Problematic social media use is associated with depression and similar to behavioral addictions: Physiological and behavioral evidence.

While many studies have examined the relationship between problematic social media use (PSMU) and mental health disorders, little is known about reward responsiveness mechanisms that might be driving this relationship and the neurophysiological characteristics of PSMU. We surveyed 96 undergraduate students at a private liberal arts college in upstate NY. PSMU was assessed using the Social Media Disorder Scale. Fourteen Individuals endorsing in five or more and three or less categories on the Social Media Disorder Scale were offered and underwent resting state QEEG. Mental health was assessed with the Center for Epidemiological Studies Depression Scale Short Form, Social Interaction Anxiety Scale, Penn State Worry Questionnaire, the 10-item Perceived Stress Scale, and a locally developed measure of Substance Use Disorder. Reward and motivational systems were studied using the Brief Sensation Seeking Scale, Behavioral Inhibition/Behavioral Activation Scale, and Temporal Experience of Pleasure Scale. SMDS scores were associated with poorer mental health on all measures except substance use. SMDS scores were positively associated with the behavioral inhibition scale, and the anticipatory pleasure scale. QEEG results revealed a negative association of high PSMU and right central and frontal lobeta, right central beta, and a positive association with frontal alpha asymmetry. The study replicates findings that PSMU is associated with mental health issues. Further the pattern of reward response is different compared with other addictive behaviors. QEEG results are consistent with previous work in substance use and depression.

Being at work improves stress, craving, and mood for people with opioid use disorder: Ecological momentary assessment during a randomized trial of experimental employment in a contingency-management-based therapeutic workplace.

Employment problems are common among people with substance use disorders (SUDs), and improving vocational functioning is an important aspect of SUD treatment. More detailed understanding of the psychosocial benefits of employment may help refine vocational interventions for people with SUDs. Here, we used ecological momentary assessment to measure possible affective improvements associated with work. Participants (n = 161) with opioid use disorder were randomized to work (job-skills training) in a contingency-management-based Therapeutic Workplace either immediately or after a waitlist delay. Throughout, participants responded via smartphone to randomly scheduled questionnaires. In linear mixed models comparing responses made at work vs. all other locations, being at work was associated with: less stress, less craving for opioids and cocaine, less negative mood, more positive mood, and more flow-like states. Some of these differences were also observed on workdays vs. non-workdays outside of work hours. These results indicate that benefits associated with work may not be restricted to being actually in the workplace; however, randomization did not reveal clear changes coinciding with the onset of work access. Overall, in contrast to work-associated negative moods measured by experience-sampling in the general population, Therapeutic Workplace participants experienced several types of affective improvements associated with work.

I feel good? Anhedonia might not mean "without pleasure" for people treated for opioid use disorder.

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).

Impact of CYP2A6 Activity on Nicotine Reinforcement and Cue-Reactivity in Daily Smokers.

INTRODUCTION: Variation in CYP2A6, the primary enzyme responsible for nicotine metabolism, is associated with nicotine dependence, cigarette consumption, and abstinence outcomes in smokers. The impact of CYP2A6 activity on nicotine reinforcement and tobacco cue-reactivity, mechanisms that may contribute to these previous associations, has not been fully evaluated. AIMS AND METHODS: CYP2A6 activity was indexed using 3 genetic approaches in 104 daily smokers completing forced-choice and cue-induced craving tasks assessing nicotine reinforcement and tobacco cue-reactivity, respectively. First, smokers were stratified by the presence or absence of reduced/loss-of-function CYP2A6 gene variants (normal vs. reduced metabolizers). As nicotine metabolite ratio (NMR) is a reliable biomarker of CYP2A6 activity, our second and third approaches used additional genetic variants identified in genome-wide association studies of NMR to create a weighted genetic risk score (wGRS) to stratify smokers (fast vs. slow metabolizers) and calculate a wGRS-derived NMR. RESULTS: Controlling for race and sex, normal metabolizers (vs. reduced) selected a greater proportion of puffs from nicotine-containing cigarettes (vs. denicotinized) on the forced-choice task (p = .031). In confirmatory analyses, wGRS-based stratification (fast vs. slow metabolizers) produced similar findings. Additionally, wGRS-derived NMR, which correlated with actual NMR assessed in a subset of participants (n = 55), was positively associated with the proportion of puffs from nicotine-containing cigarettes controlling for race and sex (p = .015). None of the CYP2A6 indices were associated with tobacco cue-reactivity in minimally deprived smokers. CONCLUSIONS: Findings suggest increased nicotine reinforcement is exhibited by smokers with high CYP2A6 activity, which may contribute to heavier smoking and poorer cessation outcomes previously reported in faster metabolizers. IMPLICATIONS: CYP2A6 activity is a key determinant of smoking behavior and outcomes. Therefore, these findings support the targeting of CYP2A6 activity, either therapeutically or as a clinically relevant biomarker in a precision medicine approach, for tobacco use disorder treatment.

Reward Responsiveness in Patients with Opioid Use Disorder on Opioid Agonist Treatment: Role of Comorbid Chronic Pain.

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 < 0.001, 95% confidence interval [CI]: 0.03 to 0.09) but not in the OUD+CP group (B = 0.03, SE = 0.02, t = 1.90, P = 0.07, 95% CI: -0.002 to 0.07). However, groups did not significantly differ in the rate of change in response bias across blocks (B = 0.03, SE = 0.02, t = 1.21, P = 0.23, 95% CI: -0.02 to 0.07). Groups did not significantly differ on state measures of reward responsiveness (P's ≥0.50). 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.

Craving mediates the association between momentary pain and illicit opioid use during treatment for opioid-use disorder: an ecological momentary assessment study.

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.

The CB1R rs2023239 receptor gene variant significantly affects the reinforcing effects of nicotine, but not cue reactivity, in human smokers.

INTRODUCTION: The cannabinoid CB1 receptor (CB1R) has been shown in preclinical studies to be involved in nicotine reinforcement and relapse-like behavior. The common single nucleotide polymorphism (SNP) rs2023239 may code for an alternative CB1R protein, alter CB1R expression, and be involved in nicotine dependence. To date, no study has explored the relationship between this SNP in CB1R and specific phenotypes of nicotine dependence. METHODS: The current study investigated the influence of CB1R rs2023239 in nicotine reinforcement and craving in regular cigarette smokers. Current smokers (n = 104, cigarettes per day ≥ 10) were genetically grouped (C allele group vs. No C allele group) and underwent laboratory measures of nicotine reinforcement and smoking cue-elicited craving. Nicotine reinforcement was assessed using a forced choice paradigm, while a cue-reactivity procedure measured cue-elicited craving. RESULTS: These results show that smokers with the C allele variant (CC + CT genotypes) experienced a lower nicotine reinforcement effect compared to those without the C allele (TT genotype). These results were similar in both our subjective and behavioral reinforcement measures, though the subjective effects did not withstand controlling for race. There was no difference between genotype groups with respect to cue-elicited craving, suggesting a lack of influence in cue reactivity. CONCLUSION: Taken together, these results suggest that the variation in the CB1R (i.e., rs2023239 SNP) may play a larger role in nicotine reinforcement compared to cue reactivity. This work provides impetus to further understand the physiological mechanisms that explain how CB1Rs influence nicotine dependence phenotypes.

Beyond abstinence and relapse: cluster analysis of drug-use patterns during treatment as an outcome measure for clinical trials.

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.

Prediction of stress and drug craving ninety minutes in the future with passively collected GPS data.

Just-in-time adaptive interventions (JITAIs), typically smartphone apps, learn to deliver therapeutic content when users need it. The challenge is to "push" content at algorithmically chosen moments without making users trigger it with effortful input. We trained a randomForest algorithm to predict heroin craving, cocaine craving, or stress (reported via smartphone app 3x/day) 90 min into the future, using 16 weeks of field data from 189 outpatients being treated for opioid-use disorder. We used only one form of continuous input (along with person-level demographic data), collected passively: an indicator of environmental exposures along the past 5 h of movement, as assessed by GPS. Our models achieved excellent overall accuracy-as high as 0.93 by the end of 16 weeks of tailoring-but this was driven mostly by correct predictions of absence. For predictions of presence, "believability" (positive predictive value, PPV) usually peaked in the high 0.70s toward the end of the 16 weeks. When the prediction target was more rare, PPV was lower. Our findings complement those of other investigators who use machine learning with more broadly based "digital phenotyping" inputs to predict or detect mental and behavioral events. When target events are comparatively subtle, like stress or drug craving, accurate detection or prediction probably needs effortful input from users, not passive monitoring alone. We discuss ways in which accuracy is difficult to achieve or even assess, and warn that high overall accuracy (including high specificity) can mask the abundance of false alarms that low PPV reveals.

Exploring the role of the Ser9Gly (rs6280) Dopamine D3 receptor polymorphism in nicotine reinforcement and cue-elicited craving.

Preclinical studies show that the dopamine D3 receptor (D3R) is involved in the reinstatement of drug seeking and motivation for drugs of abuse. A D3R gene variant, Ser9Gly (rs6280) has been linked to nicotine dependence, yet the mechanisms underlying its involvement in nicotine dependence is unclear. This study investigated the relationship between the Ser9Gly variant and measures of both nicotine reinforcement and cue-elicited craving. Phenotypes of smoking behaviors were assessed in genetically grouped (Glycine vs. No Glycine carriers) current smokers (n = 104, ≥ 10 cigarettes per day). Laboratory measures included a forced choice session (to measure reinforcement of nicotine containing vs. denicotinized cigarettes), and a cue-reactivity session (to measure smoking cues vs. neutral cues elicited craving). The forced choice procedure revealed that subjective ratings were significantly higher in response to nicotinized compared to denicotinized cigarettes; however the Ser9Gly variant did not influence this effect. By comparison, smoking cues elicited greater craving over time compared to neutral cues, and Glycine carriers of the Ser9Gly D3R variant seem to experience a significant blunted cue-elicited craving effect. Results support D3R involvement in nicotine cue reactivity. However, more research is needed to reveal how this gene variant modulates various aspects of nicotine dependence.

Multimodal assessment of sleep in men and women during treatment for opioid use disorder.

BACKGROUND: Sleep disturbance is common in patients with opioid use disorder (OUD) receiving medication for addiction treatment. Differences between patients on the two primary agonist medications-methadone and buprenorphine-are not well understood. METHODS: In patients receiving either methadone or buprenorphine treatment for OUD, we examined sleep continuity and architecture using ambulatory monitoring to gather both an objective measure (daily sleep EEG; M = 5.76 days, SD = 1.46) and a subjective measure (daily sleep diary; M = 54.10 days, SD = 25.10) of sleep. RESULTS: Patients treated with buprenorphine versus methadone did not differ on any measure of sleep continuity or architecture. Women had longer EEG-derived total sleep time than men (d = -0.68, 95 % CI -1.32 to -0.09), along with lower %N2 (d = 0.94, 95 % CI 0.34-1.64) and greater %N3 (d = -0.94, 95 % CI -1.61 to -0.32). Self-reported sleep differed from EEG-derived estimates: wake after sleep onset was greater by EEG than by diary (d = 2.58, 95 % CI 1.74-3.63), and total sleep time and sleep efficiency were lower by EEG than by diary (d for sleep time = 2.93, 95 % CI 2.06-4.14; d for efficiency = 1.69, 95 % CI 0.98-2.49). CONCLUSIONS: Patients treated with buprenorphine or methadone did not substantively differ in ambulatory measures of sleep. With both medications, there was a discrepancy between objective and subjective sleep measures. Further confirmatory evidence would inform the development of sleep-related recommendations for OUD patients undergoing agonist treatment.

Sleep reductions associated with illicit opioid use and clinic-hour changes during opioid agonist treatment for opioid dependence: Measurement by electronic diary and actigraphy.

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.

Stress, craving and mood as predictors of early dropout from opioid agonist therapy.

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.

End-of-day reports of daily hassles and stress in men and women with opioid-use disorder: Relationship to momentary reports of opioid and cocaine use and stress.

BACKGROUND AND AIMS: Stress can be validly assessed "live" or by a summary evaluation of the very recent past. Using smartphone-based ecological momentary assessment (EMA) combined with end-of-day (EOD) entries, we assessed the association between daily hassles, stressful events and use of opioids and cocaine, in opioid- and cocaine-using men and women. METHODS: For up to 16 weeks, 161 outpatients in opioid-agonist treatment who reported cigarette smoking carried smartphones on which they reported stressful events (SEs) and drug use (DU) and completed an EOD questionnaire to report hassles encountered throughout the day, current perceived stress, cigarettes/day, and current mood. We compared EOD responses on days with and without SE and DU reports and on days when thrice-weekly urine drug screens indicated opioid or cocaine use or abstinence. RESULTS: Participants (N = 161) made 11,544 EOD entries; EMA SEs were reported on 861 (7.5%) days, and DUs on 1685 (14.6%) days. The most frequently reported hassles in EOD entries were "not enough money" (31.4% of daily reports) and maintaining abstinence (18.7%). Total EOD hassles showed small but statistically significant associations [odds ratios (95% CIs)] with EMA SEs [1.09 (1.06-1.13)], DUs [1.08 (1.06-1.10)], and urine-positive opioid [1.06 (1.04-1.09)] and cocaine [1.03 (1.00-1.06)] results. Men and women had similar rates (mean/day (SD)) of hassles: men 2.25 (3.55); women 2.55 (3.76) (F1,159 = 0.53, p = 0.47). CONCLUSIONS: Daily hassles, reported at the end of the day, are associated with both same-day stressful events and drug use. Monitoring hassles and devising specific coping strategies might be useful therapeutic targets.

Testing the PPAR hypothesis of tobacco use disorder in humans: A randomized trial of the impact of gemfibrozil (a partial PPARα agonist) in smokers.

Previous pre-clinical studies demonstrated a promising role of alpha-type peroxisome proliferator-activated receptors (PPARα) agonists in decreasing nicotine self-administration and nicotine-seeking behavior in animals. Our goal was to investigate the potential of gemfibrozil, a PPARα agonist, on reducing tobacco smoking in humans. METHODS: This was a double-blind, placebo-controlled, crossover study evaluating the effects of gemfibrozil (1200 mg/day) on smoking in 27 treatment-seeking smokers. The study had two 2-week phases separated by a washout period of at least 1 week. In each phase and after 1 week on medication, participants underwent a lab session where cue reactivity and forced choice paradigms were conducted. Physiological responses and self-reported craving were monitored during the presentation of smoking and neutral cues. In addition, two types of cigarettes were used in the forced choice paradigms: the Nicotinized cigarettes (Nic) and the Denicotinized cigarettes (Denic). The goal of the forced choice was to calculate the percentage of choice of Nic cigarettes while taking gemfibrozil or placebo. The number of quit days was calculated during the two quit attempts weeks (one while taking gemfibrozil and one while taking placebo) of the study. RESULTS: There were no significant differences between gemfibrozil and placebo groups in the percentage of choice of Nic cigarettes, the cue-reactivity (both physiological and subjective measures), or in the number of days of abstinence. CONCLUSIONS: Although preclinical studies with PPAR α agonists showed promising results, this preliminary study did not demonstrate positive effect of gemfibrozil on tobacco use and cessation indices.

Before and after: craving, mood, and background stress in the hours surrounding drug use and stressful events in patients with opioid-use disorder.

RATIONALE: Ecological momentary assessment (EMA) of specific events usually focuses more on antecedents and concomitants than on aftermaths. OBJECTIVES: To examine mental state both before and after discrete episodes of stress and drug use. METHODS: For up to 16 weeks, outpatients on opioid-agonist treatment carried smartphones on which they initiated entries for stressful events (SEs) or lapses to drug use (DUs), and thrice daily when randomly prompted (RPs). Participants rated their stress, opioid craving, cocaine craving, and moods. RP entries within 5 h of an event were analyzed and compared to other RPs. RESULTS: Stress, negative mood, and craving were generally higher before and after DUs and SEs compared to background levels in participants with at least one DU (n = 149) or SE (n = 158). Before DUs, there were increases in negative mood, opioid craving, and cocaine craving, but not background stress. Before SEs, there were increases in background stress, opioid craving, and cocaine craving, but not negative mood. These changes were more variable after events than before. Neither DUs nor SEs were significantly related to positive mood. CONCLUSIONS: Stress increased before stressful-event entries, but was less evident before drug use. Craving increased in the hours before drug use and stressful events-and remained elevated in the hours after either event. These results suggest a stronger link between drug use and craving than between drug use and stress. Lapses to drug use did not improve mood or reduce stress, at least not at our 1-h-bin time resolution, suggesting that if such benefits exist, they are brief.

Using ecological momentary assessment to examine the relationship between craving and affect with opioid use in a clinical trial of clonidine as an adjunct medication to buprenorphine treatment.

BACKGROUND: In a recent clinical trial (NCT00295308), we demonstrated that clonidine decreased the association between opioid craving and moderate levels of stress and affect in patients receiving buprenorphine-based opioid agonist therapy. OBJECTIVES: To examine the relationship between illicit opioid use and craving and affect during the evaluation of clonidine as an adjunct medication in buprenorphine treatment for opioid use disorder. Secondarily, to examine whether those relationships are driven by within- or between-participant factors. METHODS: This was a secondary data analysis from our original trial. Participants (N = 108, female: n = 23, male n = 85) receiving buprenorphine were randomized to receive adjunct clonidine or placebo. Participants used portable electronic devices to rate stress, mood, and craving via ecological momentary assessment (EMA) four times randomly each day. To associate the EMA data with illicit opioid use, each EMA report was linked to participants' next urine drug screen (thrice weekly). We used generalized linear mixed models to examine the interaction between treatment group and illicit opioid use, as well as to decompose the analysis into within- and between-participant effects. RESULTS: Craving for opioids and cocaine was increased when participants were using illicit opioids; this effect was greater in the clonidine group. For affect, mood was poorer during periods preceding opioid-positive urines than opioid-negative urines for clonidine-treated participants, whereas there was no difference for placebo participants. CONCLUSION: This secondary analysis provides evidence that for participants maintained on opioid agonist therapy, clonidine minimized the behavioral impact of moderate levels of negative affect and craving.

Sex differences in daily life stress and craving in opioid-dependent patients.

BACKGROUND: Responses to stress and drug craving differ between men and women. Differences in the momentary experience of stress in relation to craving are less well-understood. OBJECTIVES: Using ecological momentary assessment (EMA), we examined sex differences in real-time in two areas: (1) causes and contexts associated with stress, and (2) the extent to which stress and drug cues are associated with craving. METHODS: Outpatients on opioid-agonist treatment (135 males, 47 females) reported stress, craving, and behavior on smartphones for 16 weeks. They initiated an entry each time they felt more stressed than usual (stress event) and made randomly prompted entries 3 times/day. In stress-event entries, they identified the causes and context (location, activity, companions), and rated stress and craving severity. RESULTS: The causes reported for stress events did not differ significantly by sex. Women reported arguing and being in a store more often during stress events, and men reported working more often during stress events, compared to base rates (assessed via random prompts). Women showed a greater increase in opioid craving as a function of stress (p < 0.0001) and had higher stress ratings in the presence of both stress and drug cues relative to men (p < 0.01). Similar effects were found for cocaine craving in men (p < 0.0001). CONCLUSION: EMA methods provide evidence based on real-time activities and moods that opioid-dependent men and women experience similar contexts and causes for stress but differ in stress- and cue-induced craving. These findings support sex-based tailoring of treatment, but because not all participants conformed to the overall pattern of sex differences, any such tailoring should also consider person-level differences.

Exacerbated Craving in the Presence of Stress and Drug Cues in Drug-Dependent Patients.

In addiction, risk factors for craving and use include stress and drug-related cues. Stress and cues have additive or more-than-additive effects on drug seeking in laboratory animals, but, surprisingly, seem to compete with one another (ie, exert less-than-additive effects) in human laboratory studies of craving. We sought heretofore elusive evidence that human drug users could show additive (or more-than-additive) effects of stress and cues on craving, using ecological momentary assessment (EMA). Outpatients (N=182) maintained on daily buprenorphine or methadone provided self-reports of stress, craving, mood, and behavior on electronic diaries for up to 16 weeks. In three randomly prompted entries (RPs) per day, participants reported the severity of stress and craving and whether they had seen or been offered opioids, cocaine, cannabis, methamphetamine, alcohol, or tobacco. In random-effects models controlling for between-person differences, we tested effects of momentary drug-cue exposure and stress (and their interaction) on momentary ratings of cocaine and heroin craving. For cocaine craving, the Stress × Cue interaction term had a positive mean effect across participants (M=0.019; CL95 0.001-0.036), denoting a more-than-additive effect. For heroin, the mean was not significantly greater than 0, but the confidence interval was predominantly positive (M=0.019; CL95 -0.007-0.044), suggesting at least an additive effect. Heterogeneity was substantial; qualitatively, the Stress × Cue effect appeared additive for most participants, more than additive for a sizeable minority, and competitive in very few. In the field, unlike in human laboratory studies to date, craving for cocaine and heroin is greater with the combination of drug cues and stress than with either alone. For a substantial minority of users, the combined effect may be more than additive.