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Attitudes toward and training in medications for opioid use disorders: a descriptive analysis among employees in the youth legal system and community mental health centers

Substance Abuse Treatment, Prevention, and Policy volume 19, Article number: 32 (2024) Cite this article

Abstract

Background

Research demonstrates gaps in medications for opioid use disorder uptake (MOUDs; methadone, buprenorphine, and naltrexone) especially among adolescents. These gaps may be partly attributable to attitudes about and training in MOUDs among youth-serving professionals. We extended prior research by conducting descriptive analyses of attitudes regarding effectiveness and acceptability of MOUDs, as well as training in MOUDs, among youth legal system (YLS) employees and community mental health center (CMHC) personnel who interface professionally with youth.

Methods

Using survey data from participants (n = 181) recruited from eight Midwest counties, we examined: (1) differences in MOUD attitudes/training by MOUD type and (2) by respondent demographics, and (3) prediction of MOUD attitudes/training by participant-reported initiatives to implement evidence-based practices (EBPs), workplace culture around EBPs, and workplace stress. Attitudes and training were measured in reference to five MOUD types (methadone, oral buprenorphine, injectable buprenorphine, oral naltrexone, injectable naltrexone) on three subscales (effectiveness, acceptability, training).

Results

Wilcoxon signed-rank tests demonstrated that most outcomes differed significantly by MOUD type (differences observed among 22 of 30 tests). Kruskal-Wallis tests suggested MOUD differences based on demographics. For methadone, CMHC providers endorsed greater perceived effectiveness than YLS providers and age explained significant differences in perceived effectiveness. For buprenorphine, CHMC providers viewed oral or injectable buprenorphine as more effective than YLS employees, respondents from more rural counties viewed oral buprenorphine as more effective than those from less rural counties, and age explained differences in perceived effectiveness. For naltrexone, perceived gender differed by gender. Hierarchical ordinal logistic regression analysis did not find an association between personal initiatives to implement EBPs, workplace culture supporting EBPs, or workplace stress and effectiveness or acceptability of MOUDs. However, personal initiatives to implement EBPs was associated with training in each MOUD.

Conclusions

These results highlight a few key findings: effectiveness/acceptability of and training in MOUDs largely differ by MOUD type; setting, rurality, age, gender, and education explain group differences in perceived effectiveness of and training in MOUDs; and implementing EBPs is associated with training in MOUDs. Future research would benefit from examining what predicts change in MOUD attitudes longitudinally.

Introduction

Addressing opioid misuse and opioid use disorders among youth (i.e., 12–17 years old) is an urgent need. Rates of synthetic opioid overdose mortality increased nearly 3000% between 1999 and 2021 [1], and since 2020, opioid overdose mortality among adolescents increased at a higher rate than adults [2]. Research suggests that approximately 3.5% of youth (1.5 million youth) reported misusing prescription opioids (using one’s own medication in any way not directed by a doctor or using without a prescription) [3, 4]. Rates of opioid use disorder (OUD) diagnosis has increased 6-fold from 2001 to 2014 among 13- to 25-year-olds [5]. Medications for opioid use disorder (MOUDs)─methadone, buprenorphine, and naltrexone─are evidence-based treatments that have been shown to be safe and effective at reducing opioid-related and overall mortality, substance use, physical and psychological problems, and legal involvement in adults [6,7,8]. MOUDs are also associated with increased treatment retention [8]. Significantly less research on MOUDs has been conducted among youth compared to adults, yet buprenorphine, naltrexone, and methadone receipt have all been associated with improved treatment retention and reduced non-prescribed opioid use while on the medication [9, 10]. The American Academy of Pediatrics, American Academy of Child and Adolescent Psychiatry, and Society for Adolescent Health and Medicine have endorsed MOUDs for adolescents.

Despite these recommendations, youth access is low [11, 12]. A study of adolescents with a documented OUD diagnosis and connected with primary care found that 86% of 16- to 17-year-olds did not receive an MOUD [13]. Youth admitted to substance use treatment services are less likely to have MOUDs included as part of their treatment plan compared to adults (2% vs. 93%) [14]. Further, a review of 160 residential substance use treatment centers that provide youth services found that only a quarter offered MOUDs [15]. While not specific to youth, research has also found that those who interact with the legal system are unlikely to receive MOUDs when diagnosed with OUD [12].

Previous research has examined attitudes toward MOUDs among various groups (e.g., physicians, people who have an OUD history). Across studies, positive attitudes toward the acceptability and effectiveness of MOUDs were associated with more knowledge about MOUDs, more frequent interaction with patients receiving MOUDs, and less stigmatizing beliefs about substance use disorders [16]. Among both prescribing and non-prescribing healthcare providers, those with more exposure to pharmacological interventions had more positive MOUD attitudes [16]. Exposure to MOUDs may be related to more specialized training and increased knowledge about their effectiveness, thereby increasing their acceptability. Among providers and the general public, greater endorsement of abstinence-only treatment philosophies (which extends to MOUDs) is negatively associated with MOUD acceptability [16, 17], and greater endorsement of viewing OUD as an illness was positively associated with beliefs about MOUD effectiveness [18]. Importantly, attitudes appear to differ by MOUD and profession. For example, physicians rated buprenorphine as more effective than methadone (contrary to the robust literature supporting methadone) [19], which was rated as more effective than naltrexone in treatment for OUD [20]. Medical professionals also held more positive views toward MOUDs compared to health care support staff [21]. Outside the health profession, US legal system personnel who endorsed stigmatizing beliefs toward legal-involved individuals endorsed more negative MOUD attitudes [22].

Closely tied to attitudes and knowledge about MOUDs is training in MOUDs. Physicians who have received training in addiction treatment or work closely with those with specialized training endorse more positive attitudes toward MOUDs [16]. Additionally, physicians rated both their knowledge about MOUDs and likelihood to prescribe MOUDs as higher following MOUD waiver training in medical school [23]. Substance use treatment counselors were also more likely to rate buprenorphine as effective if they received buprenorphine-specific training [24].

MOUD attitudes and training at the individual level need to be contextualized within workplace-related factors, which can facilitate or impede MOUD uptake. For example, physicians’ perception of their emergency department as having an innovative climate was associated with MOUD support [25]. Less emphasis on 12-step models in substance use treatment centers was associated with greater counselor-rated MOUD acceptability and effectiveness [26]. Within the adult legal system, rehabilitation-oriented agencies were more supportive of MOUDs [27]. Organizational culture surrounding attitudes toward evidence-based practice (EBP) likely extend to MOUDs, as negative attitudes toward EBPs could correspond to lower support or administration of MOUDs, consistent with an extensive literature linking such attitudes with minimal EBP uptake [28]. Organizational culture may also be captured through occupational stress, and prior research has demonstrated that workplace-related stress was associated with less interest in EBP adoption [29]. Considering associations between demographic and workplace-related factors and MOUD attitudes and training may help identify intervention targets to ultimately increase use of evidence-based substance use treatment for youth.

Prior research has guided our understanding of how various groups view MOUDs; however, three significant gaps remain. First, research has largely been conducted among medical health providers (i.e., physicians, nurses, pharmacists), with less research attention paid to other professionals from other systems. Among mental health providers broadly, research has focused on those working in substance use treatment centers (e.g., social workers, counselors, psychologists, peer recovery coaches) [30]. However, there is a significant gap in knowledge about MOUD attitudes and training among those who work in community mental health centers (CMHC) [31]. In addition to the lack of research among CMHC providers, there is limited research among professionals within the youth legal system (YLS). One review found support for the pervasiveness of negative attitudes toward MOUDs in the criminal justice system broadly [32] but this has not been extended to the YLS. Second, research has been predominantly carried out among people who serve adults, and attitudes and experiences of youth-serving professionals have been neglected. Welsh and colleagues (2022) found that substance use treatment staff were less likely to support MOUD use in adolescents compared to adults; research specifically focused on employees who interface professionally with youth is needed. Third, most research has focused on buprenorphine and methadone, with less research available on naltrexone. Despite higher youth prescription rates of buprenorphine compared to naltrexone [5], naltrexone continues to be prescribed to youth. A scoping review of 152 studies examining MOUD perceptions among patients and providers included 63 about buprenorphine, 115 about methadone, and 16 about naltrexone, demonstrating the considerable gap in attitudinal research about naltrexone [33]. This review included research from outpatient and inpatient substance use treatment programs, prisons, and primary care offices, emphasizing that naltrexone attitudes and training are not well understood among CMHC and YLS employees.

Taken together, focusing on CMHC and YLS professionals is crucial in understanding potential upstream effects on youth substance use treatment. CMHC and YLS professionals may affect whether youth are referred for treatment [34], as well as youth attitudes toward MOUDs, willingness to engage in treatment, and adherence to medication once prescribed [26, 31, 35].

The current paper aims to address gaps in the literature by conducting a descriptive analysis of MOUD attitudes and training among youth-interfacing CMHC and YLS professionals. First, while research has traditionally examined MOUDs separately, it remains an empirical question whether MOUD attitudes or training differ by MOUD (Aim 1). Second, given the need to further explore group differences in MOUD attitudes and training, we examined whether demographic information explained group differences in MOUD attitudes and training (Aim 2). Third, we examined the association between MOUD attitudes and training with demographic variables and workplace-related variables in hierarchical regression models. While the aims were exploratory, we hypothesized that methadone would be viewed less favorably compared to buprenorphine and naltrexone, CMHC employees would have more positive attitudes toward and more training in MOUDs compared to YLS employees, and endorsing a workplace culture supportive of EBPs would be associated with favorable MOUD attitudes and more training.

Materials and methods

Sample

The current sample was derived from the Alliances to Disseminate Addiction Prevention and Treatment (ADAPT) project in eight counties in a Midwest state [36]. The primary aim was to study the implementation of a learning health system between the YLS and CMHCs to increase legal-involved-youth connection to evidence-based substance use treatment. ADAPT was preregistered and approved by the author’s Institutional Review Board (Protocol #1910282231). Ethical standards were in accordance with the Declaration of Helsinki.

As part of this study, surveys of YLS and CMHC personnel were collected at five waves from 2020 to 2023 administered approximately every seven months. Subjects were identified through publicly available staff rosters, organization charts, or agency lists of contact information. Those recruited for study participation included frontline staff (i.e., probation officers, therapists, skills trainers), staff supervisors, and agency decisionmakers. Potential subjects were contacted to participate via email. We utilized data from the first wave of data collection to avoid potential changes in attitudes due to project involvement. There were 227 individuals (71 [31.3%] YLS and 156 [68.7%] CMHC) who were considered eligible and sent an invitation to participate in the first wave survey. Of those eligible, 37 (16.3%) were excluded due to no response (n = 36 [5 YLS and 31 CMHC]) or declined to participate (n = 1 [YLS]); 190 individuals (83.7%) were enrolled at baseline. Individuals provided informed consent to voluntarily participate in data collection; nine individuals did not provide affirmative consent resulting in a final analytical sample of 181 individuals. Sample characteristics are found in Appendix 1. Data are not made publicly available to protect study participant privacy. Data analytic code will be made available upon request.

Measures

Demographic predictors

The following respondent demographic information was collected: age (18–25, 26–35, 36–45, 46–55, 56–65 years old, 66 or older), race (White, Black/African American, American Indiana or Alaska Native, Asian, Native Hawaiian or Pacific Islander, Other), ethnicity (Hispanic/Latinx, Non-Hispanic/Non-Latinx, do not know), gender (female, male, transgender, nonbinary), time in position (less than one year, 1–4 years, 5–9 years, 10–14 years, 15–19 years, 20 or more years), highest education (high school, some college, Associate’s, Bachelor’s, Master’s, doctorate), job satisfaction (very dissatisfied, dissatisfied, not satisfied or dissatisfied, satisfied, very satisfied), rurality of the county in which they work (more versus less rural), and county in which they work. For rurality, we utilized the Purdue University Index of Relative Rurality from 2010 [37] with a cutoff of 0.42; less rural counties’ IRR scores ranged from 0.40 to 0.42 and more rural counties ranged from 0.45 to 0.53.

Workplace-related predictors: endorsement of evidence-based practices

Endorsement of evidence-based practices: Implementation Citizenship Behavior Scale (ICBS) and Implementation Climate Scale (ICS)

Developed by Ehrhart and colleagues (2015), the ICBS is a six-item questionnaire that measures employees’ support and pursuit of EBP implementation within two domains: helping others (e.g., “Assist others to make sure they implement evidence-based practices properly”) and remaining informed on EBPs (e.g., “Keeping informed of changes in evidence-based practice policies and procedures”). Response options are measured on a 5-point Likert from 0 (not at all) to 4 (frequently, if not always), and items were averaged. In the current sample, Cronbach’s alpha was 0.86.

Developed by Ehrhart and colleagues (2014), the ICS is an 18-item measure of organizational climate of EBP implementation along six subscales: (1) focus on EBP (e.g., “One of this team’s main goals is to use evidence-based practice effectively”), (2) educational support for EBP (e.g., “This team provides conferences, workshops, or seminars focusing on evidence-based practices”), (3) recognition for EBP (e.g., “Staff on this team who use evidence-based practice are seen as experts”), (4) rewards for EBP (e.g., “This team provides financial incentives for the use of evidence-based practices”), (5) selection for EBP (e.g., “This team selects staff who have had formal education supporting evidence-based practice”), and (6) selection for openness (e.g., “This team selects staff open to new types of interventions”). Response options were scored on a 5-point Likert from 0 (not at all) to 4 (very great extent), and all items were averaged. In the current sample, Cronbach’s alpha was 0.93.

Endorsement of workplace stress: Texas Christian University Systems of Organizational Functioning Survey

The Texas Christian University Institute of Behavioral Research developed the Systems of Organizational Functioning survey [38, 39], which is a 162-item measure comprised of 10 scales that index a wide range of organizational factors including readiness for change, job attitudes, workplace factors, and organizational climate. The Texas Christian University Institute of Behavioral Research developed the Systems of Organizational Functioning survey [38, 39], which is a 162-item measure comprised of 10 scales that index organizational factors including readiness for change, job attitudes, workplace factors, and organizational climate. The stress subscale was utilized, which is a four-item measure capturing workplace stress and pressures (e.g., “Staff members are under too many pressures to do their jobs effectively”). Respondents were asked rate their agreement with the statements on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). The items were averaged for analysis. In the current sample, Cronbach’s alpha was 0.92.

Primary outcome

Attitudes toward MOUD treatment

Survey respondents were asked to rate the perceived effectiveness and acceptability of MOUDs, as well as their training in MOUDs. For effectiveness, respondents were prompted by the following question, “Based on your knowledge and personal experience, to what extent do you consider each of the following medications for opioid use disorder to be effective with justice involved populations?” Response options ranged from 1 (not at all effective) to 7 (very effective). For acceptability, respondents were prompted by the following question, “In your opinion, how acceptable is each of the following medications for the treatment of opioid use disorder with justice involved populations?” Response options ranged from 1 (completely unacceptable) to 7 (very acceptable). For training, respondents were prompted by the following question, “To what extent have you received specific training about the following?” Response options ranged from 0 (no training) to 7 (extensive training). Refer to Appendix 2 for univariate statistics of each item. Therefore, all questions were not specifically referring to MOUDs for adolescents. For each scale (i.e., effectiveness, acceptability, and training), respondents answered questions corresponding to five MOUDs: methadone, oral buprenorphine (Suboxone®), monthly (extended-release) injection buprenorphine (Sublocade®), oral naltrexone, and monthly injection naltrexone (Vivitrol®).

Analysis

To examine differences by MOUD type (Aim 1), we performed Wilcoxon signed-rank tests, which is a nonparametric test to compare median differences of ordinal variable distributions derived from the same sample. To determine differences in MOUD outcomes by demographic variables (Aim 2), we conducted Kruskal-Wallis tests. For each analysis, a complete case sample was used.

For Aim 3, we pursued multiple imputation to increase sample size given the numerous variables included in the multivariable models. First, we removed individuals who were missing demographic information (i.e., age, race, ethnicity, gender, time at position, job satisfaction, highest education level, and county; n = 5). Second, we required at least 20% data availability by each MOUD subscale (i.e., at least one MOUD item response) and, therefore, removed those who were missing all MOUD items when rating effectiveness, acceptability, and training (n = 69) to avoid imputing an entire subscale. The final sample size was 105 respondents (sample characteristics found in Appendix 1). Third, we conducted multiple imputation with 10 imputations (for a total of 1,050 analyzable observations) using the fully conditional specification to impute categorical response options for all 15 MOUD item-level outcomes [40]. Fourth, we predicted MOUD outcomes from the ICBS, ICS, and stress scale (Aim 3). We conducted hierarchical ordinal logistic regression with a random effect for system (YLS vs. CMHC) nested within county. Multinomial distribution and cumulative logit options were specified. Demographic variables (i.e., age, race, ethnicity, education level, time at position, job satisfaction, and rurality) were included as covariates, as well as fixed effects of system. All analyses were conducted in SAS 9.4 [41].

Results

For Aim 1, we compared MOUDs by each subscale using Wilcoxon signed-rank tests (Table 1). Results suggested that perceived effectiveness of MOUDs differed significantly by type of MOUD except for the following comparisons: oral buprenorphine versus injectable buprenorphine, and oral buprenorphine versus oral naltrexone. For acceptability, the following comparisons were not statistically significantly different: oral buprenorphine versus injectable buprenorphine, oral buprenorphine versus oral naltrexone, and injectable buprenorphine versus oral naltrexone. Finally, for training, the following comparisons were not statistically significantly different: methadone versus oral buprenorphine, methadone versus injectable naltrexone, and oral naltrexone versus injectable naltrexone.

Table 1 Wilcoxon signed-rank test comparing MOUD attitudes by MOUD type
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In addition to examining whether the comparison tests were significant, the direction of the Wilcoxon signed-rank test also demonstrated important findings. Among the comparison tests that were statistically significant, methadone was viewed as less effective and acceptable compared to every other MOUD. When comparing buprenorphine and naltrexone, oral route of administration was viewed as less effective and acceptable compared to injectable route of administration. Specifically, oral buprenorphine was rated as less effective and acceptable than injectable naltrexone, and injectable buprenorphine was viewed as more effective than oral naltrexone. However, when comparing injectable buprenorphine and injectable naltrexone, buprenorphine was viewed as less effective and acceptable (Table 1).

For training in MOUDs, respondents reported more training in oral buprenorphine compared to all other MOUDs (Table 1), followed by methadone which had greater training than injectable buprenorphine and naltrexone. Respondents rated less training in injectable buprenorphine than naltrexone and less training in oral naltrexone than injectable naltrexone.

For Aim 2, we conducted a series of Kruskal-Wallis tests to examine whether demographic variables differed by MOUD item. When examining effectiveness of MOUDs (Table 2), we found group differences in perceived MOUD effectiveness based on system (i.e., YLS vs. CMHC), rurality, age, gender, and education level. There was a significant difference between YLS and CMHC respondents for methadone (χ2 = 4.13 [1, p = 0.04]), oral buprenorphine (χ2 = 10.77 [1, p < 0.01]), and injectable buprenorphine (χ2 = 5.48 [1, p = 0.02]); CMHC respondents rated all as more effective than YLS respondents. Respondents from more rural counties rated oral buprenorphine as more effective than those from less rural counties (χ2 = 3.92 [1, p = 0.05]). Significant differences by age were observed for methadone (χ2 = 12.28 [5, p = 0.03]), oral buprenorphine (χ2 = 13.85 [5, p = 0.02]), and injectable buprenorphine (χ2 = 17.29 [5, p < 0.01]). Post hoc pairwise two-sided comparisons demonstrated that 46- to55-year-olds rated methadone as less effective than 36- to 45-year-olds (Wilcoxon Z = -2.96, p = 0.04), and 36- to 45-year-olds rated injectable buprenorphine as more effective than 56- to 65-year-olds (Wilcoxon Z = 2.96, p = 0.04). Significant differences in injectable naltrexone were based on gender (χ2 = 6.91 [2, p = 0.03]), and finally, differences in oral buprenorphine were observed by education level (χ2 = 15.9 [4, p < 0.01])

Table 2 Results from Kruskal-Wallis Tests of Group Differences in Effectiveness of MOUDs by Demographic Variables
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When examining acceptability, there were no statistically significant group differences based on demographic groups (Appendix 3).

When examining training in MOUDs, age and education level were associated with group differences (Table 3). We found that endorsement of training for methadone (χ2 = 20.16 [5, p < 0.01]), oral buprenorphine (χ2 = 11.90 [5, p = 0.04]), and injectable buprenorphine (χ2 = 13.65 [5, p = 0.02]) differed by age. Post hoc pairwise two-sided comparisons demonstrated that for methadone, 46-55-year-olds endorsed less training than 36-45-year-olds (Wilcoxon Z = -2.96, p = 0.04) and 36-45-year-olds endorsed more training than 18-25-year-olds (Wilcoxon Z = 3.18, p = 0.02). Additionally, 18-25-year-olds endorsed less injectable buprenorphine training than those older than 65 (Wilcoxon Z = -2.94, p = 0.04). When examining by education level, we observed a significant difference in training for oral buprenorphine (χ2 = 15.71 [4, p < 0.01]). Post hoc pairwise two-sided comparisons demonstrated those with a Master’s degree had more training than those with a Bachelor’s (Wilcoxon Z = 3.00, p = 0.02).

Table 3 Results from Kruskal-Wallis Tests of Group Differences in Training in MOUDs by Demographic Variables
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For Aim 3, we conducted hierarchical ordinal logistic regression to examine the association between ICBS, ICS, and stress scale and MOUD effectiveness, acceptability, and training. The ICBS, ICS, and stress scale did not predict any MOUD effectiveness or acceptability. ICBS predicted each MOUD outcome when examining training. For example, for each unit increase in ICBS, the cumulative logit of being in the lowest response category (i.e., no training) for methadone training decreased by 0.96 (95% CI -1.87, -0.05). Stated differently, with greater endorsement on the ICBS scale, the likelihood of endorsing less methadone training decreased. (Table 4).

Table 4 Results from Cross-Sectional Hierarchical Ordinal Logistic Regression using Multiply Imputed Dataset
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Discussion

The current paper aimed to characterize attitudes toward and training in MOUDs among those who interact professionally with youth. Specifically, we aimed to determine whether MOUDs differ from one another, whether MOUD ratings differed by demographic characteristics, and the association between workplace-related variables and MOUDs.

Aim 1: Differences between MOUD type

First, numerous important findings emerged when comparing attitudes about and training in different types of MOUD. Results indicated that 22 out of the 30 analyses (10 comparisons each for effectiveness, acceptability, and training) suggested statistically significant differences. Acceptability and effectiveness demonstrated similar results, such that there were no statistically significant differences demonstrated for type of buprenorphine (oral versus injection). Therefore, attitudes toward buprenorphine may be similar regardless of routes of administration. However, buprenorphine training differed by route of administration; individuals reported receiving more oral buprenorphine training compared to every other MOUD.

Interestingly, methadone was viewed as the least effective or acceptable MOUD, which is consistent with prior research among counselors at substance use treatment centers [31]. However, respondents had more training in methadone compared to all MOUDs except oral buprenorphine. This study cannot establish directionality in the relationship between attitudes and training and, therefore, cannot illuminate this paradoxical finding, as we would expect training facilitates the increase in positive attitudes towards interventions. This finding may also reflect a cohort effect, as methadone has been regulated for OUD since the 1970s and approximately 60% of the sample is over age 36 and 33% over age 46. Respondents may be more familiar with methadone and may continue to hold more negative attitudes about methadone compared to other MOUDs. Despite daily administration with behavioral supports, research continues to support that the general public [52], OUD patients [53], and providers [42] hold more negative views toward methadone compared to buprenorphine and naltrexone.

While methadone demonstrated reduced acceptability and perceived effectiveness compared to buprenorphine and naltrexone, attitudes toward buprenorphine and naltrexone appeared to differ based on route of administration, where injection was viewed as more effective and acceptable than oral. While prior research has demonstrated the limited effectiveness of oral naltrexone with regard to opioid abstinence and treatment engagement in applied settings [54], we are not aware of prior research that has investigated perceived acceptability and effectiveness of MOUD by route of administration among CMHC and YLS respondents; future research is needed to replicate this finding.

Aim 2: Difference between MOUD and demographic variables

For the second aim, group differences were explored by MOUD. System, rurality, age, gender, and education level explained group differences in effectiveness, and age and education level explained differences in training. Notably, there were system-level differences in methadone and buprenorphine; CMHC employees reported greater perceived effectiveness of methadone and buprenorphine (both oral and injectable) than YLS employees. This is consistent with prior research demonstrating particularly negative MOUD attitudes among legal system employees [55]. These differences in attitudes may be due to numerous possible explanations, such as the nature of interactions with populations presenting with substance use concerns, stigmatizing beliefs of substance use disorders, and minimal resources to obtain ongoing professional training. Respondents employed in more rural counties rated oral buprenorphine as more effective than those in less rural counties. Prior research presents a conflicting picture about MOUD attitudes and rurality. Prior research that has examined rural-specific MOUD barriers identified both availability and acceptability barriers; there are few MOUD providers and providers have negative attitudes about substance use intervention [46]. However, other research has found that substance use treatment clinic providers in rural clinics endorsed more positive perceptions of naltrexone than less rural providers [30], and non-prescribing providers in rural communities endorsed more favorability of MOUD-only treatment compared to combined medication and psychosocial interventions [35]. The role of rurality on MOUD attitudes may be dependent on numerous factors (e.g., access/availability) not examined in the current study.

While gender is crudely estimated in the current study and likely interacts with a host of other factors (e.g., employment in CMHC vs. YLS, education level, stigmatizing beliefs), our results found a significant difference by gender when examining perceived effectiveness of injectable naltrexone. Post hoc pairwise comparisons did not reveal significant differences, potentially explained by low power. Prior research has demonstrated that women endorsed more favorable views toward EBPs than men [49]. Ongoing research is needed to understand the interaction between various identities to understand why such group identities may facilitate or hinder MOUD beliefs and training.

Finally, age and education level differentiated perceived effectiveness and training in various MOUDs. No clear pattern emerged by MOUD type, and results are best summarized as early and middle career professionals (aged 36–45 years) perceived certain MOUDs as more effective and had more training in certain MOUDs than younger and older age groups. We did not have measures of the amount or type of MOUD training; however, we suspect that this 36- to 45-year-old age group is correlated with professional experience and continuing education related to substance use disorder interventions (including medications). Prior research has demonstrated associations among age, education, and attitudes toward MOUDs. For example, providers working in substance use treatment facilities who had more advanced degrees endorsed greater perceived effectiveness of methadone, buprenorphine, and naltrexone. Of note, apart from gender, attitudes toward naltrexone did not differ by demographic variables. Our observed null results for naltrexone may indicate insufficient power and/or be reflective of minimal knowledge or training about this medication among a primarily youth-serving workforce.

Aim 3: MOUD prediction from workplace variables

When examining associations between workplace variables and MOUDs, the Implementation Citizenship Behavior Scale (ICBS) predicted training in each MOUD, such that greater ICBS endorsement was associated with more endorsed MOUD training. This finding attests to the importance of individual characteristics and attitudes (to pursue EBPs) in actual practice. However, there may exist a sequence between organizational climate promoting individual initiatives, which may in turn be related to EBPs training. Or, perhaps, organization climate may moderate the relationship between personal initiatives to implement EBPs and EBP training. Such analyses were not possible given the cross-sectional data. Future studies that explore the relationship among organizational and individuals support of EBPs would be beneficial to strengthen understanding of multi-level interventions to promote MOUD uptake.

Additionally, it is worth noting that no workplace variables were significantly associated with perceptions of the effectiveness or acceptability of MOUDs. It is uncertain whether the sample is underpowered to detect such effects, or these workplace variables are unrelated to MOUD attitudes. Most research investigating MOUD attitudes calls for an increase in MOUD training, or mental health training more broadly [45]. However, much research is needed to determine what training and for whom is most potent in changing MOUD attitudes, and relatedly, how MOUD attitudes impact messages delivered to legal-involved youth.

Strengths and limitations

The current study was strengthened by examining MOUDs across domains (i.e., attitudes toward effectiveness and acceptability, and training) and their relationship to numerous demographic and workplace characteristics. Additionally, past research on MOUDs is focused on health care professionals’ attitudes, with minimal research on employees within the YLS. The combination of both YLS and CMHC employees also allowed for comparing by system.

Despite these strengths, the study was limited by a few key factors. First, we lacked specificity in the questionnaire about attitudes toward and training in MOUDs for youth. Prior research has demonstrated that attitudes toward MOUDs differ based on whether questions pertained to youth or adults [14]. As examples, oral naltrexone prescribing patterns may differ between adults and youth, as the adult addiction workforce is comparatively naïve to oral naltrexone, while prescribers to youth may be more comfortable with daily observed oral dosing in youth who have caregiver supervision. Methadone is also rarely prescribed for adolescents and, therefore, may not be viewed as acceptable for youth. It is important to investigate attitudes towards and training in MOUDs when referencing treatment for youth versus adults.

Second, the sample of respondents was predominantly a White, Non-Hispanic population. Beliefs about MOUDs and messages conveyed to youth may differ based on respondent race (and its interaction with youth race). Given the homogenous sample in terms of race and ethnicity, we grouped individuals identifying with the non-majority group into one group, which limits our understanding within and across minority groups.

Third, we did not collect information from survey respondents about their lived experience with opioid use. Attitudes toward MOUDs may be dependent on personal experience with opioid use [44] and would be important to consider in future studies. Relatedly, while data for the current study were derived from a larger mixed-methods study, we did not conduct qualitative interviews to understand respondents’ views toward MOUDs, which may have offered clarification regarding attitudes toward specific MOUDs and prior MOUD training. Combining quantitative analysis with follow-up qualitative interviews will advance the field in elucidating potential mechanisms to change MOUD attitudes, or attitudes toward substance use disorders, more broadly.

Finally, we did not investigate how attitudes and training are related to messaging provided to youth and treatment referrals. Prior research has suggested that both theories of reasoned action and planned behavior predicted whether substance use treatment providers recommended medication for substance use disorders [56]; such theories may aid interventions with key stakeholders.

Conclusions

The current study investigated attitudes toward and training in MOUDs among employees in the YLS and CMHCs who interface with youth professionally. Using cross-sectional survey data from 181 respondents, we found that MOUDs largely differed from one another; system (YLS vs. CMHC), rurality age, gender, and education level explained differences in perceived effectiveness and training in certain MOUDs; and personal initiatives to support and implement EBPs in one’s workplace were associated with MOUD training. The results establish descriptive analyses to help direct future intervention studies to facilitate positive attitudes toward and uptake of MOUDs. We recommend future studies consider examining MOUD by route of administration to examine the replicability of our results, as well as examine the predictors or and mediators of MOUD attitudes in longitudinal studies. Notably, the role of organizational factors, lived experience with opioid use, and MOUD training are important factors to examine in relation to MOUD attitudinal change.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

MOUD:

Medication for opioid use disorder

OUD:

Opioid use disorder

EBP:

Evidence-based practice

CMHC:

Community mental health centers

YLS:

Youth legal system

ADAPT:

Alliances to Disseminate Addiction Prevention and Treatment

ICBS:

Implementation Citizenship Behavior Scale

ICS:

Implementation Climate Scale

ANOVA:

Analysis of variance

CI:

Confidence interval

References

  1. Gaither JR. National trends in Pediatric deaths from fentanyl, 1999–2021. JAMA Pediatr. 2023;177(7):733–5.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Friedman J, Godvin M, Shover CL, Gone JP, Hansen H, Schriger DL. Trends in Drug Overdose deaths among US adolescents, January 2010 to June 2021. JAMA. 2022;327(14):1398–400.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Carmona J, Maxwell JC, Park J-Y, Wu L-T. Prevalence and health characteristics of prescription opioid use, misuse, and Use disorders among U.S. adolescents. J Adolesc Health. 2020;66(5):536–44.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hudgins JD, Porter JJ, Monuteaux MC, Bourgeois FT. Prescription opioid use and misuse among adolescents and young adults in the United States: a national survey study. PLoS Med. 2019;16(11):e1002922.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Hadland SE, Wharam JF, Schuster MA, Zhang F, Samet JH, Larochelle MR. Trends in receipt of Buprenorphine and Naltrexone for Opioid Use Disorder among adolescents and Young adults, 2001–2014. JAMA Pediatr. 2017;171(8):747–55.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Larochelle MR, Bernson D, Land T, Stopka TJ, Wang N, Xuan Z, et al. Medication for opioid use disorder after nonfatal opioid overdose and association with mortality: a cohort study. Ann Intern Med. 2018;169(3):137–45.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ma J, Bao Y-P, Wang R-J, Su M-F, Liu M-X, Li J-Q, et al. Effects of medication-assisted treatment on mortality among opioids users: a systematic review and meta-analysis. Mol Psychiatry. 2019;24(12):1868–83.

    Article  PubMed  Google Scholar 

  8. Gossop M, Marsden J, Stewart D, Treacy S. Outcomes after methadone maintenance and methadone reduction treatments: two-year follow-up results from the National Treatment Outcome Research Study. Drug Alcohol Depend. 2001;62(3):255–64.

    Article  CAS  PubMed  Google Scholar 

  9. Matson SC, Hobson G, Abdel-Rasoul M, Bonny AE. A retrospective study of retention of opioid-dependent adolescents and young adults in an outpatient buprenorphine/naloxone clinic. J Addict Med. 2014;8(3):176–82.

    Article  CAS  PubMed  Google Scholar 

  10. Hadland SE, Bagley SM, Rodean J, Silverstein M, Levy S, Larochelle MR, et al. Receipt of timely addiction treatment and association of early medication treatment with retention in care among youths with opioid use disorder. JAMA Pediatr. 2018;172(11):1029–37.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Pilarinos A, Bromberg DJ, Karamouzian M. Access to medications for Opioid Use Disorder and Associated factors among adolescents and young adults: a systematic review. JAMA Pediatr. 2022;176(3):304–11.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Mauro PM, Gutkind S, Annunziato EM, Samples H. Use of medication for opioid use disorder among US adolescents and adults with need for opioid treatment, 2019. JAMA Netw open. 2022;5(3):e223821–e.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bagley SM, Chavez L, Braciszewski JM, Akolsile M, Boudreau DM, Lapham G, et al. Receipt of medications for opioid use disorder among youth engaged in primary care: data from 6 health systems. Addict Sci Clin Pract. 2021;16(1):46.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Welsh JW, Dennis ML, Funk R, Mataczynski MJ, Godley MD. Trends and age-related disparities in opioid use disorder treatment admissions for adolescents and young adults. J Subst Abuse Treat. 2022;132:108584.

    Article  CAS  PubMed  Google Scholar 

  15. King C, Beetham T, Smith N, Englander H, Hadland SE, Bagley SM, et al. Treatments used among adolescent residential addiction treatment facilities in the US, 2022. JAMA. 2023;329(22):1983–5.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Brown AR. Health professionals’ attitudes toward medications for opioid use disorder. Substance Abuse. 2022;43(1):598–614.

    Article  PubMed  Google Scholar 

  17. Madden EF, Prevedel S, Light T, Sulzer SH. Intervention stigma toward medications for opioid use disorder: a systematic review. Subst Use Misuse. 2021;56(14):2181–201.

    Article  PubMed  Google Scholar 

  18. Beachler T, Zeller TA, Heo M, Lanzillotta-Rangeley J, Litwin AH. Community attitudes toward opioid use disorder and medication for opioid use disorder in a rural Appalachian county. J Rural Health. 2021;37(1):29–34.

    Article  PubMed  Google Scholar 

  19. Axel Johansson B, Berglund M, Lindgren A. Efficacy of maintenance treatment with methadone for opioid dependence: a meta-analytical study. Nord J Psychiatry. 2007;61(4):288–95.

    Article  PubMed  Google Scholar 

  20. McGinty EE, Stone EM, Kennedy-Hendricks A, Bachhuber MA, Barry CL. Medication for opioid use disorder: a national survey of primary care physicians. Ann Intern Med. 2020;173(2):160–2.

    Article  PubMed  PubMed Central  Google Scholar 

  21. McCarty D, Fuller BE, Arfken C, Miller M, Nunes EV, Edmundson E, et al. Direct care workers in the National drug abuse treatment clinical trials network: characteristics, opinions, and beliefs. Psychiatr Serv. 2007;58(2):181–90.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Moore KE, Siebert SL, Kromash R, Owens MD, Allen DC. Negative attitudes about medications for opioid use disorder among criminal legal staff. Drug Alcohol Depend Rep. 2022;3:100056.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lien IC, Seaton R, Szpytman A, Chou J, Webber V, Waineo E, et al. Eight-hour medication-assisted treatment waiver training for opioid use disorder: integration into medical school curriculum. Med Educ Online. 2021;26(1):1847755.

    Article  PubMed  Google Scholar 

  24. Knudsen HK, Ducharme LJ, Roman PM, Link T. Buprenorphine diffusion: the attitudes of substance abuse treatment counselors. J Subst Abuse Treat. 2005;29(2):95–106.

    Article  PubMed  Google Scholar 

  25. Guerrero E, Ober AJ, Howard DL, Khachikian T, Kong Y, van Deen WK, et al. Organizational factors associated with practitioners’ support for treatment of opioid use disorder in the emergency department. Addict Behav. 2020;102:106197.

    Article  PubMed  Google Scholar 

  26. Bride BE, Abraham AJ, Kintzle S, Roman PM. Social workers’ knowledge and perceptions of effectiveness and acceptability of medication assisted treatment of substance use disorders. Soc Work Health Care. 2013;52(1):43–58.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Kennedy-Hendricks A, Bandara S, Merritt S, Barry CL, Saloner B. Structural and organizational factors shaping access to medication treatment for opioid use disorder in community supervision. Drug Alcohol Depend. 2021;226:108881.

    Article  CAS  PubMed  Google Scholar 

  28. Scott SD, Plotnikoff RC, Karunamuni N, Bize R, Rodgers W. Factors influencing the adoption of an innovation: an examination of the uptake of the Canadian Heart Health Kit (HHK). Implement Sci. 2008;3:1–8.

    Article  Google Scholar 

  29. Powell BJ, Mandell DS, Hadley TR, Rubin RM, Evans AC, Hurford MO, et al. Are general and strategic measures of organizational context and leadership associated with knowledge and attitudes toward evidence-based practices in public behavioral health settings? A cross-sectional observational study. Implement Sci. 2017;12(1):1–13.

    Article  Google Scholar 

  30. Pasman E, Lee G, Kollin R, Rodriguez B, Agius E, Madden EF, et al. Attitudes toward medication for opioid use disorder among substance use treatment providers. Subst Use Misuse. 2022;57(12):1828–36.

    Article  PubMed  Google Scholar 

  31. Aletraris L, Edmond MB, Paino M, Fields D, Roman PM. Counselor training and attitudes toward pharmacotherapies for opioid use disorder. Substance Abuse. 2016;37(1):47–53.

    Article  PubMed  Google Scholar 

  32. Grella CE, Ostile E, Scott CK, Dennis M, Carnavale J. A scoping review of barriers and facilitators to implementation of medications for treatment of opioid use disorder within the Criminal Justice System. Int J Drug Policy. 2020;81:102768.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Cioe K, Biondi BE, Easly R, Simard A, Zheng X, Springer SA. A systematic review of patients’ and providers’ perspectives of medications for treatment of opioid use disorder. J Subst Abuse Treat. 2020;119:108146.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Substance Abuse Mental Health Services Administration. The TEDS report: substance abuse treatment admissions referred by the criminal justice system. Substance Abuse and Mental Health Administration, Office of Applied Studies &#8230.

  35. Brown AR, Walters JE, Harmer B, Cates L, Jones AE. Non-prescribing clinicians’ treatment orientations and attitudes toward treatments for opioid use disorder: rural differences. J Subst Use Addict Treat. 2023;155:209153.

    Article  CAS  PubMed  Google Scholar 

  36. Aalsma MC, Aarons GA, Adams ZW, Alton MD, Boustani M, Dir AL, et al. Alliances to disseminate addiction prevention and treatment (ADAPT): a statewide learning health system to reduce substance use among justice-involved youth in rural communities. J Subst Abuse Treat. 2021;128:108368.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Waldorf B, Kim A. The index of relative rurality (IRR): US County Data for 2000 and 2010. Purdue University Research Repository; 2018.

  38. Institute of Behavioral Research. TCU Survey of Organizational Functioning (TCU SOF) Fort Worth, TX: Texas Christian University, Institute of Behavioral Research., 2005 [ https://ibr.tcu.edu/forms/organizational-staff-assessments/.

  39. Broome KM, Flynn PM, Knight DK, Simpson DD. Program structure, staff perceptions, and client engagement in treatment. J Subst Abuse Treat. 2007;33(2):149–58.

    Article  PubMed  PubMed Central  Google Scholar 

  40. van Buuren S. Multiple imputation of discrete and continuous data by fully conditional specification. Stat Methods Med Res. 2007;16(3):219–42.

    Article  PubMed  Google Scholar 

  41. SAS Institute Inc. Cary, NC2016.

  42. Welsh JW, Mataczynski MJ, Passetti LL, Hunter BD, Godley MD. Attitudes and beliefs among Georgia addiction treatment staff about medication for opioid use disorder in adolescents, young adults, and adults: a multi-mixed methods study. Am J Drug Alcohol Abus. 2022;48(3):347–55.

    Article  Google Scholar 

  43. Committee On Substance USE, Prevention. Medication-assisted treatment of adolescents with opioid Use disorders. Pediatrics. 2016;138(3):e20161893.

    Article  Google Scholar 

  44. Pasman E, O’Shay S, Brown S, Madden EF, Agius E, Resko SM. Ambivalence and contingencies: a qualitative examination of peer recovery coaches’ attitudes toward medications for opioid use disorder. J Subst Use Addict Treat. 2023;155:209121.

    Article  CAS  PubMed  Google Scholar 

  45. Muzyk A, Smothers ZPW, Collins K, MacEachern M, Wu LT. Pharmacists’ attitudes toward dispensing naloxone and medications for opioid use disorder: a scoping review of the literature. Subst Abus. 2019;40(4):476–83.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Lister JJ, Weaver A, Ellis JD, Himle JA, Ledgerwood DM. A systematic review of rural-specific barriers to medication treatment for opioid use disorder in the United States. Am J Drug Alcohol Abus. 2020;46(3):273–88.

    Article  CAS  Google Scholar 

  47. Ehrhart MG, Aarons GA, Farahnak LR. Going above and beyond for implementation: the development and validity testing of the implementation citizenship behavior scale (ICBS). Implement Sci. 2015;10(1):1–9.

    Article  Google Scholar 

  48. Ehrhart MG, Aarons GA, Farahnak LR. Assessing the organizational context for EBP implementation: the development and validity testing of the implementation climate scale (ICS). Implement Sci. 2014;9(1):1–11.

    Article  Google Scholar 

  49. Hamill NR, Wiener KKK. Attitudes of psychologists in Australia towards evidence-based practice in psychology. Australian Psychol. 2018;53(6):477–85.

    Article  Google Scholar 

  50. Alinsky RH, MD NC, Galagali PM, PGDAP F, Kreida EC, Robinson CA. Medication for adolescents and young adults with opioid use disorder. J Adolesc Health. 2021;68(3):632–6.

    Article  PubMed Central  Google Scholar 

  51. American Academy of Child and Adolescent Psychiatry. Opioid Use Disorder Treatment in Youth Washington DC2020 [ https://www.aacap.org/AACAP/Policy_Statements/2020/Opioid_Use_Disorder_Treatment_Youth.aspx.

  52. Matheson C, Jaffray M, Ryan M, Bond CM, Fraser K, Kirk M, et al. Public opinion of drug treatment policy: exploring the public’s attitudes, knowledge, experience and willingness to pay for drug treatment strategies. Int J Drug Policy. 2014;25(3):407–15.

    Article  CAS  PubMed  Google Scholar 

  53. Schwartz RP, Kelly SM, O’Grady KE, Mitchell SG, Peterson JA, Reisinger HS, et al. Attitudes toward buprenorphine and methadone among opioid-dependent individuals. Am J Addictions. 2008;17(5):396–401.

    Article  Google Scholar 

  54. Minozzi S, Amato L, Vecchi S, Davoli M, Kirchmayer U, Verster A. Oral naltrexone maintenance treatment for opioid dependence. Cochrane Database Syst Reviews. 2011(4).

  55. Victor G, Lee G, Pozo Bd, Silverstein S, Zettner C, Cason R, et al. Medications for opioid use disorder in the criminal/legal system: knowledge, beliefs, and attitudes among rural community-based stakeholders. J Drug Issues. 2022;52(3):389–405.

    Article  Google Scholar 

  56. Roberto AJ, Shafer MS, Marmo J. Predicting substance-abuse treatment providers’ communication with clients about medication assisted treatment: a test of the theories of reasoned action and planned behavior. J Subst Abuse Treat. 2014;47(5):307–13.

    Article  PubMed  Google Scholar 

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Acknowledgements

We would like to thank our community partners who participated in the ADAPT project.

Funding

This research was supported by the National Institutes of Health through the National Institute on Drug Abuse Justice Community Opioid Innovation Network cooperative through award number UG1DA050070.

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Authors and Affiliations

  1. Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA

    Lauren M. O’Reilly, Katherine Schwartz, Logan Gillenwater & Matthew Aalsma

  2. Department of Biostatistics and Health Data Science, Indiana University School of Medicine, 401 W. 10th St, Indianapolis, IN, 46202, USA

    Steven A. Brown

  3. Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA

    Allyson Dir, Zachary Adams, Tamika Zapolski & Leslie A. Hulvershorn

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Contributions

L.O. conceptualized the paper, conducted analyses, interpreted data, and wrote the main manuscript text. Z.A., T.Z., L.A., and M.A. acquired funding for this study. M.A. provided supervision. K.S., S.B., A.D., L.G., Z.A., T.Z., L.H., and M.A. all provided substantial revisions. All authors reviewed the manuscript.

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Correspondence to Lauren M. O’Reilly.

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Ethical standards set forth by the Declaration of Helsinki were followed. The ADAPT study was preregistered and approved by the Indiana University’s Internal Review Board (Protocol #1910282231.

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The authors declare no competing interests.

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O’Reilly, L.M., Schwartz, K., Brown, S.A. et al. Attitudes toward and training in medications for opioid use disorders: a descriptive analysis among employees in the youth legal system and community mental health centers. Subst Abuse Treat Prev Policy 19, 32 (2024). https://doi.org/10.1186/s13011-024-00614-w

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Keywords

Substance Abuse Treatment, Prevention, and Policy

ISSN: 1747-597X