Objective Neighborhood-Level Disorder Versus Subjective Safety as Predictors of HIV Transmission Risk and Momentary Well-Being.

Mental health and HIV risk behavior have been studied with ecological momentary assessment (EMA), but this approach has not been combined with tracking of activity space (where people go and what they encounter there) in people with HIV and their social relations, who may be HIV+ or HIV-. Activity space represents a modifiable risk or protective factor for behavior related to health status and quality of life, in both clinical and nonclinical populations. We conducted an observational study with 286 participants (243 HIV+ and 43 HIV-), roughly matched for socioeconomic status and neighborhood of residence via three waves of snowball sampling. Each participant carried a smartphone for up to 4 weeks, making 5 randomly prompted entries and 1 end-of-day entry each day, plus self-initiated event-contingent entries for sexual activity and drug use. Responses to randomly prompted items provided subjective evaluations of the safety of the participant's current social and physical environment (the place they were and the people they were with). GPS-based location tracking-coupled with publicly available statistic indicating neighborhood-level physical disorder and socioeconomic disadvantage-provided an indicator of each participant's exposure to objective psychosocial hazard. We examined possible relationships of these objective and subjective environmental exposures with risky sexual and intravenous drug-use behavior, knowledge and utilization of antiretroviral treatment and prophylaxis, and momentary mental health (mood and stress, which relate to risky behavior and overall well-being). We found that both risky behavior and mental health were more related to participants' subjective evaluations of their activity space than to objective measures of neighborhood-level disorder, suggesting that, even within an objectively hazardous neighborhood, people who find a niche they perceive as socially and physically safe may engage in less risky behavior and have better well-being.Trial registration Clinicaltrials.gov Identifier NCT01571752.

Health Outcomes by Neighborhood (HON): Effects of Neighborhood, Social Instability, and Health Factors on 12-Month Trajectories of Substance-Use Disorder Symptoms.

BACKGROUND: Previous studies have shown that environment and health can influence drug use trajectories and the effects of substance use disorder (SUD) treatments. We hypothesized that trajectories of drug use-related problems, based on changes in DSM-5 symptoms, would vary by type(s) of drugs used, health factors, and neighborhood characteristics. METHODS: We assessed mental and physical health, stress, social instability, neighborhood characteristics (disorderliness and home value), and DSM-5 symptom counts at two study visits, 12 months apart, in a community sample (baseline N = 735) in Baltimore, MD. Three prominent categories of drug-use trajectory were identified with K-means cluster analysis of symptom counts: Persistent (4 or more symptoms at both visits or at Visit 2), Improved (decrease from 4 or more symptoms at Visit 1 to 3 or fewer symptoms at Visit 2), and Low-Stable (3 or fewer symptoms at both visits). Baseline health and neighborhood measures were tested as predictors of trajectory in mediation and moderation models. RESULTS: Among people with current opioid- and/or stimulant-use, odds of an Improved trajectory were (1) decreased with neighborhood disorder and social instability, or (2) increased with home value and social instability. Odds of a Low-Stable trajectory were decreased by social instability and stress but increased in those who were older or self-identified as white. CONCLUSIONS: Trajectories of drug use-related problems are influenced by sociodemographic variables, neighborhood factors, and health. Assessing DSM-5 symptom counts as an outcome measure may be valuable in monitoring or predicting long-term trajectories and treatment effectiveness.

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.

Effects of sex and remifentanil dose on rats' acquisition of responding for a remifentanil-conditioned reinforcer.

Opioid-conditioned reinforcement is thought to exacerbate opioid abuse and dependence. Sex/gender can influence opioid abuse behaviors, but the effects of sex/gender on opioid-conditioned reinforcement, specifically, are unclear. In this study, we compared new-response acquisition with opioid-conditioned reinforcement in male and female rats. First, separate groups received response-independent remifentanil injections (0.0-32.0 µg/kg, intravenous) and presentations of a light-noise stimulus. In the experimental groups, injections and stimulus presentations always co-occurred [paired Pavlovian conditioning (PAV)]; in the control groups, the two occurred independently of each other (random PAV). Next, in the instrumental acquisition (ACQ) sessions, two novel nose-poke manipulanda were introduced. All animals (regardless of sex, dose, and PAV type) could respond in the active nose-poke, which produced the stimulus alone, or in the inactive nose-poke. Both males and females dose-dependently acquired nose-poke responding (active>inactive) after paired PAV, but not after random PAV. Therefore, the stimulus was a conditioned reinforcer. We identified three sex differences. First, only females acquired responding after paired PAV with 32.0 µg/kg remifentanil. Second, using a progressive ratio schedule for ACQ, both sexes acquired responding, but females made significantly more active responses. Third, when a single session of PAV was conducted, only males acquired responding. Thus, rats' sex interacts with pharmacological and environmental factors to determine opioid-conditioned reinforcement.

Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.

BACKGROUND AND AIMS: Opioid use disorder (OUD) and opioid dependence lead to significant morbidity and mortality, yet treatment retention, crucial for the effectiveness of medications like buprenorphine-naloxone, remains unpredictable. Our objective was to determine the predictability of 6-month retention in buprenorphine-naloxone treatment using electronic health record (EHR) data from diverse clinical settings and to identify key predictors. DESIGN: This retrospective observational study developed and validated machine learning-based clinical risk prediction models using EHR data. SETTING AND CASES: Data were sourced from Stanford University's healthcare system and Holmusk's NeuroBlu database, reflecting a wide range of healthcare settings. The study analyzed 1800 Stanford and 7957 NeuroBlu treatment encounters from 2008 to 2023 and from 2003 to 2023, respectively. MEASUREMENTS: Predict continuous prescription of buprenorphine-naloxone for at least 6 months, without a gap of more than 30 days. The performance of machine learning prediction models was assessed by area under receiver operating characteristic (ROC-AUC) analysis as well as precision, recall and calibration. To further validate our approach's clinical applicability, we conducted two secondary analyses: a time-to-event analysis on a single site to estimate the duration of buprenorphine-naloxone treatment continuity evaluated by the C-index and a comparative evaluation against predictions made by three human clinical experts. FINDINGS: Attrition rates at 6 months were 58% (NeuroBlu) and 61% (Stanford). Prediction models trained and internally validated on NeuroBlu data achieved ROC-AUCs up to 75.8 (95% confidence interval [CI] = 73.6-78.0). Addiction medicine specialists' predictions show a ROC-AUC of 67.8 (95% CI = 50.4-85.2). Time-to-event analysis on Stanford data indicated a median treatment retention time of 65 days, with random survival forest model achieving an average C-index of 65.9. The top predictor of treatment retention identified included the diagnosis of opioid dependence. CONCLUSIONS: US patients with opioid use disorder or opioid dependence treated with buprenorphine-naloxone prescriptions appear to have a high (∼60%) treatment attrition by 6 months. Machine learning models trained on diverse electronic health record datasets appear to be able to predict treatment continuity with accuracy comparable to that of clinical experts.

Identification and Characterization of ML321: A Novel and Highly Selective D2 Dopamine Receptor Antagonist with Efficacy in Animal Models That Predict Atypical Antipsychotic Activity.

We have developed and characterized a novel D2R antagonist with exceptional GPCR selectivity - ML321. In functional profiling screens of 168 different GPCRs, ML321 showed little activity beyond potent inhibition of the D2R and to a lesser extent the D3R, demonstrating excellent receptor selectivity. The D2R selectivity of ML321 may be related to the fact that, unlike other monoaminergic ligands, ML321 lacks a positively charged amine group and adopts a unique binding pose within the orthosteric binding site of the D2R. PET imaging studies in non-human primates demonstrated that ML321 penetrates the CNS and occupies the D2R in a dose-dependent manner. Behavioral paradigms in rats demonstrate that ML321 can selectively antagonize a D2R-mediated response (hypothermia) while not affecting a D3R-mediated response (yawning) using the same dose of drug, thus indicating exceptional in vivo selectivity. We also investigated the effects of ML321 in animal models that are predictive of antipsychotic efficacy in humans. We found that ML321 attenuates both amphetamine- and phencyclidine-induced locomotor activity and restored pre-pulse inhibition (PPI) of acoustic startle in a dose-dependent manner. Surprisingly, using doses that were maximally effective in both the locomotor and PPI studies, ML321 was relatively ineffective in promoting catalepsy. Kinetic studies revealed that ML321 exhibits slow-on and fast-off receptor binding rates, similar to those observed with atypical antipsychotics with reduced extrapyramidal side effects. Taken together, these observations suggest that ML321, or a derivative thereof, may exhibit ″atypical″ antipsychotic activity in humans with significantly fewer side effects than observed with the currently FDA-approved D2R antagonists.

Anhedonia and Substance Use Disorders by Type, Severity, and With Mental Health Disorders.

OBJECTIVES: Anhedonia can accompany substance use disorders (SUDs); its severity may vary by substance type, severity of SUD symptoms, or psychiatric comorbidity. The goal of this study was to clarify the contribution of each. METHODS: Data were from participants aged 18 to 65 years in the National Epidemiologic Survey on Alcohol and Related Conditions III (n = 30,999; 51% women), a cross-sectional, nationally representative sample reporting lifetime DSM-5 symptoms and lifetime anhedonia. We used logistic regression to test how anhedonia was associated with specific SUDs and psychiatric disorders in respondents with one lifetime diagnosis. We used latent class analysis to assess the association of anhedonia with patterns of comorbidity in all respondents. RESULTS: Opioid use disorder (OUD) had the greatest odds of anhedonia relative to other SUDs (ORs [95% CIs]): mild alcohol use disorder (AUD) ( 3.33 [1.74, 6.38]), moderate/severe AUD ( 2.73 [1.41, 5.30]), and cannabis use disorder ( 3.21 [1.43, 7.19]), though not significantly greater than stimulant use disorder ( 2.44 [.88, 6.73]). Anhedonia was more likely in mood disorders and posttraumatic stress disorder (PTSD) than in any SUD, except for PTSD versus OUD (OR [95% CIs] = .98 [.47, 2.02]). In latent class analysis analyses, the poly disorder class, which included SUDs and other diagnoses, had greater odds of anhedonia than the Poly SUD (ORs [95% CIs] = 1.62 [1.25, 2.09] and AUD 2.89 [2.40, 3.48]) classes. CONCLUSIONS: People with OUD or a lifetime history of mood disorder or PTSD may be most likely to present to SUD treatment with anhedonia.

Variability in intensively assessed mood: Systematic sources and factor structure in outpatients with opioid use disorder.

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; n = 306, person moments = 39,321) systematically vary and covary in outpatients receiving medication for opioid use disorder (MOUD). We used generalizability theory to quantify several aspects of reliability, and multilevel confirmatory factor analysis (MCFA) to detect factor structures within and across people. Generalizability analyses showed that the largest proportion of systematic variance across mood items was at the person level, followed by the person-by-day interaction and the (comparatively small) person-by-moment interaction for items reflecting low arousal. The best-fitting MCFA model had a three-factor structure both at the between- and within-person levels: positive mood, negative mood, and low-arousal states (with low arousal considered as either a separate factor or a subfactor of negative mood). We conclude that (a) mood varied more between days than between moments and (b) low arousal may be worth scoring and reporting separately from positive and negative mood states, at least in a MOUD population. Our three-factor structure differs from prior analyses of mood; more work is needed to understand the extent to which it generalizes to other populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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.

Quality of life during a randomized trial of a therapeutic-workplace intervention for opioid use disorder: Web-based mobile assessments reveal effects of drug abstinence and access to paid work.

Background: Employment and improved quality of life (QOL) are, separately, valued outcomes of substance use disorder (SUD) treatment. It is also important to understand QOL changes caused by employment itself; therefore, we assessed QOL during a randomized trial of a contingency-management-based Therapeutic Workplace for people with opioid use disorder. Methods: For 12 weeks, participants (n = 61) responded to QOL questionnaires in a mobile web app accessed with study-issued smartphones. At enrollment, participants were randomized to work in the Therapeutic Workplace immediately (immediate work group, IWG) or after a 3-week waitlist delay (delayed work group, DWG). Once both groups could work, wage-resetting contingencies were introduced for their opiate- and cocaine-urinalysis. Data were analyzed by (1) access to work with and without contingencies and (2) overall urinalysis-verified opiate- and cocaine-abstinence. Results: DWG and/or IWG reported improvements in several QOL areas (sleep, transportation, recreation); however, they also reported increased money-related difficulties and less time spent with friends/family. These changes did not coincide with DWG's work access, but some (more sleep, money-related difficulties) coincided with the urinalysis contingencies. Greater opiate- and/or cocaine-abstinence was also associated with several improvements: sleep, paying bills, time spent with friends/family, and exercising. Surprisingly, intermediate cocaine abstinence was associated with reductions in work-capacity satisfaction and recreation. Conclusions: Participants reported complex QOL differences during their experimental employment and associated with drug abstinence. Future work should help participants address issues that may be relevant to employment generally (e.g., time with friends/family) or contingency management specifically (e.g., money-related issues for non-abstinent participants).

An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches.

As digital technology increasingly informs clinical trials, novel ways to collect study data in the natural field setting have the potential to enhance the richness of research data. Cocaine use in clinical trials is usually collected via self-report and/or urine drug screen results, both of which have limitations. This article examines the feasibility of developing a wrist-worn device that can detect sufficient physiological data (i.e., heart rate and heart rate variability) to detect cocaine use. This study aimed to develop a wrist-worn device that can be used in the natural field setting among people who use cocaine to collect reliable data (determined by data yield, device wearability, and data quality) that is less obtrusive than chest-based devices used in prior research. The study also aimed to further develop a cocaine use detection algorithm used in previous research with an electrocardiogram on a chestband by adapting it to a photoplethysmography sensor on the wrist-worn device which is more prone to motion artifacts. Results indicate that wrist-based heart rate data collection is feasible and can provide higher data yield than chest-based sensors, as wrist-based devices were also more comfortable and affected participants' daily lives less often than chest-based sensors. When properly worn, wrist-based sensors produced similar quality of heart rate and heart rate variability features to chest-based sensors and matched their performance in automated detection of cocaine use events. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02915341.

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).

Beyond abstinence and relapse II: momentary relationships between stress, craving, and lapse within clusters of patients with similar patterns of drug use.

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 min 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.

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.

The chippers, the quitters, and the highly symptomatic: A 12-month longitudinal study of DSM-5 opioid- and cocaine-use problems in a community sample.

BACKGROUND: Individual trajectories of drug use and drug-related problems are highly heterogeneous. There is no standard taxonomy of these trajectories, but one could be developed by defining natural categories based on changes in symptoms of substance-use disorders over time. METHODS: Our study was conducted in a community sample in Baltimore, Maryland. At baseline, all participants were using opioids and/or cocaine, but none were in treatment. Drug use and symptomatology were assessed again at 12 months (N = 115). RESULTS: We defined Quitters as participants who had not used for at least 30 days at follow-up (17%). For the remaining participants, we performed longitudinal cluster analysis on DSM symptom-counts, identifying three trajectory clusters: newly or persistently Symptomatic (40%) participants, Chippers (21.5%) with few symptoms, and Converted Chippers (21.5%) with improved symptom counts. Logistic regression showed that profiles of Quitters did not resemble Chippers, but instead resembled Symptomatic participants, having high probability of disorderly home neighborhood, nonwhite race, and negative mood. Quitters tended to have two protective factors: initiating opioid-agonist treatment during the study (reffect = 0.25, CL95 0.02-0.48) and lack of polydrug use (reffect = 0.25, CL95 0.004-0.49). Converted Chippers tended to be white, with orderly home neighborhoods and less negative mood (reffects 0.24 to 0.31, CL95 0.01-0.54). CONCLUSIONS: Changes in DSM symptomology provided a meaningful measure of individual trajectories. Quitters shared psychosocial characteristics with Symptomatic participants, but not with participants who continued to use with few symptoms. This suggests that Quitters abstained out of necessity, not because their problems were less severe.

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.

A tilted frame deceives the eye and the hand.

A roll-tilted visual frame induced a vertical line to appear roll-tilted in the opposite direction (rod-and-frame illusion). This visual illusion was measured by finding the physical roll-tilt of the line that appeared vertical-visually perceived vertical (VPV). In separate measurements, the roll-tilted visual frame was also found to induce an illusion in the felt orientation of the hand. This manual illusion was measured by setting the orientation of the hand to feel vertical in the presence of the inducing frame (manually perceived vertical-MPV), with distance of the hand from the body as a parameter. The manual illusion was large when the hand/arm was fully extended (60 cm from the body). When the hand was close to the body (in the midfrontal plane), there was no manual illusion. In a third set of measurements, subjects matched the roll-tilt of the hand to a line set by the experimenter to the subject's VPV or to VPV +/- 5 degrees . These manual/visual matches (MVM) were accurate at 60 cm-the distance at which the manual illusion was greatest. In effect, the large manual illusion at this distance tended to compensate for the visual illusion when the subject matched the orientation of the hand to the VPV. However, when the hand was close to the body, where there was no manual illusion, the manual/visual match was poor (no manual illusion to compensate for the visual illusion). The results are discussed in terms of a proximal/distal model that employs a linear weighted sum of influences from body-referenced and visual mechanisms. The model accounts for 61% of the MVM in terms of the inducer's effect on MPV. Considered in isolation, the gross VPV errors in conjunction with the accurate MVM settings with the extended arm might appear to support a theory based on perception/action dissociation. However, that theory cannot explain the dramatic effects of hand-to-body distance. The present results are very similar to those previously reported for the dimension of elevation where hand-to-body distance dependence was also found to modulate visually guided manual behavior.

Combining ecological momentary assessment with objective, ambulatory measures of behavior and physiology in substance-use research.

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 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.

Clonidine Increases the Likelihood That Abstinence Can Withstand Unstructured Time in Buprenorphine-maintained Outpatients.

OBJECTIVE: In a clinical trial examining daily clonidine as an adjunct to buprenorphine treatment for opioid dependence, we found that clonidine increased opioid abstinence and decoupled stress from craving. From a personalized-medicine perspective, the next step is to identify people for whom clonidine would be beneficial. To that end, using data from the same clinical trial, we examined the associations of daily-life activities with treatment success. METHODS: Outpatients (N = 118) received clonidine (0.3 mg/d) or placebo during 18 weeks of buprenorphine treatment. Participants carried a smartphone that randomly prompted them 4 times per day to report their moods and activities. Using generalized linear mixed models, we assessed the likelihoods of different types of daily activity as a function of clonidine versus placebo, days of longest continuous opioid abstinence, and their interaction. RESULTS: Participants in the buprenorphine-only (buprenorphine plus placebo) control group who engaged in more responsibilities (work and child/elder care) had longer streaks of abstinence, whereas those who engaged in more unstructured-time activities had shorter streaks of abstinence. Conversely, for participants in the buprenorphine-plus-clonidine group, longer streaks of abstinence were associated with higher frequencies of activities associated with "unstructured" time. CONCLUSIONS: The study replicates findings that engaging in responsibilities is related to positive treatment outcomes in standard opioid agonist therapy. The pattern of results also suggests that clonidine helped participants engage in unstructured-time activities with less risk of craving or use than they might otherwise have had.