Brief Video Intervention to Improve Attitudes Towards Medications for Opioid Use Disorder in a Correctional Setting

Abstract

Objectives:

Medications for opioid use disorder (MOUD) in the criminal justice setting is an effective way to address opioid use disorder and prevent associated deaths in the community. The Rhode Island Department of Corrections (RIDOC) is the first statewide correctional system in the United States to offer comprehensive MOUD services to incarcerated individuals; however, due to stigma, eligible individuals may be reluctant to engage with MOUD. This study aims to 1) evaluate the efficacy of an educational video intervention and 2) characterize MOUD-related attitudes in a general incarcerated population.

Methods:

Participants were recruited from eight elective classes offered to soon-to-be-released incarcerated individuals at the RIDOC. Participants viewed an eight-minute video featuring incarcerated individuals speaking about their experiences using MOUD, designed to reduce MOUD-related stigma. Participants were administered surveys prior to and after watching the video to assess changes in MOUD knowledge (MOUD-K) and MOUD attitudes (MOUD-A).

Results:

This evaluation of the intervention included 80 incarcerated participants (median age = 35), 93% male, 36% non-Hispanic White, and 26% non-Hispanic Black). Forty percent indicated non-medical opioid use within six months prior to incarceration; 13% had previously used MOUD. Significant improvements in MOUD-K scores (t(65) = −7.0, p < 0.0001) and MOUD-A scores (t(69) = −5.8, p < 0.0001) were detected after participants viewed the video. The intervention yielded greater Δ MOUD-A scores among those identifying as non-Hispanic Black, compared to non-Hispanic Whites (β = 2.6, CI = 0.4, 4.8).

Conclusion:

The educational video improved both knowledge and positive attitudes towards MOUD, with changes in MOUD attitudes being influenced by race. These findings may inform future MOUD educational programs, thereby helping to reduce opioid use disorder-related morbidity and mortality.

1. Introduction

Opioid use disorder (OUD) and opioid-related mortalities are critical public health challenges in the United States. Criminal justice (CJ) involved individuals have a greater burden of OUD and are at substantially increased risk of overdose death following reentry to the community (Binswanger, Blatchford, Lindsay, & Stern, 2011; Binswanger, Blatchford, Mueller, & Stern, 2013; Binswanger et al., 2007; Farrell & Marsden, 2008; Merrall et al., 2010). Growing evidence suggests that medications for opioid use disorder (MOUD) are an effective, evidence-based approach to address OUD in correctional populations (Green et al., 2018; National Academies of Sciences, 2019; Sharma et al., 2016). Implementing MOUD in correctional populations has extensive benefits, including reductions in illicit opioid-use post-incarceration (Kinlock, Gordon, Schwartz, Fitzgerald, & O'Grady, 2009; Mattick, Breen, Kimber, & Davoli, 2009), criminal behavior (Deck et al., 2009), HIV risk behaviors (MacArthur et al., 2012), and overdose risk (Brinkley-Rubinstein et al., 2018; Degenhardt et al., 2011; Kerr et al., 2007).

The Rhode Island Department of Corrections (RIDOC) recently became the first statewide correctional system in the US to implement a comprehensive MOUD program (Clarke, Martin, Gresko, & Rich, 2018; Green et al., 2018), making the three FDA-approved MOUD options (methadone, buprenorphine, and naltrexone) available to all clinically eligible individuals. However, even when structural barriers to MOUD are removed (i.e., high cost, lack of access, lack of trained providers), not all eligible individuals elect to initiate MOUD treatment (Booth, Corsi, & Mikulich, 2003; Booth, Kwiatkowski, Iguchi, Pinto, & John, 1998; Uebelacker, Bailey, Herman, Anderson, & Stein, 2016).

With the removal of many structural barriers to MOUD at RIDOC for eligible individuals, MOUD stigma may be one of the most important remaining barriers impeding MOUD uptake and engagement. The stigmatization of substance use disorders including OUD is particularly common because individuals with these disorders are often seen to be at fault for their illness, which overshadows its status as a treatable medical illness (Corrigan, Kuwabara, & O'Shaughnessy, 2009; Olsen & Sharfstein, 2014). It is well-documented that stigma is a common cause for treatment avoidance and treatment dropout in these stigmatized illnesses (Copeland, 1997; Digiusto & Treloar, 2007; Semple, Grant, & Patterson, 2005). Specifically, stigma associated with opioid use disorder may cause individuals with the condition to avoid the use of opioid agonists, including methadone and buprenorphine, to assist with recovery as healthcare providers, recovery organizations, and peers may see use of these opioid substitutes as a character weakness or lack of willpower (Olsen & Sharfstein, 2014).

Stigmatized individuals often perceive stigma in their interpersonal relationships (van Boekel, Brouwers, van Weeghel, & Garretsen, 2016) and in the general public (van Boekel, Brouwers, van Weeghel, & Garretsen, 2015). In the correctional setting, MOUD engagement may be affected by the social stigma from other CJ-involved individuals. Stigmatized individuals also may internalize these negative beliefs about themselves, a process known as self-stigma that manifests as anticipated discrimination (Corrigan & Watson, 2002; van Boekel et al., 2016).

Lack of knowledge and problematic attitudes are two major contributing components to stigma (Thornicroft, 2006). Misperceptions and lack of knowledge about the efficacy, safety, and perceived consistency with being drug-free influence MOUD utilization and engagement (Gu et al., 2012; Uebelacker et al., 2016). MOUD engagement levels are influenced by misunderstandings about the treatment, such as its effect on physical health, withdrawal symptoms, side effects, and long treatment course (Luty, 2004; Schwartz et al., 2008; Stancliff, Myers, Steiner, & Drucker, 2002; Zaller, Bazazi, Velazquez, & Rich, 2009). More knowledge about MOUD is associated with more positive attitudes (Polonsky et al., 2016; Polonsky et al., 2015); however, one intervention found that even if an individual is knowledgeable about the benefits of MOUD, this individual may still hold prejudices against the treatment, especially in the correctional setting where ideological biases perpetuated by stigma and discrimination amongst peers and staff may reinforce negative beliefs about MOUD (Polonsky et al., 2016).

Inaccurate knowledge about MOUD has fostered negative attitudes about its use. This points to the need for an effective targeted intervention that increases the understanding of MOUD and contributes to reducing associated stigma, particularly in prison and jail settings. In a correctional setting, DVDs are an accessible and established medium for delivery of health education (Green et al, 2014), and there is strong evidence that video-based interventions can increase knowledge and decrease stigmatizing attitudes about mental illness and substance use (Clement et al., 2018; Dalky, 2012; Livingston, Milne, Fang, & Amari, 2012; Yamaguchi et al., 2013). Social stigma may be addressed by communicating positive stories of individuals with substance use disorder (Livingston et al., 2012), and there may be a benefit of featuring race-matched peers in a video intervention in a correctional setting (Martin et al., 2008).

We hypothesize that a peer-delivered video intervention will improve both understanding of and positive attitudes about MOUD among incarcerated individuals. These increases in knowledge and positive attitudes may lessen stigma and ultimately improve MOUD engagement for eligible individuals. This study aims to 1) evaluate the efficacy of a brief educational video intervention aimed to increase MOUD knowledge and positive attitudes and 2) characterize MOUD-related attitudes in a general correctional population.

2. Methods

2.1. Participants

Participants were recruited from all ongoing pre-release classes offered to incarcerated individuals during the month of July 2018 at RIDOC. Recruitment took place in eight classes at different RIDOC facilities, including the women’s facility and the men’s minimum and medium security facilities. Other facilities, such as maximum security and intake service center, were not included, as there were no ongoing pre-release classes at these facilities at the time of the intervention. Study participants had to be: 1) over the age of 18; 2) incarcerated at RIDOC; and 3) able to read and speak English in order to give consent. No identifying information was collected.

2.2. Procedures

All individuals in the pre-release classes were offered the chance to voluntarily participate in the study. The course instructor of the pre-release class and a research assistant asked all individuals in the class if they would like to voluntarily give feedback about a video related to MOUD. The study population included all individuals in pre-release classes, all of whom were within six months of their release date. Potential participants were asked to review a consent form, which described study procedures. Participants were not provided any incentives for participating in the research study. Individuals who chose not to participate in the survey were given crossword puzzles to complete while participants completed the surveys. Participants watched an eight-minute narrative-based video featuring two incarcerated individuals, a male person-of-color and a white female, speaking about their personal experiences with OUD and using MOUD. The full video can be viewed on http://www.prisonerhealth.org/videos-and-fact-sheets/mat-and-corrections/. The educational video was designed with the goal of increasing knowledge about the MOUD program and reducing MOUD-related stigma. A research assistant administered handwritten surveys to participants prior to and following the video screening. These surveys assessed changes in MOUD knowledge (MOUD-K) and MOUD attitudes (MOUD-A).

2.3. Ethical considerations

The Miriam Hospital Institutional Review Board and Ethics Committee and the RIDOC Medical Research Advisory Group approved the intervention, including the purpose, methods, risks, and benefits of the study. These were explained to potential participants to inform their decision to participate. Participants were assured that their participation would be completely voluntary and that they could stop participating at any stage if they did not want to continue for any reason. Neither participation nor non-participation in the research study would impact release date, privileges, probation, or parole status in any way. Identifying information, including names, were not collected.

2.4. Measures

Demographic measures included age, gender, self-identified race, time incarcerated, MOUD use history, and pre-incarceration opioid exposure. Pre-incarceration opioid exposure was defined as self-reported use of prescription opioids, heroin, or fentanyl non-medically in the six months prior to incarceration.

The research team created items based on previous studies assessing MOUD knowledge and attitudes and adapted these scales to the targeted participant population (Matejkowski, Dugosh, Clements, & Festinger, 2015; Matusow et al., 2013; Stancliff et al., 2002). Concise and simple Likert scale response options were used that allowed participants to complete the full survey in less than ten minutes. All surveys and consent forms used commonly used terms and drug names, including the trade names of some drugs.

2.4.1. MOUD-Knowledge (MOUD-K)

Knowledge of MOUD and of the MOUD program at RIDOC was assessed by responses to three items. Each was scored on a 5-point Likert scale ranging from 1 = Strongly Disagree to 5 = Strongly Agree. The statements assessing for MOUD-K included “I have heard about MOUD (Methadone, Suboxone, Vivitrol)” and “I can explain MOUD to a friend” (refer to table 2 for full question content). Higher scores on MOUD-K denoted higher knowledge about and familiarity with the MOUD program. Participants with more than 25% of the pre-video MOUD-K items (n = 2) or post-video MOUD-K items (n = 4) items missing were not included in the analysis.

Table 2.

Participant Responses to Knowledge and Attitude Surveys

Variables	Pre-Survey	Post-Survey	Difference	Pre-attitude Standardized Factor Loadings
	M (SD)	M (SD)	M (SD)
MOUD-Knowledge b	8.6 (3.7)	11.4 (2.4)	2.8 (3.3)*
1.I have heard about MOUD (Methadone, Suboxone, Vivitrol) a	3.4 (1.4)	4.0 (0.9)	0.7 (1.3)*	0.72
2. I am familiar with the ACI MOUD program a	2.7 (1.4)	3.7 (1.0)	1.1 (1.3)*	0.89
3. I can explain MOUD to a friend a	2.6 (1.3)	3.7 (1.1)	1.1 (1.3)*	0.84
MOUD-Attitudes c	17.8 (4.6)	20.4 (5.0)	2.6 (3.7)*
4. Methadone can help an addicted individual a	3.2 (1.0)	3.6 (1.1)	0.5 (0.8)*	0.87
5. Suboxone can help an addicted individual a	3.0 (1.1)	3.6 (1.1)	0.6 (0.9)*	0.98
6. Vivitrol/Naltrexone can help an addicted individual a	3.2 (1.0)	3.6 (1.1)	0.5 (1.0)*	0.80
(7) Methadone/Suboxone are bad for your healtha, d, e	2.3 (1.1)	2.7 (1.1)	0.4 (1.4)*	0.27
8. Methadone/Suboxone reduce the chances of relapse a	2.9 (1.2)	3.4 (1.1)	0.5 (1.3)*	0.73
9. Methadone/Suboxone will extend addiction a, e	2.4 (1.1)	2.8 (1.1)	0.4 (1.3)*	0.35
10. MOUD is more effective than treatment without medications a	3.1 (1.0)	3.3 (1.1)	0.2 (1.3)	0.35

Note. MOUD = Medications for Opioid Use Disorder; ACI = Adult Correctional Institute

^aItem rated from 1 = Strongly Agree to 5 = Strongly Disagree

^bScale constructed using items 1-3. Higher scores indicate a stronger familiarity MOUD.

^cScale constructed using items 4-10, imputing items to the average. Item #7 was deleted from the final construct due to low construct validity. Higher scores indicate more positive attitudes towards MOUD.

^dScale item removed after testing construct validity

^eItem was reversed scored

^*p < 0.05 for paired differences between Pre- and Post- Video Survey Responses

2.4.2. MOUD-Attitudes (MOUD-A)

Attitudes towards MOUD were assessed using responses to seven items that were developed by adapting previous research surveys to fit our participant population (Matejkowski et al., 2015; Matusow et al., 2013; Stancliff et al., 2002). Each item was scored on a 5-point Likert scale ranging from 1 = Strongly Disagree to 5 = Strongly Agree; two items were reverse scored. The statements assessing for MOUD-A included “Methadone can help an addicted individual” and “MOUD is more effective than treatment without medications” (refer to table 2 for full question content). Imputation towards the mean within each participant was performed on missing values for each of the seven items if less than 25% of the items were missing for pre-video MOUD-A (n = 4) and post-video MOUD-A (n = 5) (Siddiqui, 2015). Participants with more than 25% of the pre-video (n = 2) MOUD-A items or post-video MOUD-A items (n = 4) were not included in the analysis. Scores for the seven items were then totaled to form a composite score representing MOUD-A. Higher scores on MOUD-A denoted more positive attitudes toward MOUD.

For both pre- and post- video MOUD-K and MOUD-A scales, data were considered invalid if a participant endorsed the same choice for all scale items (n = 11). The construct validity of the scales was examined using a standardized confirmatory factor analysis, which is a theory-driven approach to scale validation. Each item was considered acceptable if it had a minimum loading factor of p < 0.01 (Babyak, 2010; Suhr, 2006). Internal consistency was assessed using Cronbach Alpha values; a value of greater than 0.70 is generally considered an acceptable reliability coefficient for internal consistency of a given scale (Tavakol & Dennick, 2011).

2.5. Statistical Analysis Plan

Raw data from the paper surveys were coded in Qualtrics. Descriptive statistics were calculated for all baseline characteristics and outcome variables. Age was dichotomized at the median value of 35. Additionally, a new variable, change in MOUD attitudes (Δ MOUD-A), was created for each individual based on (post MOUD-A) - (pre MOUD-A) = Δ MOUD-A. Paired t-tests assessed changes in MOUD-K and MOUD-A. Bivariate and multiple linear regression models were used to assess the relationship between 1) pre-video MOUD-A and 2) Δ MOUD-A and sociodemographic variables (age, race, gender, time incarcerated, substance use characteristics, and prior MOUD use). We first fit bivariate models between each of the outcomes and age, race, time incarcerated, pre-incarceration opioid exposure, pre-video MOUD-K, and pre-video MOUD-A for the Δ MOUD-A outcome. We created final multiple linear regression models for 1) pre-video MOUD-A and 2) Δ MOUD-A with variables found to be significant in the bivariate analyses and variables determined a priori (age, race, and substance use characteristics) based on the previous literature (Stancliff et al., 2002). We added all variables to the model and used backward elimination to eliminate variables until the model fit could no longer be improved according to the Bayesian information criterion (BIC) (Posada & Buckley, 2004). Assumptions for linear regression were checked. Statistical analyses were conducted using STATA SE 13.0 (StataCorp, 2013).

3. Results

3.1. Demographic and Opioid Use Characteristics

From July 16, 2018 to July 24, 2018 eight groups were offered participation in the study; 82 watched the video and 80 agreed to complete the study. The median age for the sample was 35, and 74 participants (93%) were male. Twenty-nine participants (36%) self-identified as non-Hispanic White; 21 (26%) self-identified as non-Hispanic Black; four (5%) were Asian or other; and 25 individuals (31%) identified as ethnically Latino or Hispanic. Thirty-two individuals (40%) endorsed non-medical opioid use during the six months prior to incarceration, including 29 individuals (37%) who reported using prescription opioids non-medically, four individuals (5%) who reported using fentanyl, and five individuals (6%) who reported using heroin within the six months prior to incarceration. A total of ten individuals (13%) had previously used MOUD, including six (8%) who used methadone, five (6%) who used buprenorphine, and one who used both methadone and buprenorphine. No participants indicated previous experience using depot-naltrexone. Table 1 summarizes demographic and opioid use characteristics.

Table 1.

Demographic and Opioid Use Characteristics (n = 80)

Variable	Total
	n (%)
Age*
18-34	38 (48)
35+	41 (52)
Gender
Male	74 (92)
Female	6 (8)
Race
Non-Hispanic White	29 (36)
Non-Hispanic Black	21 (26)
Hispanic/Latino/Other	30 (38)
Time Incarcerated*
<=1 year	37 (47)
>1 year	42 (53)
Pre-Incarceration Opioid Exposure
Yes	32 (40)
No	48 (60)
Prior MOUD Use
Yes	10 (13)
No	70 (87)
Valid Pre-Video Survey
Yes	72 (90)
No	8 (10)
Valid Post-Video Survey
Yes	75 (94)
No	5 (6)

Notes. MOUD = Medications for Opioid Use Disorder;

^*One participant opted not to answer this question

3.2. Inclusion for primary outcomes analysis

Eleven of the 80 participants had either pre- or post- data that was considered invalid as a result of endorsing the same choice for all scale items. An additional four individuals failed to answer more than 25% of scale items from either the MOUD-K or MOUD-A score and were also removed from the analysis. A chi- square test of independence was performed to examine the relationship between exclusion from the analysis and demographic and baseline characteristics. The only demographic characteristic difference between those included and not included in the final analysis was race: those who self-identified as Non-Hispanic White (six of the 23 excluded or 26%) or Latino/Hispanic/Other (nine of 21 or 43% excluded) were more likely to have provided data that was excluded, χ², N = 80) = 8.4, p = 0.03.

3.3. Scale Validity

A confirmatory factor analysis demonstrated that each item achieved a significant minimum loading factor as defined in our methods with the exception of one item in the proposed MOUD-A scale. Item #7, stating “Methadone/Suboxone are bad for your health,” was dropped from subsequent analysis because it failed to achieve an acceptable level on construct validity with the other items within the same construct (Table 2). All items in the MOUD-K scale reached an acceptable level of construct validity (Suhr, 2006).

We examined internal consistency using Cronbach alpha. Baseline MOUD-K was found to have an α = 0.87, and post-video MOUD-K had an α = 0.72. For the attitude scales, baseline MOUD-A had an α = 0.82, and post-video MOUD-A had an α = 0.84.

3.4. Video Effect on MOUD-K and MOUD-A

Paired t-tests demonstrate significant improvement between MOUD-K scores pre-video (M = 8.6, SD = 3.7) and MOUD-K post-video scores (M = 11.4, SD = 2.4); t(65) = −7.0, p < 0.0001. MOUD-A scores pre-video (M = 17.8, SD = 4.6) and MOUD-A scores post-video (M = 20.4, SD = 5.0) also significantly improved; t(69) = −5.8, p < 0.0001. Table 2 summarizes each scale item and participants’ responses and MOUD-K and MOUD-A item questions.

A multiple linear regression was calculated to predict pre-video MOUD-A based on age, race, incarceration time, risky opioid use behavior, and MOUD-K. Significant associations were found between higher pre-video MOUD-A scores and (a) higher pre-video MOUD-K (β = 0.4, CI = 0.1, 0.7) and (b) being incarcerated for less than one year (β = 2.9, CI = 0.6, 5.1). Participants’ pre-video MOUD-A increased by 0.4 points for every one-point increase in pre-video MOUD-K score. In addition, those incarcerated for less than one year were predicted to have pre-video MOUD-A scores 2.9 points above those incarcerated for more than one year (Table 3).

Table 3.

Multiple Linear Regressions for Pre-MOUD Attitudes and Change in MOUD Attitudes

Dependent Variable	B (95% CI)	SE B
Baseline Pre-Video MOUD Attitudes
Constant	16.3 (12.6, 20.0)	1.8
Age
18-34	Ref.
35+	0.1 (−2.4, 2.5)	1.2
Race
Non-Hispanic White	Ref.
Non-Hispanic Black	−0.3 (−3.0, 2.3)	1.3
Latino/Hispanic/Other	−1.2 (−4.0, 1.7)	1.4
Time Incarcerated
<=1 year	Ref.
>1 year	−2.9 (−5.1, −0.6)*	1.1
Pre-Incarceration Opioid Exposure
No	Ref.
Yes	−0.5 (−2.8, 1.7)	1.1
Baseline Pre-Video MOUD Knowledge	0.4 (0.1, 0.7)*	0.2
Change in MOUD Attitudes (ΔMOUD-A)
Constant	5.4 (0.8, 10.0)	2.3
Age
18-34	Ref.
35+	1.1 (−0.9, 3.1)	1.0
Race
Non-Hispanic White	Ref.
Non-Hispanic Black	2.6 (0.4, 4.8)*	1.1
Latino/Hispanic/Other	0.7 (−1.6, 3.1)	1.2
Time Incarcerated
<=1 year	Ref.
>1 year	−0.0 (−1.9, 1.9)	1.0
Pre-Incarceration Opioid Exposure
No	Ref.
Yes	1.4 (−0.5, 3.2)	0.9
Baseline Pre-Video MOUD Knowledge	−0.2 (−0.5, 0.1)	0.1
Baseline Pre-Video MOUD Attitudes	−0.2 (−0.4, 0.0)	0.1

Note. MOUD = Medications for Opioid Use Disorder; ACI = Adult

^*p < 0.05 for paired differences between Pre- and Post- Video Survey Responses

A multiple linear regression was also calculated to predict ΔMOUD-A [(post MOUD-A)-(pre MOUD-A)] based on age, race, incarceration time, risky opioid use behavior, pre-video MOUD-K and pre-video MOUD-A. Statistically significant associations were also found between greater Δ MOUD-A and identifying as non-Hispanic Black (β = 2.6, CI = 0.4, 4.8). Those self-identifying as non-Hispanic Black were predicted to have greater ΔMOUD-A scores by 2.5 more than those self-identifying as non-Hispanic White (Table 3). We identified three outliers (defined by >2 SD above the mean) and reexamined the results with these participants removed, but factors significantly associated with ΔMOUD-A were not impacted.

4. Discussion

This study is among the first to examine MOUD-related knowledge and attitudes in a general incarcerated population in the United States (Polonsky et al., 2016). The video intervention was found to improve participants’ self-rated MOUD knowledge and increase positive attitudes towards MOUD. Changes in MOUD attitudes (ΔMOUD-A) were independently associated with race, with participants identifying as non-Hispanic Black reporting larger increases in attitude scores post-intervention compared to non-Hispanic Whites. These results indicate that a video intervention could contribute to bridging the racial gap between MOUD perceptions held by the two populations.

The video intervention included the stories of two individuals with experience using MOUD, one a male person of color and the other a white female. The results found here are similar to those found in previous brief peer-delivered DVD educational interventions in a correctional setting where behavioral health outcomes improved when compared to education only or standard interventions (Martin et al., 2008). Further understanding the cultural context of the criminal justice system and subgroups inside of the criminal justice system is crucial in providing an effective health education intervention (Zaller et al., 2009).

The pre-video MOUD-A was independently associated with baseline time incarcerated. Individuals who were incarcerated for less than one year had pre-video MOUD-A scores of 2.9 points above those incarcerated for more than one year. This may indicate that MOUD stigma in the correctional environment is greater than MOUD stigma in the general population, contributing more to negative perceptions of MOUD with increased duration of incarceration. Another plausible interpretation could be misperceptions about MOUD may be amplified by peers and the incarcerated setting during the time incarcerated, which is a conclusion supported by at least one study (Polonsky et al., 2016).

These results are consistent with the prior research, which suggests that MOUD perceptions differ by community, ethnicity, and self-identified race (Zaller et al., 2009). Previous studies have demonstrated that Black and Latino injection drug users were significantly less likely to utilize methadone maintenance when compared to Whites (Lundgren, Amodeo, Ferguson, & Davis, 2001). This study also corroborates previous research, which finds a relationship between knowledge and attitudes; higher pre-video MOUD-K was associated with a higher pre-video MOUD-A (Polonsky et al., 2016; Polonsky et al., 2015; Uebelacker et al., 2016).

Data from this study may have limited generalizability. The sample size was relatively small, as we did not achieve the sample size we originally anticipated, given the challenge of conducting research in correctional facilities and recruiting participants (McKenzie, Nunn, Zaller, Bazazi, & Rich, 2009). As a result of the small sample size, our analysis lacked statistical power, and we were not able to assess differences in those with prior MOUD exposure and those without prior MOUD exposure. Additionally, the proportion of the sample with OUD is unknown, as we collected data related to opioid use prior to incarceration. Lastly, while there are demonstrated improvements in positive attitudes in our sample, it is unclear whether these changes in MOUD-related attitudes translate to behavioral changes in engagement with MOUD. Future studies should examine whether positive attitudes toward MOUD are associated with increased MOUD uptake and examine the effect of stigma on MOUD treatment engagement in correctional settings.

Our findings suggest that a brief video intervention is a feasible and replicable approach to improve MOUD-related knowledge and attitudes in correctional settings. The video used in the present study could be adapted to other jurisdictions and may even have utility for correctional officers, prison healthcare staff, and hospital administrators as these groups may also contribute to social stigma and subsequently reduced MOUD engagement among clinically eligible individuals. Educational interventions aiming to increase MOUD knowledge and attitudes are an important part of combatting the opioid crisis and reducing opioid-related mortality.

Highlights:

• Educational video improved MOUD knowledge and attitudes in a correctional setting

• More negative attitudes towards MOUD are associated with longer sentence times

• Educational interventions may bridge the gaps in MOUD perceptions between races

• This intervention yielded greater changes in MOUD attitudes among Black participants