Search

Abstract Background Legal-involved veterans with opioid use disorder (OUD) have lower receipt of medications for opioid use disorder (MOUD) than other veterans served at the Veterans Health Administration (VHA). This qualitative study examined the influence of the criminal justice system on access to MOUD for legal-involved veterans in the U.S. Methods VHA facilities (n = 14) that varied in their provision of MOUD to legal-involved veterans were selected for qualitative interviews. Interviewees included legal-involved veterans (n = 18), VHA Veterans Justice Programs Specialists (n = 15), substance use disorder treatment providers (n = 5), and criminal justice staff (n = 12). Team members applied codes to meaningful units of analysis (quotations) in the transcribed interviews. Using a matrix approach, team members created a spreadsheet matrix with codes, facility rate of MOUD, and relevant quotations summarized for each participant. Themes and connections between individual participants and cross-interview concepts were explored. Participants were not asked to provide feedback on the findings. Results Themes identified were as follows: (1) Veterans Treatment Court policies both enhanced and limited MOUD treatment access and utilization among participants; (2) cross-system collaboration strengths and challenges existed; and (3) criminal justice system treatment preferences and policies both enhanced and limited MOUD in jails and prisons. Conclusions The influence of the criminal justice system on MOUD has led to variable access to MOUD for legal-involved veterans. Our findings can help inform recommendations to enhance access to MOUD for veterans within the criminal justice system, including the development of a national database of MOUD education materials for Veterans Treatment Courts, strengthening community-court relationships, allowing individuals to use their own healthcare coverage within jails and prisons and extend Medicaid coverage into criminal justice settings, and applying national quality measures for MOUD to criminal justice settings and develop a national system for tracking these quality measures.

Abstract Background Few studies have examined the effectiveness of telephone smoking cessation interventions by severity of behavioral health symptoms. Using data from a telephone counseling study, we examined whether abstinence rates varied by level of behavioral health symptoms. Methods The parent study recruited adults who smoke cigarettes (N = 577) referred by mental health providers at six Veterans Health Administration facilities. Participants were randomized to specialized telephone counseling (intervention) or state Quitline referral (control). Participants completed assessments at baseline and 6 months, including the BASIS-24, a self-report measure of behavioral health symptoms and functioning. We used the BASIS-24 median to dichotomize participants as having high or low scores. The primary outcome was 30-day self-reported abstinence at 6 months. We compared groups on outcomes by logistic regression and performed an interaction effect analysis between treatment assignment and groups. Results At baseline, those with high behavioral health symptoms scores reported heavier nicotine dependence and more sedative and/or antidepressant use, compared to participants with low behavioral health symptoms. At 6 months, participants with low behavioral health symptoms scores in the intervention reported higher rates of 30-day abstinence compared to those in the control arm (26% vs 13%, OR = 2.3, 95% CI = 1.8, 2.9). People with high behavioral health symptoms scores reported no difference in 30-day abstinence between the treatment assignments at 6 months (12% vs. 13%, OR = 1.1, 95% CI = 0.6, 2.0). Conclusions Only participants with low behavioral health symptoms scores reported higher abstinence rates in the intervention compared to the state Quitline. Future research can examine alternative approaches for people with worse mental well-being and functioning. Trial registration The parent study is registered at www.clinicaltrials.gov NCT00724308.

Abstract Background Homelessness is a robust social determinant of acute care service utilization among veterans. Although intensive outpatient programs have been developed for homeless veterans who are high utilizers of acute care (“super utilizers”), few scalable programs have been implemented to address their needs. Objective Describe the development and pilot testing of a novel intervention that integrates the roles of a peer and whole health coach (“Peer-WHC”) in coordination with primary care teams to reduce homeless veterans’ frequent use of acute care. Design Single-arm trial in three outpatient primary care clinics at a Veterans Health Administration (VHA) medical center; pre/post design using mixed-methods. Participants Twenty veterans from VHA’s homeless registry who were super-utilizers of acute care and enrolled in primary care. Intervention Weekly health coaching sessions with a peer over 12 weeks, including discussions of patients’ health care utilization patterns and coordination with primary care. Main measures Rates of session attendance and intervention fidelity, patient-reported satisfaction and changes in patient engagement and perceptions of health, pre/post utilization of acute and supportive care services, and qualitative interviews with multiple stakeholders to identify barriers and facilitators to implementation. Key results On average, patients attended 6.35 sessions (SD = 3.5, Median = 7). Satisfaction scores (M = 28.75 out of 32; SD = 2.79) exceeded a priori benchmarks. Patients’ perceptions of health improved from pre to post [t(df)=-2.26(14), p = 0.04]. In the 3-months pre/post, 45% (n = 9) and 15% (n = 3) of patients, respectively, were hospitalized. Qualitative feedback from patients, providers, and peers and fidelity metrics suggested value in increasing the length of the intervention to facilitate goal-setting with patients and coordination with primary care. Conclusion Findings support the feasibility, acceptability, and utility of Peer-WHC to address the healthcare needs of homeless veterans. A future trial is warranted to test the impact of Peer-WHC on reducing these patients’ frequent use of acute care.

Abstract Background Recovery Colleges are a relatively recent initiative within mental health services. The first opened in 2009 in London and since then numbers have grown. They are based on principles of personal recovery in mental health, co-production between people with lived experience of mental health problems and professionals, and adult learning. Student eligibility criteria vary, but all serve people who use mental health services, with empirical evidence of benefit. Previously we developed a Recovery College fidelity measure and a preliminary change model identifying the mechanisms of action and outcomes for this group, which we refer to as service user students. The Recovery Colleges Characterisation and Testing (RECOLLECT) study is a five-year (2020–2025) programme of research in England. The aim of RECOLLECT is to determine Recovery Colleges’ effectiveness and cost-effectiveness, and identify organisational influences on fidelity and improvements in mental health outcomes. Methods RECOLLECT comprises i) a national survey of Recovery Colleges, ii) a prospective cohort study to establish the relationship between fidelity, mechanisms of action and psychosocial outcomes, iii) a prospective cohort study to investigate effectiveness and cost-effectiveness, iv) a retrospective cohort study to determine the relationship between Recovery College use and outcomes and mental health service use, and v) organisational case studies to establish the contextual and organisational factors influencing fidelity and outcomes. The programme has been developed with input from individuals who have lived experience of mental health problems. A Lived Experience Advisory Panel will provide input into all stages of the research. Discussion RECOLLECT will provide the first rigorous evidence on the effectiveness and cost effectiveness of Recovery Colleges in England, to inform their prioritising, commissioning, and running. The validated RECOLLECT multilevel change model will confirm the active components of Recovery Colleges. The fidelity measure and evidence about the fidelity-outcome relationship will provide an empirically-based approach to develop Recovery Colleges, to maximise benefits for students. Findings will be disseminated through the study website (researchintorecovery.com/recollect) and via national and international Recovery College networks to maximise impact, and will shape policy on how Recovery Colleges can help those with mental health problems lead empowered, meaningful and fulfilling lives.

Abstract Opioid use disorder is one of the most pressing public health problems of our time. Mobile health tools, including wearable sensors, have great potential in this space, but have been underutilized. Of specific interest are digital biomarkers, or end-user generated physiologic or behavioral measurements that correlate with health or pathology. The current manuscript describes a longitudinal, observational study of adult patients receiving opioid analgesics for acute painful conditions. Participants in the study are monitored with a wrist-worn E4 sensor, during which time physiologic parameters (heart rate/variability, electrodermal activity, skin temperature, and accelerometry) are collected continuously. Opioid use events are recorded via electronic medical record and self-report. Three-hundred thirty-nine discreet dose opioid events from 36 participant are analyzed among 2070 h of sensor data. Fifty-one features are extracted from the data and initially compared pre- and post-opioid administration, and subsequently are used to generate machine learning models. Model performance is compared based on individual and treatment characteristics. The best performing machine learning model to detect opioid administration is a Channel-Temporal Attention-Temporal Convolutional Network (CTA-TCN) model using raw data from the wearable sensor. History of intravenous drug use is associated with better model performance, while middle age, and co-administration of non-narcotic analgesia or sedative drugs are associated with worse model performance. These characteristics may be candidate input features for future opioid detection model iterations. Once mature, this technology could provide clinicians with actionable data on opioid use patterns in real-world settings, and predictive analytics for early identification of opioid use disorder risk.

Abstract Introduction: Behavioral health treatment disparities by race and ethnicity are well documented across the criminal legal system. Despite criminal legal settings such as drug treatment courts (DTCs) increasingly adopting evidence-based programs (EBPs) to improve care, there is a dearth of research identifying strategies to advance equitable implementation of EBPs and reduce racial/ethnic treatment disparities. This paper describes an innovative approach to identify community- and provider-generated strategies to support equitable implementation of an evidence-based co-occurring mental health and substance use disorder intervention, called Maintaining Independence and Sobriety through Systems Integration, Outreach and Networking-Criminal Justice (MISSION-CJ), in DTCs. Methods/design: Guided by the Health Equity Implementation Framework, qualitative interviews and surveys will assess factors facilitating and hindering equitable implementation of MISSION-CJ in DTCs among 30 Black/African American and/or Hispanic/Latino persons served and providers. Concept mapping with sixty Black/African American and/or Hispanic/Latino persons served and providers will gather community- and provider-generated strategies to address identified barriers. Finally, an advisory board will offer iterative feedback on the data to guide toolkit development and inform equitable implementation of MISSION-CJ within DTCs. Conclusions: The paper illustrates a protocol of a study based in community-engaged research and implementation science to understand multilevel drivers of racial/ethnic disparities in co-occurring disorder treatment and identify opportunities for intervention and improvements within criminal legal settings.

Prescription opioid use is a risk factor for the development of opioid use disorder. Digital solutions, including wearable sensors, represent a promising opportunity for health monitoring, risk stratification and harm reduction in this treatment space. However, data on their usability and acceptability in individuals using opioids is limited. To address this gap, factors that impact usability and acceptability of wearable sensor-based opioid detection were qualitatively studied in participants enrolled in a wearable sensor-based opioid monitoring research study. At the conclusion of the monitoring period, participants were invited to take part in semi-structured interviews developed based on the technology acceptance model. Thematic analysis was conducted first using deductive, then inductive coding strategies. Forty-four participants completed the interview; approximately half were female. Major emergent themes include sensor usability, change in behavior and thought process related to sensor use, perceived usefulness in sensor-based monitoring, and willingness to have opioid use patterns monitored. Overall acceptance for sensor-based monitoring was high. Aesthetics, simplicity, and seamless functioning were all reported as key to usability. Perceived behavior changes related to monitoring were infrequent while perceived usefulness in monitoring was frequently projected onto others, requiring careful consideration regarding intervention development and targeting. Specifically, care must be taken to avoid stigma associated with opioid use and implied misuse. The design of sensor systems targeted for opioid use must also consider the physical, social, and cognitive alterations inherent in the respective disease processes compared to routine daily life.

BackgroundSubstance use disorder (SUD), mental health disorders (MHD), and co-occurring mental health and substance use disorders are common among criminal justice populations. Digital health interventions (DHI) represent an opportunity to expand co-occurring disorder treatment for justice involved populations, but efficacy data are lacking.ObjectivesThe current scoping review aims to address this gap via following objectives: (1) Describe trends involving DHIs for MHD, SUD, or co-occurring disorders studied in criminal justice settings; and (2) review available evidence for the impact of DHIs on criminal justice-, substance-, and mental health-related outcomes.MethodsPubMed was searched for relevant articles that met the follow inclusion criteria: (1) focus on criminal justice-involved individuals; (2) description of an intervention focused on SUD, MHD, or co-occurring disorders; and (3) use of DHI. Articles were assessed using standardized data abstraction and quality assessment tools.ResultsFour-hundred unique articles were identified on initial search, and 19 were included in the final review. The most common focus of the intervention was SUDs. The most common modalities were telehealth and computer assisted interventions, with most utilized as an adjunct to treatment as usual. No DHIs used wearable devices, and one included justice involved youth. Feasibility and acceptability were high, and the studies that measured substance and mental health-related outcomes reported equivocal or positive results. No studies focused on long-term justice-related outcomes.ConclusionsLiterature on DHIs for criminal justice involved populations diagnosed with SUD, MHD and co-occurring disorders is limited, and largely focuses on telehealth or eHealth, with less data on mHealth approaches. Future research should focus on the inclusion of diverse populations and include objective monitoring tools.

Abstract Background Moral Reconation Therapy (MRT) is a cognitive-behavioral intervention aimed at reducing risk for criminal recidivism by restructuring antisocial attitudes and cognitions (i.e., “criminogenic thinking”). MRT has empirical support for reducing risk for criminal recidivism among civilian offenders. Recently, a version of MRT was developed for military veterans; however, no randomized controlled trials (RCT) have been conducted with the veteran-specific protocol, and the effectiveness and implementation potential of MRT outside of correctional settings has not been established. Methods Using a Hybrid Type 1 RCT design, this study will test the effectiveness of MRT to reduce risk for criminal recidivism and improve health-related outcomes among justice-involved veterans entering mental health residential treatment at three US Veterans Health Administration (VHA) Medical Centers. Upon admission to the treatment program, justice-involved veterans will complete a baseline assessment, be randomized to usual care (UC) or UC + MRT, and be followed 6 and 12 months post-baseline. A process evaluation will also be conducted to identify barriers and facilitators to implementation of MRT in residential treatment. Discussion The primary aim of this study is to evaluate the effectiveness of MRT with justice-involved veterans. If MRT proves effective in this trial, the findings can provide large healthcare systems that serve veterans with an evidence-based intervention for addressing criminogenic thinking among justice-involved adults, as well as guidance on how to facilitate future implementation of MRT in non-correctional settings. Trial registration This trial is funded by the VA Health Services Research & Development Program (IIR 14–081) and is registered with ClinicalTrials.gov (ID: NCT02524171).

Abstract Background Approximately 600,000 persons are released from prison annually in the United States. Relatively few receive sufficient re-entry services and are at risk for unemployment, homelessness, poverty, substance abuse relapse and recidivism. Persons leaving prison who have a mental illness and/or a substance use disorder are particularly challenged. This project aims to create a peer mentor program to extend the reach and effectiveness of reentry services provided by the Department of Veterans’ Affairs (VA). We will implement peer support for reentry veterans sequentially in two states. Our outcome measures are 1) fidelity of the intervention, 2) linkage to VA health care and, 3) continued engagement in health care. The aims for this project are as follows: (1) Conduct contextual analysis to identify VA and community reentry resources, and describe how reentry veterans use them. (2) Implement peer-support, in one state, to link reentry veterans to Veterans’ Health Administration (VHA) primary care, mental health, and SUD services. (3) Port the peer-support intervention to another, geographically, and contextually different state. Design This intervention involves a 2-state sequential implementation study (Massachusetts, followed by Pennsylvania) using a Facilitation Implementation strategy. We will conduct formative and summative analyses, including assessment of fidelity, and a matched comparison group to evaluate the intervention’s outcomes of veteran linkage and engagement in VHA health care (using health care utilization measures). The study proceeds in 3 phases. Discussion We anticipate that a peer support program will be effective at improving the reentry process for veterans, particularly in linking them to health, mental health, and SUD services and helping them to stay engaged in those services. It will fill a gap by providing veterans with access to a trusted individual, who understands their experience as a veteran and who has experienced justice involvement. The outputs from this project, including training materials, peer guidebooks, and implementation strategies can be adapted by other states and regions that wish to enhance services for veterans (or other populations) leaving incarceration. A larger cluster-randomized implementation-effectiveness study is planned. Trial registration This protocol is registered with clinicaltrials.gov on November 4, 2016 and was assigned the number NCT02964897 .

Homelessness is poorly captured in most administrative data sets making it difficult to understand how, when, and where this population can be better served. This study sought to develop and validate a classification model of homelessness. Our sample included 5,050,639 individuals aged 11 years and older who were included in a linked dataset of administrative records from multiple state-maintained databases in Massachusetts for the period from 2011-2015. We used logistic regression to develop a classification model with 94 predictors and subsequently tested its performance. The model had high specificity (95.4%), moderate sensitivity (77.8%) for predicting known cases of homelessness, and excellent classification properties (area under the receiver operating curve 0.94; balanced accuracy 86.4%). To demonstrate the potential opportunity that exists for using such a modeling approach to target interventions to mitigate the risk of an adverse health outcome, we also estimated the association between model predicted homeless status and fatal opioid overdoses, finding that model predicted homeless status was associated with a nearly 23-fold increase in the risk of fatal opioid overdose. This study provides a novel approach for identifying homelessness using integrated administrative data. The strong performance of our model underscores the potential value of linking data from multiple service systems to improve the identification of housing instability and to assist government in developing programs that seek to improve health and other outcomes for homeless individuals.