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. Author manuscript; available in PMC: 2023 May 1.
Published in final edited form as: J Subst Abuse Treat. 2021 Nov 14;136:108663. doi: 10.1016/j.jsat.2021.108663

Optimizing outpatient treatment outcomes among methamphetamine-using gay and bisexual men through a computerized depression intervention

Jesse B Fletcher 1, Cathy J Reback 1,2
PMCID: PMC8940664  NIHMSID: NIHMS1757961  PMID: 34801284

Abstract

Introduction:

Depression is a common sequelae of frequent methamphetamine use, and may influence rates of engagement in sexual risk-taking among methamphetamine-using cisgender gay, bisexual, and other men who have sex with men (GBMSM). The study team hypothesized that layering a brief, computerized depression intervention (i.e., MoodGym; based on Cognitive Behavioral Therapy [CBT] and Interpersonal Therapy) on top of a long-running outpatient methamphetamine treatment program (based on CBT and Contingency Management) for GBMSM could optimize reductions in methamphetamine use and sexual risk-taking among program participants.

Methods:

This pilot study, which also included analysis of historical data, employed nearest-neighbor matching algorithms to match current pilot study participants (N = 39) to prior participants of an outpatient methamphetamine treatment program (N = 703) and employed treatment effects analyses to determine the observed effects of adding depression intervention content to GBMSM-specific methamphetamine treatment.

Results:

Pilot study participants who received the MoodGym intervention were significantly less likely to submit methamphetamine-metabolite positive urine samples (Adjusted Treatment Effect [ATE] = −0.72; p < 0.01), and evidenced significantly greater reductions in receptive condomless anal intercourse with non–primary partners in the past 30 days (ATE = −1.39; p < 0.05), relative to prior participants of the outpatient methamphetamine treatment program who did not receive depression intervention content.

Conclusion:

Preliminary results suggest layering a brief computerized depression intervention onto outpatient methamphetamine treatment for GBMSM may optimize reductions in methamphetamine use and/or sexual risk-taking.

Keywords: Methamphetamine, Depression, Gay, Bisexual, HIV

1. Introduction

1.1. Methamphetamine use and HIV transmission risk among gay, bisexual, and other men who have sex with men

Gay, bisexual, and other men who have sex with men (GBMSM) constitute a key priority population in reaching the national End the HIV Epidemic goals (CDC 2021). Studies with GBMSM have long demonstrated associations among methamphetamine use, sexual risk-taking, and HIV acquisition and transmission, including high HIV prevalence (Halkitis, Levy, and Solomon 2014; Hoenigl et al., 2016; Nerlander et al., 2018; Grov et al., 2020), and research has estimated that more than a third of all incident HIV cases among sexual and gender minorities in the United States occur among methamphetamine-using GBMSM (Grov et al., 2020). Among GBMSM already living with HIV, methamphetamine use has been also associated with increased engagement in sex work, increased number of sex partners, decreased tendency to sero-/viral sort, increased engagement in condomless sex with serodiscordant partners, increased risk of infection with non-HIV STIs, increased sexual escape motivations, and decreased likelihood of progression to full viral suppression (Jin et al., 2018; Coyler et al., 2020; Hsin-Hao et al., 2020). Narratives concerning methamphetamine’s effect on sexual risk-taking among GBMSM have also begun to include discussions of depression, as some evidence suggests depressive symptomology may play an important role in decisions to use methamphetamine and engage in sexual risk-taking processes (e.g., Fletcher and Reback 2015; Fletcher, Clark, and Reback 2020).

1.2. Depression and HIV transmission risk among methamphetamine-using GBMSM

Depression is one of the most common mental health disorders reported by methamphetamine users (McKetin et al., 2008; He et al., 2020), including methamphetamine-using MSM (Javanbakht et al., 2019; Fletcher, Swendeman, and Reback 2018). Furthermore, active methamphetamine users have shown significantly greater levels of depression symptom severity than non–methamphetamine users or people using other substances, including opiates and other stimulant-type drugs (Javanbakht et al., 2019; Coyler et al., 2020; He, Zhai, and Liu 2020). Increased methamphetamine use disorder severity itself has also previously been associated with increasing likelihood of comorbid major depressive episodes among GBMSM (Fletcher, Swendeman, and Reback 2018).

Some evidence suggests that current major depression and/or increased depression symptom severity increase sexual risk-taking among methamphetamine-using GBMSM, perhaps particularly with non–primary partners (Fletcher and Reback 2015; Fletcher, Clark, and Reback 2020). Given the impossibility of observing such phenomenon with randomized controls, such results are merely observational and whatever mechanism might be underlying the association is still not well-understood. However, research has hypothesized that sexual risk-taking may be an attempt to offset or overcome uncomfortable negative feelings and effects associated with depression. If so, depression symptoms could play an important mediating or moderating role in the long-observed association between methamphetamine use and increased sexual risk-taking among GBMSM (Fletcher and Reback 2015).

It is also noteworthy that depression is a common symptom experienced by individuals attempting to abstain from long-term or binge methamphetamine use (Scott et al., 2007; Rusyniak 2013; Ren et al., 2017; Ru et al., 2019). Negative reinforcement models of addiction suggest that such depression symptoms can themselves become triggers for methamphetamine use, in an attempt to overcome discomfort of negative emotional arousal (May, Aupperle, and Steward 2020). If it is the case that depressive symptomology shares some association with sexual risk-taking among methamphetamine-using GBMSM, one could speculate that the depression symptoms that arise during attempts to abstain from methamphetamine use could similarly catalyze engagement in sexual risk-taking (i.e., in a similar attempt to overcome negative emotional arousal and “feel better”). Such reasoning is bolstered by the finding that impulsivity, a precursor of risk engagement, is strongly associated with depressive symptoms among people undergoing methamphetamine withdrawal (Zhang et al., 2015). Importantly, research has already shown interventions that may address depressive symptoms among people undergoing methamphetamine treatment to improve treatment outcomes in other groups (Kay-Lambkin et al., 2011; Glasner-Edwards & Mooney, 2014; Hellem, Lundberg, and Renshaw 2015; He et al., 2020), implying perhaps that reductions in methamphetamine use could also be optimized by adding depression intervention content to methamphetamine treatment among GBMSM.

Intervening to address depressive symptomology among treatment-seeking methamphetamine-using GBMSM may optimize reductions in methamphetamine use and sexual risk-taking, both during periods of active methamphetamine use and during periods of attempted abstinence from recent methamphetamine use. This pilot study measured the effects of layering a brief computerized depression intervention onto an established manualized methamphetamine outpatient treatment program for GBMSM. The single-arm, non-randomized pilot study compared current participants with matched historical data from an methamphetamine outpatient treatment program to estimate the observed effects of providing the computerized depression intervention to those in treatment. The research team hypothesized that layering depression-based intervention content onto an existing evidence-based outpatient treatment program would, for current participants relative to historical matched comparators, optimize methamphetamine use outcomes and reductions in sexual risk-taking during the treatment period.

2. Methods

2.1. Participants and procedures

From October 2019 to March 2020, the pilot study enrolled 40 participants. Potential participants became eligible to enroll in the pilot study upon their enrollment in Getting Off, an intensive methamphetamine outpatient treatment program. Eligibility in the pilot study extended to any point in their first two weeks of participation in Getting Off. Study staff informed potential participants that their participation in the pilot study was voluntary and that their enrollment in the Getting Off program was not dependent upon pilot study participation. Given that Getting Off was a community-based service program and not a research study, the eligibility criteria was broad: 1) identified as a gay or bisexual male; 2) used methamphetamine in the previous 12 months; and, 3) seeking treatment for methamphetamine use. Study staff provided those interested in the pilot study with informed consent, and they underwent a short baseline assessment and were subsequently provided weekly monitored access to the MoodGym depression intervention. The Friends Research Institute IRB approved and oversaw all procedures.

2.1.1. Getting Off.

The Getting Off outpatient treatment program consists of an 8-week, 24-session Gay-specific Cognitive Behavioral Therapy (GCBT) intervention combined with a low-cost, voucher-based Contingency Management (CM) intervention, followed by a 4-month continuing care component. The GCBT intervention uses the manual-driven intervention, “Getting Off: A Behavioral Treatment Intervention for Gay and Bisexual Methamphetamine Users,” authored by Cathy Reback, in collaboration with colleagues (available for download at https://www.friendscommunitycenter.org/s/Getting-Off-manual_final_3_15_19.pdf). Getting Off is an evidence-based intervention for methamphetamine-using gay and bisexual men that was adapted for implementation in a community-based setting. Phase I, weeks 1 through 8, consists of 90-minute GCBT groups on Monday, Wednesday, and Friday evenings and the CM intervention. Urine samples for the CM intervention occurred either directly before or after each GCBT group session. Phase II, weeks 9 through 24, consists of open-ended, 90-minute, continuing care groups on Thursday evenings.

2.1.2. MoodGym.

MoodGym (https://moodgym.com.au) is a seven-module interactive computer-optimized, evidenced-based intervention for adults with depression that has shown preliminary efficacy in reducing depression symptoms (Twomey and O’Reilly 2016) and is based on the principals of Cognitive Behavioral Therapy and Interpersonal Therapy (de Mello et al., 2005; Hetrick et al., 2016; Bernecker et al., 2017). MoodGym is a low-intensity, text-and-image-based intervention whose clinical significance is not yet fully known, as measured effects remain small and inconsistent; but it has the benefit of being both inexpensive and accessible. Participants of this pilot study were eligible to take a single MoodGym module each week of the 8-week Phase I Getting Off program on-site on a privately situated study computer while in the presence of a study staff member. Sessions lasted approximately one hour, with participants being provided the option to re-take any module of their choosing in the eight-week period if all seven modules (i.e., Getting Started; Feelings; Thoughts; Unwarping; Destressing; Relationships; Workbook) had been completed in the first seven weeks. The pilot study data analysis did not use any information that participants entered into the MoodGym program during the weekly sessions.

2.2. Incentives

2.2.1. MoodGym.

Participants earned $10 for each unique MoodGym module with which they engaged, for a total possible earnings of $70 over eight weeks.

2.2.2. Contingency Management.

Participants provided a urine sample on each Monday, Wednesday, and Friday. The Getting Off program used a voucher-based reinforcement therapy schedule. From July 2011 through August 2017, the maximum in possible vouchers earned, if all urine samples were negative for methamphetamine metabolites, was $238. Beginning in August 2017, the maximum in possible vouchers earned increased to $388, to reflect commensurate increases is the cost of rewards. Participants could redeem vouchers at any study visit; most redeemed their vouchers for a Target or Ralphs market gift card.

2.2.3. Getting Off.

From July 2011 through August 2017, participants earned $40 for completing the 90-day follow-up assessment. Beginning in August 2017, participants earned $50 for completing the 90-day follow-up assessment.

2.3. Measures

The Admission Form, Substance Use Form, Diagnostic and Statistical Manual for Mental Disorders, Behavioral Questionnaire-Amphetamine, and urine drug screens were each administered during normal completion of the Getting Off program; we describe each in turn.

2.3.1. Admission Form.

The study administered the Admission Form once during enrollment; it queries participants’ sociodemographic data (e.g., age, race/ethnicity, educational attainment, income, HIV status), and initiation/tenure of methamphetamine use (Rawson et al., 1995; Shoptaw et al., 2005).

2.3.2. Substance Use Form.

Study staff administered the Substance Use Form twice, once during enrollment and again at 3-month follow-up. The Substance Use Form asks participants to self-report their substance use from the past 30 days for a wide range of substances (e.g., alcohol, marijuana, methamphetamine, cocaine, opioids).

2.3.3. Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition (DSM-5; APA 2013).

Research staff administered the substance use disorder subsection of the DSM-5 only once, during enrollment. The substance use disorder subsection is a brief formal assessment that takes approximately 15–20 minutes to administer and elicits symptom criteria for DSM-V substance use disorders (e.g., alcohol, marijuana, methamphetamine, cocaine, opioids).

2.3.4. Behavioral Questionnaire-Amphetamine (hereafter: BQA).

The study team administered the BQA twice, once during enrollment and once at 3-month follow-up. Developed at the UC San Francisco Center for AIDS Prevention Studies (Chesney, Chambers, & Kahn, 1997) and subsequently modified for behavioral studies with methamphetamine-using MSM (Twitchell, Huber, Reback, & Shoptaw, 2002), the BQA gathers information on HIV-related drug and sexual risk behaviors. Topics include counts of sexual risk behaviors (e.g., condomless sexual acts with primary and non–primary partners) without substance use and while using methamphetamine.

2.3.5. Urine Drug Screening.

The study collected urine samples for urinalysis three times per week for eight weeks. This pilot study used only methamphetamine results; the study coded data as positive (1) or negative (0) using a cutoff of 1000 ng/ml methamphetamine metabolites detected (W254 Multi-Drug Test 5 in 1, W.H.P.M., Inc., Irwindale, CA, USA).

2.3.6. Center for Epidemiologic Studies Depression Scale (Revised; CESD-R).

The CESD-R, applied only to participants who participated in this pilot study and administered by a study staff member prior to the start of each MoodGym session, is a widely used depression assessment that consistently shows strong psychometric properties and concurrent validity with clinical diagnostic instruments (Eaton et al., 2004; Van Dam and Earleywine 2011). The CESD-R was not administered to the historical controls, as it was not part of the standard Getting Off protocol.

2.3.7. Antiretroviral Therapy (ART) and Pre-Exposure Prophylaxis (PrEP) Uptake and Adherence Form.

Administered only to participants of this pilot study at baseline and 3-month follow-up, the ART and PrEP Uptake and Adherence form briefly queries HIV-positive and HIV-negative participants as to whether they have begun and/or adhered to a prescribed ART or PrEP regimen in the past three months, respectively.

2.4. Statistical analysis

All variables were described using the methods most suited to their distributional properties, including means and standard deviations for continuous variables (with the median included for broadly nonparametric outcomes), or counts and their corresponding percentages for nominal variables. The study team conducted bivariate contrasts using Chi-Square analyses for categorical variables, and t-tests or ANOVAs for contrasts of continuous variables across treatment conditions or data sources. Multivariate analyses were treatment effects analyses using nearest neighbor matching algorithms employing the Mahalanobis distance metric; we created two historical matched comparator (HMC) datasets to account for the large number of participants who submitted at least one urine sample during the intervention period but who failed to attend the 3-month follow-up visit. Thus two nearest neighbor matching procedures existed: one for the urinalysis results (HMC #1) and one for the sexual risk behavior results (HMC #2).

2.5. Historical matched comparator groups

From July 2011 through December 2019, the Getting Off program enrolled 703 GBMSM into intensive outpatient methamphetamine treatment; this pool of prior program participants constituted the sampling frame for the nearest neighbor matching procedure. The matching variables were age, racial/ethnic identity (e.g., white, Black/African American, Latinx), sexual identity (i.e., gay, bisexual), HIV status (HIV positive vs. other), years of heavy methamphetamine use at intake, and days of methamphetamine use in the past 30 days at intake. A particularly high proportion of Latinx participants happened to enroll in the pilot study (~50%) relative to historical data (~40%) and, thus, the study modified the matching algorithm to match current and historical participants on racial/ethnic identity exactly wherever possible. The study had an insufficient number of Latinx historical comparators in the sexual risk behavior data (i.e., HMC #2) to accomplish this, therefore, exact matching on racial/ethnic identity was only possible in the urinalysis results. The study set the matching procedure to include at least three matches for each participant enrolled in the pilot study, and, due to the inclusion of three continuous matching variables, the treatment effects analyses on HMC #1 and HMC #2 both included the bias adjustment necessary for multiple continuous matching variables (i.e., age, years of heavy methamphetamine use, days of recent methamphetamine use; Abadie and Imbens 2011).

One individual self-withdrew shortly after enrolling without having attended any study activities or completed any assessments and is not included in the data, leaving an analytic sample of 39 GBMSM. Multivariable analyses compared current pilot study participants with their nearest historical matches in HMC #1 (N = 95 [unduplicated]; urinalysis results) and HMC #2 (N = 79 [unduplicated]; sexual risk behaviors). Outcomes included the number of methamphetamine metabolite-free urine samples submitted, the number of methamphetamine metabolite-positive urine samples submitted, and the number of missed urine submissions (comparisons with HMC #1), as well as changes in self-reported engagement in condomless insertive or receptive anal intercourse with primary and non–primary partners, both while using and not using methamphetamine from baseline to 3-month follow-up (comparisons with HMC #2). The study carried out all statistical tests with Stata 16.1SE, they were two-tailed wherever possible, and we flagged significance beginning at p < 0.05.

3. Results

On average, pilot study participants were slightly older (44.5 [SD = 10.4]) than participants from either HMC #1 (41.3 [8.9]) or HMC #2 (41.9 [9.3]; differences not significant [ns]). Additionally, the pilot data had a higher proportion of Latinx participants (51%) relative to either unweighted HMC #1 (42%) or HMC #2 (37%; ns). Participants from all three data sources predominantly identified as gay (79–81%), self-reported a HIV-positive status (67–74%), reported an average of 4.7–5.1 years prior methamphetamine use, and an average of 7.9–8.9 days of methamphetamine use in the prior 30 days at baseline.

Pilot study participants completed a total of 201 MoodGym modules (average 5.2 study site visits per participant), with 18 (46%) participants completing all seven MoodGym modules. Table 2 provides a count of how many people attended each session (given consecutively), as well as average participant CESD-R scores at each visit. CESD-R scores did not trend strongly downward over the eight-week intervention period, ranging from 22.0 (week 8; n = 14) to 31.5 (week 1; n = 39) and averaging 29.1 (SD = 17.5).

Table 2:

Participant CESDR Scores by Study Visit

Visit # Mean SD
1 (N = 39) 31.5 17.5
2 (n = 34) 30.5 19.5
3 (n = 26) 26.8 15.5
4 (n = 24) 28.5 16.5
5 (n = 24) 29.4 17.4
6 (n = 22) 29.1 18.1
7 (n = 18) 30.7 18.7
8 (n = 14) 22.0 16.8
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Table 3 provides the average number methamphetamine metabolite-free and methamphetamine metabolite-positive urine samples provided by participants, as well as how many urine submissions participants missed, for both the pilot study and in HMC #1. Over the course of the treatment period, pilot study participants provided an average of 13 methamphetamine metabolite-free (i.e., “clean”) urine samples (Median = 14), while participants in HMC #1 provided an average of 12 clean urine samples (Median = 12; ns). Attendance to MoodGym sessions was significantly associated with the number of clean urine samples provided (Pearson’s r = 0.3212; p < 0.01).

Table 3:

Urinalysis Results among Gay and Bisexual Men Seeking Outpatient Treatment for Methamphetamine Use

Pilot Data HMC #1 (UA Data; unweighted)
(N = 39) (N = 95)
n (%) or Mean [SD; Md] n (%) or Mean [SD; Md] Sig.
Urinalysis (3×/Week for 8 Weeks)
MM-Free 12.92 [9.45; 14] 12.22 [9.14; 12] ns
MM+ 0.87 [1.64; 0] 1.37 [1.93; 1] ns
Missed Urine Screens 10.21 [8.78; 10] 10.41 [8.51; 11] ns
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MM-Free: Methamphetamine-metabolite free

MM+: Methamphetamine-metabolite positive

Table 4 displays participants’ self-reported sexual risk behaviors in the past 30 days at both baseline and 3-month follow-up. Both pilot study participants and participants in HMC #2 evidenced relatively little engagement in CAI with primary male partners, with no behavior reaching an average rate of even 1 event in the past 30 days. In contrast, both data sources averaged more than one instance of both insertive (Pilot = 1.5; HMC #2 = 1.6) and receptive (Pilot = 2.4; HMC #2 = 1.0) CAI in the past 30 days with non–primary male partners. Participants in HMC #2 evidenced a significant reduction in the number of male sexual partners over the course of the intervention (5.4 to 2.3; p < 0.05).

Table 4:

Sexual Risk Behaviors by Time Point among Gay and Bisexual Men Seeking Outpatient Treatment for Methamphetamine Use

Pilot Data HMC #2 (Sex Risk Data; unweighted)
Baseline (N = 39) 12-Week Follow-Up (n =33) Baseline (N = 79) 12-Week Follow-Up (n = 79)
Mean [SD; Md] Mean [SD; Md] Mean [SD; Md] Mean [SD; Md]
Number of Male Sexual Partners 7.13 [17.21; 2] 4.97 [13.27; 0] 5.37* [7.80; 2] 2.28* [3.67;1]
CAI w/ Primary Male Partner
Insertive 0.0 [0; 0] 0.0 [0; 0] 0.35 [2.34; 0] 0.39 [1.50; 0]
Insertive w/ Meth 0.0 [0; 0] 0.0 [0; 0] 0.08 [0.68; 0] 0.22 [1.25; 0]
Receptive 0.10 [0.64; 0] 0.0 [0; 0] 0.08 [0.47; 0] 0.35 [1.64; 0]
Receptive w/Meth 0.0 [0; 0] 0.0 [0; 0] 0.08 [0.47; 0] 0.06 [0.56; 0]
CAI w/ Other Male Partners
Insertive 1.51 [7.19; 0] 0.67 [2.69; 0] 1.61 [5.73; 0] 0.39 [1.65; 0]
Insertive w/ Meth 1.51 [7.19; 0] 0.67 [2.69; 0] 1.57 [5.71; 0] 0.30 [1.52; 0]
Receptive 2.36 [4.75; 0] 0.82 [2.23; 0] 1.01 [3.30; 0] 0.46 [1.37; 0]
Receptive w/Meth 2.31 [4.77; 0] 0.79 [2.18; 0] 0.94 [3.27; 0] 0.32 [1.22; 0]
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Table 5 provides the results of the nearest neighbor treatment effects analyses comparing pilot data to HMC #1 (urine screen results; top of table) and HMC #2 (sexual risk behaviors; bottom of table). Results indicate that pilot study participants were significantly less likely to provide a methamphetamine metabolite-positive urine sample during treatment (coef. = −0.72; p < 0.01), and were significantly more likely to reduce engagement in receptive CAI with non–primary male partners (coef. = −1.39; p < 0.05), as well as receptive CAI with non–primary male partners while using methamphetamine (coef. = −1.38; p < 0.05) from baseline to 3-month follow-up.

Table 5:

Bias-Adjusted Nearest Neighbor Matched Treatment Effects Analysis of Participant Urinalyses Results and Changes in Sexual Risk-Taking from Baseline to 12-Week Follow-Up

Treatment Variable: Enrollment in MoodGym ATE 95% CI
Urinalysis Results (3×/Week for 8 Weeks)
HMC #1 MM-Free −0.46 −4.66; 3.75
MM+ −0.72 ** −1.26; −0.19
Missed Urinalyses 1.18 −2.81; 5.17
Sexual Risk-Taking from Baseline to 12-Week Follow-Up
HMC #2 Number of Male Sexual Partners 0.23 −1.59; 2.05
CAI w/ Primary Male Partner
Insertive 0.07 −0.14; 0.27
Insertive w/ Meth 0.10 −0.05; 0.25
Receptive −0.17 −0.53; 0.18
Receptive w/Meth 0.08 −0.04; 0.21
CAI w/ Other Male Partners
Insertive −0.37 −1.61; 0.95
Insertive w/ Meth −0.33 −1.60; 0.94
Receptive −1.39 * −2.71; −0.06
Receptive w/Meth −1.38 * −2.66; −0.09
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ATE: Average Treatment Effect; 95% CI: 95% Confidence Interval

MM-Free: Methamphetamine-metabolite free

MM+: Methamphetamine-metabolite positive

CAI: Condomless Anal Intercourse

*

p < 0.05

**

p < 0.01

4. Discussion

Participants in the pilot study were predominantly gay-identified, most were living with HIV, and most identified as racial/ethnic minority men. Findings demonstrated that adding a brief computerized depression intervention improved both methamphetamine use and sexual risk outcomes relative to a matched historical control group from prior participants enrolled in the same treatment program who did not receive intervention content to improve depression. Participants in the pilot study, on average, provided more clean (i.e., methamphetamine metabolite-free) urine than historical participants who were selected via matching on sociodemographic characteristics and methamphetamine use history. Additionally, pilot study participants were more likely to report reductions in receptive CAI with non–primary partners than their historical counterparts. Though preliminary and hampered by the small sample size of the pilot study participants and the lack of depression score measures for historical comparators, these findings suggest the adding content to address depression symptoms may optimize methamphetamine use and sexual risk reduction outcomes among GBMSM seeking treatment for methamphetamine use.

Though the finding that participants in the pilot study provided significantly fewer methamphetamine-positive urine samples is encouraging, the absolute magnitude of the observed difference is not dramatic (i.e., an average of one more methamphetamine metabolite-free urine sample over eight weeks as measured via median). Such a modest improvement, though statistically significant after application of statistical control, clearly constitutes at most an optimization of results, most of which are a function of the parent methamphetamine treatment program. The clinical significance of one more methamphetamine metabolite-free urine sample over eight weeks is perhaps debatable, and might indicate that more intense depression intervention content may be warranted. We do not know whether increased intensity would further optimize treatment outcomes, as MoodGym is a fairly low-intensity intervention and, thus, room remains to explore higher intensity content. Critically, however, systematic reviews indicate few known or available treatments for co-occurring methamphetamine use and depression (Hellem, Lundberg, and Renshaw 2015), with only exercise-based interventions showing consistent promise (Haglund et al., 2015; Rawson et al., 2016; Morris et al., 2018; Huang et al., 2020), which is an option not necessarily available to all persons.

Relatedly, it is interesting to note that participants’ depression symptoms did not trend linearly downward over the course of the intervention. It is important to recall that increased depression is a common symptom during early abstinence from methamphetamine use (Scott et al., 2007; Rusyniak 2013; Zhang et al., 2015; Ren et al., 2017; Luan et al., 2018; Ru et al., 2019; Shabani et al., 2019). Thus, though the MoodGym intervention did not succeed in significantly reducing depressive symptomology among the pilot study participants over time, it may have suppressed or blunted the onset of depressive symptoms during the early stages of recovery. Since research has shown impulsivity to be highly positively correlated with depression among persons undergoing withdrawal from methamphetamine (Zhang et al., 2015), avoiding depressive symptoms may have simultaneously allowed participants to avoid impulsive, potentially risky behaviors. As the matched historical control group participants were not administered the CESD-R during their Phase I treatment period, no data exist to support this argument. If, however, the MoodGym intervention succeeded in preventing increases in withdrawal-based depressive symptoms among pilot study participants, it may have helped the historical participants who may have otherwise used methamphetamine or engaged in sexual risk-taking behaviors to remain clean and/or avoid engagement in sexual risk. A future randomized controlled trial should elucidate and disambiguate these mechanisms.

Similar to the improvements in methamphetamine use outcomes, the relative reductions in sexual risk-taking evidenced by the pilot study participants compared to matched historical control group participants were modest in magnitude, once again likely reflecting at most an optimization of reductions taking place predominantly due to the treatment program. It is important and interesting to note that nearly all of the sexual risk self-reported by both the pilot study and matched historical control group participants occurred with non–primary male partners and while using methamphetamine. These findings support and reinforce previous work that demonstrates the associations between methamphetamine use, sexual risk-taking, HIV acquisition and transmission, and high HIV prevalence (Shoptaw and Reback 2006; Halkitis, Levy, and Solomon 2014; Hoenigl et al., 2016; Nerlander et al., 2018; Reback and Fletcher 2018; Grov et al., 2020) among GBMSM. The study team finds it encouraging that the area of sexual risk-taking that showed the greatest optimization in the pilot study was receptive CAI, the sexual positioning that results in the greatest HIV transmission risk among serodiscordant partners. This finding also dovetails with prior evidence that suggests that the bulk of sexual risk-taking among methamphetamine-using GBMSM experiencing depression occurs specifically with non–primary partners (Fletcher, Clark, & Reback 2020).

5. Conclusion

Although the promising findings from this pilot study suggest depression intervention content may optimize methamphetamine treatment outcomes among GBMSM, we should note limitations to the current data and study design. Most generally, this study suffers from the self-reported nature of the sexual risk data, the potential bias introduced via the use of treatment-seeking individuals who volunteered to participate in the intervention, the relatively small sample size and lack of randomization, and the very specific nature of the sample (i.e., predominantly HIV-positive GBMSM in a large city). Additionally, the low-intensity nature of the MoodGym intervention leaves some questions as to whether the modest improvements observed in methamphetamine use and sexual risk behaviors, as well as the lack of linear reductions in depressive symptoms over time, would have been more dramatic or more evident if the study had used a higher-intensity depression intervention. The use of the MoodGym intervention, whose clinical significance remains unclear, may also have been a weakness of this pilot study, relative to a more well-established depression intervention. Finally, the lack of any measures of positive affect are a limitation, as anhedonia or lack of positive emotional arousal may also prompt engagement in methamphetamine use (Carrico et al., 2013; Carrico et al., 2019; Mutumba et al., 2021), and these are distinct mechanisms from the arousal of depression. Despite these limitations, however, results from the pilot study reinforce findings that suggest that depression plays an important role in the link between methamphetamine use and sexual risk-taking among GBMSM, and extends this narrative by demonstrating that applying depression intervention content to treatment-seeking GBMSM may serve to optimize methamphetamine treatment outcomes. Given that reaching the End the HIV Epidemic goals is important to public health, and the critical role that methamphetamine use plays in sexual risk-taking and HIV transmission, larger sample, randomized controlled trials should replicate and refine the findings reported here.

Table 1:

Sociodemographic Characteristics among Gay and Bisexual Men Seeking Outpatient Treatment for Methamphetamine Use

Pilot Data HMC #1 (UA Data; unweighted) HMC #2 (Sex Risk Data; unweighted)
N = 39 N = 95 N = 79
n (%) or Mean [SD; Md] n (%) or Mean [SD; Md] n (%) or Mean [SD; Md] Sig.
Age
years 44.5 [10.4; 47] 41.3 [8.9; 43] 41.9 [9.3; 44] ns
Racial/Ethnic Identity
 White 12 (30.8%) 34 (35.8%) 32 (40.5%) ns
 Black 4 (10.3%) 12 (12.6%) 13 (16.5%)
 Latinx 20 (51.3%) 40 (42.1%) 29 (36.7%)
 Multiracial/Other 3 (7.7%) 9 (9.5%) 5 (6.3%)
Sexual Identity (n = 38)
 Gay 30 (79.0%) 76 (80.0%) 64 (81.1%) ns
 Bisexual 8 (21.1%) 19 (20.0%) 15 (19.0%)
HIV Status
 HIV-Negative/DK 10 (25.6%) 29 (30.5%) 26 (32.9%) ns
 HIV-Positive 29 (74.4%) 66 (69.5%) 53 (67.1%)
Tenure of Heavy Meth Use
years 5.13 [5.34; 3] 4.72 [5.14; 3] 4.80 [5.47; 3] ns
Meth Use at Baseline
days/past 30 8.51 [9.46; 4] 8.91 [9.32; 5] 7.91 [8.60; 4] ns
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ns: Differences between groups did not reach statistical significance at p < 0.05 (F-tests and t-tests for continuous variables, Chi-square for categorical variables).

Highlights.

  • Depression may be an important factor in the well-established relationship between methamphetamine use and sexual risk behavior among gay, bisexual, and other MSM (GBMSM).

  • Depression is a common consequence of methamphetamine withdrawal, and thus adding depression intervention content to methamphetamine treatment may mitigate sexual risk-taking among GBMSM in outpatient treatment for methamphetamine use.

  • Data from this pilot study indicates adding a brief computerized depression intervention to outpatient methamphetamine treatment for GBMSM may optimize reductions in methamphetamine use and/or sexual risk-taking.

FUNDING ACKNOWLEDGMENT:

Funding for this study was provided by the National Institute of Mental Health, supplement to grant #P30MH58107 (PI: Shoptaw). Funding for the parent service program was provided by the Los Angeles County, Department of Public Health, Division of HIV and STD programs contract #PH-001039 and the City of West Hollywood, Division of Social Services. Dr. Reback acknowledges additional support from the National Institute of Mental Health (P30MH58107).

Footnotes

DISCLOSURE OF INTEREST: The authors report no conflict of interest.

Participants were matched on age, racial/ethnic identity, sexual identity, HIV status, years of heavy methamphetamine use, and days of methamphetamine use in the past 30 days at baseline; age, years of heavy methamphetamine use, and days of methamphetamine use at baseline were all included in the bias adjustment.

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