Search

Until recently, most modern neuroscience research on addiction using animal models did not incorporate manipulations of social factors. Social factors play a critical role in human addiction: social isolation and exclusion can promote drug use and relapse, while social connections and inclusion tend to be protective. Here, we discuss the state of the literature on social factors in animal models of opioid and psychostimulant preference, self-administration, and relapse. We first summarize results from rodent studies on behavioral, pharmacological, and circuit mechanisms of the protective effect of traditional experimenter-controlled social interaction procedures on opioid and psychostimulant conditioned place preference, self-administration, and relapse. Next, we summarize behavioral and brain-mechanism results from studies using newer operant social-interaction procedures that inhibit opioid and psychostimulant self-administration and relapse. We conclude by discussing how the reviewed studies point to future directions for the addiction field and other neuroscience and psychiatric fields, and their implications for mechanistic understanding of addiction and development of new treatments.SIGNIFICANCE STATEMENTIn this review, we propose that incorporating social factors into modern neuroscience research on addiction could improve mechanistic accounts of addiction and help close gaps in translating discovery to treatment. We first summarize rodent studies on behavioral, pharmacological, and circuit mechanisms of the protective effect of both traditional experimenter-controlled and newer operant social-interaction procedures. We then discuss potential future directions and clinical implications.

Kratom, a plant that produces opioid-like effects, has gained popularity in the U.S. for self-treating symptoms of chronic pain, mood disorders, and substance-use disorders (SUDs). Most data on kratom are from surveys into which current kratom-using adults could self-select; such surveys may underrepresent people who have used kratom and chosen to stop. Available data also do not adequately assess important psychosocial factors surrounding kratom use. In this study, U.S. adults who reported past 6-month alcohol, opioid, and/or stimulant use (N = 1,670) were recruited via Amazon Mechanical Turk between September and December 2020. Of the 1,510 evaluable respondents, 202 (13.4%) reported lifetime kratom use. Kratom-using adults, relative to others, were typically younger, male, unpartnered, without children, and had lower income. They had higher rates of chronic pain (31.7% vs. 21.9%, p = .003), childhood adversity, anxiety, and depression (p < .001), and lower perceived social rank (d = .19, .02-.22) and socioeconomic status (d = .37 .16-.26). They also reported higher use rates for most substances (except alcohol); this included medically supervised and unsupervised use of prescription opioids and diverted opioid agonist therapy (OAT) medications. Most (83.2%) met diagnostic criteria for any past-year SUD. Those reporting kratom use were less likely to reside in an urban/suburban area. The strongest predictors of kratom use were use of other drugs: cannabidiol (OR = 3.73), psychedelics (OR = 3.39), and nonmedical prescription opioids (OR = 1.72). Another strong predictor was lifetime OAT utilization (OR = 2.31). Despite seemingly poorer psychosocial functioning and health among respondents reporting lifetime kratom use, use of other substances may be the strongest indicators of kratom use. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

INTRODUCTION: Since 2007, kratom use in the United States has increased, centered around nonmedical self-treatment of pain, psychiatric, and substance use disorder (SUD) symptoms. Reports of kratom withdrawal have emerged amidst description of therapeutic effects, yet we know little about disordered use. Our objective was to assess DSM-5 SUD for kratom (“kratom use disorder”, KUD) and examine kratom withdrawal symptoms among those who ever used regularly. We also sought to identify clinical characteristics of respondents who qualified for current, remitted, or never KUD. METHODS: Between April-May 2021, we re-recruited online respondents who reported lifetime kratom use on an unrelated survey into our cross-sectional kratom survey study, permitting a diverse sample of current and former kratom-using persons. RESULTS: A total of 129/289 (44.6%) evaluable surveys were obtained. Over half (52.7%) of respondents never met KUD diagnostic criteria; 17.8% were assessed remitted, and 29.5% met current (past-year) KUD threshold. For past-year KUD, severity was: 14.0% mild, 7.0% moderate, and 8.5% severe. Pain, psychiatric symptoms, and polydrug use were found across all groups. KUD symptoms reflected increased use, tolerance, withdrawal, unsuccessful quit attempts, and craving; 9.3% reported decreases in important social, occupational, or recreational activities because of use. Withdrawal symptoms were moderate and included gastrointestinal upset, restlessness, anxiety, irritability, fatigue/low energy, and craving. CONCLUSIONS: As assessed here, tolerance and withdrawal are primary KUD features rather than psychosocial impairments. As kratom is often used among persons with a myriad of health conditions, clinicians should be aware of and assess for kratom use and withdrawal.

Patients receiving medication for opioid use disorder (MOUD) may continue using nonprescribed drugs or have trouble with medication adherence, and it is difficult to predict which patients will continue to do so. In this study, we develop and validate an automated risk-modeling framework to predict opioid abstinence and medication adherence at a patient's next attended appointment and evaluate the predictive performance of machine-learning algorithms versus logistic regression.Urine drug screen and attendance records from 40,005 appointments drawn from 2742 patients at a multilocation office-based MOUD program were used to train logistic regression, logistic ridge regression, and XGBoost models to predict a composite indicator of treatment adherence (opioid-negative and norbuprenorphine-positive urine, no evidence of urine adulteration) at next attended appointment.The XGBoost model had similar accuracy and discriminative ability (accuracy, 88%; area under the receiver operating curve, 0.87) to the two logistic regression models (accuracy, 88%; area under the receiver operating curve, 0.87). The XGBoost model had nearly perfect calibration in independent validation data; the logistic and ridge regression models slightly overestimated adherence likelihood. Historical treatment adherence, attendance rate, and fentanyl-positive urine at current appointment were the strongest contributors to treatment adherence at next attended appointment.There is a need for risk prediction tools to improve delivery of MOUD. This study presents an automated and portable risk-modeling framework to predict treatment adherence at each patient's next attended appointment. The XGBoost algorithm appears to provide similar classification accuracy to logistic regression models; however, XGBoost may offer improved calibration of risk estimates compared with logistic regression.

Introduction: Surveys and case reports have documented kratom use in the United States (US) for over a decade. However, those reports have generally not examined in depth the role kratom plays in the lives of those who use it regularly for sustained periods. Until there are controlled studies of the pharmacology and subjective effects of kratom alkaloids in humans, one of the best sources of insight on kratom-product use remains qualitative data with nuanced descriptions of kratom effects from those who use it regularly.Method: We conducted semistructured qualitative interviews with adults who regularly use kratom products, as part of a laboratory study of kratom-product self-administration. This qualitative component of the study was conducted as a narrative case-report series (n = 10).Results: Despite some differences among participants, all experienced acute combination effects that were largely, even simultaneously, analgesic and stimulatory. Most participants had decreased their dosages over time, and one planned to quit. Five of the 10 participants met DSM-5-based criteria for kratom-use disorder (3 mild, 1 moderate, 1 severe, by symptoms counts). When kratom was inadvertently taken in larger than intended doses, participants described a constellation of symptoms that they called “the wobbles” (a jittery feeling accompanied by what seemed to be nystagmus); this was rare, but could be of scientific and clinical interest as a possible manifestation of serotonin syndrome. Most participants described tolerance but considered kratom generally safe at low-moderate doses, providing perceived benefits with less potential risk for adverse effects compared to pharmaceuticals or illicit drugs.Discussion: In-depth interview data like these help confirm and clarify findings from larger survey studies and clinician-driven case reports. They are needed to inform the policy practice regarding kratom and may also help inform future experimental designs.

ImportanceDrug overdoses from opioids like fentanyl and heroin and stimulant drugs such as methamphetamine and cocaine are a major cause of mortality in the United States, with potential sex differences across the lifespan.ObjectiveTo determine overdose mortality for specific drug categories across the lifespan of males and females, using a nationally representative state-level sample.DesignState-level analyses of nationally representative epidemiological data on overdose mortality for specific drug categories, across 10-year age bins (age range: 15-74).SettingPopulation-based study of Multiple Cause of Death 2020-2021 data from the Centers of Disease Control and Prevention (CDC WONDER platform).ParticipantsDecedents in the United States in 2020-2021Main outcome measuresThe main outcome measure was sex-specific rates of overdose death (per 100,000) for: synthetic opioids excluding methadone (ICD-10 code: T40.4; predominantly fentanyl), heroin (T40.1), psychostimulants with potential for misuse, excluding cocaine (T43.6, predominantly methamphetamine; labeled “psychostimulants” hereafter), and cocaine (T40.5). Multiple regression analyses were used to control for ethnic-cultural background, household net worth, and sex-specific rate of misuse of the relevant substances (from the National Survey on Drug Use and Health, 2018-2019).ResultsFor each of the drug categories assessed, males had greater overall overdose mortality than females, after controlling for rates of drug misuse. The mean male/female sex ratio of mortality rate for the separate drug categories was relatively stable across jurisdictions: synthetic opioids (2.5 [95%CI, 2.4-2.7]), heroin, (2.9 [95%CI, 2.7-3.1], psychostimulants (2.4 [95%CI, 2.3-2.5]), and cocaine (2.8 [95%CI, 2.6-2.9]). With data stratified in 10-year age bins, the sex difference generally survived adjustment for state-level ethnic-cultural and economic variables, and for sex-specific misuse of each drug type (especially for bins in the 25-64 age range). For synthetic opioids, the sex difference survived adjustment across the lifespan (i.e., 10-year age bins ranging from 15-74), including adolescence, adulthood and late adulthood.Conclusions and RelevanceThe robustly greater overdose mortality in males versus females for synthetic opioids (predominantly fentanyl), heroin, and stimulant drugs including methamphetamine and cocaine indicate that males who misuse these drugs are significantly more vulnerable to overdose deaths. These results call for research into diverse biological, behavioral, and social factors that underlie sex differences in human vulnerability to drug overdose.Key PointsQuestionWhat are the current national trends in overdose mortality from opioids (synthetic opioids such as fentanyl, and heroin) and stimulant drugs (psychostimulants such as methamphetamine and cocaine) for males and females, over the lifespan (overall range 15-74 years)?FindingsState-level analyses of data from CDC for 2020-2021 indicate that after controlling for rates of drug misuse, males had significantly greater (2-3 fold) overdose mortality rates than females for synthetic opioids, heroin, psychostimulants and cocaine. These findings were generally consistent across the lifespan, studied as 10-year age bins (especially in the 25-64 age range).MeaningThese data indicate that males who misuse opioids and stimulant drugs are considerably more vulnerable to overdose mortality, compared to females. This finding calls for research on the underlying biological, behavioral, and social factors.

Syphilis among men who have sex with men (MSM) has increased greatly in the past twenty years in the U.S. Geographically explicit ecological momentary assessment (GEMA), in which behaviors are geotagged and contextualized in time and space, may contribute to a greater understanding of transmission risk. The objective was to determine the acceptability and feasibility of GEMA for assessing HIV and syphilis transmission risk behaviors among a sample of MSM. Participants responded to a brief survey five times a day for two weeks. Feasibility was measured by participant recruitment, enrollment, prompts received and answered, geotagged prompts, and technical interference with data collection. Acceptability was measured by ratings of enjoyment and willingness for future participation. Summaries of five behavioral measures from the brief survey were calculated. Among the 83 participants contacted, 67.5% (56) expressed interest, 98% (55) were scheduled, and 81.8% (45) were enrolled. Participants answered 78.3% (2,277) of prompts received and 87.7% (1,998) of answered prompts were geotagged. Overall, 70.5% (31) enjoyed participating and 91.1% (41) were willing to participate in the future. Among prompts answered, missingness was low for five behavioral measures (range 0.2% (4) to 0.7% (16)). Feasibility and acceptability were high and missingness was low on behavioral measures in this MSM study population. Most participants reported that they would participate again. Future work should focus on whether GEMA improves our understanding of syphilis and HIV transmission risk.

Social reinforcement-based treatments are effective for many, but not all, people with addictions to drugs. We recently developed an operant rat model that mimics features of one such treatment, the community-reinforcement approach. In this model, rats uniformly choose social interaction over methamphetamine or heroin. Abstinence induced by social preference protects against the incubation of drug-seeking that would emerge during forced abstinence. Here, we determined whether these findings generalize to cocaine and whether delaying or increasing effort for social interaction could reveal possibly human-relevant individual differences in responsiveness. We trained male and female rats for social self-administration (6 days) and then for cocaine self-administration, initially for 2-h/day for 4 days, and then for 12-h/day continuously or intermittently for 8 days. We assessed relapse to cocaine seeking after 1 and 15 days. Between tests, the rats underwent either forced abstinence or social-choice-induced abstinence. After establishing stable social preference, we manipulated the delay for both rewards or for social reward alone, or the response requirements (effort) for social reward. Independent of cocaine-access conditions and sex, operant social interaction inhibited cocaine self-administration and prevented incubation of cocaine seeking. Preference for social access was decreased by the delay of both rewards or social reward alone, or by increased response requirements for social reward, with notable individual variability. This choice procedure can identify mechanisms of individual differences in an animal model of cocaine use and could thereby help screen medications for people who are relatively unresponsive to treatments based on rewarding social interaction.

Anhedonia is usually defined as partial or total loss of the capacity for pleasure. People with anhedonia in the context of major depressive disorder may have an unexpected capacity for event-related mood brightening, observable when mood is assessed dynamically (with smartphone-based ecological momentary assessment [EMA]) rather than only statically via questionnaire. We used EMA to monitor mood and pleasant events for 4 weeks in 54 people being treated with opioid agonist medication for opioid-use disorder (OUD), which is also associated with anhedonia, said to manifest especially as loss of pleasure from nondrug reward. We compared OUD patients' EMA reports with those of 47 demographically similar controls. Background positive mood was lower in OUD patients than in controls, as we hypothesized (Cohen ds = .85 to 1.32, 95% CIs [.66, 1.55]), although, contrary to our hypothesis, background negative mood was also lower (ds = .82 to .85, 95% CIs [.73, .94]). As hypothesized, instances of nondrug pleasure were as frequent in OUD patients as in controls-and were not rated much less pleasurable (d = .18, 95% CI [-.03, .35]). Event-related mood brightening occurred in both abstinent and nonabstinent OUD patients (ds = .18 to .37, CIs [-.01, .57]) and controls (ds = .04 to .60, CIs [-.17, .79]), brightening before each event began earlier for controls than OUD patients, but faded similarly postevent across groups. Our findings add to the evidence that anhedonia does not rule out reactive mood brightening, which, for people with OUD being treated on opioid agonist medication, can be elicited by nondrug activities. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

In intensive longitudinal studies using ecological momentary assessment, mood is typically assessed by repeatedly obtaining ratings for a large set of adjectives. Summarizing and analyzing these mood data can be problematic because the reliability and factor structure of such measures have rarely been evaluated in this context, which-unlike cross-sectional studies-captures between- and within-person processes. Our study examined how mood ratings (obtained thrice daily for 8 weeks

ImportanceMethadone treatment is the most effective evidence-based treatment for opioid use disorder (OUD), but challenges related to dosing and premature treatment dropout argue for adjunct interventions to improve outcomes. One potential behavioral intervention with low risk involves harnessing placebo effects.ObjectiveTo determine the effect of a pharmacologically conditioned open-label placebo (C-OLP) on 90-day methadone dose, retention, drug use, withdrawal, craving, quality of life, and sleep.Design, Setting, and ParticipantsThis 2-arm, open-label, single-blind randomized clinical trial was conducted between December 5, 2017, and August 2, 2019, in an academically affiliated community opioid treatment program. Analyses were conducted between October 1, 2019, and April 30, 2020. A total of 320 newly enrolled adults seeking treatment for moderate to severe OUD were assessed for study eligibility; 131 met eligibility criteria, provided informed consent, and were randomized to either C-OLP or treatment as usual (TAU) in an unequal-block (3:2) manner. Exclusion criteria were pregnancy, hospital/program transfers, and court-ordered treatment.InterventionsParticipants randomized to C-OLP received pharmacologic conditioning and a placebo pill and methadone, and participants randomized to TAU were given methadone only. Participants met with the study team 5 times: at baseline (treatment intake) and 2, 4, 8, and 12 weeks postbaseline. Interactions were balanced between the 2 groups.Main Outcomes and MeasuresOutcomes included 90-day methadone dose (primary) and treatment retention, drug use, withdrawal, craving, quality of life, and sleep quality (secondary). Analyses were conducted as intention-to-treat.ResultsOf the 131 people enrolled in the study, 54 were randomized to TAU and 77 to C-OLP. Mean (SD) age was 45.9 (11.2) years; most of the participants were Black or African American (83 [63.4%]) and male (84 [64.1%]). No significant group differences were observed in the mean (SD) 90-day methadone dose (83.1 [25.1] mg for group TAU, 79.4 [19.6] mg for group C-OLP; t = 0.621991; P = .43), but the groups differed significantly in their retention rates: 33 (61.1%) for TAU and 60 (77.9%) for C-OLP (χ21 = 4.356; P = .04; number needed to treat for the beneficial outcome of 3-month treatment retention, 6; 95% CI, 4-119). C-OLP participants also reported significantly better sleep quality.Conclusions and RelevanceIn this randomized clinical trial, C-OLP had no effect on the primary outcome of 90-day methadone dose. However, C-OLP participants were significantly more likely to remain in treatment. These findings support the use of C-OLP as a methadone treatment adjunct, but larger trials are needed to further examine the use of C-OLP.Trial RegistrationClinicalTrials.gov Identifier: NCT02941809

The high efficacy mu-opioid receptor (MOR) agonist methadone is an effective opioid use disorder (OUD) medication used exclusively in opioid-dependent patients. However, methadone has undesirable effects that limit its clinical efficacy. Intermediate efficacy MOR agonists may treat OUD with fewer undesirable effects. We compared the effects of methadone with the intermediate efficacy MOR agonist TRV130 (oliceridine) on fentanyl-vs.-food choice and somatic withdrawal signs in opioid-dependent and post-opioid-dependent rats. Male rats (n = 20) were trained under a fentanyl-vs.-food choice procedure. Rats were then provided extended fentanyl (3.2 µg/kg/infusion) access (6 p.m.-6 a.m.) for 10 days to produce opioid dependence/withdrawal. Rats were treated with vehicle (n = 7), TRV130 (3.2 mg/kg; n = 8), or methadone (3.2 mg/kg; n = 5) three times per day after each extended-access session (8:30 a.m., 11 a.m., 1:30 p.m.). Withdrawal sign scoring (1:55 p.m.) and choice tests (2-4 p.m.) were conducted daily. Vehicle, TRV130, and methadone effects on fentanyl choice were redetermined in post-opioid-dependent rats. Vehicle-, TRV130-, and methadone-treated rats had similar fentanyl intakes during extended access. Vehicle-treated rats exhibited increased withdrawal signs and decreased bodyweights. Both methadone and TRV130 decreased these withdrawal signs. TRV130 was less effective than methadone to decrease fentanyl choice and increase food choice in opioid-dependent rats. Neither methadone nor TRV130 decreased fentanyl choice in post-opioid-dependent rats. Results suggest that higher MOR activation is required to reduce fentanyl choice than withdrawal signs in fentanyl-dependent rats. Additionally, given that TRV130 did not precipitate withdrawal in opioid-dependent rats, intermediate efficacy MOR agonists like TRV130 may facilitate the transition of patients with OUD from methadone to lower efficacy treatments like buprenorphine.

Objective Evidence suggests that blunted reward responsiveness may account for poor clinical outcomes in both opioid use disorder (OUD) and chronic pain. Understanding how individuals with OUD and comorbid chronic pain (OUD+CP) respond to rewards is, therefore, of clinical interest because it may reveal a potential point of behavioral intervention. Methods Patients with OUD (n = 28) and OUD+CP (n = 19) on opioid agonist treatment were compared on: 1) the Probabilistic Reward Task (an objective behavioral measure of reward response bias) and 2) ecological momentary assessment of affective responses to pleasurable events. Results Both the OUD and the OUD+CP groups evidenced an increase in reward response bias in the Probabilistic Reward Task. The rate of change in response bias across blocks was statistically significant in the OUD group (B = 0.06, standard error [SE] = 0.02, t = 3.92, P Conclusions Overall, findings across objective and subjective measures were mixed, necessitating follow-up with a larger sample. The results suggest that although there is a reward response bias in patients with OUD+CP treated with opioid agonist treatment relative to patients with OUD without CP, it is modest and does not appear to translate into patients’ responses to rewarding events as they unfold in daily life.

Purpose of Review Addiction scientists have begun using ambulatory assessment methods—including ecological momentary assessment (EMA), experience sampling, and daily diaries—to collect real-time or near-real-time reports of participants’ internal states in their natural environments. The goal of this short review is to synthesize EMA findings from our research group, which has studied several hundred outpatients during treatment for opioid-use disorder (OUD). (We cite pertinent findings from other groups, but have not tried to be comprehensive.) One of our main goals in using EMA is to examine momentary changes in internal states that proximally predict, or concurrently mark, events such as lapses to opioid use. Recent Findings We summarize findings evaluating several classes of momentary markers or predictors (craving, stress, negative and positive moods, and physical pain/discomfort) of lapses and other states/behaviors. Craving and some negatively valenced mood states are concurrently and prospectively associated with lapses to opioid use during treatment. Craving is also concurrently and prospectively associated with momentary changes in stress and mood. Convincing evidence has not yet emerged for stress as a robust redictor of lapse to opioid use; it appears to be contributory, but neither necessary nor sufficient. Summary Ambulatory assessment can capture changes in internal states and drug-related behaviors in situ and at high temporal resolution. We recommend research strategies that may increase the clinical and prognostic utility of ambulatory assessment, including denser sampling (i.e., more assessments per day) and more attention to heterogeneity across people and across populations.

AIM To assess the role of momentary pain on opioid craving and illicit opioid use among individuals receiving opioid agonist treatment. DESIGN Observational study using ecological momentary assessment. SETTING The National Institute of Drug Abuse Intramural Research Program in the United States. PARTICIPANTS Fifty-six adults who qualified for opioid agonist treatment. MEASUREMENTS Participants completed randomly prompted assessments of pain severity, stress, negative mood, opioid craving and illicit opioid use for a mean of 66 days [standard deviation (SD) = 27]. Urine samples were collected two to three times/week throughout. FINDINGS Almost 70% of participants reported moderate average pain severity in the past 24 hours at intake and 35% of participants reported chronic pain. There were no significant differences in percent of opioid-positive urine samples (P = 0.73) and average level of opioid craving during the study period (P = 0.91) among opioid agonist treatment only patients versus opioid agonist treatment patients with chronic pain. However, momentary pain severity significantly predicted concurrent opioid craving [B = 0.02, 95% confidence interval (CI) = 0.01, 0.04], over and above stress and negative mood. Momentary opioid craving, in turn, significantly predicted illicit opioid use that was assessed in the next moment [odds ratio (OR) = 1.72, 95% CI = 1.12, 2.64), while controlling for autocorrelation and the effects of pain, negative mood and stress. Momentary opioid craving significantly mediated the prospective association between momentary pain and illicit opioid use (95% CI = 0.003, 0.032). Exploratory analysis revealed that momentary pain severity also significantly moderated the momentary association between stress and opioid craving (B = 0.02, 95% CI = 0.00, 0.04), such that when momentary pain severity increased, the association between the two intensified. CONCLUSIONS Among people receiving opioid agonist treatment, momentary pain appears to be indirectly associated with illicit opioid use via momentary opioid craving.

Background Maintenance treatment with opioid agonists (buprenorphine, methadone) is effective for opioid addiction but does not eliminate opioid use in all patients. We modeled maintenance treatment in rats that self-administered the prescription opioid oxycodone. The maintenance medication was either buprenorphine or the G protein–biased mu opioid receptor agonist TRV130. We then tested prevention of oxycodone seeking and taking during abstinence using a modified context-induced reinstatement procedure, a rat relapse model. Methods We trained rats to self-administer oxycodone (6 hours/day, 14 days) in context A; infusions were paired with discrete tone-light cues. We then implanted osmotic pumps containing buprenorphine or TRV130 (0, 3, 6, or 9 mg/kg/day) and performed 3 consecutive tests: lever pressing reinforced by oxycodone-associated discrete cues in nondrug context B (extinction responding), context-induced reinstatement of oxycodone seeking in context A, and reacquisition of oxycodone self-administration in context A. We also tested whether TRV130 maintenance would protect against acute oxycodone-induced decreases in nucleus accumbens oxygen levels. Results In male rats, buprenorphine and TRV130 decreased extinction responding and reacquisition of oxycodone self-administration but had a weaker (nonsignificant) effect on context-induced reinstatement. In female rats, buprenorphine decreased responding in all 3 tests, while TRV130 decreased only extinction responding. In both sexes, TRV130 prevented acute brain hypoxia induced by moderate doses of oxycodone. Conclusions TRV130 decreased oxycodone seeking and taking during abstinence in a partly sex-specific manner and prevented acute oxycodone-induced brain hypoxia. We propose that G protein–biased mu opioid receptor agonists, currently in development as analgesics, should be considered as relapse prevention maintenance treatment for opioid addiction.

Critical features of human addiction are increasingly being incorporated into complementary animal models, including escalation of drug intake, punished drug seeking and taking, intermittent drug access, choice between drug and non-drug rewards, and assessment of individual differences based on criteria in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Combined with new technologies, these models advanced our understanding of brain mechanisms of drug self-administration and relapse, but these mechanistic gains have not led to improvements in addiction treatment. This problem is not unique to addiction neuroscience, but it is an increasing source of disappointment and calls to regroup. Here we first summarize behavioural and neurobiological results from the animal models mentioned above. We then propose a reverse translational approach, whose goal is to develop models that mimic successful treatments: opioid agonist maintenance, contingency management and the community-reinforcement approach. These reverse-translated ‘treatments’ may provide an ecologically relevant platform from which to discover new circuits, test new medications and improve translation. Recent advances in animal addiction models have emphasized translational challenges. In this Review, Venniro and colleagues introduce a reverse translational approach that may provide an ecologically relevant platform from which to discover new circuits, test new medications and improve translation.

People in remission from substance use disorders (SUDs) have a history of using their own experience (also referred to as “experiential knowledge” or “expertise”) to support those in or seeking SUD remission. In recent years, people with this experiential knowledge are being incorporated into research protocols to better guide research questions and inform the real-world uptake of SUD treatments and recovery supports. In these research contexts, however, those with research expertise and addiction rarely speak freely about these overlapping perspectives. The aim of this commentary is to increase awareness regarding the existence of this group (addiction researchers with addiction) and to explore the possibility that their expertise may help advance addiction science while helping to reduce stigma.

RATIONALE: Many people being treated for opioid use disorder continue to use drugs during treatment. This use occurs in patterns that rarely conform to well-defined cycles of abstinence and relapse. Systematic identification and evaluation of these patterns could enhance analysis of clinical trials and provide insight into drug use. OBJECTIVES: To evaluate such an approach, we analyzed patterns of opioid and cocaine use from three randomized clinical trials of contingency management in methadone-treated participants. METHODS: Sequences of drug-test results were analyzed with unsupervised machine-learning techniques, including hierarchical clustering of categorical results (i.e., whether any samples were positive during each week) and K-means longitudinal clustering of quantitative results (i.e., the proportion positive each week). The sensitivity of cluster membership as an experimental outcome was assessed based on the effects of contingency management. External validation of clusters was based on drug craving and other symptoms of substance use disorder. RESULTS: In each clinical trial, we identified four clusters of use patterns, which can be described as opioid use, cocaine use, dual use (opioid and cocaine), and partial/complete abstinence. Different clustering techniques produced substantially similar classifications of individual participants, with strong above-chance agreement. Contingency management increased membership in clusters with lower levels of drug use and fewer symptoms of substance use disorder. CONCLUSIONS: Cluster analysis provides person-level output that is more interpretable and actionable than traditional outcome measures, providing a concrete answer to the question of what clinicians can tell patients about the success rates of new treatments.

Sleep problems are commonly reported during opioid agonist treatment (OAT) for opioid use disorders. Inpatient studies have found both sleep disturbances and improved sleep during OAT. Illicit opioids can also disrupt sleep, but it is unclear how they affect sleep in outpatients receiving OAT. Therefore, we used electronic diary entries and actigraphy to measure sleep duration and timing in opioid-dependent participants (n = 37) treated with methadone (n = 15) or buprenorphine (n = 22). For 16 weeks, participants were assigned to attend our clinic under different operating hours in a crossover design: Early hours (07:00–09:00) vs. Late hours (12:00–13:00) for 4 weeks each in randomized order, followed for all participants by our Standard clinic hours (07:00–11:30) for 8 weeks. Throughout, participants made daily electronic diary self-reports of their sleep upon waking; they also wore a wrist actigraph for 6 nights in each of the three clinic-hour conditions. Drug use was assessed by thrice-weekly urinalysis. In linear mixed models controlling for other sleep-relevant factors, sleep duration and timing differed by drug use and by clinic hours. Compared to when non-using, participants slept less, went to bed later, and woke later when using illicit opioids and/or both illicit opioids and cocaine. Participants slept less and woke earlier when assigned to the Early hours. These findings highlight the role OAT clinic schedules can play in structuring the sleep/wake cycles of OAT patients and clarify some of the circumstances under which OAT patients experience sleep disruption in daily life.

Kratom products available in the United States are becoming increasingly diverse both in terms of content and in terms of how they are marketed. Prior survey research indicates that kratom has been primarily used in the US to self-treat anxiety, depression, pain, fatigue, and substance use disorder (SUD) symptoms. Kratom is also well-known for its use as a short- or long-term full opioid agonist substitute. Therefore, use may be greater in regions particularly impacted by addiction to prescription opioids. Use may also be greater in demographic groups targeted by media outlets (such as specific podcasts) in which kratom is touted. Here, we aimed to determine whether lifetime and past-year kratom use were associated with region of residence and with being young, White, post-secondary educated, and employed. To strengthen confidence in our findings, we analyzed data from two sources: our own crowdsourced online convenience sample and the 2019 National Survey on Drug Use and Health (NSDUH). In our sample (N = 2,615), 11.1% reported lifetime and 6.7% reported past-year kratom use, and the odds of kratom use were higher among people who were White, younger, at least high school educated, employed, and above the poverty line, as well as those reporting nonmedical opioid use, past-year SUD, or lifetime SUD treatment; residence was not a significant predictor. In NSDUH data, suburban residence and other demographic factors, concordant with those from the crowdsourced sample, were associated with kratom use. Taken together, the findings support a general “White middle-class suburban” profile of the modal kratom user, but more research is needed to understand it. In the interim, focus should be on our finding that lifetime nonmedical opioid use was associated with an up to five times greater likelihood of past-year kratom use, suggesting that drug-use history may presently be the strongest predictor of kratom use.

Affect and craving are dynamic processes that are clinically relevant in opioid use disorder (OUD) treatment, and can be quantified in terms of intra-individual variability and stability. The purpose of the present analysis was to explore associations between opioid use and variability and stability of affect and craving among individuals receiving medication treatment for OUD (MOUD). Adults (N = 224) with OUD in outpatient methadone or buprenorphine treatment completed ecological momentary assessment (EMA) prompts assessing positive affect, negative affect, opioid craving, and opioid use. Dynamic structural equation modeling (DSEM) was used to quantify person-level indices of magnitude and stability of change. Beta regression was used to examine associations between intra-individual variability and stability and proportion of opioid-use days, when controlling for overall intensity of affect and craving. Results suggested that greater magnitude of craving variability was associated with opioid use on a greater proportion of days, particularly among individuals with lower average craving. Low average positive affect was also associated with higher proportion of days of use. Individuals who experience substantial craving variability in the context of lower average craving may be particularly vulnerable to opioid use during treatment. Ongoing assessment of craving may be useful in identifying treatment needs. Examining correlates of intra-individual variability and stability in MOUD treatment remains a relevant direction for future work.

There is limited understanding regarding kratom use among US adults. Although motivations for use are increasingly understood, typical kratom doses, threshold of (low and high) doses for perceived effectiveness, and effects produced during cessation are not well documented. We aimed to extend prior survey work by recruiting adults with current and past kratom exposure. Our goal was to better understand kratom dosing, changes in routines, and perception of effects, including time to onset, duration, and variability of beneficial and adverse outcomes from use and cessation. Among respondents who reported experiencing acute kratom effects, we also sought to determine if effects were perceived as helpful or unhelpful in meeting daily obligations. Finally, we attempted to detect any signal of a relationship between the amount of kratom consumed weekly and weeks of regular use with ratings of beneficial effects from use and ratings of adverse effects from cessation. We conducted an online survey between April-May 2021 by re-recruiting participants from a separate study who reported lifetime kratom use. A total of 129 evaluable surveys were collected. Most (59.7%) had used kratom >100 times and reported currently or having previously used kratom >4 times per week (62 weeks on average). Under half (41.9%) reported that they considered themselves to be a current “regular kratom user.” A majority (79.8%) reported experiencing acute effects from their typical kratom dose and that onset of effects began in minutes but dissipated within hours. Over a quarter reported that they had increased their kratom dose since use initiation, whereas 18.6% had decreased. Greater severity of unwanted effects from ≥1 day of kratom cessation was predicted by more weeks of regular kratom use (β = 6.74, p = 0.02). Acute kratom effects were largely reported as compatible with, and sometimes helpful in, meeting daily obligations. In the absence of human laboratory studies, survey methods must be refined to more precisely assess dose-effect relationships. These can help inform the development of controlled observational and experimental studies needed to advance the public health understanding of kratom product use.

Background: Originally believed to be an atypical antidepressant acting at serotonin transporters, tianeptine is now known to also be an atypical agonist at mu-opioid receptors. Its nonmedical use may be increasing amidst the broader context of novel drug and supplement use. Objectives: To analyze social-media text from current, former, and prospective tianeptine users for better understanding of their conceptualizations of tianeptine, motives for and patterns of use, and reported benefits and harms. Methods: Reddit posts were obtained and thematically coded; additional quantitative analyses were conducted. Results: A total of 210 posts mentioning tianeptine were made between 2012 and 2020. Eighteen thematic categories were identified, 10 of which were consistent with expected themes. Two independent raters coded all text, generating 1,382 unique codes, of which 1,090 were concordant (78.9% interrater agreement). Tianeptine use was frequently associated with use of other drugs, particularly kratom, phenibut, and racetams. People conceptualized and variously used tianeptine as an opioid, antidepressant, and “nootropic” (cognitive enhancer). Between 2014 and 2020, mentions of positive effects decreased, while mentions of adverse effects and withdrawal increased. Motivations for use included substitution or withdrawal mitigation for other drugs (especially opioids) and for kratom itself; self-treatment for psychiatric symptoms; and improvement of quality of life, mood, or performance. Descriptions of tolerance, withdrawal, and addiction were evident. Intravenous use was rare and strongly discouraged, with detrimental effects described. Conclusion: Tianeptine is recognized as an opioid (though not only an opioid) in online communities. Posts describe benefits, acute risks, and patterns of co-use that warrant greater clinical attention.

Background Treatment with opioid agonists is effective for opioid use disorder, but early discontinuation of treatment is a major obstacle to success. Intensive longitudinal methods — which take many repeated measurements over time, usually in the field— have provided unique insight into the effects of stress, mood and craving on drug use while people are being treated; these methods might also be useful for studying the processes that lead people to drop out of treatment. Methods Ecological momentary assessment (EMA) was conducted for up to 17 weeks by obtaining multiple electronic diary entries per day from 238 participants being treated with methadone or buprenorphine-naloxone. Survival analysis was used to study two outcomes: dropping out of treatment and noncompliance with EMA self-report requirements. Self-reports of stress, craving, and mood were used as time-varying predictors. Demographic and psychosocial variables measured with the Addiction Severity Index at the start of treatment were used as time-invariant predictors. Results Dropping out of treatment was more likely in participants with more reported hassles (a measure of stress), higher levels of cocaine craving, lower levels of positive mood, a recent history of emotional abuse, a recent history of being bothered frequently by psychological problems, and with buprenorphine rather than methadone as their medication. In contrast, study noncompliance was not significantly associated with any of the variables analyzed. Conclusions Assessment of stress, craving and mood during treatment might identify people who are at greater risk of dropping out, and therapeutic interventions targeting these processes might increase retention.

AIMS: To examine evidence for subtypes of opioid craving trajectories during medication for opioid use disorder (MOUD), and to (a) test whether these subtypes differed on MOUD-related outcomes, and (b) determine whether nonresponders could be identified before treatment initiation. DESIGN, SETTING, AND PARTICIPANTS: Outpatients (n = 211) being treated with buprenorphine or methadone for up to 16 weeks. Growth mixture modeling was used to identify unobserved craving-trajectory subtypes. Support Vector Machines (SVM) were trained to predict subtype membership from pretreatment data. MEASUREMENTS: Self-reported opioid craving (Ecological Momentary Assessment – EMA – three random moments per day). Participant-initiated EMA reports of drug use or higher-than-usual stress. Addiction Severity Index (ASI) pretreatment. FINDINGS: Four craving trajectories were identified: Low (73%); High and Increasing (HIC) (10.9%); Increasing and Decreasing (8.5%); and Rapidly Declining (7.6%). The HIC subgroup reported the highest use of heroin, any opiate, and cannabis during treatment. The Low Craving subgroup reported the lowest use of heroin or any opiate use, and the lowest levels of stress and drug-cue exposure during treatment. SVM models predicting HIC membership before treatment initiation had a sensitivity of 0.70, specificity of 0.78, and accuracy of 0.77. Including 3 weeks of EMA reports increased sensitivity to 0.78, specificity to 0.84, and accuracy to 0.85. CONCLUSIONS: Subgroups of MOUD patients show distinct patterns of opioid craving during treatment. Subgroups differ on critical outcomes including drug-use lapse, stress, and exposure to drug cues. Data from enrollment and early in treatment may help focus clinical attention.

The epidemic of addiction and overdose is real. Addiction among pain patients accounts for only a small proportion but a large number. Scientific opinion leaders can be most effective on two fronts, each relatively low-tech: dissemination and oversight of empirically established treatments, and promulgation of social-science-based strategies for population-level prevention.

Addiction treatment has not been appreciably improved by neuroscientific research. One problem is that mechanistic studies using rodent models do not incorporate volitional social factors, which play a critical role in human addiction. Here, using rats, we introduce an operant model of choice between drugs and social interaction. Independent of sex, drug class, drug dose, training conditions, abstinence duration, social housing, or addiction score in Diagnostic & Statistical Manual IV-based and intermittent access models, operant social reward prevented drug self-administration. This protection was lessened by delay or punishment of the social reward but neither measure was correlated with the addiction score. Social-choice-induced abstinence also prevented incubation of methamphetamine craving. This protective effect was associated with activation of central amygdala PKCδ-expressing inhibitory neurons and inhibition of anterior insular cortex activity. These findings highlight the need for incorporating social factors into neuroscience-based addiction research and support the wider implantation of socially based addiction treatments.

Background We previously showed, in people starting treatment for opioid use disorder (OUD), that stress is neither necessary nor sufficient for lapses to drug use to occur, despite an association between the two. Both theoretical clarity and case-by-case prediction accuracy may require initial differentiation among patients. Aim To examine: (a) evidence for distinct overall trajectories of momentary stress during OUD treatment, (b) relationships between stress trajectory and treatment response, and (c) relationships between stress trajectory and momentary changes in stress and craving prior to lapses. Methods We used ecological momentary assessment (EMA) to collect ratings of stress and craving 3x/day for up to 16 weeks in 211 outpatients during agonist treatment for OUD. With growth mixture models, we identified trajectories of stress. We used mixed effect models to examine trajectory-group differences in the dynamics of stress and craving just before lapses to any drug use. Results We identified four trajectories of stress: Increasing (13.7 %); Moderate and Stable (23.7 %); Declining and Increasing (18 %); and Low (44.6 %). Overall drug use and opioid craving were lowest in the Low Stress group. Overall drug use was highest in the Moderate and Stable group. Alcohol use and opioid craving were highest in the Increasing Stress group. Opioid craving increased before lapse for most groups, but stress increased before lapses for only the Moderate and Stable group. Conclusion There are natural groupings of participants with distinct patterns of stress severity during OUD treatment. Momentary stress/craving/lapse associations may be better characterized when these groupings are considered first.

UNSTRUCTURED As of December 2020, the SARS-CoV-2 virus has been responsible for over 78 million cases of COVID-19 worldwide, resulting in over 1.7 million deaths. In the United States in particular, protective measures against the COVID-19 pandemic have been hampered by political polarization and discrepancies among federal, state, and local policies. As a result, a huge amount of information surrounding COVID-19, some of it contradictory or blatantly false, has proliferated on social media. In this mixed scoping review, we survey the role of automated accounts, or “bots,” in spreading misinformation during past epidemics, natural disasters, and politically polarizing events through the lens of the COVID-19 pandemic. We also review strategies used by bots to spread (mis)information and machine learning methods for detecting bot activity. We conclude by conducting and presenting a secondary analysis of known bots, finding that up to 66% of bots are discussing COVID-19. The proliferation of COVID-19 (mis)information by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic.

As of March 2021, the SARS-CoV-2 virus has been responsible for over 115 million cases of COVID-19 worldwide, resulting in over 2.5 million deaths. As the virus spread exponentially, so did its media coverage, resulting in a proliferation of conflicting information on social media platforms-a so-called "infodemic." In this viewpoint, we survey past literature investigating the role of automated accounts, or "bots," in spreading such misinformation, drawing connections to the COVID-19 pandemic. We also review strategies used by bots to spread (mis)information and examine the potential origins of bots. We conclude by conducting and presenting a secondary analysis of data sets of known bots in which we find that up to 66% of bots are discussing COVID-19. The proliferation of COVID-19 (mis)information by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic.

RATIONALE: Given that many patients being treated for opioid-use disorder continue to use drugs, identifying clusters of patients who share similar patterns of use might provide insight into the disorder, the processes that affect it, and ways that treatment can be personalized. OBJECTIVES AND METHODS: We applied hierarchical clustering to identify patterns of opioid and cocaine use in 309 participants being treated with methadone or buprenorphine (in a buprenorphine-naloxone formulation) for up to 16 weeks. A smartphone app was used to assess stress and craving at three random times per day over the course of the study. RESULTS: Five basic patterns of use were identified: frequent opioid use, frequent cocaine use, frequent dual use (opioids and cocaine), sporadic use, and infrequent use. These patterns were differentially associated with medication (methadone vs. buprenorphine), race, age, drug-use history, drug-related problems prior to the study, stress-coping strategies, specific triggers of use events, and levels of cue exposure, craving, and negative mood. Craving tended to increase before use in all except those who used sporadically. Craving was sharply higher during the 90 minutes following moderate-to-severe stress in those with frequent use, but only moderately higher in those with infrequent or sporadic use. CONCLUSIONS. People who share similar patterns of drug-use during treatment also tend to share similarities with respect to psychological processes that surround instances of use, such as stress-induced craving. Cluster analysis combined with smartphone-based experience sampling provides an effective strategy for studying how drug use is related to personal and environmental factors.

Background The Covid-19 pandemic and its accompanying public-health orders (PHOs) have led to (potentially countervailing) changes in various risk factors for overdose. To assess whether the net effects of these factors varied geographically, we examined regional variation in the impact of the PHOs on counts of nonfatal overdoses, which have received less attention than fatal overdoses, despite their public health significance. Methods Data were collected from the Overdose Detection Mapping Application Program (ODMAP), which recorded suspected overdoses between July 1, 2018 and October 25, 2020. We used segmented regression models to assess the impact of PHOs on nonfatal-overdose trends in Washington DC and the five geographical regions of Maryland, using a historical control time series to adjust for normative changes in overdoses that occurred around mid-March (when the PHOs were issued). Results The mean level change in nonfatal opioid overdoses immediately after mid-March was not reliably different in the Covid-19 year versus the preceding control time series for any region. However, the rate of increase in nonfatal overdose was steeper after mid-March in the Covid-19 year versus the preceding year for Maryland as a whole (B = 2.36; 95% CI, 0.65 to 4.06; p = .007) and for certain subregions. No differences were observed for Washington DC. Conclusions The pandemic and its accompanying PHOs were associated with steeper increases in nonfatal opioid overdoses in most but not all of the regions we assessed, with a net effect that was deleterious for the Maryland region as a whole.

Background: Kratom is taken to self-treat pain and symptoms of psychiatric disorders, including substance-use disorders (SUDs) and opioid withdrawal. Before COVID-19, kratom use was increasing in the US, however, there are few published data on whether that trend continued during the COVID-19 pandemic, which could have affected kratom use in multiple ways. Aim: To examine COVID-19-related changes in kratom use and how these changes were experienced, relative to changes in other commonly used substances. Methods: Using Amazon Mechanical Turk, 2615 evaluable surveys were completed between September 2020 and March 2021. Responses from past-month and past-year kratom-using adults (N = 174) indicating changes for the better or worse were examined using generalized linear mixed effects models, and relevant open-text responses (n = 85) were thematically coded. Results: For kratom 33% (n = 58) reported a Covid-related increase and 24% (n = 42) reported a Covid-related decrease. Controlling for changes in amount used, alcohol (OR = 5.02), tobacco (OR = 4.72), and nonmedical opioid use (OR = 3.42) were all more likely to have changed for the worse, compared with kratom use. Relative to decreases in kratom use, decreases in alcohol (OR = 3.21) and tobacco (OR = 6.18) use were more likely to be changes for the better. Cannabis use was the only substance to display a probability lower than 50% of being a decrease for the better, and of the increases, cannabis use displayed the highest probability of being for the better. Conclusions: Increases in kratom and cannabis use were less likely than alcohol and tobacco to be reported as changes for the worse, and decreases in kratom and cannabis use were more likely than alcohol and tobacco to be reported as changes for the better. These findings indicate that people differently conceptualize their relationships with kratom and cannabis, compared to their relationships with alcohol and tobacco.

Adherence monitoring is a vital component of clinical efficacy trials, as the regularity of medication consumption affects both efficacy and adverse effect profiles. Pill-counts do not confirm consumption, and invasive plasma assessments can only assist post hoc assessments. We previously reported on the pharmacokinetics of a potential adherence marker to noninvasively monitor dosage consumption during a trial without breaking a blind. We reported that consumption cessation of subtherapeutic 15 mg acetazolamide (ACZ) doses showed a predictable urinary excretion decay that was quantifiable for an extended period. The current study describes the clinical implementation of 15 mg ACZ doses as an adherence marker excipient in distinct cohorts taking ACZ for different "adherence" durations. We confirm that ACZ output did not change (accumulate) during 18-20 days of adherence, and developed and assessed urinary cutoffs as nonadherence indicators. We demonstrate that whereas an absolute concentration cutoff (989 ng/mL) lacked sensitivity, a creatinine normalized equivalent (1,376 ng/mg ACZ) was highly accurate at detecting nonadherence. We also demonstrate that during nonadherent phases of three trials, creatinine-normalized urinary ACZ elimination was reproducible within and across trials with low variability. Excretion was first order, with a decay half-life averaging ~ 2.0 days. Further, excretion remained quantifiable for 14 days, providing a long period during which the date of last consumption might be determined. We conclude that inclusion of 15 mg ACZ as a dosage form adherence marker excipient, provides a reliable and sensitive mechanism to confirm medication consumption and detect nonadherence during clinical efficacy trials.

BACKGROUND: Preliminary evidence suggested that the PPARγ agonist pioglitazone reduces opioid-withdrawal symptoms, possibly by inhibiting increases in proinflammatory cytokines. METHODS: A randomized, placebo-controlled clinical trial was conducted utilizing two different study designs (entirely outpatient, and a combination of inpatient and outpatient) to evaluate the safety and efficacy of pioglitazone as an adjunct medication for people with opioid physical dependence undergoing a buprenorphine taper. Participants were stabilized on buprenorphine/naloxone (sublingual, up to 16/4 mg/day), then randomized to receive oral pioglitazone (up to 45 mg/day) or placebo before, during, and after buprenorphine taper. Outcome measures included the Subjective Opiate Withdrawal Scale (SOWS) and Clinical Opiate Withdrawal Scale, use of rescue medications to alleviate opioid withdrawal symptoms, and opioid-positive urine specimens. Cerebrospinal fluid (CSF) and plasma were collected during the taper in a subset of participants for measurement of proinflammatory cytokines. RESULTS: The clinical trial was prematurely terminated due to slow enrollment; 40 participants per group were required for adequate statistical power to test study hypotheses. Twenty-four participants enrolled; 17 received at least one dose of study medication (6 pioglitazone, 11 placebo). SOWS scores were higher in the pioglitazone arm than in the placebo arm after adjusting for use of rescue medications; participants in the pioglitazone arm needed more rescue medications than the placebo arm during the post-taper phase. SOWS scores were positively correlated with monocyte chemoattractant protein-1 (MCP-1) in CSF (r = 0.70, p = 0.038) and plasma (r = 0.77, p = 0.015). Participants having higher levels of plasma MCP-1 reported higher SOWS, most notably after the buprenorphine taper ended. CONCLUSIONS: Results from this study provide no evidence that pioglitazone reduces opioid withdrawal symptoms during buprenorphine taper. High correlations between MCP-1 and opioid withdrawal symptoms support a role of proinflammatory processes in opioid withdrawal. TRIAL REGISTRATION: clinicaltrials.gov identifier: NCT01517165

Whereas substance-use researchers have long combined self-report with objective measures of behavior and physiology inside the laboratory, developments in mobile/wearable electronic technology are increasingly allowing for the collection of both subjective and objective information in participants’ daily lives. For self-report, ecological momentary assessment (EMA), as implemented on contemporary smartphones or personal digital assistants, can provide researchers with near-real-time information on participants’ behavior and mood in their natural environments. Data from portable/wearable electronic sensors measuring participants’ internal and external environments can be combined with EMA (e.g., by timestamps recorded on questionnaires) to provide objective information useful in determining the momentary context of behavior and mood and/or validating participants’ self-reports. Here, we review three objective ambulatory monitoring techniques that have have been combined with EMA, with a focus on detecting drug use and/or measuring the behavioral or physiological correlates of mental events (i.e., emotions, cognitions): (1) collection and processing of biological samples in the field to measure drug use or participants’ physiological activity (e.g, hypothalamic-pituitary-adrenal axis activity); (2) global positioning system (GPS) location information to link environmental characteristics (disorder/disadvantage, retail drug outlets) to drug use and affect; (3) ambulatory electronic physiological monitoring (e.g., electrocardiography) to detect drug use and mental events, as advances in machine learning algorithms make it possible to distinguish target changes from confounds (e.g., physical activity). Finally, we consider several other mobile/wearable technologies that hold promise to be combined with EMA, as well as potential challenges faced by researchers working with multiple mobile/wearable technologies simultaneously in the field.

This study examined how contextual areas defined and operationalized differently may lead to different exposure estimates. Substance users’ exposures to environmental stress (in terms of two variab...