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. Author manuscript; available in PMC: 2025 Mar 12.
Published in final edited form as: J Subst Use Addict Treat. 2024 May 3;163:209361. doi: 10.1016/j.josat.2024.209361

Perceptions around medications for opioid use disorder among a diverse sample of U.S. adults

Kaitlyn Jaffe a,b, Stephanie Slat c, Liying Chen d, Colin Macleod c, Amy Bohnert e,f, Pooja Lagisetty c,f
PMCID: PMC11897984  NIHMSID: NIHMS2004125  PMID: 38703949

Abstract

Introduction

Medications for opioid use disorder (MOUD) including methadone (MMT), buprenorphine (BUP), and naltrexone (NTX) are safe and effective. However, there are significant negative perceptions surrounding MOUD, creating barriers to uptake. While research on MOUD stigma has largely focused on provider and patient experiences, fewer studies have explored MOUD perceptions among the general public. Given that MOUD stigma expressed by social ties surrounding individuals with OUD can influence treatment choices, we assessed MOUD perceptions among U.S. adults to determine how beliefs impacted treatment preference. We further explored how MOUD perceptions may be amplified among racialized groups with histories of experiencing drug-related discrimination.

Methods

Survey data were collected from a diverse sample of U.S. adults (n=1508) between October 2020 and January 2021. The survey measured knowledge of MOUD and non-medication treatments, relative agreement with common MOUD perceptions, and treatment preferences. Multinomial logistic regression analysis was used to test associations with treatment preference, stratified by race/ethnicity.

Results

Descriptive results indicated that across groups, many respondents (66.8%) had knowledge of MOUD, but believed MOUD was a “substitute” for opioids and had some degree of concern about misuse. Multivariable results showed knowledge of non-medication treatments was positively associated with MOUD preference among White (MMT OR=3.16, 95% CI=1.35–7.39; BUP OR=2.69, CI=1.11–6.47), Black (MMT OR=3.91, CI=1.58–9.69), and Latino/a (MMT OR=5.12, CI=1.99–13.2; BUP OR=3.85, CI=1.5–9.87; NTX OR=4.51, CI=1.44–14.06) respondents. Among White respondents, we identified positive associations between MOUD experience and buprenorphine preference (OR=4.33, CI=1.17–16.06); non-medication treatment experience and preference for buprenorphine (OR=2.86, CI=1.03–7.94) and naltrexone (OR=3.17, CI=1.08–9.28). Concerns around misuse of methadone were negatively associated with methadone preference among White (OR=0.65, CI=0.43–0.98) and Latino/a (OR=0.49, CI=0.34–0.7), and concerns around misuse of buprenorphine was negatively associated with preference for MOUD among White (MMT OR=0.62, CI=0.39–0.99; BUP OR=0.48, CI=0.3–0.77; NTX OR=0.6, CI=0.36–0.99) and Latino/a (BUP OR=0.59, CI=0.39–0.89) respondents.

Conclusions

This analysis offers critical insights into treatment perceptions beyond the patient population, finding that negative beliefs around MOUD are common and negatively associated with preferences for medication-based treatment. These findings highlight implications for public support of evidence-based treatment and lay the groundwork for future interventions addressing public stigma toward MOUD.

Keywords: medications for opioid use disorder, public stigma, opioid use disorder, medication perceptions

1. Introduction

As a strategy to address rising opioid-related overdose deaths and prevalence of opioid use disorder (Ahmad et al., 2022), medications for opioid use disorder (MOUD), including methadone, buprenorphine, and naltrexone, have been shown to be safe and more efficacious than non-medication treatments (Degenhardt et al., 2019; Wakeman et al., 2020). However, despite the efficacy of MOUD, there are substantial barriers to uptake, ranging from institutional obstacles (e.g., clinic resistance, lack of trained providers, etc.; Cioe et al., 2020; Slat et al., 2021) to broader, structural issues (e.g., access, healthcare coverage, etc.; Cooper et al., 2020; Lagisetty et al., 2019; Mitchell et al., 2022). At the individual level, stigma also serves as a deterrent to accessing MOUD, highlighted by emerging research on MOUD stigma as both experienced by patients and expressed by providers (Cioe et al., 2020; Madden et al., 2021).

Stigmatizing beliefs about MOUD among healthcare providers and people who use drugs are pervasive. Medications for opioid use disorder are often perceived as illegitimate or described as “dependence”—messaging that has been internalized by potential patients and can deter providers from prescribing MOUD (Allen et al., 2019; Doernberg et al., 2019; Jaffe & Richardson, 2023; Madden et al., 2021; Malvini Redden et al., 2013; Uebelacker et al., 2016). Reflecting the strict dispensation requirements, MOUD has also been framed as dangerous and easy to misuse or divert (McElrath, 2018), negative associations that are applied to people accessing MOUD treatment, who are then perceived as dangerous or deceitful (Harris & McElrath, 2012; Radcliffe & Stevens, 2008; Woo et al., 2017). These stigmatizing effects are further amplified for racial and ethnic minority groups that have been disproportionately impacted by criminalization through the “War on Drugs” and consequent negative cultural narratives and racialized imagery (Hansen & Roberts, 2012; Hatcher et al., 2018; Kulesza et al., 2016; Netherland & Hansen, 2016). White patients are more likely to access MOUD than people of color and are more likely to receive the less stigmatized buprenorphine compared to more stigmatized methadone (Andraka-Christou, 2021; Hansen & Roberts, 2012; Lagisetty et al., 2019). Methadone-related stigma is rooted in its history as a “crime prevention” tool of control over people of color, with strict dispensation and surveillance of patients (e.g., supervised doses, urine drug screens) and with clinics primarily located in urban areas populated by Black and Latino/a communities (Andraka-Christou, 2021; Bruce, 2013; Hansen & Roberts, 2012; McElrath, 2018). Conversely, buprenorphine is available through office-based physicians, with greater uptake from White patients with access to prescribing providers. Patients receiving buprenorphine benefit from its more flexible prescribing, less strict regulation, and the ability to access it through community pharmacies, resulting in relatively lower treatment stigma (Andraka-Christou, 2021; Hansen & Roberts, 2012; Madden, 2019; McElrath, 2018). The histories and social meaning surrounding MOUD may shape preferences for medications across racial and ethnic groups.

The extensive stigma surrounding MOUD can lead to significant health and social harms for people who use drugs (PWUD). Previous research with PWUD has found that internalized MOUD stigma has been associated with resistance or discontinuation of treatment (Chou et al., 2022; Damon et al., 2017), limited access to health or social support (Malvini Redden et al., 2013; Paquette et al., 2018), or collateral consequences for other aspects of their lives, such as personal relationships or employment (Sanders et al., 2013; Woo et al., 2017). In studies of individuals with a family member with opioid use disorder, there was lower acceptance of MOUD and belief in its efficacy, compared to non-medication treatments (Nayak et al., 2021; Slocum et al., 2023), which may have impacts upon individuals’ treatment decisions. Among providers, MOUD stigma has contributed to hesitancy in prescribing MOUD or even engagement in discriminatory practices against people accessing MOUD (Gidman & Coomber, 2014; Mackey et al., 2020; Madden, 2019; Paquette et al., 2018), especially among patients of color who are less likely to be prescribed MOUD (Andraka-Christou, 2021; Barnett et al., 2023; Lagisetty et al., 2019). However, while significant research has assessed treatment stigma and its consequences among MOUD patients, families, and providers, few studies focus beyond internalized and interpersonal stigma to understand MOUD stigma and its etiologies among the general public, and how these perceptions may differ by race and ethnicity (Friedman et al., 2022).

Substantial research has explored public stigma toward treatment for other stigmatized illnesses, including HIV and mental illness, with implications for acceptability or perceived efficacy (Calabrese & Underhill, 2015; Parcesepe & Cabassa, 2013). Yet few studies have assessed public perceptions of substance use treatment, outside of treatment-engaged populations and providers. Given the prevalence of drug-related stigma beyond the patient population, we conducted an original survey to assess perceptions of treatment for opioid use disorder among a diverse sample of U.S. adults. We hypothesized that respondents who preferred non-medication-based treatments for opioid use disorder would hold more negative stigmatizing perceptions of MOUD, including concerns for misuse and dependence. By understanding broader public perceptions of MOUD, we can start to build public acceptance of evidence-based treatments and consequently, improve supports for people accessing MOUD and for the expansion of treatment services.

2. Methods

2.1. Study sample

Data for this study were derived from a web-based survey (n=1530) conducted between October 2020 and January 2021. Respondents were recruited through Dynata, a survey research firm that touts the “world’s largest first-party data analytics and insights platform,” with “70 million consumers” (Dynata, 2022). Dynata maintains a panel of survey respondents and has been used across health and social science research fields to recruit representative samples of US adults (Ellithorpe et al., 2022; Milne et al., 2019; Vordenberg & Zikmund-Fisher, 2020). A strength of this platform is success in recruiting equal samples stratified by race and ethnicity to allow for within and between group comparisons. We focused on recruiting White, Black, and Latino/a participants, given they are the majority minority populations and to ensure a sufficient sample size for each group. Potential participants were emailed with standardized details about the survey, with recruitment ongoing until sample sizes were sufficient across race/ethnicity (i.e., White, Black, Latino/a) and within each racial/ethnic group by gender, age, and income. Dynata does not share specific details of their survey incentives, but they utilize a credit-based system, in which respondents earn credit that can be redeemed through cash or gift cards. Incentive rates were set by Dynata and are commensurate to the time needed to complete the survey. This study was deemed exempt from full review by the University of Michigan Institutional Review Board.

2.2. Survey design

The survey was designed to assess opioid use, knowledge of and attitudes toward treatments for opioid use disorder, previous treatment experiences, perceived access to treatment, beliefs about healthcare, beliefs about drug use, and demographic information. To assess these measures, the survey used original vignettes in video format. Respondents were randomly assigned to view a vignette featuring a hypothetical patient with problematic opioid use (i.e., heroin, prescription opioids). Vignettes featured different types of opioid use to capture perceptions of heroin versus prescription opioids as they have been shown to have different perceptions around stigma and severity of drug use (Netherland & Hansen, 2016; Tsai et al., 2019). χ2 tests were used to test the potential association between treatment preferences and types of vignettes within each racial/ethnic group. To assess how people may make treatment decisions for a community member, we sought racial/ethnic concordance between survey respondents and hypothetical patients to cue this decision-making (Mutz, 2015). This was facilitated through the explicit statement of patient race/ethnicity (e.g. “a Black man”) as well as through use of racially or ethnically distinct patient names (Crabtree et al., 2023). In each vignette, the respondents were also provided with basic information in the form of 60-second videos that would be reflective of what respondents would find in a basic web search on buprenorphine, methadone, naltrexone, and non-medication-based treatments for opioid use disorder, including initiation, mechanisms, and success rates. Links to vignette videos can be found in the supplemental information.

2.3. Survey measures

Following the vignette, each respondent answered multiple choice questions about potential treatment choices for the hypothetical patient. Our dependent variable assessed respondents’ perceptions of the best treatment [methadone; buprenorphine (e.g., Suboxone); naltrexone (i.e., Vivitrol); non-medication treatment] for the hypothetical patient in the vignette. Other key measures assessed respondent perceptions of MOUD. The first and second MOUD measures assessed respondents’ concern for misuse of methadone and of buprenorphine (i.e., “taking more medication than prescribed”), with four-point Likert scale response options ranging from “not at all concerned” to “very concerned.” The third measure assessed respondents’ agreement with the perception that MOUD treatment is “substituting one opioid for another,” (Bruce, 2013) recoded to a five-point Likert scale, where higher scores indicate greater levels of agreement.

Other covariates reflected participant knowledge of MOUD, including methadone, buprenorphine, and naltrexone. Respondents were asked “How much do you know about each of the following medications?” with five response options, from “none at all” to “a great deal.” These responses were dichotomized as no knowledge vs. any knowledge for ease of conceptual interpretation and to ensure adequate statistical power. We also assessed respondents’ knowledge of non-medication treatment options, including counseling, behavioral therapy (talk therapy to treat unwanted behaviors), residential addiction treatment (also known as rehab), detoxification, and Alcoholics Anonymous (AA) or Narcotics Anonymous (NA). We used the same five-option scale as a response, and dichotomized responses as no knowledge of non-medication treatment vs. any knowledge of non-medication treatment. To account for respondents’ experiences with addiction treatments, respondents were asked about experiences with addiction treatments. To reduce social desirability bias and since we hypothesized that friends and family experiences with treatment could shape perceptions, we asked whether treatments were tried by respondent or respondent’s friend or respondent’s family with multiple choices allowed. Participants selecting methadone, buprenorphine, or naltrexone were categorized as having any experience with medications for opioid use disorder; otherwise, they were considered to have no experience with MOUD treatment. Similarly, respondents who selected counseling, behavioral therapy, residential addiction treatment, detoxification, or AA/NA were classified as having any experience with other treatments, while those who did not select any of these options were deemed to have no experience with other treatments. Demographic characteristics included age group (continuous), and income group (continuous). Our survey also asked about gender, with the prompt, “Please indicate the current gender with which you most identify” and response options that included “woman,” “man”, “non-binary/third gender,” “prefer to self-describe” with an open text response option, and “prefer not to say.” Ultimately, we received too few responses that reflected gender identities outside of the binary and 16 responses were excluded in analysis for low cell counts. All demographic questions were adapted from those used by the Pew Research Center and their National Public Opinion Reference Survey (National Public Opinion Reference Survey (NPORS), 2023).

2.3. Analysis

Of 1530 respondents, 22 respondents (1.43%) were excluded from the final analysis due to missing data on key variables (n=6), or low statistical power for other gender identities (n=16), resulting in an analytic sample of 1508 respondents. Descriptive analysis of all independent variables, including demographic characteristics, knowledge of MOUD and non-medication treatment, experiences with MOUD and other treatments, and perceptions of MOUD, was conducted by reporting frequencies and proportions within three racial/ethnic groups (i.e., White, Black, Latino/a). We applied χ2 tests to examine differences of these independent features between racial and ethnic groups.

We performed bivariate and multivariate multinomial logistic regression within each group to assess the race/ethnicity-stratified relationships between all independent variables described above and the most preferred treatment for opioid use disorder. In the multinomial logistic regression, odds ratios (ORs) reflect the association between independent variables and preference for each specific MOUD versus non-MOUD treatment (i.e., of preference for methadone vs. non-medication treatment; buprenorphine vs. non-medication treatment; and naltrexone vs. non-medication treatment) and the corresponding 95% confidence intervals (CI). Benjamini-Hochberg adjusted p-values were reported for the univariate multinomial logistic regressions. We further conducted multivariate logistic regressions within each racial group to evaluate the association between independent variables and preference for one type of MOUD to another type: buprenorphine versus methadone (reference); naltrexone versus methadone (reference); and naltrexone versus buprenorphine (reference), which served as direct pairwise comparisons for the three types of MOUDs. These tables can be found in supplementary materials. Multicollinearity diagnostics were conducted by applying condition index and no evidence of severe multicollinearity among independent variables was found with the largest condition index smaller than 18.47 (Belsley, 1991; Alin 2010). All statistical analyses were conducted by using R Statistical Software (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria). All p-values were two-sided and significant at 0.05.

3. Results

In the analytic sample (n=1508), 528 (35.0%) respondents were White, 501 (33.2%) were Black, 479 (31.8%) were Latino/a, and 851 (56.4%) were women. Across all groups, 340 (22.5%) respondents reported a household income of less than $20,000, 535 (35.5%) reported income ranging from $20,000 to $49,999, 459 (30.4%) reported income between $50,000 and $99,999, and 174 (11.5%) reported income equal to or greater than $100,000. Sociodemographic characteristics are displayed in Table 1. Notably, we did not detect any significant differences in treatment preferences between two types of vignettes within each racial/ethnic group (see Supplementary Information Table 3).

Table 1.

Sample characteristics, stratified by race/ethnicity, n=1508

Characteristics White (n=528) Black (n=501) Latino/a (n=479) p-value
Sociodemographic n (%) n (%) n (%)
 Women 290 (54.90) 263 (52.50) 298 (62.21) 0.006
 Men 238 (45.08) 238 (47.51) 181 (37.79)
 Age
  <24 years old 60 (11.36) 104 (20.76) 117 (24.43) <0.001
  25–35 years old 154 (29.17) 160 (31.94) 175 (36.53)
  35–44 years old 46 (8.71) 32 (6.39) 38 (7.93)
  45–54 years old 32 (6.06) 29 (5.79) 23 (4.80)
  55–64 years old 90 (17.05) 60 (11.98) 47 (9.81)
  > 65 years old 146 (27.65) 116 (23.15) 79 (16.49)
 Household income
  < $20,000 103 (19.51) 143 (28.54) 94 (19.62) 0.003
  $20,000–49,999 180 (34.09) 175 (34.93) 180 (37.58)
  $50,000–99,999 177 (33.52) 129 (25.75) 153 (31.94)
  $100,000 or greater 68 (12.88) 54 (10.78) 52 (10.86)
Treatment Knowledge and Experience (none vs. any)
 MOUD knowledge 342 (64.77) 339 (67.66) 326 (68.06) 0.475
 Non-MOUD knowledge 455 (86.17) 448 (89.42) 429 (89.56) 0.160
 MOUD treatment experience 68 (12.88) 67 (13.37) 79 (16.49) 0.212
 Other treatment experience 128 (24.24) 124 (24.75) 145 (30.27) 0.059
Perceptions of MOUD
 Concern for Methadone Misuse
  Not at all concerned 127 (24.05) 92 (18.36) 94 (19.62) 0.156
  Slightly concerned 160 (30.30) 167 (33.33) 162 (33.82)
  Moderately concerned 149 (28.22) 133 (26.55) 121 (25.26)
  Very concerned 92 (17.42) 109 (21.76) 102 (21.29)
 Concern for Buprenorphine Misuse
  Not at all concerned 98 (18.56) 76 (15.17) 71 (14.82) 0.030
  Slightly concerned 217 (41.10) 175 (34.93) 200 (41.75)
  Moderately concerned 149 (28.22) 177 (35.33) 158 (32.99)
  Very concerned 64 (12.12) 73 (14.57) 50 (10.44)
 MOUD as substitution
  Strongly disagree 52 (9.85) 32 (6.39) 43 (8.98) 0.086
  Somewhat disagree 64 (12.12) 46 (9.18) 45 (9.39)
  Neither agree nor disagree 98 (18.56) 98 (19.56) 89 (18.58)
  Somewhat agree 142 (26.89) 124 (24.75) 142 (29.65)
  Strongly agree 172 (32.58) 201 (40.12) 160 (33.40)
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Note: MOUD, Medications for Opioid Use Disorder

In assessing respondents’ levels of knowledge of MOUD, two-thirds of respondents (66.8%) had at least some knowledge about methadone, buprenorphine, or naltrexone. However, only 14.2% and 26.3% respondents had experience in MOUD treatments or other treatments, respectively. Many respondents (62.4%) agreed somewhat or strongly with the perception that MOUD is a “substitute” for opioids. Further, most respondents had some level of concern around misuse of methadone (79.2%) and buprenorphine (83.8%). However, when assessing first choice preference for treatment, a greater proportion of respondents choose methadone (35.8%) or buprenorphine (34.8%), while fewer respondents expressed preference for naltrexone or non-medication treatments. Black respondents were more likely to prefer non-medication treatments (17.0%) compared to White (11.0%) and Latino/a (13.4%) respondents (p =.02).

In multivariable analysis (Table 2), there were several noteworthy associations. One of our covariates, knowledge of non-medication treatments, was significantly associated with preference for methadone (adjusted Odds Ratio (OR)=3.16, 95% CI=1.35–7.39) and buprenorphine (OR=2.69, 95% CI=1.11–6.47) among White respondents. Among Black respondents, knowledge of non-medication treatments was positively associated with preferences for methadone (OR=3.91, 95% CI=1.58–9.69). Among Latino/a respondents, knowledge of non-medication treatments was positively associated with preferences for methadone (OR=5.12, 95% CI=1.99–13.2), buprenorphine (OR=3.85, 95% CI=1.5–9.87), and naltrexone (OR=4.51, 95% CI=1.44–14.06).

Table 2.

Multinomial logistic regression of treatment preference, (reference category=non-medication treatment)

White (n=528)
Odds Ratio (95% CI)		 Black (n=501)
Odds Ratio (95% CI)		 Latino/a (n=479)
Odds Ratio (95% CI)
MMT BUP NTX MMT BUP NTX MMT BUP NTX
Sociodemographic
Age 1.00
(0.84–1.20)		 0.95
(0.79–1.13)		 0.94
(0.77–1.14)		 0.98
(0.84–1.13)		 0.90
(0.78–1.05)		 0.97
(0.81–1.16)		 0.98
(0.82–1.18)		 0.96
(0.80–1.14)		 1.07
(0.88–1.31)
Gender (ref=man) 1.34
(0.71–2.53)		 1.91
(1.00–3.65)		 1.37
(0.68–2.78)		 1.00
(0.58–1.73)		 1.17
(0.68–2.03)		 0.78
(0.41–1.51)		 1.28
(0.68–2.40)		 1.11
(0.60–2.06)		 1.50
(0.73–3.07)
Household income 1.14
(0.80–1.61)		 1.22
(0.86–1.74)		 1.06
(0.72–1.55)		 1.30
(0.97–1.74)		 1.43 *
(1.07–1.92) 		1.05
(0.74–1.50)		 1.12
(0.79–1.6)		 1.25
(0.88–1.76)		 1.30
(0.88–1.94)
Treatment Knowledge and Experience (ref = none)
MOUD knowledge 1.33
(0.65–2.70)		 1.64
(0.79–3.41)		 0.87
(0.39–1.92)		 1.09
(0.57–2.08)		 1.24
(0.64–2.39)		 1.15
(0.52–2.55)		 0.85
(0.40–1.79)		 1.34
(0.63–2.85)		 0.74
(0.32–1.73)
Non-MOUD knowledge 3.16 **
(1.35–7.39) 		2.69 *
(1.11–6.47) 		2.32
(0.89–6.02)		 3.91 **
(1.58–9.69) 		1.98
(0.85–4.60)		 3.05
(0.95–9.86)		 5.12 ***
(1.99–13.2) 		3.85 **
(1.50–9.87) 		4.51 **
(1.44–14.06)
Experience with MOUD treatments 2.09
(0.54–8.02)		 4.33 *
(1.17–16.06) 		3.27
(0.82–13.05)		 1.84
(0.69–4.94)		 1.58
(0.59–4.23)		 2.65
(0.92–7.64)		 0.91
(0.36–2.28)		 1.00
(0.42–2.42)		 1.40
(0.52–3.78)
Experience with other treatments 2.00
(0.72–5.58)		 2.86 *
(1.03–7.94) 		3.17 *
(1.08–9.28) 		0.97
(0.49–1.92)		 1.37
(0.70–2.70)		 1.36
(0.62–2.98)		 0.59
(0.29–1.2)		 0.81
(0.41–1.6)		 0.82
(0.38–1.80)
Perceptions of MOUD
Concern for MMT misuse 0.65 *
(0.43–0.98) 		0.95
(0.62–1.44)		 0.94
(0.60–1.47)		 0.92
(0.66–1.30)		 1.15
(0.82–1.62)		 1.21
(0.81–1.82)		 0.49 ***
(0.34–0.70) 		1.00
(0.70–1.44)		 0.82
(0.55–1.24)
Concern for BUP misuse 0.62 *
(0.39–0.99) 		0.48 **
(0.3–0.77) 		0.6 *
(0.36–0.99) 		0.69
(0.47–1.01)		 0.72
(0.49–1.05)		 0.7
(0.45–1.11)		 0.96
(0.63–1.46)		 0.59 *
(0.39–0.89) 		0.91
(0.56–1.48)
MOUD as substitution
(disagree=>agree)		 0.94
(0.73–1.22)		 0.94
(0.72–1.21)		 1.26
(0.94–1.7)		 1.07
(0.85–1.36)		 0.95
(0.75–1.19)		 0.95
(0.72–1.26)		 1.01
(0.77–1.32)		 0.88
(0.68–1.14)		 1.29
(0.94–1.77)
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*

p <.05,

**

p <.01,

***

p<.001.

Note: MOUD, Medications for Opioid Use Disorder; PO, prescription opioid; MMT, Methadone; BUP, Buprenorphine; NTX, Naltrexone

While there were no significant differences in experience with MOUD and other treatments across race/ethnicity, experience with MOUD treatments was positively associated with preference for buprenorphine among White respondents alone (OR=4.33, 95% CI=1.17–16.06). Additionally, experience with other treatments was positively associated with preference for buprenorphine (OR=2.86, 95% CI=1.03–7.94) and naltrexone (OR=3.17, 95% CI=1.08–9.28), but only among White respondents. Our primary association of interest was the relationship between perceptions of MOUD and treatment preferences. We found concern around the misuse of methadone was negatively associated with preference for methadone among White (OR=0.65, 95% CI=0.43–0.98) and Latino/a respondents (OR=0.49, 95% CI=0.34–0.7), but not Black respondents. Additional supplementary analyses directly comparing methadone to buprenorphine indicated similar results, where concern around methadone was associated with preference for buprenorphine among White (OR=1.46, 95% CI=1.11–1.94) and Latino/a (OR=2.09, 95% CI=1.58–2.81) respondents (see II. Supplementary Information). Similarly, concern around the misuse of buprenorphine was negatively associated with preference for methadone (OR=0.62, 95% CI=0.39–0.99), buprenorphine (OR=0.55, 95% CI=0.35–0.88) and naltrexone (OR=0.6, 95% CI=0.36–0.99) among White respondents and for buprenorphine (OR=0.59, 95% CI=0.39–0.89) among Latino/a respondents.

4. Discussion

By surveying a sample of the general U.S. population, this study provides critical insights into perceptions of medications for opioid use disorder that extend beyond those with problematic opioid use. Further, by intentionally sampling roughly similar numbers of participants from three racial/ethnic groups, this design allows adequately-powered comparisons of MOUD public opinion within and between racial/ethnic groups. Results show a majority of respondents had at least some familiarity with MOUD, but there were key differences in treatment preferences and perceptions across racial and ethnic groups. Black respondents were more likely to prefer non-medication treatment than White or Latino/a respondents. It may be that Black respondents perceive non-medication treatment as more efficacious, or more favorable due to racialized stigma, concerns about racism in medical settings, or perceived inaccessibility of office-based treatments (Andraka-Christou, 2021; Hansen & Roberts, 2012; Kulesza et al., 2016; Lagisetty et al., 2019), but more research is needed to understand the root of these preferences. However, in multivariable analysis, across all groups, knowledge of non-medication treatments was associated with preference for MOUD (i.e., methadone, buprenorphine, naltrexone). While knowledge of non-medication treatment was high, this finding may be signaling that respondents have some concurrent awareness of the lower efficacy or effectiveness of non-medication treatments as well. In addition, we found that experience with MOUD and other treatment options was far less prevalent than knowledge and only positively associated with MOUD for White respondents. Several comparative studies and systematic reviews have shown treatment with MOUD is associated with better outcomes (e.g., treatment efficacy; lower rates of overdose; opioid-related hospitalization) compared to non-pharmacological approaches to OUD (Mattick et al., 2009; Rosenthal et al., 2013; Wakeman et al., 2020).

Despite preference for MOUD over non-medication treatments, beliefs about MOUD were not consistently positive. Previous research has highlighted the prevalence of MOUD misperceptions and MOUD stigma among PWUD and providers (Cioe et al., 2020; Madden et al., 2021). Building on this research, the current analysis provides original evidence of the prevalence of stigmatizing MOUD beliefs among the public and across racial/ethnic groups. In descriptive analyses, a majority of respondents held beliefs that MOUD is a “substitute” for opioid use, as well as concern around misuse of MOUD, even after hearing about clinical care guidelines through video vignettes embedded in the survey. These results emphasize the strong parallels between drug- and treatment-related stigma, as taking MOUD may be perceived as problematic substance use, as well as the persistence of cultural messages that frame PWUD as untrustworthy and apt to misuse medication. Further, multivariable model results indicate beliefs about misuse were significantly associated with negative preference for either methadone or buprenorphine treatments across all racial/ethnic groups. Consistent with previous research with PWUD (Paquette et al., 2018), these associations highlight how medication beliefs can have tangible consequences for uptake, and consequently, health outcomes.

Findings around the prevalence of stigmatizing MOUD beliefs among U.S. adults have critical implications for the wellbeing of people who use drugs. First, stigma can permeate social ties and impact others’ health behaviors, particularly for people with health issues deemed “blameworthy,” as substance use disorders are often framed (Frank & Nagel, 2017; Thoits, 2011). Previous research has noted that when PWUD perceived MOUD stigma from their social networks, they reconsidered taking MOUD (Chou et al., 2022). People who hold negative beliefs of MOUD may be reluctant to support friends or family or to seek MOUD themselves, should they need to access treatment in the future (Madden et al., 2021). Second, negative perceptions of MOUD among the public may be associated with decreased political support for government funding of treatment (Pecoraro et al., 2012; Pyra et al., 2022). Prior work has underscored that need does not dictate health coverage for drug treatment, but that public resources and political factors shape drug treatment coverage (Tempalski et al., 2020). Amidst rising overdose rates and eroding social and health services, it is critical that voters support and prioritize public funding for evidence-based substance use treatments. Finally, related to political support, people with negative perceptions of MOUD may be more opposed to accommodating MOUD treatment facilities (e.g., methadone clinics) in their communities (Smith, 2010; Tempalski et al., 2007). This form of public stigma may ultimately produce “treatment deserts,” areas in which MOUD is entirely unavailable (Mitchell et al., 2022; Smith, 2010).

Our analysis has several limitations. First, while our study samples had substantial demographic diversity, respondents were not randomly sampled and stratified and thus we cannot claim representativeness of the U.S. population. Further, the company we used for the web-based survey did not provide response rates and are subject to selection bias. Recent findings highlight that online survey respondents may have lower self-rated health and greater mental health issues than the general population (Mortensen et al., 2018; Walters et al., 2018). However, internet samples can contribute valuable perspectives on substance use perceptions and behaviors (Borodovsky, 2022), and the use of internet-based recruitment facilitates the equal and sufficient study samples for analysis between and within racial and ethnic groups—a strength of this analysis. Second, respondents were shown educational videos about MOUD in the survey, which may have shaped their treatment preferences. However, educational information established baseline knowledge and was designed to be similar to web search results, thus reflecting real-world circumstances in seeking knowledge about treatment options. Third, the survey modality presented limitations in representing the full range of respondent social locations, including race/ethnicity. Respondents’ racial and ethnic backgrounds may reflect multiple identities and we cannot be certain that, for instance, Latino/a respondents did not also identify with Black or White racial categories. We also did not recruit other racial/ethnic populations, including Native American and Alaskan Natives, who experience high rates of overdose relative to population size and may have less access to MOUD in rural settings. Future studies should examine treatment perceptions among Native American and Alaskan Natives and other populations disproportionately impacted by the overdose crisis.

While earlier studies have assessed dimensions of MOUD stigma, this study is among the first to assess perceptions of MOUD among a racially stratified sample of US adults. Analyses revealed a significant portion of the sample held negative perceptions of MOUD, and that these beliefs were negatively associated with preference for MOUD treatment. Taken together, these results expand understandings of MOUD stigma beyond the patient population and highlight implications for public support of the expansion of MOUD treatment. Expanding on these findings, future research should explore mechanisms for reducing public stigma through healthcare providers and public awareness campaigns that normalize MOUD, emphasize its legitimacy as medical treatment, and promote its efficacy in addressing opioid use disorders.

Supplementary Material

Video Vignette Links
Supplementary Table 3.

Acknowledgements

The authors would like to thank Adrianne Kehne and Jennifer Thomas for their thoughtful contributions to survey design.

Funding

The study was funded by the National Institute on Drug Abuse at the US National Institutes of Health [K23 DA047475 (PL)]. AB is supported by Blue Cross Blue Shield of Michigan and the Michigan Department of Health and Human Services for work related to MOUD.

Footnotes

Declarations of Interest

None. The authors have no conflicts of interest to report. AB served as an expert witness in cases against opioid distributors.

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Supplementary Materials

Video Vignette Links
NIHMS2004125-supplement-Video_Vignette_Links.docx (14.4KB, docx)
Supplementary Table 3.
NIHMS2004125-supplement-Supplementary_Table_3_.docx (23.6KB, docx)

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