Abstract
Background:
The process by which individuals change their substance use is personal and often non-linear, with periods of recovery, return to use, and treatment re-entry. This study characterizes utilization of substance use services and barriers to treatment access among United States (U.S.) adults with a self-identified lifetime alcohol and/or drug use problem who are versus are not in recovery.
Methods:
This study uses a subset of adults from the 2023 National Survey on Drug Use and Health (NSDUH) who self-identified as having had a problem with alcohol and/or drugs at some point in their lifetime (unweighted n=5,260, 38.4% female, 24.5% people of color).
Results:
Most participants (72.9%) self-identified as being in recovery. Individuals in recovery (relative to those with a lifetime problem but not in recovery) were more likely to report past-year substance use treatment (aOR=1.48); this difference appeared to be driven by the greater likelihood of using support groups (aOR=1.53) and peer support specialists or recovery services (aOR=1.17) among those in recovery. No differences were observed for other treatment types. Among those with past-year perceived unmet need for treatment (8.0% of the overall sample), individuals in recovery were significantly less likely to endorse concerns regarding stigma (aOR=0.25) and readiness to change (aORs=0.17–0.20). Otherwise, no differences were observed for other barriers.
Conclusions:
Our findings highlight stigma as a unique distinguishing feature between those who are and are not in recovery from a substance use problem. Stigma-reducing interventions are needed to ensure that a greater proportion of individuals receive effective treatment.
Clinical impact statement:
Of people with a lifetime self-identified problem with alcohol and/or drug use, most also self-identified as being in recovery. We found that people in recovery were more likely to use support groups and peer-based services, while stigma stood out as a unique barrier to accessing treatment among those not in recovery. Increasing access to recovery-focused services might help to promote a recovery identity, thereby reducing stigma as a barrier to accessing treatment.
Keywords: substance use recovery, treatment utilization, barriers to treatment utilization, stigma
Introduction
Substance use disorders (SUDs) are among the most prevalent mental and behavioral health concerns and are characterized by a constellation of physical and behavioral symptoms including withdrawal, tolerance, and craving (American Psychiatric Association, 2013). In 2024, 17.7% of United States (U.S.) adults met criteria for a SUD (Substance Abuse and Mental Health Services Administration [SAMHSA], 2025a). The process by which individuals change their substance use is personal (Laudet, 2007) and often non-linear, characterized by cycling periods of recovery, return to use, and treatment re-entry (Kelly et al., 2019). Access to treatment and recovery services is critical to reduce the incidence of substance use-related harm. Of note, various evidence-based interventions for SUD have been developed. These interventions include inpatient or residential services (e.g., detoxification), outpatient services, and medication, and more informal services such as support groups and peer support services. However, most people with a SUD never access treatment - only 19.5% of those who needed substance use treatment reported receiving it in the U.S. in 2024 (SAMHSA, 2025a). Commonly reported barriers to receiving substance use treatment include structural barriers (e.g., didn’t know where to go), attitudinal (e.g., stigma-related barriers such as concern regarding what other people would think) and readiness to change barriers (e.g., not being ready to stop using substances; Haeny et al., 2021).
Recovery from SUDs is a dynamic process in which individuals achieve increasingly stable remission and enhanced quality of life over time (Kelly & Hoeppner, 2015) and is inclusive of changes occurring in the context of formal treatment or services or outside of such services (often termed “natural recovery;” Pongsavee et al., 2021). The construct of recovery has evolved in its definition and use over time, though many perspectives highlight the individual’s subjective experience of their own change (Zemore et al., 2023). In particular, the social identity model of recovery proposes that recovery reflects a transition wherein one’s self-identity shifts from that of a person who is actively using substance to one who is “in recovery,” often evidenced by shifting away from social groups that promote substance use and towards those that are promotive of recovery efforts and who reinforce and normalize the new recovery identity (Best et al., 2016). Individuals who hold a recovery identity have been found to have greater likelihood of sustaining recovery, perhaps due to increased recovery capital (i.e., personal, social, and community resources that support one’s recovery, such as meaningful daily activities, social and professional support, housing, etc.; Best & Hennessy, 2022). Recovery capital has, in turn, been positively linked to motivation to complete treatment (Baker et al., 2020) and better treatment outcomes (Headid et al., 2024). Yet, it is not clear the extent to which individuals who self-identify as being in recovery (versus not in recovery) use treatment services or experience barriers to treatment utilization.
This study leverages nationally representative U.S. data (i.e., the National Survey on Drug Use and Health [NSDUH]) to characterize treatment access and barriers to treatment access among U.S. adults with a self-identified lifetime problem with alcohol and/or drug use who do and do not self-identify as being in recovery. We hypothesized that individuals who self-identify as being in recovery would endorse greater treatment utilization and reduced barriers to treatment.
Methods
Participants and Procedures
This study was declared exempt from review (not human subjects research) by the Yale University Institutional Review Board. This study uses a subset of adults from the 2023 wave of the NSDUH. The NSDUH is a large-scale cross-sectional survey which estimates the presence and associated determinants of substance use, mental illness, and other health-related issues in the U.S. civilian population, sponsored by the SAMHSA. Stratified multistage probability sampling is used to obtain nationally representative cohorts of individuals residing in households or non-institutional group settings. The NSDUH does not include individuals with no fixed household address (e.g., unhoused individuals), active-duty military personnel, those residing in institutional group settings (e.g., nursing homes, correctional facilities, treatment centers), and those unable to complete the survey in English or Spanish. NSDUH data and extensive information regarding methodology for data collection, procedures, and participant information is publicly available at the SAMHSA Data Archive (SAMHSA, 2025b). Participants provided informed consent prior to engaging in data collection procedures and were compensated $30 for their participation. This study used a subset of adults who self-identified as having had a problem with alcohol or drugs at some point in their lifetime (n = 5,260, 38.4% female, 24.5% people of color).
Measures
Recovery Identity
Participants were asked a single item regarding whether they considered themselves “to be in recovery or recovered from a problem with drugs or alcohol” at the time they were interviewed with response options 0 (no) and 1 (yes). Affirmative responses are hereafter referred to as reflecting being “in recovery” for the sake of brevity.
Substance Use
Participants reported how frequently they drank alcohol in the past year (i.e., number of days of use in the past 365); this value was dichotomized to reflect whether participants had used any alcohol in the past year (coded as 0 = none in the past year and 1 = any in the past year). Participants reported whether they had used a range of drugs (e.g., cocaine, hallucinogen, heroin) in the past year. These values were collapsed to create a single variable reflecting whether they had used any illicit drugs in the past year, with response options 0 (no) and 1 (yes).
Past-year SUD symptoms were assessed using items corresponding to DSM-5 criteria. Individuals who endorsed at least two of these items were categorized as meeting criteria for SUD. These items were asked only of respondents who reported using alcohol and/or drugs on six or more occasions in the past year.
Treatment Utilization
Participants were asked whether they had received treatment for substance use in the past year. Then, those who received substance use treatment were asked in what type of setting they had received treatment (e.g., inpatient locations, outpatient locations, medication for alcohol use or opioid use, support groups, peer support services) with response options 0 (no) and 1 (yes) for each treatment type.
Barriers to Treatment Utilization
First, participants were asked whether there was a time in the past year that they either sought substance use treatment or believed that they needed substance use treatment but did not receive such treatment, with response options 0 (no) and 1 (yes). Then, those who answered affirmatively were asked 18 questions about their reasons for not receiving or seeking out substance use treatment in the past year. For each question, participants responded with “one of the reasons” or “not one of the reasons” that they did not receive or seek treatment. Of note, NSDUH assesses reasons for not seeking treatment and reasons for not receiving treatment together (versus assessing whether each barrier is, separately, a reason not to have sought out treatment and/or a reason not to have received treatment). Barriers to treatment assessed include structural barriers (e.g., cost, access to providers), attitudinal barriers (e.g., thinking treatment wouldn’t help, concerns about what people would think or say), readiness to change barriers (i.e., not ready to start treatment, not ready to change their substance use), and other barriers (e.g., concerns about losing their home, job, or children, thinking that no one would care if they got better).
Data Analytic Strategy
All analyses were conducted using PROC SURVEYLOGISTIC in SAS 9.4. Logistic regression analyses were used to examine whether likelihood of past-year treatment utilization and barriers to past-year treatment access varied across recovery status. First, we ran a series of unadjusted models in which recovery status was entered as the only independent variable and each treatment type and barrier were entered as binary dependent variables. Then, for treatment types and barriers that were found to be significantly related to recovery status in unadjusted models, additional models were examined adjusting for age, sex, race, income, education, and insurance status. All models accounted for complex sampling procedures, which accounted for weight, stratum, and cluster variables. Given the large sample size and number of comparisons, α = .01.
Results
Nearly three-quarters of individuals who self-identified as having a lifetime substance use problem also identified being in recovery (unweighted n = 3,726, 72.9%, SE = 1.2). Demographic characteristics in the overall sample and by recovery status are presented in Table 1. Compared to individuals in recovery, those who were not in recovery were significantly more likely to be 18–25 years old (OR = 2.10, 95%CI [1.42, 3.09]); otherwise, there were no significant differences in demographic characteristics across recovery status. Individuals in recovery were significantly less likely to report past-year alcohol use (aOR = 0.19, 95%CI [0.13, 0.27]) and past-year drug use (aOR = 0.56, 95%CI [0.45, 0.70]) than individuals not in recovery. Further, individuals in recovery were significantly less likely to have a past-year SUD (aOR = 0.21, 95%CI [0.16, 0.29]).
Table 1.
Demographic and descriptive characteristics of the overall sample and by recovery status, % (SE)
| Characteristic | Overall (unweighted N = 5,260) |
In Recovery (unweighted n = 3,726) |
Not in Recovery (unweighted n = 1,518) |
|---|---|---|---|
| Age | |||
| 18 – 25 years old | 9.1% (0.5) | 8.0% (0.5) | 12.1% (0.9) |
| 26 – 34 years old | 18.0% (0.9) | 17.7% (0.9) | 18.8% (1.7) |
| 35 – 49 years old | 30.5% (1.0) | 30.6% (1.2) | 30.4% (1.8) |
| 50 – 64 years old | 26.5% (1.5) | 26.6% (1.7) | 26.5% (2.2) |
| 65 or older | 15.8% (1.1) | 17.1% (1.3) | 12.3% (1.7) |
| Sex assigned at birth | |||
| Female | 38.4% (1.2) | 38.3% (1.5) | 38.4% (2.3) |
| Male | 61.6% (1.2) | 61.7% (1.5) | 61.6% (2.3) |
| Racial and ethnic background | |||
| Non-Hispanic White | 75.5% (1.1) | 75.0% (1.3) | 77.0% (1.9) |
| Non-Hispanic Black or African American | 6.6% (0.6) | 6.6% (0.7) | 6.7% (1.0) |
| Non-Hispanic American Indian or Alaska Native | 0.8% (0.2) | 0.7% (0.2) | 0.9% (0.4) |
| Non-Hispanic Native Hawaiian or other Pacific Islander | 0.3% (0.1) | 0.2% (0.1) | 0.6% (0.4) |
| Non-Hispanic Asian | 1.9% (0.3) | 1.6% (0.4) | 2.1% (0.9) |
| Non-Hispanic Multiracial | 3.4% (0.5) | 3.4% (0.5) | 3.1% (0.7) |
| Hispanic | 11.6% (0.9) | 12.4% (0.9) | 9.6% (1.6) |
| Marital status | |||
| Never married | 34.5% (1.7) | 33.6% (1.4) | 36.9% (2.0) |
| Married | 42.3% (1.1) | 43.3% (1.3) | 39.2% (2.1) |
| Divorced or separated | 30.1% (1.1) | 19.8% (1.2) | 21.2% (1.9) |
| Widowed | 3.1% (0.4) | 3.3% (0.6) | 2.7% (0.8) |
| Education attainment | |||
| Less than high school | 8.2% (0.7) | 8.2% (0.8) | 8.5% (1.3) |
| High school diploma/GED | 25.2% (1.0) | 26.7% (1.1) | 20.9% (1.8) |
| Associate’s degree/Some college | 33.7% (1.0) | 34.3% (1.2) | 32.3% (2.2) |
| College degree or higher | 32.9% (1.2) | 30.8% (1.4) | 38.3% (1.9) |
| Annual family income | |||
| Less than $20,000 | 15.9% (0.8) | 15.8% (0.9) | 16.4% (1.8) |
| $20,000 – $49,999 | 25.9% (1.0) | 26.7% (1.1) | 23.7% (2.2) |
| $50,000 - $74,999 | 14.3% (0.8) | 14.4% (1.0) | 14.2% (1.2) |
| $75,000 or more | 43.8% (1.1) | 43.1% (1.4) | 45.7% (2.2) |
| Employment status | |||
| Employed full-time | 51.4% (1.2) | 50.9% (1.5) | 52.6% (2.2) |
| Employed part-time | 12.5% (0.6) | 12.4% (0.7) | 12.8% (1.3) |
| Unemployed | 5.1% (0.5) | 4.5% (0.6) | 6.7% (1.0) |
| Other | 31.0% (1.1) | 32.2% (1.3) | 27.9% (2.4) |
| Covered by health insurance | 91.8% (0.5) | 92.3% (0.6) | 90.2% (1.2) |
| Past-year alcohol use | 70.6% (1.4) | 63.3% (1.7) | 90.1% (1.3) |
| Past-year drug use | 59.3% (1.3) | 55.3% (1.5) | 69.7% (2.1) |
| Past-year SUD | 50.0% (1.5) | 40.8% (1.6) | 74.7% (2.2) |
| Past-year treatment utilization | 25.4% (1.0) | 27.5% (1.3) | 20.3% (1.9) |
| Past-year unmet treatment need | 8.0% (0.8) | 3.4% (0.6) | 20.2% (2.2) |
Note. SUD = substance use disorder; bolded typeface denotes significant difference between those who are (versus are not) in recovery when accounting for demographic characteristics (p < .01)
Differences in Treatment Utilization by Recovery Status
Participants in recovery were significantly more likely to have used any treatment to address their substance use in the past year (aOR = 1.48, 95%CI [1.12, 1.96]). Rates of use of each treatment type in the overall sample and by recovery status among those who reported using at least one type of treatment (unweighted n = 1,359, 25.4%, SE = 1.02) are presented in Table 2. Examination of particular treatment types revealed individuals in recovery were significantly more likely to have used support groups (aOR = 2.53, 95%CI [1.74, 3.68]) and peer support specialists or recovery coaches (aOR = 2.17, 95%CI [1.25, 3.75]) in the past year. There were no differences observed in likelihood of having used any other type of treatment in the past year.
Table 2.
Treatment services used in the overall sample and by recovery status among those who reported using at least one type of treatment, % (SE)
| Treatment Type | Overall (unweighted N = 1,359) |
In Recovery (unweighted n = 1,067) |
Not in Recovery (unweighted n = 292) |
|---|---|---|---|
| Specialty Substance Use Services | |||
| Residential substance use rehabilitation/ treatment center | 22.7% (2.7) | 26.1% (3.4) | 15.3% (4.4) |
| Outpatient substance use rehabilitation/ treatment center | 29.2% (3.0) | 32.2% (4.1) | 22.5% (4.6) |
| Prescription medication to cut back or stop alcohol use | 12.6% (1.5) | 11.7% (1.6) | 14.4% (2.6) |
| Prescription medication to cut back or stop heroin/PNR use | 25.5% (2.7) | 26.6% (3.2) | 23.3% (4.4) |
| Detox services for withdrawal symptoms | 19.8% (2.9) | 23.5% (3.8) | 11.7% (3.5) |
| Support group | 48.6% (3.2) | 52.5% (3.8) | 39.9% (4.4) |
| Peer support specialist/recovery coach | 25.5% (2.6) | 30.3% (3.7) | 14.9% (3.0) |
| General Mental Health Services | |||
| Residential mental health treatment center | 13.2% (1.5) | 12.3% (2.2) | 15.0% (3.5) |
| Outpatient mental health treatment center | 25.1% (3.2) | 27.6% (4.0) | 19.7% (5.0) |
| Therapist office | 46.8% (2.6) | 48.4% (4.0) | 43.1% (4.5) |
| School health/counseling | 6.4% (1.7) | 6.7% (2.2) | 5.8% (2.7) |
| Other Services | |||
| Emergency department | 21.1% (2.2) | 22.0% (3.1) | 18.9% (3.2) |
| Inpatient hospitalization | 24.0% (2.7) | 24.0% (2.9) | 24.2% (6.1) |
| Other inpatient treatment | 9.1% (1.8) | 8.8% (2.1) | 9.7% (4.0) |
| General medical office | 33.3% (3.4) | 36.0% (3.9) | 27.4% (5.2) |
| Hospital as outpatient | 14.9% (2.9) | 13.7% (3.4) | 17.6% (6.5) |
| Other outpatient treatment | 11.4% (2.1) | 11.5% (3.0) | 11.1% (3.9) |
| Phone/video services | 46.9% (3.0) | 46.2% (4.2) | 48.2% (6.7) |
Note. Bolded typeface denotes a significant difference between those who are (versus are not) in recovery when accounting for demographic characteristics (p < .01)
Differences in Barriers to Treatment Access by Recovery Status
Approximately 8% of individuals reported unmet need for treatment in the past year (SE = 0.75, unweighted n = 362). Participants in recovery were significantly less likely to report past-year unmet need for substance use treatment (aOR = 0.13, 95%CI [0.08, 0.21]). Rates of endorsement of each barrier to treatment access in the past year in the overall sample and by recovery status among those who reported unmet need for treatment are presented in Table 3. Participants in recovery were significantly less likely to endorse readiness to change barriers: not being ready to start treatment (aOR = 0.20, 95%CI [0.09, 0.48]) and not being ready to stop or cut back on substance use (aOR = 0.17, 95%CI [.07, .45]). Otherwise, the only barrier for which a significant difference was observed was related to anticipated stigma: individuals in recovery were significantly less likely to endorsed being worried about what people would think and say (aOR = 0.25, 95%CI [0.13, 0.51]).
Table 3.
Barriers to past-year treatment utilization in the overall sample and by recovery status among those who reported past-year unmet need for treatment, % (SE)
| Barrier | Overall (unweighted N = 362) |
In Recovery (unweighted n = 118) |
Not in Recovery (unweighted n = 243) |
|---|---|---|---|
| Structural Barriers | |||
| Cost too much | 45.2% (4.8) | 53.2% (6.4) | 41.4% (5.1) |
| No health insurance coverage | 29.8% (4.1) | 29.3% (5.9) | 30.0% (4.5) |
| Health insurance didn’t cover enough | 34.2% (5.0) | 34.6% (6.8) | 34.1% (5.0) |
| Didn’t know where to get treatment | 38.6% (4.4) | 40.4% (7.4) | 37.8% (5.0) |
| Couldn’t find preferred provider | 26.4% (3.9) | 29.1% (6.1) | 25.2% (3.5) |
| No opening with preferred provider | 11.6% (2.8) | 13.5% (5.8) | 10.7% (2.9) |
| Problem with transportation, childcare, appointment timing | 22.8% (3.5) | 32.0% (6.3) | 18.5% (4.0) |
| Not enough time for treatment | 38.0% (4.4) | 39.8% (7.1) | 37.0% (5.2) |
| Attitudinal Barriers | |||
| Didn’t think treatment would help | 22.8% (3.6) | 25.7% (6.8) | 21.4% (3.2) |
| Worried what people would think/say | 39.7% (3.9) | 22.9% (4.5) | 47.3% (4.4) |
| Family/friends/religion wouldn’t like it* | 14.0% (2.4) | 5.8% (1.8) | 17.4% (2.6) |
| Thought could handle problem on own | 76.3% (4.7) | 72.5% (4.3) | 77.8% (5.4) |
| Afraid to be forced against will | 16.9% (3.1) | 13.3% (4.1) | 18.4% (4.2) |
| Readiness to Change Barriers | |||
| Not ready to start treatment | 65.9% (4.5) | 48.5% (5.8) | 73.7% (4.2) |
| Not ready to stop/cut back on substance use | 59.3% (4.9) | 38.1% (6.3) | 68.9% (5.6) |
| Other Barriers | |||
| Worried information would not be kept private | 29.8% (3.7) | 25.6% (4.5) | 31.5% (5.0) |
| Thought would lose home/job/child | 28.9% (4.0) | 27.6% (4.4) | 29.4% (4.9) |
| No one would care if you got better | 18.1% (3.7) | 12.7% (4.4) | 20.2% (4.3) |
Note.
Indicates a significant difference between those who are (versus are not) in recovery in unadjusted models (p < .01); bolded typeface denotes significant difference between those who are (versus are not) in recovery when accounting for demographic characteristics (p < .01)
Discussion
The goal of the present study was to examine whether treatment utilization and barriers to treatment differed as a function of one’s recovery identity. First, we found that most individuals (72.9%) who reported a lifetime problem with drug or alcohol use also self-identified as being in recovery. Individuals in recovery were more likely to have accessed substance use treatment in the past year, despite being less likely to meet criteria for SUD, while also more likely to engage with informal services, including support groups, peer recovery support specialists, and recovery coaches. Next, we found that individuals in recovery were less likely to endorse concerns related to readiness to change and stigma as barriers to seeking or receiving substance use treatment in the past year. suggesting behavioral change may occur without a recovery identity. Additional work is needed to understand this process of behavior change among those who do not hold a recovery identity despite having successfully met substance use-focused change goals.
It is possible that individuals who hold a recovery identity are more likely to engage with treatment services, or that these types of treatments foster individuals’ development of a recovery identity. The social identity model of recovery (Best et al., 2016) emphasizes that adopting a recovery-oriented identity can enhance treatment outcomes (Lancaster et al., 2025a; Lancaster et al., 2025b). In line with this model, it may be that engaging with support groups or recovery support services promotes contact with a supportive social network who prioritize substance use recovery, thereby fostering one’s identity transformation and prompting adoption of a recovery identity. Alternatively, it may be that individuals who already hold a recovery identity seek out informal service settings to support their recovery. Additional research is needed to better understand when in their behavior change process individuals develop a recovery identity to better understand how this identity transformation interacts with treatment utilization. Further, it is important to note that empirical evidence regarding the use of support groups and peer recovery services have each been mixed in part due to heterogeneity across services (Gormley et al., 2021; Tracy & Wallace, 2016).
Findings highlight stigma as a unique barrier distinguishing those who are in recovery from a substance use problem and those who are not. It is notable that the stigma-related barriers were also among the most commonly reported barriers across the sample. Stigma-reducing interventions are needed to ensure that the proportion of individuals receiving effective treatment increases. Considering our findings together, support groups and peer recovery services might be promising interventions to address stigma as a harmful barrier to substance use care. Growing evidence suggests that these types of interventions reduce stigma among individuals in mental health treatment (Sun et al., 2022; Vayshenker et al., 2016). Although the underlying mechanisms by which these interventions may reduce stigma are not yet clear, one plausible explanation is that both generally offer direct contact with individuals in recovery, which may challenge stereotypes about individuals with SUDs (Keyes et al., 2010). This is important given that substantial stigma exists around using substances and having a SUD (Corrigan et al., 2017; Rundle et al., 2025; Zwick et al., 2020), on top of stigma related to accessing SUD treatment. Interacting individuals who have previously used SUD and who are perceived as being successful in their recovery may help disrupt the internalization of these messages, promoting positive long-term outcomes. It is important to note, however, that not all support groups or peer support services are created equally. For example, 12-step groups tend to encourage adoption of a “diseased identity” focused on one’s history of use, which can exacerbate negative self-perceptions and inhibit engagement with other types of support (Gormley et al., 2021; Tracy & Wallace, 2016).
Findings should be considered within the context of limitations. The NSDUH does not reflect the experiences of individuals with no fixed household addresses (e.g., unhoused and incarcerated individuals) who may be engaged in recovery and treatment services or who may be experiencing the most extreme barriers to receiving care. Additionally, this study does not consider recovery identity as a dynamic construct (Lancaster et al., 2025a). Lastly, the cross-sectional nature of the NSDUH data impedes establishing causal relationships or directionality.
Conclusions
Findings of the present study suggest that engagement in services that promote contact with a supportive social network who prioritize substance use recovery may be crucial to promoting adoption of a recovery identity and reducing the deleterious effects of stigma as a help-seeking barrier. Support groups and peer recovery services seem to be promising interventions to support individuals in recovery, (Gormley et al., 2021; SAMHSA, 2025a; Tracy & Wallace, 2016) emphasizing the need for further research on their effectiveness across recovery outcomes and treatment settings. For instance, if these types of services promote adoption of a recovery identity, integrating such services into less traditional substance use service settings (e.g., into primary care) may serve to reduce stigma and improve outcomes. Additional research is needed to continue to elucidate the nature of the associations among one’s recovery-related identity and treatment access and engagement.
Funding:
Work on this manuscript was supposed by National Institutes of Health grants K23DA059609 and K99AA029154. The funding source had no role in the study design, data collection, analysis, and interpretation, writing of the report, or decision to submit the article for publication.
Footnotes
Conflicts of Interest: The authors report no conflicts of interest.
Positionality statement: Recognizing that our identities shape our scientific perspectives and the questions we prioritize, the authors wish to acknowledge our positionality. The authors are four cisgender women, two of whom self-identify as White and two who self-identify as Latina. Three authors have direct and/or familial lived experience of addiction and recovery.
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