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Veterans with PTSD and SUDs often fail to initiate, or prematurely discontinue, mental health treatment in Veteran Affairs Medical Centers (VAMC). While much is known about clinical characteristics and demographic factors impacting treatment engagement in this population, less is known about the role of social factors. This retrospective study examines primary care-based screening assessment and specialty mental healthcare appointment data in a VAMC, to test whether social factors predict treatment initiation and appointment attendance. Findings reveal veterans were more likely to initiate treatment when (a) those with SUDs (n = 235) reported more frequent negative exchanges with others and (b) those with PTSD (n = 2107) reported more perceived support or being partnered. Those with PTSD who were partnered had higher appointment attendance rates. Findings suggest social factors are relevant to treatment initiation among veterans with PTSD and SUDs and that close others may be helpful in facilitating referrals.

Engagement in mental health treatment is low, which can lead to poor outcomes. We evaluated the efficacy of offering patients financial incentives to increase their mental health treatment engagement, also referred to as contingency management.We meta-analyzed studies offering financial incentives for mental health treatment engagement, including increasing treatment attendance, medication adherence, and treatment goal completion. Analyses were run within a multilevel framework. All study designs were included, and sensitivity analyses were run including only randomized and high-quality studies.About 80% of interventions incentivized treatment for substance use disorders. Financial incentives significantly increased treatment attendance (Hedges' g = 0.49, [0.33, 0.64], k = 30, I2 = 83.14), medication adherence (Hedges' g = 0.95, [0.47, 1.44], k = 6, I2 = 87.73), and treatment goal completion (Hedges' g = 0.61, [0.22, 0.99], k = 5, I2 = 60.55), including completing homework, signing treatment plans, and reducing problematic behavior.Financial incentives increase treatment engagement with medium to large effect sizes. We provide strong evidence for their effectiveness in increasing substance use treatment engagement and preliminary evidence for their effectiveness in increasing treatment engagement for other mental health disorders. Future research should prioritize testing the efficacy of incentivizing treatment engagement for mental health disorders aside from substance use. Research must also identify ways to incentivize treatment engagement that improve functioning and long-term outcomes and address ethical and systemic barriers to implementing these interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Approximately 20.4 million Americans met criteria for a substance use disorder (SUD) in 2019; however, only about 12.2% of persons with an SUD receive specialty care. Telehealth offers alternatives to traditional forms of substance use treatment.To synthesize recent findings on the efficacy of telehealth for SUDs.MEDLINE, Embase, PubMed, and the Cochrane Library from January 2015 through August 2021 (English language only).Randomized controlled trials (RCTs) of adults with a diagnosis of SUD based on theOne investigator abstracted data and assessed study quality, and a second checked for accuracy.This rapid review synthesized evidence from 17 RCTs. Evidence is very uncertain that telehealth provided as videoconference therapy (1 RCT) or web-based cognitive behavioral therapy (CBT) (3 RCTs) has similar effects to in-person therapy for improving abstinence from alcohol or cannabis. Low-strength evidence suggests that web-based CBT has similar effects for improving abstinence in multiple SUDs (2 RCTs). Low-strength evidence suggests that adding supportive text messaging to follow-up care improves abstinence and amount of alcohol per day (2 RCTs) but does not improve emergency department visits or frequency of consumption (2 RCTs). Enhanced telephone monitoring likely reduces readmissions for SUD detoxification compared with usual follow-up alone (1 RCT) but does not reduce days of substance use (low-strength evidence).Narrative synthesis, heterogeneity of telehealth interventions, no assessment of publication bias, and study methodology.Evidence is very uncertain that telehealth is similar to in-person care for SUD outcomes. Limited evidence suggests some benefit of adding telehealth to usual SUD care.U.S. Department of Veterans Affairs Veterans Health Administration.

Individuals with psychiatric disorders often struggle to initiate and engage in treatment. Financial incentives improve treatment engagement, including treatment attendance, medication adherence, and abstinence from substance use. The U.S. Department of Veterans Affairs (VA) recently made the first large-scale, successful effort to implement incentive-based interventions in substance use disorder treatment. Health care systems, including the VA, can increase the impact of these interventions by extending them to target a range of psychiatric disorders, adapting them for specific clinical contexts, using insights from behavioral economics, and partnering with corporations to fund incentives and implement interventions.

Sequential, multiple assignment, randomized trials (SMARTs) compare sequences of treatment decision rules called dynamic treatment regimes (DTRs). In particular, the Adaptive Treatment for Alcohol and Cocaine Dependence (ENGAGE) SMART aimed to determine the best DTRs for patients with a substance use disorder. While many authors have focused on a single pairwise comparison, addressing the main goal involves comparisons of >2 DTRs. For complex comparisons, there is a paucity of methods for binary outcomes. We fill this gap by extending the multiple comparisons with the best (MCB) methodology to the Bayesian binary outcome setting. The set of best is constructed based on simultaneous credible intervals. A substantial challenge for power analysis is the correlation between outcome estimators for distinct DTRs embedded in SMARTs due to overlapping subjects. We address this using Robins’ G-computation formula to take a weighted average of parameter draws obtained via simulation from the parameter posteriors. We use non-informative priors and work with the exact distribution of parameters avoiding unnecessary normality assumptions and specification of the correlation matrix of DTR outcome summary statistics. We conduct simulation studies for both the construction of a set of optimal DTRs using the Bayesian MCB procedure and the sample size calculation for two common SMART designs. We illustrate our method on the ENGAGE SMART. The R package SMARTbayesR for power calculations is freely available on the Comprehensive R Archive Network (CRAN) repository. An RShiny app is available at https://wilart.shinyapps.io/shinysmartbayesr/.

Issues Relapse is a theoretical construct and empirical object of inquiry. It is unclear how relapse is operationalised with regard to the various phases in substance use disorders (SUD). The aim was to investigate relapse operationalisations in SUDs studies after short- and long-term abstinence and remission, recovery and slip/lapse. Approach Systematic review using the following databases: Epistemonikos, Cochrane Central Register of Controlled Trials (CENTRAL and DARE), MEDLINE, EMBASE, Google Scholar, CINAHL, Web of Science and PsycINFO. Search returned 3426 articles, with 276 meeting the following inclusion criteria: empirical study published in English in a peer-reviewed journal; samples meet diagnostic criteria for dependence syndrome or moderate–severe drug use disorder or alcohol use disorder; reports relapse, abstinence, recovery, remission, slip or lapse. Review protocol registration: PROSPERO (CRD42020154062). Key Findings Thirty-two percent of the studies had no definition of ‘relapse’. Most relapse operationalisations were defined according to measure (26%), time (17%), use (26%) and amount and frequency (27%). Of the 16 studies with a follow-up duration of up to 2 years, one (6%) contained a definition of ‘long-term abstinence’. Of the 64 studies with a follow-up duration of more than 2 years, four (6%) contained a definition of ‘long-term abstinence’. Of those, one (2%) mentioned ‘early relapse’ and one (2%) mentioned ‘late relapse’. Implications Future research is needed to explore the possible difference between early and late relapse. Moreover, working to increase consensus on relapse operationalisations in SUD research is warranted. Conclusions We identified no consensus on relapse operationalisations nor agreement on the differentiation between early and late relapse. The clinical utility of current relapse operationalisations seems low and may compromise knowledge accumulation about relapse and implementation of research into treatment.

BACKGROUND Self-efficacy has been proposed as a key predictor of alcohol treatment outcomes and a potential mechanism of success in achieving abstinence or drinking reductions following alcohol treatment. Integrative data analysis, where data from multiple studies are combined for analyses, can be used to synthesize analyses across multiple alcohol treatment trials by creating a commensurate measure and controlling for differential item functioning (DIF) to determine whether alcohol treatments improve self-efficacy. METHOD The current study used moderated nonlinear factor analysis (MNLFA) to examine the effect of treatment on self-efficacy across four different treatment studies (N = 3720; 72.5% male, 68.4% non-Hispanic white). Self-efficacy was measured using the Alcohol Abstinence Self-Efficacy Scale (AASE) in the COMBINE Study (n = 1383) and Project MATCH (n = 1726), and the Drug Taking Confidence Questionnaire (DTCQ) in two studies of Telephone Continuing Care (TEL Study 1: n = 303; TEL Study 2: n = 212). DIF was examined across time, study, treatment condition, marital status, age, and sex. RESULTS We identified 12 items from the AASE and DTCQ to create a commensurate measure of self-efficacy using MNLFA. All active treatments, including cognitive-behavioral treatment, a combined behavioral intervention, medication management, motivation enhancement treatment, telephone continuing care, twelve-step facilitation, and relapse prevention, were associated with significant increases in self-efficacy from baseline to posttreatment that were maintained for up to a year. Importantly, treatment as usual in community settings, which consisted of weekly group therapy that included addiction counseling and twelve-step recovery support, was not associated with significant increases in self-efficacy. CONCLUSIONS Alcohol self-efficacy increases following treatment and numerous evidence-based treatments are associated with significant increases in self-efficacy, which are maintained over time. Community treatment that focuses solely on addiction counseling and twelve-step support may not promote increases in self-efficacy.

PURPOSE OF REVIEW: To provide an update of studies on the effectiveness of digital and telephonic approaches to providing remote continuing care for substance use disorders. RECENT FINDINGS: Effective continuing care can be provided via smartphone apps, text messaging, interactive voice response, and structured telephone counseling. The remote continuing care interventions with the strongest evidence of efficacy are the Addiction Comprehensive Health Enhancement Support System (ACHESS) app and Telephone Monitoring and Counseling (TMC). Positive effects for these intervention on drinking outcomes in patients with alcohol use disorders were replicated in a recent randomized controlled study. SUMMARY: Continuing care is widely believed to be an important component of treatment for substance use disorders, especially for sustaining positive outcomes. However, many individuals do not attend clinic-based continuing care, due to a variety of reasons including competing work and family responsibilities, disabilities, transportation challenges, and recently the COVID 19 pandemic. Remote continuing care, provided via smartphone apps, text messaging, and various telephonic approaches, has been shown to be effective, and could be used to provide continuing care to patients who would otherwise not receive it. Further work is needed to determine how to effectively combine more traditional continuing care with newer digitized and telephonic approaches.

Self-report measures can improve evidence-based assessment practices in substance use disorder treatment, but many measures are burdensome and costly, limiting their utility in community practice and non-specialty healthcare settings. This systematic review identified and evaluated the psychometric properties of brief, free, and readily accessible self-report measures of substance use and related factors.We searched two electronic databases (PsycINFO and PubMed) in May 2021 for published literature on scales, measures, or instruments related to substance use, substance use treatment, and recovery, and extracted the names of all measures. Measures were included if they were: (1) brief (25 items or fewer), (2) freely accessible in a ready-to-use format, and (3) had published psychometric data.An initial search returned 411 measures, of which 73 (18%) met criteria for inclusion. Included measures assessed a variety of substances (e.g., alcohol, nicotine, opioids, cannabinoids, cocaine) and measurement domains (e.g., use, severity, expectancies, withdrawal). Among these measures, 14 (19%) were classified as psychometrically "excellent," 27 (37%) were rated as "good," 32 (44%) were "adequate."Despite the shift toward evidence-based assessment in substance use disorder treatment in the last twenty years, key areas of public health concern are lacking pragmatic, psychometrically valid measures. Among the brief measures we reviewed, less than a fifth met criteria for psychometric "excellence" and most of these instruments fell into one measurement domain: screening for problematic substance use. Future research should focus both on improving the evidence base for existing brief self-report measures and creating new low-burden measures for specific substances and treatment constructs.

In August 2021, leadership within the U.S. Department of Veterans Affairs (VA) and U.S. Department of Defense (DoD) approved a joint clinical practice guideline (CPG) for the management of substance use disorders (SUDs). This synopsis summarizes key recommendations.In March 2020, the VA/DoD Evidence-Based Practice Work Group assembled a team to update the 2015 VA/DoD Clinical Practice Guideline for the Management of Substance Use Disorders that included clinical stakeholders and conformed to the National Academy of Medicine's tenets for trustworthy CPGs. The guideline panel developed key questions, systematically searched and evaluated the literature, created two 1-page algorithms, and distilled 35 recommendations for care using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. This synopsis presents the recommendations that were believed to be the most clinically impactful.The scope of the CPG is broad; however, this synopsis focuses on key recommendations for the management of alcohol use disorder, use of buprenorphine in opioid use disorder, contingency management, and use of technology and telehealth to manage patients remotely.

Issues Recovery is a theoretical construct and empirical object of inquiry. The aim was to review whether outcome measures used in randomised controlled trials of drug treatment reflect a comprehensive conceptualisation of recovery. Approach Systematic review using the following databases: Cochrane Database of Systematic Reviews, Cochrane Controlled Register of Trials, Database of Abstracts of Reviews of Effect, Web of Science, MEDLINE, Embase and PsycINFO. Search returned 6556 original articles and 504 met the following inclusion criteria: randomised controlled trial in English‐language peer‐reviewed journal; sample meets criteria for drug dependence or drug use disorder; reports non‐substance use treatment outcomes. Review protocol registration: PROSPERO (CRD42018090064). Key Findings 3.8% of the included studies had a follow up of 2 years or more. Withdrawal/craving was present in 31.1% of short‐term versus 0% of long‐term studies. Social functioning in 8% of short‐term versus 36.8% of long‐term studies. Role functioning (0.9 vs. 26.3%), risk behaviour (15.6 vs. 36.8%) and criminality (3.8 vs. 21.1%) followed a similar pattern. Housing was not examined short‐term and unregularly long‐term (2.0%). ‘Use of health‐care facilities’, clinical psychological, behavioural factors were frequently reported. Physiological or somatic health (15.2 vs. 10.5%), motivation (14.2 vs. 15.8%) and quality of life (7.1 vs. 0%) were less frequently reported. Conclusion The short time interval of the follow up and lack of information on relevant factors in recovery prevents the development of evidence‐based approaches to improve these factors. Particularly, measures of social and role functioning should be added to reflect an adequate conceptualisation of recovery. publishedVersion

In recent years, there has been increased interest in the development of adaptive interventions across various domains of health and psychological research. An adaptive intervention is a protocolized sequence of individualized treatments that seeks to address the unique and changing needs of individuals as they progress through an intervention program. The sequential, multiple assignment, randomized trial (SMART) is an experimental study design that can be used to build the empirical basis for the construction of effective adaptive interventions. A SMART involves multiple stages of randomizations; each stage of randomization is designed to address scientific questions concerning the best intervention option to employ at that point in the intervention. Several adaptive interventions are embedded in a SMART by design; many SMARTs are motivated by scientific questions that concern the comparison of these embedded adaptive interventions. Until recently, analysis methods available for the comparison of adaptive interventions were limited to end-of-study outcomes. The current article provides an accessible and comprehensive tutorial to a new methodology for using repeated outcome data from SMART studies to compare adaptive interventions. We discuss how existing methods for comparing adaptive interventions in terms of end-of-study outcome data from a SMART can be extended for use with longitudinal outcome data. We also highlight the scientific utility of using longitudinal data from a SMART to compare adaptive interventions. A SMART study aiming to develop an adaptive intervention to engage alcohol- and cocaine-dependent individuals in treatment is used to demonstrate the application of this new methodology. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

BACKGROUND: The goal of this paper is to advance the understanding of mechanisms of action involved in behavioral-driven aftercare interventions for substance use disorders (SUDs) among youth populations. This paper reports data from a study that measured the impact of an aftercare intervention on primary substance use relapse among youth who completed treatment in Los Angeles County for SUDs.(1) The aftercare intervention, Project ESQYIR-Educating and Supporting inQuisitive Youth In Recovery, utilized text messaging to monitor relapse and recovery processes, provide feedback, reminders, support, and education among youth from SUD specialty settings during the initial three-month period following treatment completion. METHOD: Mediational modeling informed by Baron and Kenny was used to examine the extent to which select recovery processes including participation in extracurricular activities and self-help, were impacted by the texting intervention, and if such processes helped sustain recovery and prevent primary substance use relapse.(2) The data come from a two-group randomized controlled pilot study(1) testing the initial efficacy of a mobile health texting aftercare intervention among 80 youth (M(age)= 20.7, SD = 3.5, range: 14-26 years) who volunteered to participate after completing SUD treatment between 2012 and 2013. RESULTS: Among the two recovery processes examined in the mediational modeling, only involvement in extracurricular activities mediated the effects of the texting aftercare intervention on reductions in primary substance use relapse; not self-help participation. CONCLUSION: Findings from this pilot study offer greater understanding about potential recovery-related mechanisms of action of mobile aftercare interventions. Mobile texting was found to promote increased engagement in recovery-related behaviors such as participation in extracurricular activities, which mediated the effects of the mobile aftercare intervention on decreasing primary substance use relapse. Findings suggest mobile approaches may be effective for increasing adherence to a wide-array of recovery behavioral regiments among youth populations challenged by complex behavioral issues.

Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rules which can be used to guide the delivery of a sequence of treatments or interventions that are tailored to the changing needs of the individual. The sequential multiple-assignment randomized trial (SMART) is a research tool which allows for the construction of effective DTRs. We derive easy-to-use formulae for computing the total sample size for three common two-stage SMART designs in which the primary aim is to compare mean end-of-study outcomes for two embedded DTRs which recommend different first-stage treatments. The formulae are derived in the context of a regression model which leverages information from a longitudinal outcome collected over the entire study. We show that the sample size formula for a SMART can be written as the product of the sample size formula for a standard two-arm randomized trial, a deflation factor that accounts for the increased statistical efficiency resulting from a longitudinal analysis, and an inflation factor that accounts for the design of a SMART. The SMART design inflation factor is typically a function of the anticipated probability of response to first-stage treatment. We review modeling and estimation for DTR effect analyses using a longitudinal outcome from a SMART, as well as the estimation of standard errors. We also present estimators for the covariance matrix for a variety of common working correlation structures. Methods are motivated using the ENGAGE study, a SMART aimed at developing a DTR for increasing motivation to attend treatments among alcohol- and cocaine-dependent patients., Supplementary material at https://osf.io/q7zv8/ This version updates funding information not previously included. Text remains the final accepted version of the manuscript in Statistical Methods in Medical Research

Introduction Little is known about the experiences of continuing care workers (CCW) in the implementation of continuing care programs. The current study sought to understand CCWs and supervisor perceptions of the successes and challenges of implementing a telephone-based continuing care intervention following residential alcohol and other drug treatment services. It also aimed to provide recommendations for treatment providers wishing to integrate continuing care into their treatment model, including the resources, training and supervision needs of CCWs. Methods The participants were eight CCWs and two independent supervisors who completed semi-structured interviews. Interview coding and analysis was guided by Iterative Categorisation procedures and an implementation framework. The Consolidated Framework for Implementation Research was used. Results Telephone delivery was advantageous, but even more enhanced, when there was a face-to-face session first to build rapport. Other key successes included CCWs who were confident and competent, as well as a match between the organisation's values and the philosophy of the continuing care program. Key challenges faced by CCWs related to a perceived lack of support from managers, difficulties accessing quiet office spaces and participant disengagement. Discussion and conclusions Interviews revealed several factors that may influence successful delivery of continuing care as part of alcohol and other drug treatment. These included features of the intervention (e.g. telephone delivery, evidence-based content), characteristics of the individual CCWs (e.g. flexibility in delivery of the intervention while maintaining fidelity), organisational culture (e.g. alignment of organisational values with continuing care) and resources (e.g. office space, flexible work schedules).

BACKGROUND AND AIMS Management of alcohol use disorder (AUD) could be enhanced by effective remote treatments. Study tested whether supplementing intensive outpatient programs (IOPs) with continuing care delivered via: (1) telephone, (2) smartphone, or (3) their combination improves outcomes relative to (4) IOP only. Continuing care conditions were also compared. DESIGN Randomized controlled trial of 4 groups with 3, 6, 9, 12, and 18-month follow-ups. SETTING University research center in Philadelphia, Pennsylvania, USA. PARTICIPANTS Participants (N=262) met DSM-V criteria for AUD, were largely male (71%) and African-American (82%). INTERVENTIONS AND COMPARATOR Telephone Monitoring and Counseling (TMC; N=59), Addiction Comprehensive Health Enhancement Support System (ACHESS; N=68), and TMC+ACHESS (N=70) provided for 12 months. The control condition received IOP only (TAU; N=65). MEASUREMENT Primary outcome was percent days heavy drinking (PDHD) in months 1-12. Secondary outcomes were any drinking, any drug use, drinking consequences, and quality of life. FINDINGS Mean PDHD in months 1-12 was 10.29 in TAU, 5.41 in TMC, 6.80 in ACHESS, and 5.99 in TMC+ACHESS. PDHD was lower in TMC (d=.35, p=0.018, 95% confidence interval (CI) = [-1.42, -0.20]), ACHESS (d= .31, p= .031, 95% CI= [-1.27, -0.06]), and TMC+ACHESS (d= .36, p=0.009, 95% CI = [-1.40, -0.20]) than in TAU. Differences between TMC+ACHESS, TMC, and ACHESS were small (d< .06) and non-significant. Findings were inconclusive as to whether or not the treatment conditions differed on PDHD at 18 months. A significant effect was obtained on Any Drinking, which was higher in months 1-12 in TAU than in TMC (odds ratio (OR)= 3.02, standard error (SE)=0.43, 95% CI= [1.30, 6.99], p=0.01) and TMC+ACHESS (OR= 2.43, SE=0.39, 95% CI= [1.12, 5.27], p=0.03). No other significant effects were obtained on other secondary outcomes during or after treatment. CONCLUSIONS A telephone-delivered intervention and a smartphone-delivered intervention, alone and in combination, provided effective remote continuing care for alcohol use disorder. The combination of both interventions was not superior to either alone and effects did not persist post-treatment.

Continuing care is widely believed to be an important component of effective treatment for substance use disorder, particularly for those individuals with greater problem severity. The purpose of this review was to examine the research literature on continuing care for alcohol and drug use disorders, including studies that addressed efficacy, moderators, mechanisms of action, and economic impact. This narrative review first considered findings from prior reviews (published through 2014), followed by a more detailed examination of studies published more recently. The review found that research has generally supported the efficacy of continuing care for both adolescents and adults, but the picture is complex. Reviews find relatively small effects when results from individual studies are combined. However, continuing care of longer duration that includes more active efforts to keep patients engaged may produce more consistently positive results. Moreover, patients at higher risk for relapse may benefit to a greater degree from continuing care. Several newer approaches for the provision of continuing care show promise. These include incentives for abstinence and automated mobile health interventions to augment more conventional counselor-delivered interventions. Primary care can be used to provide medications for opioid and alcohol use disorders over extended periods, although more research is needed to determine the optimal mix of behavioral treatments and other psychosocial services in this setting. Regardless of the intervention selected for use, the status of most patients will change and evolve over time, and interventions need to include provisions to assess patients on a regular basis and to change or adapt treatment when warranted.

The longitudinal cohort study is the gold standard in observational epidemiology. A central challenge with this design is the risk of attrition over time, especially in studies of inaccessible clinical populations, such as individuals with substance use disorder (SUD). Research on individuals who have achieved stable substance use abstinence and functional recovery is scarce. 30 participants from a longitudinal cohort study (the Stayer study), were interviewed concerning their experiences of participation over several years to explore retention factors. Interviewers with first-hand experience of recovery from SUD conducted the interviews. Data were analyzed using a thematic analytic approach within an interpretative–phenomenological framework. The analyses yielded the following themes: (1) Individuals’ substance use: adaptation to slips and relapses in treatment and research, (2) “Show that you care”: Developing working relationships in research with study participants by negotiating expectations flexibly, and (3) “You don’t just make dropouts”: A long-term focus on study participation and treatment can increase retention. Several factors were perceived as relevant to participation in a long-term follow-up study with diverse recovery routes, including working research relationships and explicit contracts allowing follow-up participation, even during periods of drug use. Longitudinal studies could benefit from including such factors in the tracking procedures in addition to more traditional tracking techniques. Clinical services could benefit from developing interventions that use knowledge of long-term recovery processes as non-linear, heterogeneous trajectories, and proactive approaches to motivate recovery.

Dynamic treatment regimens (DTRs), also known as treatment algorithms or adaptive interventions, play an increasingly important role in many health domains. DTRs are motivated to address the unique and changing needs of individuals by delivering the type of treatment needed, when needed, while minimizing unnecessary treatment. Practically, a DTR is a sequence of decision rules that specify, for each of several points in time, how available information about the individual's status and progress should be used in practice to decide which treatment (e.g., type or intensity) to deliver. The sequential multiple assignment randomized trial (SMART) is an experimental design widely used to empirically inform the development of DTRs. Sample size planning resources for SMARTs have been developed for continuous, binary, and survival outcomes. However, an important gap exists in sample size estimation methodology for SMARTs with longitudinal count outcomes. Further, in many health domains, count data are overdispersed - having variance greater than their mean. We propose a Monte Carlo-based approach to sample size estimation applicable to many types of longitudinal outcomes and provide a case study with longitudinal overdispersed count outcomes. A SMART for engaging alcohol and cocaine-dependent patients in treatment is used as motivation., Comment: Key words: dynamic treatment regimen (DTR); longitudinal outcome; overdispersed count; sample size estimation; sequential multiple assignment randomized trial (SMART)

We tested the predictive validity of the Progress Assessment (PA), a brief counselor administered tool for use in measurement-based care for substance use disorders. The PA includes 5 items assessing relapse risk and 5 items assessing factors protective against relapse. Data were drawn from a completed study of continuing care for cocaine dependence (McKay et al., 2013) and includes 12 months of follow-up on158 participants (76% male) who received brief telephone or face-to-face sessions. Each session began with the administration of the PA, followed by cognitive-behavioral counseling tied to the results of the PA and anticipated risky situations. Outcome was assessed via urine toxicology every 3 months. As administered in an effectiveness trial, average PA risk and protective scales within each 3-month segment of the study predicted urine toxicology results at the end of that period, with higher risk scores and lower protective scores predicting greater rates of cocaine positive urine drug screens. PA scores did not predict dropout from continuing care participation. The 10-item PA shows promise as a pragmatic clinical tool for ongoing monitoring during continuing care for substance dependence.

BackgroundA priority area in the field of substance dependence treatment is reducing the rates of relapse. Previous research has demonstrated that telephone delivered continuing care interventions are both clinically and cost effective when delivered as a component of outpatient treatment. This protocol describes a NSW Health funded study that assesses the effectiveness of delivering a telephone delivered continuing care intervention for people leaving residential substance treatment in Australia.Methods/designAll participants will be attending residential alcohol and other drug treatment provided by The Salvation Army or We Help Ourselves. The study will be conducted as a randomised controlled trial, where participants will be randomised to one of three treatment arms. The treatment arms will be: (i) 12-session continuing care telephone intervention; (ii) 4-session continuing care telephone intervention, or (iii) continuing care plan only. Baseline assessment batteries and development of the participants’ continuing care plan will be completed prior to participants being randomised to a treatment condition. Research staff blind to the treatment condition will complete follow-up assessments with participants at 3-months and 6-months after they have been discharged from their residential service.DiscussionThis study will provide comprehensive data on the effect of delivering the continuing care intervention for people exiting residential alcohol and other drug treatment. If shown to be effective, this intervention can be disseminated to improve the rates of relapse among people leaving residential alcohol and other drug treatment.Trial registrationAustralian New Zealand Clinical Trials Registry, ACTRN12618001231235. Registered on 23rd July 2018.https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375621&isReview=true

BackgroundBeing a participant in longitudinal follow-up studies is not commonly a factor considered when investigating useful self-change aspects for individuals attempting recovery from substance use disorder (SUD). This study reports on how ongoing monitoring, and feedback on data results in a longitudinal follow-up study of SUD recovery were perceived by individuals who had achieved long-term abstinence and social recovery.MethodsInterviewers with first-hand experience with the topic conducted interviews with 30 participants and analysed the data using a thematic analytic approach within an interpretative–phenomenological framework.ResultsAnalyses resulted in the following themes. 1) Ongoing short text messaging (SMS) monitoring: helped participants by offering recovery milestones and reminders of the past. 2) Feedback on data results helped participants track physical and cognitive recovery: “I am more like myself”. 3) Using feedback in treatment: understanding the importance of a functional brain to participants may help with long-term retention in treatment.ConclusionsSelf-changes that were challenging to detect on a day-to-day basis were available for reflection through longitudinal study participation, including ongoing monitoring and feedback on the results, allowing personal consolidation of change processes. Clinical services could benefit from continuing development and implementation of such technology for ongoing monitoring and feedback on assessments to motivate self-change in SUD recovery. The development of guidelines for providing the results of research assessments to individuals could help reduce attrition in research projects and support recovery and healthy choices for study participants.

A non-invasive functional-brain-imaging system based on optically-pumped-magnetometers (OPM) is presented. The OPM-based magnetoencephalography (MEG) system features 20 OPM channels conforming to the subject’s scalp. We have conducted two MEG experiments on three subjects: assessment of somatosensory evoked magnetic field (SEF) and auditory evoked magnetic field (AEF) using our OPM-based MEG system and a commercial MEG system based on superconducting quantum interference devices (SQUIDs). We cross validated the robustness of our system by calculating the distance between the location of the equivalent current dipole (ECD) yielded by our OPM-based MEG system and the ECD location calculated by the commercial SQUID-based MEG system. We achieved sub-centimeter accuracy for both SEF and AEF responses in all three subjects. Due to the proximity (12 mm) of the OPM channels to the scalp, it is anticipated that future OPM-based MEG systems will offer enhanced spatial resolution as they will capture finer spatial features compared to traditional MEG systems employing SQUIDs.

Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimensional working models are typically used to estimate certain nuisance parameters, and misspecification of these working models can result in residual confounding and/or efficiency loss. We propose a robust Q-learning approach which allows estimating such nuisance parameters using data-adaptive techniques. We study the asymptotic behavior of our estimators and provide simulation studies that highlight the need for and usefulness of the proposed method in practice. We use the data from the “Extending Treatment Effectiveness of Naltrexone” multi-stage randomized trial to illustrate our proposed methods.

Background In 2011, the Department of Veterans Affairs launched an initiative to expand patients’ access to contingency management (CM) for the treatment of substance use disorders, particularly stimulant use disorder. This study evaluates the uptake and effectiveness of the VA initiative by presenting data on participation in coaching, fidelity to key components of the CM protocol, and clinical outcomes (CM attendance and substance use). Methods Fifty-five months after the first VA stations began offering CM to patients in June 2011, 94 stations had made CM available to 2060 patients. As those 94 VA stations began delivering CM to Veterans, their staff participated in coaching calls to maintain fidelity to CM procedures. As a part of the CM coaching process, those 94 implementation sites provided data describing the setting and structure of their CM programs as well as their fidelity practices. Additional data on patients’ CM attendance and urine test results also were collected from the 94 implementation sites. Results The mean number of coaching calls the 94 programs participated in was 6.5. The majority of sites implemented CM according to recommended standard guidelines and reported high fidelity with most CM practices. On average, patients attended more than half their scheduled CM sessions, and the average percent of samples that tested negative for the target substance was 91.1%. Conclusion The VA’s CM implementation initiative has resulted in widespread uptake of CM and produced attendance and substance use outcomes comparable to those found in controlled clinical trials.

Objective Commitment to change is an innovative potential mediator and mechanism of behavior change (MOBC) that has not been examined in adolescents with substance use disorders (SUD). The Adolescent Substance Abuse Goal Commitment (ASAGC) questionnaire is a reliable and valid 2-scale measure developed to assess the adolescent's commitment to either abstinence or harm reduction (HR) that includes consumption reduction as a stated treatment goal. The objective of this study was to examine the ASAGC's ability to predict alcohol use treatment outcome. Method During sessions three and nine of a 10-week treatment program, therapists completed the ASAGC for 170 adolescents 13–18 years of age with alcohol use disorder (AUD). Drinking behaviors were assessed during and after a continued-care phase until 12-month from study onset. Results Analysis of Variance results indicated that adolescents who reported no alcohol use had significantly higher scores on the commitment to abstinence scale than adolescents who reported alcohol use. None of the ANOVA models were significant for commitment to HR. When treatment outcome was examined, commitment to abstinence consistently predicted number of drinking days, number of heavy drinking days, and the maximum number of drinks post-treatment. In contrast, commitment to HR did not predict any of the drinking outcomes. These results suggest that the more adolescents were committed to abstinence during treatment, the less they used and abused alcohol after treatment completion. Conclusions In addition to the ASAGC's ability to differentiate between commitment to abstinence and commitment to HR, study findings demonstrate that goal commitment consistently predicts AUD treatment outcome.

While continuing care for substance use treatment has been associated with reduced involvement in the criminal justice system, much of this research lacks random assignment to continuing care and so is limited by self-selection bias. This study sought to determine the impact of adding telephone-based continuing care to intensive outpatient programs on criminal justice outcomes for people with cocaine dependence. In three continuing care studies, spanning 1998-2008, participants were randomly assigned to an intensive outpatient program or an intensive outpatient program plus a telephone-based continuing care intervention. Cocaine-dependent participants from these three studies were included in the analyses, with outcomes derived from a dataset of jurisdiction-wide criminal sentences from a state sentencing agency. Multiple logistic regression was employed to examine the odds of a criminal conviction occurring in the 4 years after enrollment in a continuing care study. The results showed that, controlling for a criminal sentence in the previous year, gender, age, and continuing care study, people with cocaine dependence randomized to an intensive outpatient program plus a telephone-based continuing care intervention had 54% lower odds (p = 0.05, odds ratio = 0.46, 95% CI: 0.20-1.02) of a criminal sentence in the 4 years after enrollment in the continuing care study, compared with those randomized to an intensive outpatient program alone. We can conclude that adding telephone monitoring and counseling to intensive outpatient programs is associated with fewer criminal convictions over a 4-year follow-up period compared with intensive outpatient programs alone.

Background New smartphone communication technology provides a novel way to provide personalized continuing care support following alcohol treatment. One such system is the Addiction version of the Comprehensive Health Enhancement Support System (A-CHESS), which provides a range of automated functions that support patients. A-CHESS improved drinking outcomes over standard continuing care when provided to patients leaving inpatient treatment. Effective continuing care can also be delivered via telephone calls with a counselor. Telephone Monitoring and Counseling (TMC) has demonstrated efficacy in two randomized trials with alcohol-dependent patients. A-CHESS and TMC have complementary strengths. A-CHESS provides automated 24/7 recovery support services and frequent assessment of symptoms and status, but does not involve regular contact with a counselor. TMC provides regular and sustained contact with the same counselor, but no ongoing support between calls. The future of continuing care for alcohol use disorders is likely to involve automated mobile technology and counselor contact, but little is known about how best to integrate these services. Methods/Design To address this question, the study will feature a 2 × 2 design (A-CHESS for 12 months [yes/no] × TMC for 12 months [yes/no]), in which 280 alcohol-dependent patients in intensive outpatient programs (IOPs) will be randomized to one of the four conditions and followed for 18 months. We will determine whether adding TMC to A-CHESS produces fewer heavy drinking days than TMC or A-CHESS alone and test for TMC and A-CHESS main effects. We will determine the costs of each of the four conditions and the incremental cost-effectiveness of the three active conditions. Analyses will also examine secondary outcomes, including a biological measure of alcohol use, and hypothesized moderation and mediation effects. Discussion The results of the study will yield important information on improving patient alcohol use outcomes by integrating mobile automated recovery support and counselor contact. Trial registration ClinicalTrials.gov, NCT02681406. Registered on 2 September 2016. Electronic supplementary material The online version of this article (10.1186/s13063-018-2466-1) contains supplementary material, which is available to authorized users.

Introduction and aims Although continuing care programs have been shown to improve alcohol and other drug (AOD) treatment outcomes, uptake of continuing care has been low. The current study aimed to determine predictors of participants’ who both re-confirmed consent to engage in telephone-based continuing care and commenced continuing care once they left residential AOD treatment. These participants had initially consented to partake in continuing care during the course of their residential stay. Methods Participants were 391 individuals (232 males, 59% and 158 females, 40%) accessing therapeutic communities for AOD treatment provided by The Australian Salvation Army and We Help Ourselves (WHOS). Measures at baseline, collected during residential treatment, included demographics, primary substance of concern, abstinence goal, refusal self-efficacy, cravings for substances, mental health diagnoses, psychological distress, quality of life and feelings of loneliness. All measures were used as predictor variables to determine characteristics of participants who re-confirmed consent to engage in continuing care and commenced continuing care following residential AOD treatment. Results Completing residential treatment, being unmarried, and higher levels of loneliness predicted re-confirmation of consent to participate in continuing care following discharge from residential treatment. Participants who were Aboriginal and/or Torres Strait Islander were less likely to provide re-confirmation of consent. Participants were more likely to commence continuing care if they completed residential treatment, were older, and had longer years of substance use. Conclusions Tailoring continuing care programs to reach a broader array of individuals such as Indigenous populations and persons who exit treatment services early is needed to ensure these programs can reach all individuals who might need them.

High dropout rates threaten the validity of longitudinal studies involving participants suffering from substance use disorder (SUD). The objective of this article is to evaluate strategies to improve retention. The data analysis was based on an ongoing study of long-term recovery of neurocognitive and psychosocial functions. We used traditional strategies to enhance the contact rate. Common factors in psychosocial treatments and biweekly Short Message Service (SMS; text messaging) monitoring were added to further increase the contact rate. The participants (n = 146) were recruited from treatment facilities for SUD. Assessments were measured at 3 months, 6 months, 9 months, and 12 months. This study was successful in retaining a cohort of participants who are typically characterized as having a negative prognosis because of their unstable living arrangements and incomes. Compared to those using GHB, addictive medications, and opiates, the retention rate was the lowest among participants with severe alcohol...

Background We estimated the efficacy of the Addiction-Comprehensive Health Enhancement Support System (A-CHESS) in increasing the use of services for addiction and examined the extent to which this use of services mediated the effects of A-CHESS on risky drinking days and abstinence from drinking. Methods We conducted secondary data analyses of the A-CHESS randomized controlled trial. Recruitment occurred in five residential treatment programs operated by two addiction treatment organizations. Participants were 349 adults with alcohol use disorders recruited two weeks before discharge from residential treatment. We provided intervention arm participants with a smartphone, the A-CHESS application, and an 8-month service plan. Control arm participants received treatment as usual. Telephone interviews at 4, 8, and 12-month follow-ups assessed past-month risky drinking days, past-month abstinence, and post-discharge service utilization (past-month outpatient addiction treatment and past-week mutual help including Alcoholics Anonymous and Narcotics Anonymous). Using mixed effects latent variable models, we estimated the indirect effects of A-CHESS on drinking outcomes, as mediated by post-discharge service utilization. Results Approximately 50.5% of participants reported outpatient addiction treatment and 75.5% reported mutual help at any follow-up interview in the year following randomization. Assignment to the A-CHESS intervention was associated with an increased odds of outpatient addiction treatment across follow-ups, but not mutual help. This use of outpatient addiction treatment mediated the effect of A-CHESS on risky drinking days, but not abstinence. The effect of A-CHESS through outpatient addiction treatment appeared to reduce the expected number of risky drinking days across follow-ups by 11%. Conclusions The mobile health (mHealth) intervention promoted the use of outpatient addiction treatment, which appeared to contribute to its efficacy in reducing risky drinking. Future research should investigate how mHealth interventions could link patients to needed treatment services and promote the sustained use of these services.

Intimate partnerships are discouraged during early recovery, despite research that highlights their capacity to be resources for change.This study seeks to provide descriptions of intimate partnerships and how such partnerships challenge and/or support minimizing HIV sex-risk among participants in continuing care for cocaine addiction in order to inform substance use programming.Forty-two recorded continuing care counseling sessions of 33 people who discussed HIV sex-risk behavior were transcribed and analyzed using thematic analysis. This sample was derived from a larger randomized controlled trial that looked at the impact of a continuing care intervention for people with cocaine use problems.Although participants expressed the desire for a primary intimate partnership, casual intimate partnerships that often involved HIV sex-risk behavior were more prevalent. Challenges to having a primary intimate partner included the belief that intimate partnerships do not support recovery, difficulty in developing friendships with women among heterosexual men, and the ubiquity of drug use and sex work in home environments with limited economic opportunity. Despite these challenges, some participants reported having primary intimate partners that supported their recovery through open communication.Clinicians providing substance use interventions can consider encouraging components of intimate partnerships that support recovery. In addition, the strong environmental influence on individual HIV sex-risk behavior should be considered in delivering any substance use intervention.

Background: The perceived benefits of drug use are not currently integrated into the treatment of substance use disorder. This omission appears paradoxical and is unsubstantiated by empirical research. As the perceived benefits of drug use are catalysts for drug initiation, relapse and continuous use, increased knowledge about these benefits seems crucial to efficacious treatment. Aims: To investigate the perceived benefits of drug use in substance use disorder. Method: The study is a phenomenological-hermeneutical investigation using thematic analysis of interviews with 30 long-term recovered adult service users. Results: Our thematic analysis resulted in three themes and several sub-themes: (1) Benefits of drug use; (2) Necessity of intense experiences; and (3) Importance of being unconventional. Conclusions: Findings indicate that the benefits of non-problematic and problematic drug use are motivated by similar individual and social needs. An absolute distinction between problematic and non-problematic drug use thus seems arbitrary and potentially counterproductive for clinical practice. The benefits of drug use should be researched as a possible add-on treatment module, as this knowledge may be of significant clinical value in treatment frameworks. publishedVersion

The purpose of this sequential multiple-assignment randomization treatment pilot study was to examine if (a) adding working memory training to contingency management (CM) for youth with cannabis use disorder (CUD) and (b) switching nonresponding youth to higher magnitude CM incentives boosts outcomes. In Phase 1, youth with CUD (n = 59, M age = 16, male = 71%) attending an intensive outpatient program were randomly assigned to 14 weeks of CM only or CM plus working memory training (WMT). In Week 4, a Phase 2 treatment was assigned. Those with negative urine drug tests (responders) continued in their Phase 1 treatment. Those who were drug positive (nonresponders) were randomly assigned to remain in their Phase 1 treatment or to higher magnitude CM. Zero-inflated negative binomial models comparing those assigned to CM versus CM + WMT indicated no differences in the likelihood of having ≥ 1 week of continuous abstinence or longer abstinence duration. Those assigned to WMT showed greater but nonsignificant improvements in working memory (n = 35; β = .69, p = .06). Working memory improvements were associated with achieving any abstinence (odds ratio = 3.50, 95% CI [1.01, 12.10], p = .05). Phase 2 randomization to higher magnitude CM did not boost outcomes. Overall results suggest that WMT appears promising, but the sample size was small, attrition was high, and replication is important. Alternative strategies should continue to be explored to improve outcomes for adolescent substance use disorders, such as different approaches for nonresponders, tailoring to other baseline or response characteristics, or more robust first-line interventions. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Sequential multiple assignment randomized trials (SMARTs) are a useful and increasingly popular approach for gathering information to inform the construction of adaptive interventions to treat psychological and behavioral health conditions. Until recently, analysis methods for data from SMART designs considered only a single measurement of the outcome of interest when comparing the efficacy of adaptive interventions. Lu and co-workers (2016) proposed a method for considering repeated outcome measurements to incorporate information about the longitudinal trajectory of change. While their proposed method can be applied to many kinds of outcome variables, they focused mainly on linear models for normally distributed outcomes. Practical guidelines and extensions are required to implement this methodology with other types of repeated outcome measures common in behavioral research. In this paper we discuss implementation of this method with repeated binary outcomes. We explain how to compare adaptive interventions in terms of various summaries of repeated binary outcome measures, including average outcome (area under the curve) and delayed effects. The method is illustrated using an empirical example from a SMART study to develop an adaptive intervention for engaging alcohol- and cocaine-dependent patients in treatment. Monte Carlo simulations are provided to demonstrate the good performance of the proposed technique.

Background: Social networks that support recovery lead to enhanced treatment outcomes and sobriety regardless if this support stems from family, peer groups or 12-Step programs. Treatment process f...