Using causal mediation to examine self-efficacy as a mechanism through which continuing care interventions reduce alcohol use.

OBJECTIVE: Understanding the causal mechanisms through which telephone and mobile health continuing care approaches reduce alcohol use can help develop more efficient interventions that effectively target these mechanisms. Self-efficacy for successfully coping with high-risk alcohol relapse situations is a theoretically and empirically supported mediator of alcohol treatment. This secondary analysis aims to examine self-efficacy as a mechanism through which remote-delivered continuing care interventions reduce alcohol use. METHOD: The study included 262 adults (Mage = 46.9, SD = 7.4) who had completed 3 weeks of an intensive outpatient alcohol treatment program. The sample was predominantly male (71%), African American (82%), and completed a high school education (71%). The four-arm randomized clinical trial compared three active continuing care interventions (telephone monitoring and counseling [TMC], addiction comprehensive health enhancement support system [ACHESS], and combined delivery of TMC and ACHESS) to usual care and assessed longitudinal measures of alcohol use and self-efficacy. Analyses employed the potential outcomes framework and sensitivity analyses to address threats to causal inference resulting from an observed mediator variable. RESULTS: Relative to usual care, the two intervention conditions that included TMC reduced alcohol use through improvements to self-efficacy. There was no evidence that self-efficacy mediated the effect of ACHESS on alcohol use. CONCLUSIONS: Based on our findings, self-efficacy is an important mechanism through which telephone continuing care interventions affect alcohol use. Future research to identify which components of TMC influence self-efficacy and factors that mediate ACHESS effects could enhance the effectiveness of remote delivery of continuing care. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effects of Bundling Medication for Opioid Use Disorder With an mHealth Intervention Targeting Addiction: A Randomized Clinical Trial.

OBJECTIVE: Medication for opioid use disorder (MOUD) improves treatment retention and reduces illicit opioid use. A-CHESS is an evidence-based smartphone intervention shown to improve addiction-related behaviors. The authors tested the efficacy of MOUD alone versus MOUD plus A-CHESS to determine whether the combination further improved outcomes. METHODS: In an unblinded parallel-group randomized controlled trial, 414 participants recruited from outpatient programs were assigned in a 1:1 ratio to receive either MOUD alone or MOUD+A-CHESS for 16 months and were followed for an additional 8 months. All participants were on methadone, buprenorphine, or injectable naltrexone. The primary outcome was abstinence from illicit opioid use; secondary outcomes were treatment retention, health services use, other substance use, and quality of life; moderators were MOUD type, gender, withdrawal symptom severity, pain severity, and loneliness. Data sources were surveys comprising multiple validated scales, as well as urine screens, every 4 months. RESULTS: There was no difference in abstinence between participants in the MOUD+A-CHESS and MOUD-alone arms across time (odds ratio=1.10, 95% CI=0.90-1.33). However, abstinence was moderated by withdrawal symptom severity (odds ratio=0.95, 95% CI=0.91-1.00) and MOUD type (odds ratio=0.57, 95% CI=0.34-0.97). Among participants without withdrawal symptoms, abstinence rates were higher over time for those in the MOUD+A-CHESS arm than for those in the MOUD-alone arm (odds ratio=1.30, 95% CI=1.01-1.67). Among participants taking methadone, those in the MOUD+A-CHESS arm were more likely to be abstinent over time (b=0.28, SE=0.09) than those in the MOUD-alone arm (b=0.06, SE=0.08), although the two groups did not differ significantly from each other (∆b=0.22, SE=0.11). MOUD+A-CHESS was also associated with greater meeting attendance (odds ratio=1.25, 95% CI=1.05-1.49) and decreased emergency department and urgent care use (odds ratio=0.88, 95% CI=0.78-0.99). CONCLUSIONS: Overall, MOUD+A-CHESS did not improve abstinence relative to MOUD alone. However, MOUD+A-CHESS may provide benefits for subsets of patients and may impact treatment utilization.

Patient Preferences for Mobile Health Applications to Support Recovery.

INTRODUCTION: Smartphone apps to support individuals in recovery from substance use disorders (SUDs) are increasingly available. Although many people with SUDs express interest in recovery support apps, few try them or use them long-term. Strategies like gamification and contingency management are increasingly being considered to sustain engagement. This study sought to describe features of a recovery support app called the Addiction version of the Comprehensive Health Enhancement Support System (A-CHESS) that are most used by individuals in SUD recovery and what makes individuals more likely to use these apps. METHODS: A total of 202 people with A-CHESS accounts completed an online survey assessing their experiences using A-CHESS between April and June 2021. We described app features reported to be most beneficial for managing anxiety, loneliness, and isolation during COVID-19; reasons for not using A-CHESS; and suggested app features for future recovery support apps. RESULTS: Respondents had a mean age of 41 years, 85% were White, and 61% were female. Respondents reported that app features related to messaging (ie, open discussion boards and private messaging) and informational or motivational resources were the most useful for managing isolation, anxiety, and loneliness. Reasons for not using A-CHESS were not knowing how to use the app and the app not being part of a personalized treatment plan. The most common suggested components for future apps were rewards for meeting goals and a support meeting locator. CONCLUSIONS: Ensuring that health apps are intuitive and include features that appeal to patients and educating patients about features apps already include that help them meet goals may enhance engagement with recovery apps.

Behavioral healthcare organizations' experiences related to use of telehealth as a result of the COVID-19 pandemic: an exploratory study.

BACKGROUND: Due to the COVID-19 pandemic, healthcare providers were forced to shift many services quickly from in-person to virtual, including substance use disorder (SUD) and mental health (MH) treatment services. This led to a sharp increase in telehealth services, with health systems seeing patients virtually at hundreds of times the rate as before the onset of the COVID-19 pandemic. By analyzing qualitative data about SUD and MH care organizations' experiences using telehealth, this study aims to elucidate emergent themes related to telehealth use by the front-line behavioral health workforce. METHODS: This study uses qualitative data from large-scale web surveys distributed to SUD and MH organizations between May and August 2020. At the end of these surveys, the following question was posed in free-response form: "Is there anything else you would like to say about use of telehealth during or after the COVID-19 pandemic?" Respondents were asked to answer on behalf of their organizations. The 391 responses to this question were analyzed for emergent themes using a conventional approach to content analysis. RESULTS: Three major themes emerged: COVID-specific experiences with telehealth, general experiences with telehealth, and recommendations to continue telehealth delivery. Convenience, access to new populations, and lack of commute were frequently cited advantages of telehealth, while perceived ineffectiveness of and limited access to technology were frequently cited disadvantages. Also commonly mentioned was the relaxation of reimbursement regulations. Respondents supported continuation of relaxed regulations, increased institutional support, and using a combination of telehealth and in-person care in their practices. CONCLUSIONS: This study advanced our knowledge of how the behavioral health workforce experiences telehealth delivery. Further longitudinal research comparing treatment outcomes of those receiving in-person and virtual services will be necessary to undergird organizations' financial support, and perhaps also legislative support, for virtual SUD and MH services.

Using Smart Displays to Implement an eHealth System for Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial.

BACKGROUND: Voice-controlled smart speakers and displays have a unique but unproven potential for delivering eHealth interventions. Many laptop- and smartphone-based interventions have been shown to improve multiple outcomes, but voice-controlled platforms have not been tested in large-scale rigorous trials. Older adults with multiple chronic health conditions, who need tools to help with their daily management, may be especially good candidates for interventions on voice-controlled devices because these patients often have physical limitations, such as tremors or vision problems, that make the use of laptops and smartphones challenging. OBJECTIVE: The aim of this study is to assess whether participants using an evidence-based intervention (ElderTree) on a smart display will experience decreased pain interference and improved quality of life and related measures in comparison with participants using ElderTree on a laptop and control participants who are given no device or access to ElderTree. METHODS: A total of 291 adults aged ≥60 years with chronic pain and ≥3 additional chronic conditions will be recruited from primary care clinics and community organizations and randomized 1:1:1 to ElderTree access on a smart display along with their usual care, ElderTree access on a touch screen laptop along with usual care, or usual care alone. All patients will be followed for 8 months. The primary outcomes are differences between groups in measures of pain interference and psychosocial quality of life. The secondary outcomes are between-group differences in system use at 8 months, physical quality of life, pain intensity, hospital readmissions, communication with medical providers, health distress, well-being, loneliness, and irritability. We will also examine mediators and moderators of the effects of ElderTree on both platforms. At baseline, 4 months, and 8 months, patients will complete written surveys comprising validated scales selected for good psychometric properties with similar populations. ElderTree use data will be collected continuously in system logs. We will use linear mixed-effects models to evaluate outcomes over time, with treatment condition and time acting as between-participant factors. Separate analyses will be conducted for each outcome. RESULTS: Recruitment began in August 2021 and will run through April 2023. The intervention period will end in December 2023. The findings will be disseminated via peer-reviewed publications. CONCLUSIONS: To our knowledge, this is the first study with a large sample and long time frame to examine whether a voice-controlled smart device can perform as well as or better than a laptop in implementing a health intervention for older patients with multiple chronic health conditions. As patients with multiple conditions are such a large cohort, the implications for cost as well as patient well-being are significant. Making the best use of current and developing technologies is a critical part of this effort. TRIAL REGISTRATION: ClinicalTrials.gov NCT04798196; https://clinicaltrials.gov/ct2/show/NCT04798196. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37522.

Effect of an eHealth intervention on older adults' quality of life and health-related outcomes: a randomized clinical trial.

BACKGROUND: By 2030, the number of US adults age ≥65 will exceed 70 million. Their quality of life has been declared a national priority by the US government. OBJECTIVE: Assess effects of an eHealth intervention for older adults on quality of life, independence, and related outcomes. DESIGN: Multi-site, 2-arm (1:1), non-blinded randomized clinical trial. Recruitment November 2013 to May 2015; data collection through November 2016. SETTING: Three Wisconsin communities (urban, suburban, and rural). PARTICIPANTS: Purposive community-based sample, 390 adults age ≥65 with health challenges. EXCLUSIONS: long-term care, inability to get out of bed/chair unassisted. INTERVENTION: Access (vs. no access) to interactive website (ElderTree) designed to improve quality of life, social connection, and independence. MEASURES: Primary outcome: quality of life (PROMIS Global Health). Secondary: independence (Instrumental Activities of Daily Living); social support (MOS Social Support); depression (Patient Health Questionnaire-8); falls prevention (Falls Behavioral Scale). Moderation: healthcare use (Medical Services Utilization). Both groups completed all measures at baseline, 6, and 12 months. RESULTS: Three hundred ten participants (79%) completed the 12-month survey. There were no main effects of ElderTree over time. Moderation analyses indicated that among participants with high primary care use, ElderTree (vs. control) led to better trajectories for mental quality of life (OR=0.32, 95% CI 0.10-0.54, P=0.005), social support received (OR=0.17, 95% CI 0.05-0.29, P=0.007), social support provided (OR=0.29, 95% CI 0.13-0.45, P<0.001), and depression (OR= -0.20, 95% CI -0.39 to -0.01, P=0.034). Supplemental analyses suggested ElderTree may be more effective among people with multiple (vs. 0 or 1) chronic conditions. LIMITATIONS: Once randomized, participants were not blind to the condition; self-reports may be subject to memory bias. CONCLUSION: Interventions like ET may help improve quality of life and socio-emotional outcomes among older adults with more illness burden. Our next study focuses on this population. TRIAL REGISTRATION: ClinicalTrials.gov ; registration ID number: NCT02128789.

Intraindividual, Dyadic, and Network Communication in a Digital Health Intervention: Distinguishing Message Exposure from Message Production.

Communicating within digital health interventions involves a range of behaviors that may contribute to the management of chronic illnesses in different ways. This study examines whether communication within a smartphone-based application for addiction recovery produces distinct effects depending on 1) the "level" of communication, defined as intraindividual communication (e.g., journal entries to oneself); dyadic communication (e.g., private messaging to other individuals); or network communication (e.g., discussion forum posts to all group members), and 2) whether individuals produce or are exposed to messages. We operationalize these communication levels and behaviors based on system use logs as the number of clicks dedicated to each activity and assess how each category of system use relates to changes in group bonding and substance use after 6 months with the mobile intervention. Our findings show that (1) intraindividual exposure to one's own past posts marginally predicts decreased drug use; (2) dyadic production predicts greater perceived bonding; while dyadic exposure marginally predicts reduced drug use; (3) network production predicts decreased risky drinking. Implications for digital health interventions are discussed.

Efficacy and comparative effectiveness of telephone and smartphone remote continuing care interventions for alcohol use disorder: a randomized controlled trial.

BACKGROUND AND AIMS: Management of alcohol use disorder (AUD) could be enhanced by effective remote treatments. This 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 four groups with 3-, 6-, 9-, 12- and 18-month follow-ups. SETTING: University research center in Philadelphia, PA, 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: The primary outcome was percentage of 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 [Cohen's d = 0.35, P = 0.018, 95% confidence interval (CI) = (-1.42, -0.20)], ACHESS [d = 0.31, P = 0.031, 95% CI = (-1.27, -0.06)] and TMC + ACHESS [d = 0.36, P = 0.009, 95% CI = (-1.40, -0.20)] than in TAU. Differences between TMC + ACHESS, TMC and ACHESS were small (d ≤ 0.06) 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 = 0.025). 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.

Clinician Perspectives on Barriers and Facilitators to Implementing e-Health Technology in Substance Use Disorder (SUD) Treatment Facilities.

BACKGROUND: Substance use disorders (SUDs) in the United States cause many preventable deaths each year. Finding effective ways to manage SUDs is vital to improving outcomes for individuals seeking treatment. This has increased interest in using e-health technologies in behavioral healthcare settings. This research is part of a larger study evaluating the efficacy of the NIATx coaching intervention for implementing RISE Iowa, an e-health patient recovery app, in SUD treatment organizations and seeks to examine clinician perspectives of the barriers and facilitators to its implementation. METHOD: Semi-structured qualitative interviews were conducted with 13 clinicians from 9 different intervention sites involved in the study. RESULTS: Major barriers to implementing e-health technology include inability to access the technology, lack of time for both patients and clinicians, and a perceived lack of patient motivation to make changes. Facilitators to implementation include collaboration with other staff using e-health technology and integrating technology use into typical workflows. CONCLUSIONS: Implementation of e-health technology in SUD treatment will require integrating the technology into clinical workflows and improving patient access to the technology.

Prospective Prediction of Lapses in Opioid Use Disorder: Protocol for a Personal Sensing Study.

BACKGROUND: Successful long-term recovery from opioid use disorder (OUD) requires continuous lapse risk monitoring and appropriate use and adaptation of recovery-supportive behaviors as lapse risk changes. Available treatments often fail to support long-term recovery by failing to account for the dynamic nature of long-term recovery. OBJECTIVE: The aim of this protocol paper is to describe research that aims to develop a highly contextualized lapse risk prediction model that forecasts the ongoing probability of lapse. METHODS: The participants will include 480 US adults in their first year of recovery from OUD. Participants will report lapses and provide data relevant to lapse risk for a year with a digital therapeutic smartphone app through both self-report and passive personal sensing methods (eg, cellular communications and geolocation). The lapse risk prediction model will be developed using contemporary rigorous machine learning methods that optimize prediction in new data. RESULTS: The National Institute of Drug Abuse funded this project (R01DA047315) on July 18, 2019 with a funding period from August 1, 2019 to June 30, 2024. The University of Wisconsin-Madison Health Sciences Institutional Review Board approved this project on July 9, 2019. Pilot enrollment began on April 16, 2021. Full enrollment began in September 2021. CONCLUSIONS: The model that will be developed in this project could support long-term recovery from OUD-for example, by enabling just-in-time interventions within digital therapeutics. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29563.

Effect of an mHealth Intervention on Hepatitis C Testing Uptake Among People With Opioid Use Disorder: Randomized Controlled Trial.

BACKGROUND: The growing epidemic of opioid use disorder (OUD) and associated injection drug use has resulted in a surge of new hepatitis C virus (HCV) infections. Approximately half of the people with HCV infection are unaware of their HCV status. Improving HCV awareness and increasing screening among people with OUD are critical. Addiction-Comprehensive Health Enhancement Support System (A-CHESS) is an evidence-based, smartphone-delivered relapse prevention system that has been implemented among people with OUD who are receiving medications for addiction treatment (MAT) to improve long-term recovery. OBJECTIVE: We incorporated HCV-related content and functionality into A-CHESS to characterize the HCV care continuum among people in early remission and receiving MAT for OUD and to determine whether incorporating such content and functionality into A-CHESS increases HCV testing. METHODS: HCV intervention content, including dissemination of educational information, private messages tailored to individuals' stage of HCV care, and a public discussion forum, was implemented into the A-CHESS platform. Between April 2016 and April 2020, 416 participants with OUD were enrolled in this study. Participants were randomly assigned to receive MAT alone (control arm) or MAT+A-CHESS (experimental arm). Quarterly telephone interviews were conducted from baseline to month 24 to assess risk behaviors and HCV testing history. Cox proportional hazards regression was used to assess whether participants who used A-CHESS were tested for HCV (either antibody [Ab] or RNA testing) at a higher rate than those in the control arm. To assess the effect of A-CHESS on subsets of participants at the highest risk for HCV, additional analyses were performed to examine the effect of the intervention among participants who injected drugs and shared injection equipment. RESULTS: Overall, 44.2% (184/416) of the study participants were HCV Ab positive, 30.3% (126/416) were HCV Ab negative, and 25.5% (106/416) were considered untested at baseline. At month 24, there was no overall difference in HCV testing uptake between the intervention and control participants. However, among the subset of 109 participants who engaged in injection drug use, there was a slight trend toward increased HCV testing uptake among those who used A-CHESS (89% vs 85%; hazard ratio: 1.34; 95% CI 0.87-2.05; P=.18), and a stronger trend was observed when focusing on the subset of 32 participants who reported sharing injection equipment (87% vs 56%; hazard ratio: 2.92; 95% CI 0.959-8.86; P=.06). CONCLUSIONS: Incorporating HCV prevention and care information into A-CHESS may increase the uptake of HCV testing while preventing opioid relapse when implemented among populations who engage in high-risk behaviors such as sharing contaminated injection equipment. However, more studies that are powered to detect differences in HCV testing among high-risk groups are needed. TRIAL REGISTRATION: ClinicalTrials.gov NCT02712034; https://clinicaltrials.gov/ct2/show/NCT02712034. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/12620.

A Web-Based eHealth Intervention to Improve the Quality of Life of Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial.

BACKGROUND: Multiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients' lives. OBJECTIVE: This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. METHODS: In this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. RESULTS: Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. CONCLUSIONS: With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. TRIAL REGISTRATION: ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/25175.

Potential Influences of the COVID-19 Pandemic on Drug Use and HIV Care Among People Living with HIV and Substance Use Disorders: Experience from a Pilot mHealth Intervention.

People living with HIV (PLWH) and substance use disorder (SUD) are particularly vulnerable to harmful health consequences of the global COVID-19 pandemic. The health and social consequences of the pandemic may exacerbate substance misuse and poor management of HIV among this population. This study compares substance use and HIV care before and during the pandemic using data collected weekly through an opioid relapse prevention and HIV management mobile-health intervention. We found that during the pandemic, PLWH and SUD have increased illicit substance use and contact with other substance-using individuals and decreased their confidence to stay sober and attend recovery meetings. The proportion of people missing their HIV medications also increased, and confidence to attend HIV follow-up appointments decreased. Optimal support for PLWH and SUD is critical during pandemics like COVID-19, as drug-related and HIV antiretroviral therapy (ART) non-adherence risks such as overdose, unsafe sexual behaviors, and transmission of infectious diseases may unfold.

RESUMEN: Personas con VIH y con trastornos por abuso de sustancias son más vulnerable a las consecuencias de la pandemia: COVID-19. Dentro estas poblaciones, las consecuencias sociales y de la salud, causadas por la pandemia, pueden exacerbar el mal uso de las sustancias, y la adherencia a los antiretrovirales. Este estudio compara el abuso de sustancias y el cuidado del VIH, antes y durante la pandemia, usando datos colectados semanal de otro programa que también investigo la prevención entre personas que han recaído con el uso de opioides y que tienen VIH. Nuestro análisis encuentra, que durante la pandemia, incrementaron el uso de sustancias ilícitas, y contacto con otras personas que usan sustancias, y perdieron la capacidad de mantenerse sobrios, y tambien dejaron de asistir reuniones de recuperación/apoyo. También, el porcentaje de personas con VIH no siguiendo con sus planes de tratamiento de VIH, incrementó; perdieron su motivacion en mantener sus citas médicos. Es muy crítico, durante una pandemia como COVID-19, tener recursos para personas que pertenecen a estas poblaciones, si no, casos de sobredosis, sexo sin protección y la transmisión de enfermedades infecciosas van a prevaler.

Exploring the Role of Social Support in Promoting Patient Participation in Health Care among Women with Breast Cancer.

Scholars have adopted Street's (2003) ecological model of communication in medical encounters to investigate the factors promoting patient participation in health care. However, factors demonstrated in the ecological model were bounded in the context of medical care primarily focusing on health care providers and patients. Social factors, such as patients' relationships and supportive communication with others outside the context of health care remain relatively unexplored. To expand the purview of our understanding of factors that influence patient participation, this research integrated social support literature into the research on physician-patient communication and proposed a model which described a process through which social support can enhance patient participation in health care. The data analyzed in this study were a part of two larger clinical trials in which 661 women with breast cancer were recruited from three cancer institutions in the United States. The results from structural equation modeling analysis from cross-sectional and longitudinal data provided strong evidence for the hypotheses predicting that perceived social support was positively associated with health information competence, which in turn fully mediated the association between social support and patient participation in health care. Theoretical and practical implications are discussed.

NIATx-TI versus typical product training on e-health technology implementation: a clustered randomized controlled trial study protocol.

BACKGROUND: Substance use disorders (SUDs) lead to tens-of-thousands of overdose deaths and other forms of preventable deaths in the USA each year. This results in over $500 billion per year in societal and economic costs as well as a considerable amount of grief for loved ones of affected individuals. Despite these health and societal consequences, only a small percentage of people seek treatment for SUDs, and the majority of those that seek help fail to achieve long-term sobriety. E-health applications in healthcare have proven to be effective at sustaining treatment and reaching patients traditional treatment pathways would have missed. However, e-health adoption and sustainment rates in healthcare are poor, especially in the SUD treatment sector. Implementation engineering can address this gap in the e-health field by augmenting existing implementation models, which explain organizational and individual e-health behaviors retrospectively, with prospective resources that can guide implementation. METHODS: This cluster randomized control trial is designed to test two implementation strategies at adopting an evidence-based mobile e-health technology for SUD treatment. The proposed e-health implementation model is the Network for the Improvement of Addiction Treatment-Technology Implementation (NIATx-TI) Framework. This project, based in Iowa, will compare a control condition (using a typical software product training approach that includes in-person staff training followed by access to on-line support) to software implementation utilizing NIATx-TI, which includes change management training, followed by coaching on how to implement and use the mobile application. While e-health spans many modalities and health disciplines, this project will focus on implementing the Addiction Comprehensive Health Enhancement Support System (A-CHESS), an evidence-based SUD treatment recovery app framework. This trial will be conducted in Iowa at 46 organizational sites within 12 SUD treatment agencies. The control arm consists of 23 individual treatment sites based at five organizations, and the intervention arm consists of 23 individual SUD treatment sites based at seven organizations DISCUSSION: This study addresses an issue of substantial public health significance: enhancing the uptake of the growing inventory of patient-centered evidence-based addiction treatment e-health technologies. TRIAL REGISTRATION: ClinicalTrials.gov , NCT03954184 . Posted 17 May 2019.

Understanding how e-health interventions meet psychosocial needs of breast cancer patients: The pathways of influence on quality of life and cancer concerns.

OBJECTIVE: This investigation explores how using different e-health interventions facilitates positive psychosocial changes and how these changes reduce cancer concerns and improve quality of life in breast cancer patients over time. METHODS: A total of 326 breast cancer patients were randomly assigned to one of three e-health interventions: (a) Internet only, (b) the Comprehensive Health Enhancement Support System information and support services (CHESS-IS), or (c) CHESS with mentor. Proximal health outcomes such as information overload, emotional functioning, and social support were measured alongside distal outcomes like cancer concerns and quality of life. Participants completed surveys at four time points: pretest as a baseline, 6 weeks, 3 months, and 6 months. RESULTS: Both interventions were effective in improving patient health beyond Internet only but they differed in type of change mechanism and clinical benefit. The CHESS-IS enhanced proximal outcomes at 3 months through improved information competence. The CHESS with mentor intervention reduced breast cancer concerns at 6 months, mediated mainly by emotional-social competence and emotional functioning. CONCLUSIONS: Using e-health interventions like CHESS can help patients improve cancer information management skills and emotional functioning, contributing to better short-term health outcomes. Adding a human mentor can enhance the benefits of CHESS use, extending the experience among breast cancer patients. Theoretical, practical, and clinical implications of the study results are discussed.

Giving and receiving social support in online substance use disorder forums: How self-efficacy moderates effects on relapse.

OBJECTIVE: Individuals in recovery for substance use disorders (SUDs) increasingly use online social support forums, necessitating research on how communicating through these forums can affect recovery. This study examines how giving and receiving support within an SUDs recovery forum predict substance use, and considers whether effects vary according to participants' self-efficacy. METHODS: We applied content analysis to 3440 messages that were posted by 231 participants in an online SUDs forum. Surveys assessed social support reception and substance use at three timepoints. We assessed relationships between giving and receiving support and substance use (risky drinking days, illicit drug use days), and the interactions between self-efficacy and social support in predicting substance use outcomes. RESULTS: Receiving more emotional support was associated with reduced illicit drug use at 6 and 12 months. For those with low self-efficacy, giving more emotional support predicted less risky drinking at month 12, whereas giving more informational support predicted more risky drinking at month 12. CONCLUSION: These results suggest conditional benefits of exchanging support in an online SUDs forum, depending upon type of support (informational versus emotional), the participants' role (giver or receiver), and their self-efficacy. PRACTICE IMPLICATIONS: We discuss implications for designing and using peer-to-peer support platforms.

A smartphone-based support group for alcoholism: Effects of giving and receiving emotional support on coping self-efficacy and risky drinking.

The purpose of this study was to investigate the nature and effects of exchanging emotional support via a smartphone-based support group for patients with alcohol dependence. Of the 349 patients who met the Diagnostic and Statistical Manual of Mental Disorders (4th ed.) criteria for alcohol dependence, 153 patients participated in the discussion group within the Addiction-Comprehensive Health Enhancement Support System, a smartphone application aimed at reducing relapse. This was developed to prevent problem drinking by offering individuals in recovery for alcohol dependence automated 24/7 recovery support services and frequent assessment of their symptom status as part of their addiction care. The results showed that receiving emotional support from health care providers improved coping self-efficacy. Giving emotional support and receiving emotional support from health care providers acted as a buffer, protecting patients from the harmful effects of emotional distress on risky drinking. Clinicians and researchers should use the features of smartphone-based support groups to reach out to alcoholic patients in need and encourage them to participate in the exchange of emotional support with others.

A Mobile Health Intervention to Improve Hepatitis C Outcomes Among People With Opioid Use Disorder: Protocol for a Randomized Controlled Trial.

BACKGROUND: People who inject drugs are at a disproportionate risk for contracting hepatitis C virus (HCV). However, use of HCV prevention and treatment services remains suboptimal among people with substance use disorders due to various health system, societal, and individual barriers. Mobile health applications offer promising strategies to support people in recovery from substance use disorders. We sought to determine whether the Addiction-Comprehensive Health Enhancement Support System (A-CHESS), an existing mobile health application for opioid use disorder, could be adapted to improve HCV screening and treatment. OBJECTIVE: The goals of this paper are to describe: (1) the components and functionality of an HCV intervention incorporated into the existing A-CHESS system; and (2) how data are collected and will be used to evaluate HCV testing, linkage to care, and treatment. METHODS: People with recent opioid use were enrolled in a randomized controlled trial to test whether A-CHESS reduced relapse. We developed and implemented HCV intervention content within the A-CHESS platform to simultaneously evaluate whether A-CHESS improved secondary outcomes related to HCV care. All A-CHESS users received the HCV intervention content, which includes educational information, private messages tailored to an individual's stage of HCV care, and a public discussion forum. Data on patients' HCV risk behaviors and stage of care were collected through quarterly telephone interviews and weekly surveys delivered through A-CHESS. The proportion of people with opioid use disorder who are HCV untested, HCV-negative, HCV antibody-positive, or HCV RNA-positive, as well as linked to care, treated and cured at baseline is described here. The 24-month follow-up is ongoing and will be completed in April 2020. Survey data will then be used to assess whether individuals who received the HCV-enhanced A-CHESS intervention were more likely to reduce risky injection behaviors, receive HCV testing, link to medical care, initiate treatment, and be cured of HCV compared to the control group. RESULTS: Between April 2016 and April 2018, 416 individuals were enrolled and completed the baseline interview. Of these individuals, 207 were then randomly assigned to the control arm and 209 were assigned to the intervention arm. At baseline, 202 individuals (49%) self-reported ever testing HCV antibody-positive. Of those, 179 (89%) reported receiving HCV RNA confirmatory testing, 134 (66%) tested HCV RNA-positive, 125 (62%) were linked to medical care and 27 (13%) were treated and cured of HCV. Of the remaining 214 individuals who had never tested HCV antibody-positive, 129 (31%) had tested HCV antibody-negative within the past year and 85 (20%) had not been tested within the past year. CONCLUSIONS: The A-CHESS mobile health system allows for the implementation of a bundle of services as well as the collection of longitudinal data related to drug use and HCV care among people with opioid use disorders. This study will provide preliminary evidence to determine whether HCV-specific services embedded into the A-CHESS program can improve HCV outcomes for people engaged in addiction treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT02712034; https://clinicaltrials.gov/ct2/show/NCT02712034. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12620.

Using Smartphones to Improve Treatment Retention Among Impoverished Substance-Using Appalachian Women: A Naturalistic Study.

OBJECTIVES: Longer retention in treatment is associated with positive outcomes. For women, who suffer worse drug-related problems than men, social technologies, which are more readily adopted by women, may offer promise. This naturalistic study examined whether a smartphone-based relapse-prevention system, A-CHESS (Addiction-Comprehensive Health Enhancement Support System), could improve retention for women with substance use disorders in an impoverished rural setting. METHODS: A total of 98 women, age 18 to 40, in southeastern Kentucky and mandated to treatment, received A-CHESS with intensive outpatient treatment for 6 months. For comparison, data were obtained for a similar but non-equivalent group of 100 same-age women also mandated to treatment in the same clinics during the period. Electronic medical record data on length-of-stay and treatment service use for both groups were analyzed, with A-CHESS use data, to determine whether those using A-CHESS showed better retention than those without. RESULTS: Women with A-CHESS averaged 780 service units compared with 343 for the comparison group. For those with discharge dates prior to the study's end, A-CHESS patients stayed in treatment a mean of 410 vs 262 days for the comparison group. CONCLUSIONS: Given associations between retention and positive outcomes, mobile health technology such as A-CHESS may help improve outcomes among women, especially in settings where access to in-person services is difficult. The findings, based on a non-equivalent comparison, suggest the need for further exploration with rigorous experimental designs to determine whether and to what degree access to a smartphone with A-CHESS may extend and support recovery for women.