficient to adequately explain the com-plex behavior changes required by nurses who useresearch optimally and appropriately. Importantly, ourmodeling of such an archetypical patient care unit,allowed us to identify contextual factors (e.g., importanceof access to continuing education, co-worker support,questioning behavior) that can be modified to increaseresearch use.Study LimitationsWhile this was a multi-centre study, the sample size in theanalyses reported here was relatively small and may havebeen inadequate to detect differences between units forsome of the variables. This study was also exploratory innature and the findings drawn from seven units and thenurses employed on those units. The results must be inter-preted with caution and are not generalizable either tonurses or units. While this study sheds light on the factorsthat may influence research use at the patient care unitlevel, further research is needed to expand on this knowl-edge. In particular, contextual factors (nursing workload,patient acuity, and re-sequencing of work) that have notbeen previously reported in relation to research use sug-gest directions for study.While we were able to identify and build a model of anideal patient care unit from a research utilization perspec-tive from our analyses, it is important to note that we didnot collect data on several potentially important contex-tual factors. For example, Greenhalgh et al. [107], in areview of the diffusion of service innovations, identifiedseveral structural factors that have been shown to influ-ence the likelihood of innovation adoption (e.g., size, bedcapacity, functional differentiation, decision-makingstructure, slack resources). Future research examiningresearch utilization patterns at the unit level should incor-porate such structural factors.Aggregating individual nurse scores on a variable of inter-est to obtain scores for the unit on that characteristic canalso introduce bias into the findings if the variable takeson a different meaning and thus has different effects atvarious levels of analysis. Reliability and validity measuresfor the following variables of interest raise questionsabout their suitability for aggregation: attitude, criticalthinking dispositions, workload (influence of students),and some unit culture variables (e.g., importance of accessto continuing education, work values – creativity, workvalues – efficiency, questioning behavior).Finally, we adjusted the research utilization score used inthe correspondence analysis by taking a weighted averageof the score obtained from asking the question on threeseparate occasions throughout the survey. We assignedhigher weights to the research utilization question eachtime it appeared in the questionnaire because we hypoth-esized participants learned more about research utiliza-tion over the course of questionnaire completion.However, it is also possible that participants may haveobtained higher scores on the question each subsequenttime it appeared because they learned how to answer thequestion.Page 13 of 16(page number not for citation purposes)Implementation Science 2008, 3:31 http://www.implementationscience.com/content/3/1/31ConclusionOur findings offer preliminary support for the argumentthat context matters. Contextual factors at the patient careunit level, in addition to individual nurse characteristics,were important to promoting research utilization bynurses. By studying several different patient care units, wewere able to suggest modifiable components of context atthe patient care unit level that may be important determi-nants of nurses' use of research. We were also able tomodel an archetypical patient care unit, that is, a patientcare unit displaying features optimal for research use.Contextual features identified for such a unit included:higher reported unit culture [as measured by importanceof access to continuing education, work values (creativityand efficiency), questioning behavior, and co-worker sup-port] and lower reported environmental complexity (asmeasured by changing patient acuity and re-sequencing ofwork). These factors represent modifiable conditions inthe hospital environment and have important practicalimplications for work and unit structures and for organiz-ing nursing service delivery to enhance nurses' use ofresearch findings to improve patient outcomes.Competing interestsThe authors declare that they have no competing interests.Authors' contributionsCAE conceived the study and its design, secured funding,provided leadership and coordination for the two projectsand participated in data analysis and interpretation, writ-ing, and final approval of the submitted manuscript, SS,KMcG, and JPM participated in data collection and con-current data analysis, SS participated in drafting the man-uscript, JES made substantial contributions to dataanalysis and interpretation and made major contributionsto writing of the manuscript, BS participated in conceptu-alization of study, securing grant funding, in the start-upof the study (with data collection) and served as a leadinvestigator for the pediatric study, coordinating one ofthe participating sites, JWW participated in conceptualiza-tion of study, securing grant funding, in the start-up of thestudy (with data collection) and served as a lead investiga-tor for the adult study, coordinating one of the participat-ing sites, JL participated in conceptualization of study,securing grant funding and in the start-up of the study(with data collection), LOP participated in study concep-tion, served as a senior advising member on work envi-ronment measures, and funded the collection ofworkload data in two hospitals. KGB participated in inter-pretation of the findings, GD participated in study con-ception, data collection and interpretation, GBparticipated in start-up of the study helping to shape thesampling and data collection activities, CKH coordinatedparticipated in data analysis and interpretation, providedcritical commentary and served as senior advisor to theteam and principal investigator. All authors read andapproved the final manuscript.Additional materialAcknowledgementsThis work was supported by grants-in-aid from the Canadian Institutes of Health Research (CIHR) and the Alberta Heritage Foundation for Medical Research (AHFMR). We would also like to thank William Midodzi and Lin-glong Kong, University of Alberta, Canada for their assistance with data analysis.References1. Grol RP, Bosch MC, Hulscher ME, Eccles MP, Wensing M: Planningand studying improvement in patient care: the use of theo-retical perspectives.  Milbank Q 2007, 85:93-138.2. 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