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Published in final edited form as: Drug Alcohol Depend. 2020 Nov 13;218:108397. doi: 10.1016/j.drugalcdep.2020.108397

Dyadic associations between relationship quality and risk of opioid use among couples receiving methadone for opioid use disorder*

Courtney A Polenick a,b,c, Diarratou Kaba a, Annie N Zhou a, Benjamin H Han d, Brandi Parker Cotton e
PMCID: PMC8115745  NIHMSID: NIHMS1653557  PMID: 33276296

Abstract

Background:

Social relationships may serve as both protective factors and risk factors for opioid use (nonmedical prescription opioid or illicit opioid use) among patients receiving methadone for opioid use disorder (OUD). Yet little is known about how relationship quality is linked to outcomes among couples receiving methadone. We evaluated the links between relationship quality and risk of opioid use among couples in which both partners received methadone.

Methods:

Participants included 53 heterosexual married or cohabiting couples aged 18 and older who were drawn from two opioid treatment programs in Rhode Island and Massachusetts. Both members of the couple completed a self-administered survey assessing their sociodemographic information, relationship and treatment characteristics, and risk of opioid use.

Results:

Roughly half of women (47.2%) and men (52.8%) had a moderate to high risk of nonmedical prescription opioid use and almost two-thirds (64.2%) had a moderate to high risk of street opioid use. Risk of street opioid use was highly correlated within couples. Actor-partner interdependence models revealed that when women reported higher positive relationship quality, they had a lower risk of nonmedical prescription opioid use and their partners had a lower risk of street opioid use. Negative relationship quality was not significantly linked to risk of opioid use.

Conclusions:

Couples in which both partners receive methadone for OUD may be at risk of return to use, and positive partner relationships may play a role in lowering this risk. Women’s perceptions of relationship quality might be a particularly important target for clinical care and interventions.

Keywords: Opioid Use Disorder, Methadone Maintenance, Couples, Social Relations

1. Introduction

Opioid use disorder (OUD) is a major public health concern in the United States, with an estimated 130 Americans dying from an opioid overdose each day (Centers for Disease Control and Prevention, 2018). Methadone is an evidence-based agonist therapy for treating OUD delivered through opioid treatment programs. Although methadone is effective, it is often stressful and may place a strain on patients and their close relationships (Amato et al., 2015; Fei et al., 2016; Wittenberg et al., 2016; Yee et al., 2016). Relationships with spouses or romantic partners can lower or increase substance use (e.g., Fairbairn and Cranford, 2016; Heinz et al., 2009; Tracy et al., 2005). However, little is known about the link between partner relationship quality and risk of opioid use among couples receiving methadone for OUD. Understanding how partner relationships are associated with couples’ risk of return to use would inform clinical care and interventions. In this study, we evaluated the links between partner relationship quality and risk of nonmedical prescription opioid and street opioid use among heterosexual couples in which both partners received methadone.

According to interdependence theory (Rusbult and Van Lange, 2008), members of a couple affect one another’s thoughts, feelings, and behaviors. Consistent with this perspective, spouses or romantic partners are a prominent source of health-related influence across multiple contexts, including substance use (Derrick et al., 2019; Meyler et al. 2007). Specific to methadone treatment, partners tend to be similar in their use of illicit opioids (Gogineni et al. 2001; Powers and Anglin, 1996) and methadone dose (Huang et al., 2018). Receiving methadone through opioid treatment programs can also have a negative impact on both partners’ well-being and quality of life (Wittenberg et al., 2016). This treatment can be highly demanding and long-term, often requiring years of methadone dispensing and laboratory testing for illicit substance use (World Health Organization, 2009). Additionally, methadone presents a host of obstacles that are psychological (e.g., perceived stigma, persistence to continue treatment) and behavioral (e.g., drug-free lifestyle changes, sexual dysfunction as a side effect), which impact the everyday lives of patients and their partners (Teoh et al., 2017; Warren et al., 2016; Wittenberg et al., 2016; Woo et al., 2017). Partners who receive methadone for OUD at the same time may also differ in their motivation and/or ability to remain drug-free (Cavacuiti, 2004; Simmons and McMahon, 2012; Simmons and Singer, 2006), and this may increase stress and make treatment adherence more difficult. Given the interdependence within couples, it is important to consider the role of both partners’ views of partner relationship quality (i.e., positive and negative aspects of partner relationships) in opioid use risk among couples receiving care through opioid treatment programs. Partner relationship quality may be especially important when both partners receive methadone because they serve as a critical source of support or strain that shapes the course of treatment and recovery (Cavacuiti, 2004; Simmons and McMahon, 2012; Simmons and Singer, 2006).

Positive aspects of the partner relationship may promote treatment adherence and drug abstinence (De Maeyer et al., 2011; Derrick et al., 2019; Heinz et al., 2009). For example, previous research has found that greater relationship closeness is linked to a lower percentage of cocaine-positive and heroin-positive urine samples over a 35-week period among married individuals in treatment (Heinz et al., 2009). By contrast, negative components of the partner relationship might exacerbate substance use and raise the risk of return to use (Derrick et al., 2019; Fairbairn and Cranford, 2016; Tracy et al., 2005). For instance, intimate partner violence has been associated with increased drug use among individuals receiving methadone for OUD (de Dios et al., 2014), and arguments with partners about drug use are a common source of strain that may contribute to the perpetuation and maintenance of illicit opioid use patterns (Cavacuiti, 2004; Simmons and McMahon, 2012; Simmons and Singer, 2006). OUD may also hinder communication patterns in close relationships, which in turn exacerbates feelings of social isolation (Crowley and Miller, 2020). Taken together, this research highlights the importance of considering both partners’ views of positive and negative relationship quality and their links to opioid use risk among couples receiving methadone for OUD.

To provide targeted clinical care and interventions, it is important to consider potential gender differences in the dyadic links between perceptions of relationship quality and opioid use risk among couples receiving methadone for OUD. Compared with men, women typically encounter more interpersonal strain (Birditt and Fingerman, 2003; Mohr et al., 2003) and are more likely to seek social support in the context of substance use (Bonin et al., 2000; Rahimi et al. 2019). Among patients receiving methadone for OUD, women are also faced with greater challenges that are socioeconomic (e.g., unemployment, lower incomes), health-related (e.g., more comorbidities), and interpersonal (e.g., less partner and family support) relative to men (Bawor et al., 2015; Grella et al., 2003; Puigdollers et al., 2004; Riehman et al., 2003; Vigna-Taglianti et al., 2016). These heightened challenges and the more central role of interpersonal relationships among women suggest that partner relationship quality may be more likely to mitigate or intensify opioid use risk during methadone treatment for OUD among women than men in heterosexual couples.

The present study adds to the literature by evaluating the association between partner relationship quality and risk of using opioids among couples in which both partners receive methadone. We hypothesized that own and partner reports of more positive partner relationship quality would be linked to lower risk of nonmedical prescription opioid and street opioid use. We also hypothesized that own and partner reports of more negative partner relationship quality would be linked to higher risk of nonmedical prescription opioid and street opioid use. We further predicted that these links would be stronger for women than for men.

2. Methods

2.1. Sample and Procedures

A total of 144 patients were recruited from two large Opioid Treatment Programs in Rhode Island (n = 84) and Massachusetts (n = 60). Clinical staff assisted in the recruitment of married or cohabiting partners who were both currently receiving methadone (i.e., 72 patient dyads). All patients in these programs also received at least one other group, individual, or couple therapy. Individuals under age 18 or not fluent in English were excluded. Both partners typically came together for methadone dosing, and clinicians shared fliers with couples who were interested in the study. Although response rates were not collected for this convenience sample, we estimate that at least 80% of these couples agreed to participate. Couples in which both partners consented to participate were enrolled. During scheduled clinic visits, participants were asked to complete an in-person self-administered survey and an informed consent document. Survey completion was monitored by the principal investigator (B.P.C). Couples completed the surveys at the same time in separate rooms. Both partners were asked to keep their responses confidential. There was no identifying information included on the survey. After survey completion, each participant received a $20.00 gift card. On average, the survey took 20–30 minutes to complete. This study was approved by the Institutional Review Board of the University of Rhode Island.

Figure 1 depicts the selection of the analytic sample. Six individuals in three same-sex couples were removed to allow for testing of gender differences within couples and because the small number of same-sex couples did not permit a meaningful comparison with heterosexual couples. Of the remaining 138 individuals in 69 couples, one had missing data on partner negative relationship quality; two had missing data on relationship type and relationship duration; 15 had missing data on nonmedical prescription opioid use risk; and 14 had missing data on street opioid use risk. The analytic sample included 106 individuals in 53 couples with complete data on study variables (see Table 1). Relative to individuals who were removed because of missing data, individuals in this study did not significantly differ in their reports on study variables (partner relationship quality and risk of opioid use), age, education, or work status; however, individuals in this study were less likely to be homeless, χ2(1, N = 137) = 5.11, p = .024, and were less likely to be racial/ethnic minorities, χ2(1, N = 112) = 4.55, p = .033.

Figure 1.

Figure 1.

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Selection of the analytic sample.

Table 1.

Background Characteristics and Scores on Study Variables Among Couples.

Women Men
Variable M SD Range M SD Range
Age 37.66* 11.34 19–68 40.12 9.71 24–60
SI score: prescription opioids 4.74 5.77 0–31 7.30 9.76 0–37
SI score: street opioids 8.92 9.77 0–38 9.94 11.74 0–39
SI score: cannabis 5.79 8.41 0–39 7.65 9.11 0–39
SI score: cocaine 5.47 9.61 0–37 6.48 8.76 0–36
SI score: sedatives 3.40 7.34 0–32 3.78 7.48 0–35
SI score: stimulants 2.16 5.14 0–27 2.00 4.99 0–24
SI score: methamphetamine 0.71 1.63 0–6 0.92 3.73 0–25
SI score: hallucinogens 0.70 1.58 0–6 1.24 2.43 0–11
SI score: inhalants 0.58 1.59 0–6 0.61 1.69 0–8
Positive RQ with partner 3.17 0.74 1.33–4.00 3.28 0.74 1.00–4.00
Negative RQ with partner 2.37 0.90 1.00–4.00 2.25 0.74 1.00–4.00
n % n %
Relationship type (married) 15 28.3 15 28.3
Relationship duration (5+ years) 31 58.5 31 58.5
Racial/ethnic minoritya 12 27.3 13 31.7
Employed full-time or part-timeb 9 17.0* 20 38.5
Education levelc
 Less than high school 16 30.8 16 30.2
 Completed high school 19 36.5 25 47.2
 Some college 14 26.9 9 17.0
 Graduated college 3 5.8 3 5.7
Current living situationb
 Living in own home 37 69.8 36 69.2
 Living with a friend 11 20.8 11 21.2
 Staying in a shelter/sober house 1 1.9 1 1.9
 Homeless 4 7.5 4 7.7
Treatment duration (2+ years)d 32 61.5 32 62.7
SI score range: prescription opioids
 Lower risk (scores of 0–3) 28 52.8 25 47.2
 Moderate risk (scores of 4–26) 24 45.3 23 43.4
 High risk (scores ≥ 27) 1 1.9 5 9.4
SI score range: street opioids
 Lower risk (scores of 0–3) 19 35.8 19 35.8
 Moderate risk (scores of 4–26) 29 54.7 26 49.1
 High risk (scores ≥ 27) 5 9.4 8 15.1
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Note. RQ = relationship quality. SI = substance involvement.

a

Missing data for 9 women and 12 men.

b

Missing data for 1 man.

c

Missing data for 1 woman.

d

Missing data for 1 woman and 2 men. N = 53 dyads.

*

Significant gender difference within couples at p < .05.

2.2. Measures

2.2.1. Risk of opioid use.

The National Institute on Drug Abuse (NIDA) Modified – ASSIST was used to assess risk of opioid use (WHO ASSIST Working Group, 2002). This validated and reliable 8-item measure is widely used to detect and manage substance use in general medical care settings (Humeniuk et al., 2008). ASSIST calculates a Substance Involvement (SI) score for tobacco, alcohol, and 7 classes of drugs, and combines illicit opioid use and nonmedical use of prescription opioids into a single category. We distinguished between nonmedical prescription opioid use (fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) and street opioid use (heroin, opium, etc.) by separately calculating participant scores. For each substance, scores of 0–3 indicate lower risk, scores of 4–26 represent moderate risk, and scores of 27 or higher reflect high risk.

2.2.2. Partner relationship quality.

Participants were asked about the relationship with their partners using items from the Health and Retirement Study (Smith et al., 2017). Positive relationship quality was captured using three items. On a scale ranging from 1 (a lot) to 4 (not at all), participants reported how much their partner: really understands the way they feel about things; can be relied upon if they have a serious problem; and how much they can open up to them if they need to talk about their worries. Negative relationship quality was assessed with four items. On a scale ranging from 1 (a lot) to 4 (not at all), participants reported how much their partner: makes too many demands on them; criticizes them; lets them down when counted upon; and gets on their nerves. Prior research indicates that these measures produce valid and reliable responses (Bertera, 2005; Schuster et al., 1990; Walen and Lachman, 2000). The items were reverse coded and averaged such that higher scores represented greater positive relationship quality (women: α = .82; men: α = .75) and greater negative relationship quality (women: α = .87; men: α = .79).

2.2.3. Covariates.

We controlled for relationship type (1 = married, −1 = cohabiting) and relationship duration (1 = 5 years or longer, −1 = less than 5 years). In post hoc tests, we also controlled for treatment duration. To account for differences in risk of opioid use among patients in treatment long enough to be stable on methadone (Ward et al. 1998), we examined whether patients received treatment for two or more years (1 = 2 years or more, −1 = less than 2 years).

2.3. Analytic Strategy

In preliminary analyses, we used paired t-tests and McNemar tests to consider gender differences in background characteristics and scores on study variables among couples. The main analyses were estimated using actor-partner interdependence models (APIM; Kenny et al., 2006) with the MIXED procedure in SPSS version 27. The APIM combines a conceptual model of interdependence in social relationships with statistical procedures that allow for the evaluation of mutual influences. Models allowed for correlated errors between women and men within couples using a heterogeneous compound symmetry (CSH) covariance structure. Actor effects in this study refer to the extent to which one’s own reports of relationship quality are associated with risk of using opioids. Partner effects in this study refer to the extent to which partners’ reports of relationship quality are associated with risk of using opioids.

Models for positive and negative relationship quality were conducted separately. Model 1 tested the associations between own and partner perceptions of relationship quality and risk of nonmedical prescription opioid use and risk of street opioid use. Model 2 added relationship type and duration as covariates. A distinguishing variable (1 = woman, −1 = man) was used to estimate separate intercepts and slopes for women and men within couples (Kenny et al., 2006).

3. Results

Table 1 shows participant characteristics and scores on key study variables for the 53 married or cohabiting couples (106 individuals). On average, women and men were in their late 30s to early 40s and had been together for 8.56 years (SD = 8.96, range = 0.17 to 35.0). Most participants were non-Hispanic White, had a high school education or less, and lived in their own homes; but almost one in twelve were homeless. About one in four of couples were married. Among women and men, about 6 in 10 had been in treatment for two years or longer. There were few gender differences within couples. Compared with their male partners, women were significantly younger and were significantly less likely to be employed full- or part-time but did not differ on any other background characteristics or study variables. We found that approximately half of women (47.2%) and men (52.8%) had SI scores for prescription opioid use that reflected moderate risk (scores of 4–26) or high risk (scores ≥ 27). Similarly, almost two-thirds of women and men (64.2%) had SI scores for street opioid use that indicated moderate or high risk. Women and men had SI scores for prescription opioids, street opioids, cannabis, and cocaine that indicated moderate risk of use on average. Most participants in the moderate risk category for prescription opioids had an SI score of 6 among both women (58.3%) and men (69.6%). Similarly, the most frequent SI score in the moderate risk category for street opioids was 6 among both women (48.3%) and men (57.7%).

APIM parameter estimates for the positive relationship quality model are presented in Table 2 (nonmedical prescription opioids) and Table 3 (street opioids). Partial intraclass correlations (ICCs) showed high within-couple correlations for risk of street opioid use (ICC = 0.64, p < .001 in Model 1 and ICC = 0.66, p < .001 in Model 2); but not nonmedical prescription opioid use (ICC = 0.08, p = .580 in Model 1 and ICC = 0.05, p = .708 in Model 2). Negative partner relationship quality was not significantly linked to risk of nonmedical prescription or street opioid use; therefore, the estimates for these models are shown in Supplementary Tables 1 and 2.

Table 2.

Actor-Partner Interdependence Model Examining Dyadic Associations Between Positive Relationship Quality and Risk of Nonmedical Prescription Opioid Use Among Couples.

Women’s SI Score: Prescription Opioids Men’s SI Score: Prescription Opioids
Predictor b SE 95% CI b SE 95% CI
Model 1
 Actor RQ with partner −2.56* 1.05 −4.67, −0.45 −1.81 1.79 −5.41, 1.79
 Partner RQ with partner 0.26 1.05 −1.86, 2.37 −3.41ϯ 1.79 −7.00, 0.18
Model 2
 Actor RQ with partner −2.34* 1.10 −4.56, −0.13 −2.35 1.81 −5.98, 1.28
 Partner RQ with partner 0.16 1.08 −2.01, 2.33 −2.52 1.84 −6.23, 1.18
 Relationship type (married) −0.41 0.91 −2.25, 1.42 −2.48 1.53 −5.56, 0.59
 Relationship duration (5+ years) −0.72 0.80 −2.32, 0.88 −0.36 1.33 −3.04, 2.32
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Note. RQ = CI = confidence interval. RQ = relationship quality. SI = substance involvement. N = 53 dyads.

ϯ

p < .07.

*

p < .05.

Table 3.

Actor-Partner Interdependence Model Examining Dyadic Associations Between Positive Relationship Quality and Risk of Street Opioid Use Among Couples.

Predictor Women’s SI Score: Street Opioids Men’s SI Score: Street Opioids
b SE 95% CI b SE 95% CI
Model 1
 Actor RQ with partner −3.49ϯ 1.8 −7.11, 0.13 −2.4 2.13 −6.67, 1.87
 Partner RQ with partner −0.89 1.81 −4.52, 2.75 −4.62* 2.12 −8.88, −0.36
Model 2
 Actor RQ with partner −3.27 1.9 −7.08, 0.55 −3.41 2.06 −7.55, 0.73
 Partner RQ with partner −1.1 1.86 −4.84, 2.63 −3.05 2.1 −7.28, 1.17
 Relationship type (married) −1.04 1.57 −4.21, 2.12 −4.63* 1.74 −8.14, −1.12
 Relationship duration (5+ years) 1.24 1.37 −1.51, 4.00 0.17 1.52 −2.89, 3.22
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Note. CI = confidence interval. RQ = relationship quality. SI = substance involvement. N = 53 dyads.

ϯ

p < .07.

*

p < .05.

3.1. Links Between Relationship Quality and Risk of Nonmedical Prescription Opioid Use

3.1.1. Women’s risk of opioid use.

Table 2 (Model 1) shows that there was a significant actor effect for women. When women perceived higher positive relationship quality, they had a significantly lower risk of nonmedical prescription opioid use (b = −2.56, p = .018). This link remained significant after controlling for relationship characteristics in Model 2 (b = −2.34, p = .039). Thus, for each one-unit increase in women’s perceived positive relationship quality, their SI score for prescription opioids decreased by nearly 2.5 points. Partners’ reports of positive relationship quality were not linked to women’s nonmedical prescription opioid use risk.

3.1.2. Men’s risk of opioid use.

There was a marginally significant partner effect such that when their partners reported higher positive partner relationship quality, men had a lower risk of nonmedical prescription opioid use in Model 1 (b = −3.41, p = .062) but not in Model 2 after accounting for relationship characteristics. Men’s own perceptions of positive partner relationship quality were not associated with their risk of using nonmedical prescription opioids.

3.2. Links Between Relationship Quality and Risk of Street Opioid Use

3.2.1. Women’s risk of opioid use.

As shown in Table 3, there was a marginally significant actor effect for women. When women reported higher positive relationship quality, they had a lower risk of street opioid use in Model 1 (b = −3.49, p = .059) but not in Model 2 after controlling for relationship characteristics. Partners’ views of positive relationship quality were not associated with women’s risk of using street opioids

3.2.2. Men’s risk of opioid use.

In Model 1, there was a significant partner effect for men such that when their partners reported higher positive partner relationship quality, men had a lower risk of street opioid use (b = −4.62, p = .034). In other words, for each one-unit increase in their partners’ perceived positive relationship quality, men’s SI score for street opioids decreased by slightly more than four and a half points. This link became nonsignificant in Model 2, however, after accounting for relationship characteristics. Men’s own perceptions of positive relationship quality were not associated with their risk of using street opioids.

3.3. Post Hoc Tests

We estimated models controlling for own and partner reports of treatment duration in a reduced sample of 50 couples with complete data on these variables. The findings did not change in these models.

4. Discussion

This study builds on the literature by demonstrating that positive qualities of partner relationships are associated with lower risk of opioid use among couples receiving methadone. In particular, women’s views of positive relationship quality appear consequential to both their own and their partners’ risk of using opioids. Among this sample of women and men in heterosexual couples, we found that about half had a moderate to high risk of prescription opioid use and nearly two-thirds had a moderate to high risk of street opioid use. Moreover, risk of street opioid use was highly correlated within couples, suggesting strong interdependence. These findings indicate that married or cohabiting couples in which both partners receive methadone for OUD may be at a substantial risk of return to use. Strategies to promote positive relationships may enhance the ongoing clinical care and treatment of these couples.

When women reported a more positive relationship, they had a lower risk of nonmedical use of prescription opioids. Consistent with our hypothesis, women who perceive more positive qualities in their partner relationships may be more resilient during methadone treatment for OUD. Relative to men, women with OUD have higher rates of receiving a physician prescription for opioids (Nosyk et al., 2014), are at greater risk of nonmedical use of prescription opioids (Marsh et al., 2018), and are more likely to use nonmedical prescription opioids to cope with negative emotions (McHugh et al., 2013). Among patients receiving methadone for OUD, women have also been found to be more likely than men to use illicit opioids in the past month when they have severe levels of loneliness (Polenick et al., 2019). In highly positive relationships, women might feel greater support and understanding from their partners that facilitates adaptive, drug-free ways to manage psychosocial stress. Notably, this finding held even when controlling for relationship characteristics and treatment duration in post hoc tests, which indicates that the link between women’s views of positive partner relationship quality and their risk of nonmedical prescription opioid use is robust. Partners’ views of positive relationship quality were not linked to women’s opioid use risk, suggesting that their own perceptions likely play a more prominent role.

Among men, their partners’ perceptions of positive relationship quality seemed to be most consequential. In line with our hypothesis, when their partners reported more positive relationship quality, men had a lower risk of street opioid use. This association became nonsignificant after controlling for relationship characteristics, however, which suggests that other aspects of the partner relationship may be more important for men. Of note, being married (versus cohabiting) was significantly linked to men’s lower risk of using street opioids. One possibility is that the presence of a committed partner relationship is protective for men receiving methadone for OUD, beyond the quality of that relationship. Marriage has been found to benefit men’s well-being more than women’s in a variety of ways, such as reducing engagement in health-risk behaviors (e.g., August and Sorkin, 2010; Umberson, 1992). Men often inject street opioids and other drugs with drug-using friends or relatives (e.g., Liu et al., 2018; Young et al., 2014), but these behaviors may be less likely to occur when men are in committed partner relationships and when their partners view these relationships more positively. Men’s own views of positive relationship quality were not associated with their risk of nonmedical prescription or street opioid use, indicating that their partners’ evaluation may matter more.

Contrary to our hypothesis, negative partner relationship quality was not associated with opioid use risk among women or men. These findings contrast with prior research showing that negative qualities in the partner relationship are linked to adverse outcomes including higher rates of return to use in substance use disorder treatment (e.g., Fairbairn and Cranford, 2016; Mattson et al., 2010; Tracy et al., 2005). Although more research is needed, the present study indicates that positive relationship quality may play a stronger part in shaping outcomes among heterosexual couples receiving methadone for OUD. It is worth noting, however, that this sample reported low overall levels of negative relationship quality. As such, negative relationship quality may be significantly linked to opioid use risk among more distressed couples.

We acknowledge several limitations. First, causal associations cannot be determined in a cross-sectional study. For instance, women may have reported more positive relationships partly because they and their partners are less likely to use opioids. Second, the self-selected sample could introduce bias. It is plausible, for example, that couples who participated have better relationships and a lower risk of opioid use than couples who did not participate. Third, given that the rates of missing data in the larger sample were 10.9% and 10.2% for the nonmedical prescription and street opioid measures, respectively, individuals with higher scores may have been less likely to respond. Fourth, we lacked data on past substance use, methadone dose, and treatment performance (e.g., attendance, ratio of positive opioid responses in the urine samples). Fifth, the findings may not apply to couples in which only one partner receives methadone treatment or in which one or both partners receive different OUD treatments. Sixth, the sample was heterosexual and primarily non-Hispanic White, and so the results may not generalize to same-sex couples or racially/ethnically diverse couples. Finally, the sample size was small but similar to those of previous studies with one or both partners in substance use disorder treatment (e.g., Kelley et al., 2016; Flanagan et al., 2018; Schumm et al., 2019). Nevertheless, the present study has a number of important strengths including data from both members of the couples, the use of reliable and valid measures of relationship quality and opioid use, and statistical procedures to permit the assessment of mutual influences between partners.

Additional studies are needed to examine how partner relationship quality is associated with risk of opioid use over time among couples receiving methadone. Future research should also consider potential mechanisms that account for the current findings. For example, positive partner relationships may be a central source of social support and reinforcement for engaging in healthy, non-drug activities. Partners in more positive relationships may also have more supportive communication about OUD and may influence one another’s attitudes toward opioid use (e.g., whether street opioid use is acceptable) in ways that lower their risk of return to use. Identifying potentially modifiable pathways through which positive partner relationships are linked to a lower risk of opioid use might help to reward abstinence and sustain recovery.

3.1. Conclusions

In summary, this study indicates that positive partner relationships may have important implications for risk of opioid use among couples in which both partners receive methadone for OUD. The findings underscore the value of considering mutual influences within these couples. Couples receiving methadone for OUD likely face considerable obstacles to long-term recovery, including a shared history of opioid use that may complicate their response and adherence to treatment (Simmons and McMahon, 2012; Simmons and Singer, 2006). Prior research indicates that couple-based treatment is associated with improvements in relationship functioning as well as reductions in substance use (McCrady et al., 2016; Powers et al., 2008). Consequently, approaches to strengthen and expand on positive qualities in their relationships may maximize treatment outcomes among this particularly vulnerable subgroup of patients.

Supplementary Material

Supplementary Tables

Highlights.

  • Risk of street opioid use is highly correlated within couples in MMT

  • More positive partner relationships are linked to lower opioid use risk

  • Women’s reports of positive partner relationships may be a key intervention target

Role of Funding Source:

This work was supported by the American Nurses Foundation and the Eastern Nursing Research Society [grant number 6292]. C.A.P. was supported by the National Institute on Aging at the National Institutes of Health [grant number K01 AG059829]. B.H.H. was supported by the National Institute on Drug Abuse at the National Institutes of Health [grant number K23 DA043651]. The funding organizations had no role in any of the following: study design and conduct; the collection, analysis, and interpretation of data; the writing of the report; and in the decision to submit the article for publication.

Footnotes

*

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi: 10.1016/j.drugalcdep.2020.108397

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Author Disclosures

Conflict of interest: No conflict declared.

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