Counselor attitudes toward and use of evidence-based practices in private substance use disorder treatment centers: a comparison of social workers and non-social workers.
The purpose of this study was to examine factors that may be
associated with variation in social workers' perceptions of
effectiveness, perceptions of acceptability, and use of psychosocial
evidence-based practices (EBPs) for the treatment of substance use
disorders (SLID) in comparison to other SUD counselors who are
non-social workers. A national sample of 1,140 counselors in private SUD
treatment settings completed a mailed survey. Overall, counselors
perceive both motivational interviewing (MI) and contingency management
(CM) to be effective and acceptable interventions, with MI perceived to
be both more effective and more acceptable than CM. The results of this
study also shed light on the factors associated with perceptions of
effectiveness and acceptability of MI and CM. The results of this study
underscore the importance of exposure to EBPs in the development of
positive attitudes toward and use of EBPs. In particular, professional
networks are an important route to introduce social workers to EBPs, as
is professional training on specific EBPs. Efforts to increase the
uptake of evidence-based SUD interventions should not be limited to
dissemination of information regarding effectiveness; rather, efforts
should also be expended to expose social workers to EBPs.
KEY WORDS: attitudes; evidence-based practice; knowledge; social workers; substance abuse treatment
Social workers (Practice)
Substance abuse (Care and treatment)
Substance abuse (Quality management)
Bride, Brian E.
Abraham, Amanda J.
Roman, Paul M.
|Publication:||Name: Health and Social Work Publisher: Oxford University Press Audience: Academic; Professional Format: Magazine/Journal Subject: Health; Sociology and social work Copyright: COPYRIGHT 2012 Oxford University Press ISSN: 0360-7283|
|Issue:||Date: August, 2012 Source Volume: 37 Source Issue: 3|
|Topic:||Event Code: 310 Science & research; 200 Management dynamics; 353 Product quality|
|Product:||Product Code: 8000143 Alcohol & Drug Abuse Programs NAICS Code: 62142 Outpatient Mental Health and Substance Abuse Centers SIC Code: 8093 Specialty outpatient clinics, not elsewhere classified|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
Emphasis on the identification and use of evidence-based practices
(EBPs) is increasingly prominent in social work and in the substance use
disorders (SUD) treatment field, yet uptake of psychosocial
interventions with demonstrated effectiveness in the treatment of SUDs
continues to be low (Bride, Abraham, & Roman, 2011; Compton et al.,
2005). Research on factors that facilitate or impede the adoption of
EBPs in SUD treatment settings has largely focused on organizational
variables, with much less attention paid to the role of direct service
providers. Being at the point of service delivery, SUD counselors are
critical arbiters of clients' acceptance and use of innovations.
Such support or the lack thereof depends on their knowledge of and
attitudes toward particular innovations (Abraham, Ducharme, & Roman,
2009; Rieckmann, Daley, Fuller, Thomas, & McCarty, 2007). However,
most studies that have considered counselors' roles in the adoption
of EBPs have focused on pharmacological rather than psychosocial
treatments; no studies have examined the role of social workers in the
adoption of EBPs in the SUD treatment environment. Because of their
presence in a wide range of service delivery systems, social workers are
often the first service providers to come into contact with individuals
experiencing SUD, and therefore they are in a unique position to refer
clients or to provide appropriate treatment (Smith, Whitaker, &
Weismiller, 2006). Social workers also comprise a significant portion of
the specialty SUD treatment workforce (Roman, Johnson, Ducharme, &
Knudsen, 2006). For these reasons, social workers are often key opinion
leaders who may influence decisions regarding service delivery in the
SUD treatment sector. As such, it is important to have an understanding
of social workers' perceptions and use of evidence-based
psychosocial interventions for SUD as well as how they may differ from
other substance abuse counselors.
The purpose of this study was to examine factors that may be associated with variation in social workers' perceptions of effectiveness, perceptions of acceptability, and use of psychosocial EBPs for the treatment of SLID in comparison to other SUD counselors who are non-social workers. As the targets of our inquiry, we selected motivational interviewing (MI) and contingency management (CM). Both interventions were introduced more than 25 years ago and have been the subject of a copious amount of professional and research literature documenting their effectiveness. Thus, there has been sufficient opportunity for the diffusion and adoption of these practice innovations.
Developed as an alternative approach to the widely used confrontational interventions in SUD treatment, MI is "a collaborative, person-centered form of guiding to elicit and strengthen motivation for change" (Miller & Rollnick, 2009, p. 137). MI uses strategies from client-centered counseling, cognitive therapy, systems theory, and the psychology of persuasion, such as eliciting self-motivational statements, affirming client self-worth, presenting addictive behavior as modifiable, and using reflective listening to encourage clients to openly discuss their use of substances and related life events while providing a highly empathetic and supportive environment to enhance the clients' motivation to change (Miller & Rollnick, 2002; Schneider, Casey, & Kohn, 2000). MI employs a counseling style that is generally quiet and eliciting. Readiness to change is seen as fluctuating in relation to interpersonal interaction, and the counseling relationship is more like a partnership or companionship than expert-recipient roles (Miller, 1996). The results of several meta-analyses indicate that MI is effective in the treatment of a variety of substances of abuse and the positive effects are durable (Burke, Arkowitz, & Menchola, 2003; Hettema, Steele, & Miller, 2005; Lundahl & Burke, 2009; Lundahl, Kunz, Brownell, Tollefson, & Burke, 2010; Vasilaki, Hosier, & Cox, 2006).
Furthermore, MI is effective for a range of severity levels, may be more effective for clients with severe SUD, and may be particularly effective for African Americans and Hispanic Americans (Hettema et al., 2005; Lundahl et al., 2010; Lundahl & Burke, 2009). Although research has yet to explore why MI may be more effective among ethnic minorities, the fact that MI is client-centered, supportive, and nonconfrontational may make it more relevant for traditionally marginalized and oppressed populations.
Also referred to as "motivational incentives" or "voucher-based reinforcement therapy," CM is based on the principles of behavior modification, with tangible reinforcement provided when a target behavior is demonstrated (Petry & Simcic, 2002). In SUD treatment, common target behaviors include abstinence or reduction of substance use, treatment attendance, compliance with program rules and policies, completion of treatment goals, and vocational or educational accomplishment (Bride, Abraham, & Roman, 2010). Reinforcers include services, such as increased clinic privileges, or goods (for example, food, toiletries, movie passes, and clothing) often provided in the form of gift certificates or vouchers (Bride et al., 2011; Prendergast, Podus, Finney, Greenwell, & Roll, 2006). Over the past 30 years, research has consistently demonstrated the effectiveness of CM in promoting abstinence and increasing treatment attendance among substance abusers (Griffith, Rowan-Szal, Roark, & Simpson, 2000; Lussier, Heil, Mongeon, Badger, & Higgins, 2006; Prendergast et al., 2006). Effectiveness has been demonstrated among individuals dependent on alcohol (Petry, Martin, Cooney, & Kranzler, 2000), cocaine (Higgins et al., 1994), methamphetamines (Shoptaw et al., 2005), opiates (Carroll et al., 2001), and stimulants (Perry et al., 2005). CM has also shown positive results in a variety of settings, such as drug courts (Prendergast, Hall, Roll, & Warda, 2008), adolescent treatment programs (Corby, Roll, Ledgerwood, & Schuster, 2000; Kamon, Budney, & Stanger, 2005), and methadone clinics (Griffith et al., 2000).
PREDICTORS OF ATTITUDES AND USE OF EBPs
Congruent with Rogers' (2003) theory of diffusion of innovations, professional characteristics, norms and values, and exposure to a particular EBP have been demonstrated to be associated with SUD counselor attitudes toward and use of EBPs. Professional characteristics such as educational level and tenure in the field are predictive of use of EBPs in SUD treatment settings (Forman, Bovasso, & Woody, 2001; Kirby, Benishek, Dugosh, & Kerwin, 2006; Roman & Johnson, 2002). Findings have been mixed regarding the influence of tenure on counselor perceptions of CM, however. One study found that counselors with more experience had more positive attitudes toward CM (Kirby et al., 2006), whereas a second study found that longer tenure was associated with less favorable views of CM (Bride et al., 2010).
Norms and values are reflected in personal recovery status, endorsement of a 12-step treatment philosophy, and attitudes toward EBPs in general. Kirby et al. (2006) found no impact of recovery status on attitudes toward CM, whereas Bride et al. (2010) found that recovering SUD counselors held more positive attitudes toward CM than their colleagues. Attitudes toward EBPs have also been found to be associated with ratings of the effectiveness and acceptability of both pharmacological and psychosocial EBPs among SUD counselors (Abraham et al., 2009; Bride et al., 2010). Counselor exposure to the EBP occurs directly when they receive specific training in the practice or indirectly when the practice is regularly used by a colleague. Both of these variables have been found to be associated with positive attitudes toward pharmacological (Abraham et al., 2009) and psychosocial (Bride et al., 2010) EBPs in SUD treatment settings. Though we have drawn upon the work cited previously, the present study is unique in that it is the first to examine attitudes toward and use of MI and CM among counselors in private treatment centers and is the first study to specifically examine these issues in social workers.
Sampling and Data Collection Procedures
Data were collected from SUD counselors employed in a nationally representative sample of 345 private SUD treatment programs. Treatment programs were considered to be private if less than 50 percent of their operating budget was derived from relatively stable governmental sources such as block grants and contracts. Additional inclusion criteria required programs to be community-based and offer, at a minimum, structured outpatient level of care in accordance with the American Society of Addiction Medicine guidelines (Mee-Lee, Shulman, Fishman, Gastfriend, Griffith, 2007). Programs that offered only detoxification services, programs whose sole modality was methadone maintenance, private practices and halfway houses were thus excluded. In addition, treatment programs located in Veterans Administration facilities or correctional settings were ineligible, because they are not accessible to the general public.
To identify a nationally representative sample of treatment programs, we used a two-stage sampling process. The first stage involved assigning all counties in the United States to one of 10 strata on the basis of population and randomly sampling within strata to ensure that programs located in urban, suburban, and rural areas would be included. The second stage involved the enumeration of all SUD treatment facilities in the sampled counties using published national and state directories. Treatment programs were then proportionately sampled across strata, with telephone screening used to establish eligibility for the study. Programs screened as ineligible were replaced by random selection of alternate programs from the same geographic stratum. Two-thirds (67 percent) of contacted treatment programs agreed to participate in the study. A list of all SUD counselors employed in the program was obtained from the clinical director of each program. All listed counselors were mailed a packet including a questionnaire, consent form, study description, and a self-addressed stamped envelope. Those who completed and returned the survey received an incentive payment in the amount of $40. A total of 1,140 questionnaires were completed and returned, representing a 58 percent response rate. The institutional review board at the university approved study procedures.
Dependent Variables. Three dependent variables were measured for MI and for CM: (1) perceived effectiveness, (2) perceived acceptability, and (3) use. To measure perceived effectiveness, respondents rated the effectiveness of MI and CM independently using a seven-point Likert-type scale. Response options ranged from 1 = not at all effective to 7 = very effective. For example, respondents were asked, "Based upon your knowledge and personal experience, to what extent do you consider motivational interviewing to be effective?" To measure perceived acceptability, respondents rated the acceptability of MI and of CM using a seven-point Likert-type scale. Response categories ranged from 1 = completely unacceptable to 7 = very acceptable. For example, respondents were asked, "To you as a treatment professional, how acceptable is the use of motivational interviewing as a treatment technique for substance abuse?" Respondents had the option to respond with "don't know" to these questions. Such responses were excluded from the analysis of the perceived effectiveness and perceived acceptability variables, resulting in a different sample size for each analysis. The final dependent variables measured use of MI and CM. Respondents reporting current use of MI or CM were coded as 1, and nonusers were coded 0. For example, respondents were asked, "Do you personally use motivational interviewing in treating clients?"
Independent Variables. Seven predictor variables were included in all regression models: (1) education, (2) tenure, (3) recovery, (4) 12-step orientation, (5) EBP attitudes, (6) use by colleagues in program, and (7) training. Education was measured as a dichotomous variable identifying counselors with (1) and without (0) a master's degree or higher. Tenure was measured as the number of years that the respondent had worked in SUD treatment. Recovery was measured as a dichotomous variable identifying counselors as personally being in recovery from SUD (1 = yes, 0 = no). Twelve-step orientation was measured as the sum (range = three through 21) of counselors' responses to three items ([alpha] = .83) developed by Kasarabada et al. (2001). Specifically, counselors indicated the extent to which they agreed (1 = strongly disagree, 7 = strongly agree) that clients need to accept a lack of control over their addiction while placing faith in a higher power, that clients need to reach out to others in recovery, and that treatment should have the goal of clients working the 12 steps. To measure EBP attitudes, counselors indicated the extent to which they agreed (1 = strongly disagree, 7 = strongly agree) with the statement, "Scientifically supported treatments can be useful." Use by colleagues refers to two separate variables indicating whether MI and CM, respectively, were used by other counselors in the respondent's treatment program (1 = yes, 0 = no). Amount of training refers to two variables indicating to what extent (1 = no training received, 7 = extensive training received) they had received specific training in the use of MI or CM. These measures have been widely used in prior research on the diffusion and adoption of innovations in SUD treatment (for example, Abraham et al., 2009; Ducharme, Knudsen, Roman, & Johnson, 2007; Knudsen, Ducharme, Roman, & Link, 2005). Two additional variables, gender and ethnicity, were included as dichotomous control variables because of their unequal distribution across categories and some evidence from prior studies that they are associated with the dependent variables of interest. Gender was coded as 1 = female and 0 = male; ethnicity was coded as 1 = Caucasian and 0 = other.
Data analysis was conducted using Stata version 17.0 (Stata Corp., College Station, TX). We used t tests and chi-square analyses to test for differences between social workers and other counselors on demographic and professional variables and used analysis of variance (ANOVA) to compare social workers with counselors from other disciplines on their attitudes toward and use of MI and CM. Multiple regression was used to model the influence of the seven independent and two control variables on perceptions of the effectiveness and acceptability of MI and CM. The acceptability models also included perceived effectiveness as an independent variable. Logistic regression was used to model the influence of the seven independent and two control variables, as well as the perceived effectiveness and perceived acceptability variables on use of MI and CM. Separate regression models were conducted for social workers and non-social workers. It should be noted that the counselor-level data are clustered, meaning that in many cases there are several counselor respondents employed by the same center, thereby violating the assumption of independence that is required by regression modeling. As such, we employed Stata's "cluster()" command, which corrects for the effects of clustered data and leads to robust standard errors (Long & Freese, 2003). Data screening verified that the remaining assumptions for ANOVA, ordinary least squares (OLS) and logistic regression, were tenable.
Social workers comprised 25 percent (n = 285) of the total sample, which was largely female (65 percent) and Caucasian (86 percent). More than half (54 percent) of the respondents had at least a master's degree, and less than half (46 percent) reported being in recovery from an SUD. The mean age of counselors was 46 years, and the mean tenure was 11 years. Social workers were more likely to have an advanced degree, a more positive attitude toward EBP, and less of an orientation to 12-step philosophy than counselors from other disciplines. Social workers were also less likely to be in recovery and did not differ from other counselors in the amount of MI or CM training received or their colleagues' use of MI (74 percent) or CM (20 percent) in their programs (see Table 1).
Counselors provided relatively high ratings of the effectiveness (M = 5.96, SD = 1.11) and acceptability (M = 6.47, SD = 0.98) of MI, and 82 percent reported that they use MI (see Table 2). In contrast, counselors provided somewhat lower ratings of the effectiveness (M = 4.83, SD = 2.03) and acceptability (M = 5.36, SD = 1.98) of CM. The differences in ratings of the effectiveness and acceptability of the two interventions were statistically significant (t = 16.30, p < .001; and t = 15.63, p < .001, respectively), with large effect sizes (d = 0.69, r = .33; and d = 0.71, r = .33, respectively) (Cohen, 1988). Use of CM by counselors was low (18 percent). Of the six dependent variables examined, two were statistically significant when social workers were compared with other counselors. Social workers rated the acceptability of MI higher than other counselors, although the effect size was small (d = 0.21, r = .10). Social workers were also more likely to use MI (odds ratio [OR] = 1.47; 95 percent confidence interval = 1.003, 2.145).
In the model of perceived effectiveness of MI, four variables were statistically significant in the social work subsample (see Table 3). Longer tenure in the SUD treatment field was associated with lower ratings of MI effectiveness, whereas having a graduate degree, MI use by colleagues, and increasing amount of training in MI were associated with higher ratings of effectiveness. The model of perceived effectiveness of CM found only one variable to be statistically significant. Increased amount of training in CM was associated with higher ratings of CM effectiveness. Three variables were statistically significant in the model of non-social workers' ratings of MI effectiveness: Ratings of the effectiveness of MI were positively associated with being non-Caucasian, having positive attitudes toward EBPs, and increasing training in MI. The model of perceived effectiveness of CM among non-social workers resulted in two statistically significant variables. Ratings of the effectiveness of CM were positively associated with use of CM by colleagues and amount of training in CM.
Three variables were statistically significant in the model of perceived acceptability of MI among social workers (see Table 4). Longer tenure in the SUD treatment field was associated with lower ratings of MI acceptability, whereas MI use by colleagues and perception of MI effectiveness were positively associated with ratings of the acceptability of MI. The model of perceived acceptability of CM also resulted in three statistically significant variables. Positive attitudes toward EBPs, amount of training related to CM, and perception of CM effectiveness were positively associated with acceptability of CM among social workers. Among non-social workers, only two variables were statistically significant predictors of ratings of MI acceptability. Positive attitudes toward EBPs and ratings of MI effectiveness were positively associated with ratings of the MI acceptability. The model of acceptability of CM among non-social workers resulted in seven statistically significant predictors. Perceptions of CM acceptability were associated with male gender; having a graduate degree, less experience, less of a 12-step orientation, and positive attitudes toward EBPs; use of CM by colleagues, and belief that CM is effective.
Use of MI by social workers was positively associated with use of MI by colleagues, amount of MI training received, and perceptions of the acceptability of MI as an intervention but was negatively associated with positive attitudes toward EBPs (see Table 5). Ethnicity was dropped from the model by Stata because all non-Caucasian social workers reported use of MI. Use of CM by social workers was positively associated with the use of CM by colleagues, amount of training related to CM, and perceptions of CM effectiveness and was negatively associated with recovery status. Among non-social workers, use of either MI or CM was associated with colleague use of the intervention and amount of training received in the intervention. In addition, use of MI was negatively associated with tenure and was positively associated with being in recovery and perceptions of MI effectiveness. Use of CM was associated with ethnicity; Caucasian social workers were less likely to use CM.
The results of this study provide a snapshot of SUD counselors' perceptions of effectiveness, perceptions of acceptability, and use of two EBPs for the treatment of SUD in private treatment centers. Counselors, both social workers and non-social workers, perceived MI and CM to be effective and acceptable interventions that are use at similar rates by both groups. Although we identified statistically significant differences between social workers and non-social workers in terms of perceptions of acceptability and use of MI, the size of the differences was small. However, both social workers and non-social workers believe MI to be more effective and more acceptable than CM, which may account for the finding that MI is use by most counselors whereas CM is used by few.
As previously noted, both MI and CM have a long history and are widely identified as evidence-based treatments for SUD, each being effective in reducing substance use as well as increasing treatment completion and time in treatment (Manuel, Hagedorn, & Finney, 2011). Given that no studies have been published that directly compare the effectiveness of MI and CM, the higher ratings of effectiveness and higher rates of use cannot be based on comparative effectiveness data. One alternative explanation is that there has been less success in diffusing CM to the SUD treatment workforce as compared with MI. Recall that in rating the effectiveness of each intervention, respondents had the option to respond to the item with "don't know." Using this as a measure of diffusion as has been done in a number of studies of the diffusion of SUD innovations (see Abraham et al., 2009; Bride et al., 2010; Knudsen et al., 2005), we found a significant difference in the rate of diffusion of MI (90 percent) and CM (60 percent) to the study sample. It is unlikely, however, that diffusion rates fully account for the lower use of CM as compared with MI. Indeed, when we excluded counselors who lacked knowledge regarding the interventions, there was still a sizable difference in the use rates--89 percent for MI, compared with 28 percent for CM.
Another possibility is that controversial aspects of CM account for lower use rates. For example, SUD counselors have questioned the appropriateness of paying clients for abstinence or treatment attendance (Ducharme, Knudsen, Abraham, & Roman, 2010; Kirby et al., 2006; McCarty et al., 2007). However, we found that counselor perceptions of acceptability of CM did not influence use among either social workers or non-social workers; rather, use of CM was influenced by exposure through training or use by colleagues. Social workers' use of CM was also influenced by their views of its effectiveness, perhaps due to social work education's focus on EBP and evaluation of practice. A third possibility is that use of CM is limited due to financial constraints, which is one of the most widely cited barriers to its implementation (Benishek, Kirby, Dugosh, & Padovano, 2010). Unfortunately, we did not survey counselors in this regard, thus future research should examine the influence of cost on CM use.
The results of this study also shed light on the factors associated with counselor perceptions of effectiveness and acceptability of MI and CM as well as similarities and differences between social workers and non-social workers in this regard. Exposure to the particular EBP through colleagues' use of the intervention, through training in the intervention, or both is an important factor influencing views of effectiveness in both groups. Social workers and non-social workers differed in the additional factors involved in their ratings of effectiveness. Social workers views of effectiveness were influenced by having an advanced degree and being newer to the field, whereas non-social workers views of MI effectiveness were not influenced by education or tenure but by positive attitudes toward EBPs in general.
Although exposure influenced ratings of acceptability of MI and CM, it did so to a lesser extent than for views of effectiveness. Counselors' views of effectiveness were important predictors of perceptions of acceptability for both subsamples and both interventions. Another common source of influence was positive attitudes toward EBPs in general. Being newer to the field was associated with positive views of acceptability of MI for social workers and was associated with positive views of acceptability for both MI and CM among non-social workers. Non-social workers' views of CM acceptability were more complicated. A total of seven variables were statistically significant. In addition to those variables already discussed, non-social workers' views of CM acceptability were influenced by having an advanced degree, being male, being newer to the field, and having less of a 12-step orientation.
Last, we examined factors associated with social worker use of MI and CM. Again, the exposure variables of colleagues' use of the EBP and training in the intervention were important predictors of counselors' use for both social workers and non-social workers. Colleagues' use of the intervention was an especially powerful influence. If a colleague used MI, then social workers were almost 13 times and non-social workers were more than 16 times more likely to use MI. The influence is even more dramatic for CM. Non-social workers exposed to CM via a colleague were more than 19 times more likely to use CM, whereas social workers exposed to CM were more than 100 times more likely to use CM. It is important to consider this finding along with prior findings that indicate that if CM is used in a treatment program, it is typically used with all clients (Bride et al., 2010). Therefore, if one counselor is using CM in a treatment program, all counselors are likely to use it, as it is typically adopted as a programwide intervention, whereas MI can be more readily adopted on an individual basis. Although this helps to explain why colleagues' use is a more powerful predictor of CM use as compared with MI use, it does not explain the vast difference between social workers and non-social workers in this regard. Among social workers, use rates were also influenced by attitudes toward EBPs in general for MI and being in recovery for CM. We were surprised to find that positive attitudes toward EBPs among social workers actually lowered the likelihood of use of MI, especially in light of social workers' high ratings of both effectiveness and acceptability of MI. Social workers in recovery were less likely to use CM, likely due to a belief that intrinsic rather than extrinsic motivation is necessary for successful treatment. Among non-social workers, use rates were positively influenced by being in recovery and less experience for MI and by ethnicity for CM.
The results of this study underscore the importance of exposure to EBPs in the development of positive attitudes toward and use of EBPs. In particular, professional networks are an important route to introduce social workers to EBPs, as is professional trainings on specific EBPs. Even though perceptions of the effectiveness of EBPs influence perceptions of the acceptability of EBPs, neither of these factors contribute to the use of MI, and only perceptions of effectiveness influence the use of CM. Thus, efforts to increase the uptake of evidence-based SUD interventions should not be limited to "dissemination of information regarding effectiveness; rather, efforts should be expended to expose social workers to EBPs.
It is important to acknowledge the limitations of the study. First, even though a respectable 58 percent response rate was obtained, response bias is a possibility. Data collected during the clinical director interviews were used as a means to assess response bias in the counselor surveys. Each clinical director reported the sociodemographic characteristics of the program's counseling staff. These figures were aggregated across all participating treatment programs and compared with the aggregate data from the completed surveys. These comparisons revealed no significant differences between the responding counselors and the pool of potential respondents in terms of gender, age, race, education, tenure, or recovery status. Second, the data analyzed are cross-sectional, which limits our ability to determine causal pathways. Third, these data are representative of social workers in the private sector, not the counseling workforce as a whole. Thus, caution should be exercised in generalizing these results to counselors or social workers in excluded settings such as public, Veterans Affairs, and detoxification-only programs. Last, it is important to note that our measure of use cannot be extrapolated to infer treatment fidelity. However, the focus of this study was not treatment fidelity, but rather adoption and use of MI and CM. Despite these limitations, this study provides a unique contribution to our understanding of social workers' attitudes toward and use of MI and CM and the factors that influence these variables.
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Brian E. Bride, PhD, LCSW, is professor and PhD program director, and Sara Kintzle, PhD, MSW, is a research assistant, School of Social Work, University of Georgia, Athens. Amanda J. Abraham, PhD, is assistant professor, Arnold School of Public Health, University of South Carolina, Columbia. Paul M. Roman, PhD, is Regents' Professor of Sociology, Department of Sociology, University of Georgia, Athens. The project described was supported by National Institute on Drug Abuse (NIDA) grants K01DA024718 and R37DA013110. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIDA or the National Institutes of Health. Address correspondence to Brian E, Bride, School of Social Work, University of Georgia, 425 Tucker Hall, Athens, GA 30602-7016; e-mail: email@example.com.
Original manuscript received September 19, 2011
Final revision received January 8, 2012
Accepted January 19, 2012
Advance Access Publication October 16, 2012
Table 1: Sample Demographic and Professional Characteristics Social Workers Variable n % M (SD) Gender Female 194 69.3 Male 86 30.7 Ethnicity African American 25 9.4 Caucasian 235 88.0 Other 7 2.6 Education High school 4 1.4 College degree 60 21.1 Masters or higher 221 77.5 In recovery 97 34.0 Age (years) 278 45.3 (11.7) Years of experience 278 11.6 (9.0) 12-step orientation 280 12.1 (5.0) EBP attitudes 285 6.1 (1.1) MI use by colleagues 285 74.7 CM use by colleagues 285 22.5 MI training 276 5.5 (1.8) CM training 265 3.4 (2.3) Non-Social Workers Variable n % M (SD) p Gender .057 Female 510 63.0 Male 300 37.0 Ethnicity .463 African American 94 11.9 Caucasian 681 86.1 Other 16 1.5 Education <.001 High school 142 17.1 College degree 288 34.8 Masters or higher 398 48.1 In recovery 420 50.5 <.001 Age (years) 811 46.8 (12.2) .074 Years of experience 811 11.2 (9.0) .516 12-step orientation 803 13.9 (4.7) <.001 EBP attitudes 832 5.7 (1.4) <.001 MI use by colleagues 832 73.6 .696 CM use by colleagues 832 18.6 .160 MI training 795 5.5 (1.7) .648 CM training 760 3.4 (2.2) .728 Note: EBP = evidence-based practice; MI = motivational interviewing; CM = contingency management. Table 2: Comparison of Social Workers and Non-Social Workers on Perceptions of Effectiveness and Acceptability and Use of MI and CM Social Workers Variable n % M (SD) Perceptions of effectiveness of MI 258 6.02 (.95) CM 175 4.65 (1.71) Perceptions of acceptability of MI 263 6.62 (.78) CM 220 5.47 (1.83) Use of MI 246 86.3 CM 57 20.0 Non-Social Workers Variable n % M (SD) P Perceptions of effectiveness of MI 753 5.91 (1.15) 0.087 CM 528 4.80 (2.05) 0.323 Perceptions of acceptability of MI 757 6.43 (1.02) 0.002 CM 601 5.31 (2.01) 0.102 Use of MI 675 81.1 0.047 CM 142 17.1 0.264 Note: MI = motivational interviewing; CM = contingency management. Table 3: Multiple Regression Analyses of Social Workers' and Non-Social Workers' Ratings of the Effectiveness of MI and CM Social Workers MI Variable b (SE) [beta] Gender .171 (0.12) .083 Ethnicity -.204 (0.17) -.068 Education .327 (0.14) * .142 Tenure -.017 (0.01) ** -.158 Recovery .125 (0.11) .063 12-step orientation -.004 (0.01) -.022 EBP attitudes .103 (0.05) .125 Use by colleagues .491 (0.16) *** .205 Amount of training .222 (0.04) *** .357 Adjusted [R.sup.2] .241 n 230 Social Workers CM Variable b (SE) [beta] Gender .272 (0.26) .08 Ethnicity -.380 (0.32) -.09 Education .093 (0.31) .03 Tenure -.013 (0.01) -.07 Recovery -.034 (0.25) -.01 12-step orientation -.002 (0.03) -.O1 EBP attitudes .199 (0.13) .14 Use by colleagues .459 (0.25) *** .13 Amount of training .313 (0.06) .43 Adjusted [R.sup.2] .240 n 155 Non-Social Workers MI Variable b (SE) [beta] Gender .149 (0.10) .063 Ethnicity -.293 (0.12) * -.09 Education -.108 (0.09) -.047 Tenure -.008 (0.01) -.067 Recovery .055 (0.09) .024 12-step orientation -.007 (0.01) -.027 EBP attitudes .137 (0.04) *** .161 Use by colleagues .052 (0.12) .019 Amount of training .201 (0.03) *** .272 Adjusted [R.sup.2] .111 n 741 Non-Social Workers CM Variable b (SE) [beta] Gender .399 (0.23) .096 Ethnicity -.227 (0.21) -.042 Education -.067 (0.20) -.016 Tenure -.024 (0.01) -.102 Recovery .019 (0.19) .005 12-step orientation 002 (0.02) .006 EBP attitudes .083 (0.08) .056 Use by colleagues .396 (0.17) * .087 Amount of training .113 (0.05) * .121 Adjusted [R.sup.2] .035 n 523 Note: MI = motivation al interviewing; CM = contingency management; EBP = evidenced-based practice. * p < .05. ** p < .01. *** p < .001. Table 4: Multiple Regression Analyses of Social Workers' and Non-Social Workers' Ratings of the Acceptability of MI and CM Social Workers MI Variable b (SE) [beta] Gender .098 (0.09) .058 Ethnicity .122 (0.14) .050 Education .94 (0.12) .050 Tenure -.009 (0.00) * -.106 Recovery .059 (0.09) .037 12-step orientation -.008 (0.01) -.053 EBP attitudes .054 (0.04) .076 Use by colleagues .303 (0.14) * .153 Amount of training -.023 (0.04) -.044 Effectiveness .426 (0.07) *** .516 Adjusted [R.sup.2] .361 n 227 Social Workers CM Variable b (SE) [beta] Gender .060 (0.24) .017 Ethnicity .348 (0.27) .076 Education .080 (0.20) .021 Tenure -.022 (0.01) -.121 Recovery .126 (0.21) .036 12-step orientation -.010 (0.02) -.03 EBP attitudes .189 (0.08) * .124 Use by colleagues .345 (0.18) .095 Amount of training .120 (0.05) * .157 Effectiveness .615 (0.07) *** .592 Adjusted [R.sup.2] .576 n 150 Non-Social Workers MI Variable b (SE) [beta] Gender .134 (0.07) .007 Ethnicity .143 (0.08) .051 Education .122 (0.06) .062 Tenure -.010 0.00) * -.086 Recovery -.105 (0.06) -.053 12-step orientation -.012 (0.01) -.057 EBP attitudes .058 (0.2) ** .079 Use by colleagues -.026 (0.08) -.011 Amount of training .039 (0.03) .059 Effectiveness .459 (0.5) *** .525 Adjusted [R.sup.2] .339 n 728 Non-Social Workers CM Variable b (SE) [beta] Gender -.277 (0.13) * -.066 Ethnicity -.053 (0.18) -.010 Education .329 (0.13) * .080 Tenure -.020 (0.01) * -.085 Recovery -.095 (0.16) -.023 12-step orientation -.033 (0.14) * -.078 EBP attitudes .133 (0.05) ** .088 Use by colleagues .249 (0.14) *** .054 Amount of training .135 (0.04) .141 Effectiveness .611 (0.04) *** .604 Adjusted [R.sup.2] .460 n 509 Note: MI = motivational interviewing; CM = contingency management; EBP = evidenced-based practice. * p < .05. ** p < .01. *** p < .001. Table 5: Logistic Regression Analyses of Social Workers' and Non-Social Workers' Use of MI and CM Social Workers MI Variable OR (95% CI) Gender 0.26 (0.06, 1.06) Ethnicity -- -- Education 0.74 (0.11, 4.90) Tenure 0.92 (0.84, 1.00) Recovery 0.37 (0.38, 3.54) 12-step orientation 0.98 (0.84, 1.14) EBP attitudes 0.45 ** (0.26, 0.79) Use by colleagues 12.95 ** (2.13, 78.65) Amount of training 2.17 ** (1.23, 3.82) Effectiveness 1.84 (0.54, 6.26) Acceptability 3.17 * (1.28, 7.86) Nagelkerke [R.sup.2] .566 n 200 Social Workers CM Variable OR (95% CI) Gender 1.73 (0.32, 9.44) Ethnicity 1.19 (0.30, 4.64) Education 0.32 (0.09, 1.20) Tenure 0.99 (0.92, 1.06) Recovery 0.11 * (0.02, 0.74) 12-step orientation 1.04 (0.91, 1.19) EBP attitudes 0.64 (0.38, 1.08) Use by colleagues 100.96 *** (13.84, 736.28) Amount of training 1.84 ** (1.20, 2.82) Effectiveness 2.26 ** (1.30, 3.91) Acceptability 0.73 (0.41, 1.31) Nagelkerke [R.sup.2] .713 n 146 Non-Social Workers MI Variable OR (95% CI) Gender 0.65 (0.29, 1.43) Ethnicity 0.66 (0.23, 1.87) Education 1.74 (0.95, 3.18) Tenure 0.95 ** (0.91, 0.98) Recovery 2.16 * (1.11, 4.18) 12-step orientation 0.95 (0.89, 1.02) EBP attitudes 0.78 (0.60, 1.01) Use by colleagues 16.57 *** (7.61, 36.11) Amount of training 2.17 *** (1.82, 2.60) Effectiveness 1.27 * (1.02, 1.58) Acceptability 0.99 (0.74, 1.33) Nagelkerke [R.sup.2] .554 n 719 Non-Social Workers CM Variable OR (95% CI) Gender 0.73 (0.41, 1.28) Ethnicity 0.42 * (0.20, 0.88) Education 0.60 (0.31, 1.19) Tenure 0.97 (0.94, 1.01) Recovery 0.65 (0.35, 1.19) 12-step orientation 1.02 (0.97, 1.08) EBP attitudes 0.88 (0.71, 1.10) Use by colleagues 19.69 *** (10.88, 35.63) Amount of training 1.40 *** (1.21, 1.62) Effectiveness 1.16 (0.99, 1.36) Acceptability 1.09 (0.91, 1.31) Nagelkerke [R.sup.2] .545 n 497 Notes: Dashes represent the fact that MI (motivational interviewing) was dropped from the model because it perfectly predicts MI use in the social work subsample. CM = contingency management; OR = odds ratio; CI = confidence interval. * p < .05. ** p < .01. *** p < .001.
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