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

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.

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.

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.

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.

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.

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.

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

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.

Pilot Test of a Computer-Based System to Help Family Caregivers of Dementia Patients

BACKGROUND

Family members absorb much of the care of dementia patients. The burden of care substantially impacts caregivers' health, further straining our healthcare system. By 2050, the incidence of Alzheimer's disease will more than double, increasing the numbers of family caregivers proportionally. Interventions that reduce their burden are needed to preserve their health as well as the viability of the healthcare system.

OBJECTIVE

This paper reports on the development and feasibility testing of a computer-based system intended to improve the lives of caregivers. D-CHESS (Dementia-Comprehensive Health Enhancement Support System) allows users to obtain information, communicate with other caregivers, get help with care decisions, and share information with experts.

METHOD

Thirty-one caregivers were randomly assigned to an intervention group receiving D-CHESS for 6 months or to a control group receiving a caregiving book. Surveys at 0, 2, 4, and 6 months evaluated caregiver burden, family conflict, satisfaction with decisions, social support, loneliness, anxiety, depression, and coping competence.

RESULTS

Survey findings suggest D-CHESS participants may perform better on measures of social support, anxiety, loneliness, and coping competence; the groups were equivalent on caregiver burden, decision satisfaction, and depression, and the control group reported less family conflict than the intervention. D-CHESS use data suggested enhancements to system design and content to increase awareness and use of various features.

CONCLUSION

This study suggests that D-CHESS has potential to positively impact family caregivers and that the system merits further development and investigation with a full-scale clinical trial.

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

A Longitudinal Investigation of Empathic Exchanges in Online Cancer Support Groups: Message Reception and Expression Effects on Patients' Psychosocial Health Outcomes

Recent studies have devoted attention to the effects of both expression and reception in communication process. However, there remain both theoretical and methodological complexities concerning whether and under what condition message expression and reception play significant but different roles in explaining various psychosocial health outcomes. Relying on theoretical insights from the social support literature and methodological innovations offered by computational social science, this study aims to examine the effects of empathic exchanges on cancer patient's short- and long-term psychosocial health outcomes. Our findings suggest that both empathy expression and reception are crucial to attaining benefits for cancer patients, each predicting differential cognitive and affective health outcomes. Further, our finding supports the stress-buffering hypothesis such that empathy reception provides a beneficial effect for patients who experienced a higher degree of depression associated with their cancer diagnosis and follow-up treatments.

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.

Interactivity, Presence, and Targeted Patient Care: Mapping e-Health Intervention Effects Over Time for Cancer Patients with Depression

This study examined the interplay of depression and different types of e-health interventions on breast cancer patients' perceived healthcare competence, emotional processing, and social well-being over time. The three e-health interventions--Internet Only as a control condition, CHESS (Comprehensive Health Enhancement Support System) Only, and CHESS with a Human Mentor, a cancer information specialist--provided varying degrees of interactivity and presence. A total of 328 women with breast cancer participated in one of the three interventions for a 6-month period. Women were further split into two groups based on reported levels of depression. For perceived healthcare competence and social well-being, results revealed significant interaction effects for intervention type by depression over time, such that breast cancer patients with higher levels of depression benefited most from the CHESS with Mentor intervention over the 6-month study period. For emotional processing, depressed cancer patients benefited more from the CHESS with Mentor than the other two interventions, regardless of time. These findings have (a) theoretical implications on how mental health factors can intersect with interactivity and presence to influence psychosocial outcomes, (b) conceptual implications for the role of human interaction within e-health systems, and (c) practical implications for the development of e-health interventions for cancer patients with depression.

An Outcome Study of the CASA-CHESS Smartphone Relapse Prevention Tool for Latinx Spanish-Speakers with Substance Use Disorders

Background: Hispanic/Latinx persons with alcohol and other drug disorders (AOD) have limited access to culturally competent continuity of care. To address this, the evidence-based smartphone recovery application Addiction-Comprehensive Health Enhancement Support System (A-CHESS) was translated and adapted for Latinx Spanish-speakers with AOD, developing CASA-CHESS. Objectives: This study examined the AOD and mental health outcomes for Latinx Spanish-speaking clients using the CASA-CHESS smartphone tool over a 6-month period, post-residential treatment. This single group, pre-post study design included seventy-nine male and female Spanish-speaking Latinx clients, equipped with CASA-CHESS as they completed residential AOD treatment. Primary outcome measures at baseline and 6-month follow-up included substance use and other mental health symptoms. Results: While over 70% of the sample reported past heroin use and alcohol use, clients had low baseline rates of substance use, depression and anxiety and elevated social support scores as they graduated from residential treatment. Overall participants maintained their relatively low baseline rates during the 6-month post-residential period while using the CASA-CHESS relapse prevention tool. Those who discontinued using CASA-CHESS within the first 4 months after leaving residential treatment reported higher rates of substance use as well as anxiety and depression symptoms than those using it for 4 or more months, suggesting that continued use of CASA-CHESS may contribute to maintenance of successes gained in treatment. Conclusions/Importance: CASA-CHESS may reduce the risk of relapse for Latinx Spanish-speakers following residential services and extend needed access to culturally and linguistically competent aftercare services for those with AOD.

What Do You Say Before You Relapse? How Language Use in a Peer-to-peer Online Discussion Forum Predicts Risky Drinking among Those in Recovery

Increasingly, individuals with alcohol use disorder (AUD) seek and provide support for relapse prevention in text-based online environments such as discussion forums. This paper investigates whether language use within a peer-to-peer discussion forum can predict future relapse among individuals treated for AUD. A total of 104 AUD sufferers who had completed residential treatment participated in a mobile phone-based relapse-prevention program, where they communicated via an online forum over the course of a year. We extracted patterns of language use on the forum within the first four months on study using Linguistic Inquiry and Word Count (LIWC), a dictionary-based text analysis program. Participants reported their incidence of risky drinking via a survey at 4, 8, and 12 months. A logistic regression model was built to predict the likelihood that individuals would engage in risky drinking within a year based on their language use, while controlling for baseline characteristics and rates of utilizing the mobile system. Results show that all baseline characteristics and system use factors explained just 13% of the variance in relapse, whereas a small number of linguistic cues, including swearing and cognitive mechanism words, accounted for an additional 32% of the total 45% of variance in relapse explained by the model. Effective models for predicting relapse are needed. Messages exchanged on AUD forums could provide an unobtrusive and cost-effective window into the future health outcomes of AUD sufferers, and their psychological underpinnings. As online communication expands, models that leverage user-submitted text toward predicting relapse will be increasingly scalable and actionable.

Using ecological momentary assessments to predict relapse after adult substance use treatment

BACKGROUND

A key component of relapse prevention is to self-monitor the internal (feelings or cravings) and external (people, places, activities) factors associated with relapse. Smartphones can deliver ecological momentary assessments (EMA) to help individuals self-monitor. The purpose of this exploratory study was to develop a model for predicting an individual's risk of future substance use after each EMA and validate it using a multi-level model controlling for repeated measures on persons.

METHODS

Data are from 21,897 observations from 43 adults following their initial episode of substance use treatment in Chicago from 2015 to 2016. Participants were provided smartphones for six months and asked to complete two to three minute EMAs at five random times per day (81% completion). In any given EMA, 2.7% reported substance use and 8% reported any use in the next five completed EMA. Chi-square Automatic Interaction Detector (CHAID) was used to classify EMAs into six levels of risk and then validated with a hierarchical linear model (HLM).

RESULTS

The major predictors of substance use in the next five completed EMAs were substance use pattern over the current and prior five EMAs (no recent/current use, either recent or current use [but not both], continued use [both recent and current]), negative affect (feelings), and craving (rating). Negative affect was important for EMAs with no current or recent use reported; craving was important for EMAs with either recent or current use; and neither mattered for EMAs with continued use. The CHAID gradated EMA risk from 0.7% to 36.6% of the next five completed EMAs with substance use reported. It also gradated risk of "any" use in the next five completed EMAs from 3% to 82%.

CONCLUSIONS

This study demonstrated the potential of using smartphone-based EMAs to monitor and provide feedback for relapse prevention in future studies.

When support is needed: Social support solicitation and provision in an online alcohol use disorder forum

Background

Obtaining adequate social support presents a challenge for many in addiction recovery. Increasingly, individuals in recovery use online forums to exchange support with peers, yet it is unclear which help-seeking strategies most effectively recruit peer support, and which forms of support are most valued by recipients.

Methods

This study applied quantitative content analysis to examine social support solicitation and delivery in an online forum for alcohol use disorder (AUD). We compared the frequency with which peers provided informational, emotional, and companionship support after solicitations that: (1) were direct or indirect, (2) disclosed positive or negative emotions, and (3) mentioned or did not mention recovery problems. We assessed likelihood that recipients would express gratitude after receiving each type of support, and assessed whether the “match” between solicitation and disclosure styles influenced rates of gratitude expression.

Results

Emotional disclosures, whether positive or negative, received the highest volume of supportive replies. Emotional support was the most common response to solicitations overall, and was disproportionately offered after recipients disclosed positive emotions. Informational support was disproportionately offered after recipients disclosed negative emotions or recovery problems, or explicitly requested help. Regardless of their solicitation style, recipients expressed more gratitude after receiving emotional support than other support types.

Conclusions

Providing emotional support was common in an online AUD forum, and precipitated expressing gratitude from recipients to support providers. The results may be helpful in guiding participants to more effectively obtain and provide recovery support in online forums.

Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum

Background

Online discussion forums allow those in addiction recovery to seek help through text-based messages, including when facing triggers to drink or use drugs. Trained staff (or “moderators”) may participate within these forums to offer guidance and support when participants are struggling but must expend considerable effort to continually review new content. Demands on moderators limit the scalability of evidence-based digital health interventions.

Objective

Automated identification of recovery problems could allow moderators to engage in more timely and efficient ways with participants who are struggling. This paper aimed to investigate whether computational linguistics and supervised machine learning can be applied to successfully flag, in real time, those discussion forum messages that moderators find most concerning.

Methods

Training data came from a trial of a mobile phone-based health intervention for individuals in recovery from alcohol use disorder, with human coders labeling discussion forum messages according to whether or not authors mentioned problems in their recovery process. Linguistic features of these messages were extracted via several computational techniques: (1) a Bag-of-Words approach, (2) the dictionary-based Linguistic Inquiry and Word Count program, and (3) a hybrid approach combining the most important features from both Bag-of-Words and Linguistic Inquiry and Word Count. These features were applied within binary classifiers leveraging several methods of supervised machine learning: support vector machines, decision trees, and boosted decision trees. Classifiers were evaluated in data from a later deployment of the recovery support intervention.

Results

To distinguish recovery problem disclosures, the Bag-of-Words approach relied on domain-specific language, including words explicitly linked to substance use and mental health (“drink,” “relapse,” “depression,” and so on), whereas the Linguistic Inquiry and Word Count approach relied on language characteristics such as tone, affect, insight, and presence of quantifiers and time references, as well as pronouns. A boosted decision tree classifier, utilizing features from both Bag-of-Words and Linguistic Inquiry and Word Count performed best in identifying problems disclosed within the discussion forum, achieving 88% sensitivity and 82% specificity in a separate cohort of patients in recovery.

Conclusions

Differences in language use can distinguish messages disclosing recovery problems from other message types. Incorporating machine learning models based on language use allows real-time flagging of concerning content such that trained staff may engage more efficiently and focus their attention on time-sensitive issues.

Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study

BACKGROUND

Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care.

OBJECTIVE

The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians.

METHODS

In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.

RESULTS

The outcomes according to the RE-AIM framework are as follows: Reach-Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness-Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption-Patients sustained high levels of Seva use-between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation-At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance-Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this.

CONCLUSIONS

Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.

Effects of automated smartphone mobile recovery support and telephone continuing care in the treatment of alcohol use disorder: study protocol for a randomized controlled trial

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.

Reducing Symptom Distress in Patients With Advanced Cancer Using an e-Alert System for Caregivers: Pooled Analysis of Two Randomized Clinical Trials

Background

Symptom distress in patients toward the end of life can change rapidly. Family caregivers have the potential to help patients manage those symptoms, as well as their own stress, if they are equipped with the proper resources. Electronic health (eHealth) systems may be able to provide those resources. Very sick patients may not be able to use such systems themselves to report their symptoms but family caregivers could.

Objective

The aim of this paper was to assess the effects on cancer patient symptom distress of an eHealth system that alerts clinicians to significant changes in the patient’s symptoms, as reported by a family caregiver.

Methods

A pooled analysis from two randomized clinical trials (NCT00214162 and NCT00365963) compared outcomes at 12 months for two unblinded groups: a control group (Comprehensive Health Enhancement Support System [CHESS]-Only) that gave caregivers access to CHESS, an online support system, and an experimental group (CHESS+CR [Clinician Report]), which also had CHESS but with a CR that automatically alerted clinicians if symptoms exceeded a predetermined threshold of severity. Participants were dyads (n=235) of patients with advanced lung, breast, or prostate cancer and their respective family caregivers from 5 oncology clinics in the United States of America. The proportion of improved patient threshold symptoms was compared between groups using area-under-the-curve analysis and binomial proportion tests. The proportion of threshold symptoms out of all reported symptoms was also examined.

Results

When severe caregiver-reported symptoms were shared with clinicians, the symptoms were more likely to be subsequently reported as improved than when the symptoms were not shared with clinicians (P<.001). Fewer symptom reports were completed in the group of caregivers whose reports went to clinicians than in the CHESS-Only group (P<.001), perhaps because caregivers, knowing their reports might be sent to a doctor, feared they might be bothering the clinician.

Conclusions

This study suggests that an eHealth system designed for caregivers that alerts clinicians to worrisome changes in patient health status may lead to reduced patient distress.

Trial Registration

Clinicaltrials.gov NCT00214162; https://clinicaltrials.gov/ct2/show/NCT00214162 (Archived by WebCite at http://www.webcitation.org/6nmgdGfuD) and Clinicaltrials.gov NCT00365963; https://clinicaltrials.gov/ct2/show/NCT00365963 (Archived by WebCite at http://www.webcitation.org/6nmh0U8VP)

Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building

This study investigates how social support and family relationship perceptions influence breast cancer patients' online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or "broadcast" communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships.

Use of a Smartphone Recovery Tool for Latinos with Co-Occurring Alcohol and Other Drug Disorders and Mental Disorders

OBJECTIVE

Addressing alcohol and other drug disorders and other mental disorders among adult Hispanics/Latinos is of critical concern, as they are one of the fastest-growing ethnic groups with a disproportionate rate of disease, mental disorders, and poverty. Although improvement in outcomes is associated with sustained participation in ongoing treatment for co-occurring alcohol and other drug disorders/mental disorders, continuing care is rare for these chronic conditions, especially for Latinos with more limited access to culturally and linguistically competent services.

METHODS

The evidence-based smartphone recovery application Addiction-Comprehensive Health Enhancement Support System (A-CHESS) was translated and adapted for Spanish-speaking Latinos with alcohol and other drug disorders/mental disorders, thus developing CASA-CHESS to address a high level of need for services, high rates of relapse, and lack of existing culturally competent services for Latinos.

RESULTS

Of the 79 Latino clients who completed residential treatment and received a smartphone equipped with CASA-CHESS, 26.6% discontinued using CASA-CHESS and 73.4% remained active for four or more months. CASA-CHESS usage was sustained over the four months across all three tenets of self-determination theory (competence, relatedness, and autonomy), with the most commonly utilized services being relevant to relatedness (e.g., messaging, discussion boards). CASA-CHESS clients demonstrated a similar pattern of usage to A-CHESS clients.

CONCLUSIONS

Findings illustrate that Spanish-speaking Latinos with alcohol and other drug disorders/mental disorders will use a smartphone application to assist with their recovery, continuing their access to resources, case management, and quality information after leaving residential treatment. Consistent with previous findings, our results also emphasize the importance of social support during the four months post-discharge. Such evidence-based, theory-driven digital interventions may extend access to culturally and linguistically competent services.

How Cancer Patients Use and Benefit from an Interactive Cancer Communication System

Despite the mounting evidence of efficacy of eHealth interventions, their mechanisms of action remain unknown. The current study analyzed patient log data as each patient engaged in an eHealth system called the Comprehensive Health Enhancement Support System (CHESS) and reports on how patients engage with different combinations of eHealth services over time. Newly diagnosed breast cancer patients (N = 443) were given access for 6 months to one of four different configurations of CHESS: (1) Information, (2) Information and Support, (3) Information, Support, and Coaching (Full CHESS), and (4) Full CHESS and Mentor. Besides a baseline survey, three follow-up posttests were administered. Action log data on how patients engaged with the CHESS were also collected and merged with surveys to examine how patients benefit during the cancer experience. The findings suggest that usage patterns were not competitive, implying that cancer patients' access to more complex tools generates more use with their time spreading out over the diverse services. Despite overall decline in usage rates, it was less severe in Full CHESS and Mentor condition, suggesting that communication functions drive long-term engagement with the system. Notably, the strongest relation between use and cancer information competence appeared late in the follow-up period.

Breast Cancer Survivors' Contribution to Psychosocial Adjustment of Newly Diagnosed Breast Cancer Patients in a Computer-Mediated Social Support Group

This study investigated the role of breast cancer survivors in a computer-mediated social support (CMSS) group for women with breast cancer. Applying a computer-aided content analytic method, the present study examined the differences in support provision between survivors and newly diagnosed patients. This study further investigated the impacts of survivor-provided social support on psychosocial adjustment of newly diagnosed patients. The results revealed that, compared with newly diagnosed patients, breast cancer survivors provided more emotional and informational support. Receiving emotional support from survivors contributed to an improvement in the quality of life and the depression of patients. The effects of survivor-provided informational support were not significant.

Expression and Reception: An Analytic Method for Assessing Message Production and Consumption in CMC

This article presents an innovative methodology to study computer-mediated communication (CMC), which allows analysis of the multi-layered effects of online expression and reception. The methodology is demonstrated by combining the following three data sets collected from a widely tested eHealth system, the Comprehensive Health Enhancement Support System (CHESS): 1) a flexible and precise computer-aided content analysis; 2) a record of individual message posting and reading; and 3) longitudinal survey data. Further, this article discusses how the resulting data can be applied to online social network analysis and demonstrates how to construct two distinct types of online social networks - open and targeted communication networks - for different types of content embedded in social networks.

Treatment seeking as a mechanism of change in a randomized controlled trial of a mobile health intervention to support recovery from alcohol use disorders

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.

iSurvive: An Interpretable, Event-time Prediction Model for mHealth

An important mobile health (mHealth) task is the use of multimodal data, such as sensor streams and self-report, to construct interpretable time-to-event predictions of, for example, lapse to alcohol or illicit drug use. Interpretability of the prediction model is important for acceptance and adoption by domain scientists, enabling model outputs and parameters to inform theory and guide intervention design. Temporal latent state models are therefore attractive, and so we adopt the continuous time hidden Markov model (CT-HMM) due to its ability to describe irregular arrival times of event data. Standard CT-HMMs, however, are not specialized for predicting the time to a future event, the key variable for mHealth interventions. Also, standard emission models lack a sufficiently rich structure to describe multimodal data and incorporate domain knowledge. We present iSurvive, an extension of classical survival analysis to a CT-HMM. We present a parameter learning method for GLM emissions and survival model fitting, and present promising results on both synthetic data and an mHealth drug use dataset.

What Influences Participation in QI? A Randomized Trial of Addiction Treatment Organizations

Healthcare providers have increased the use of quality improvement (QI) techniques, but organizational variables that affect QI uptake and implementation warrant further exploration. This study investigates organizational characteristics associated with clinics that enroll and participate over time in QI. The Network for the Improvement of Addiction Treatment (NIATx) conducted a large cluster-randomized trial of outpatient addiction treatment clinics, called NIATx 200, which randomized clinics to one of four QI implementation strategies: (1) interest circle calls, (2) coaching, (3) learning sessions, and (4) the combination of all three components. Data on organizational culture and structure were collected before, after randomization, and during the 18-month intervention. Using univariate descriptive analyses and regression techniques, the study identified two significant differences between clinics that enrolled in the QI study (n = 201) versus those that did not (n = 447). Larger programs were more likely to enroll and clinics serving more African Americans were less likely to enroll. Once enrolled, higher rates of QI participation were associated with clinics' not having a hospital affiliation, being privately owned, and having staff who perceived management support for QI. The study discusses lessons for the field and future research needs.

Self-Determination Theory and Computer-Mediated Support: Modeling Effects on Breast Cancer Patient's Quality-of-Life

A breast cancer diagnosis typically results in dramatic and negative effects on an individual's quality of life. Web-based interactive support systems such as the Comprehensive Health Enhancement Support System (CHESS) offer one avenue for mitigating these negative effects. While evidence supports the efficacy of such systems, evaluations typically fail to provide a true test of the theorized model of effects, treating self-determination theory's constructs of competence, relatedness, and autonomy as outcomes rather than mediators. Using path analysis, this study tests the nature of the proposed mediated relationship between system engagement and quality-of-life indicators utilizing data collected from women (N = 90) who participated in the treatment condition of a CHESS randomized controlled trial. Findings support a latent model, indicating that system effects are mediated through an intertwined measure of autonomy, competence, and relatedness.

Implementing an mHealth system for substance use disorders in primary care: a mixed methods study of clinicians' initial expectations and first year experiences

Background

Millions of Americans need but don’t receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs’ implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients’ health tracking and relapses. We examined (a) clinicians’ initial perspectives about implementing Seva, and (b) the first year of implementation at Site 1.

Methods

Prior to staggered implementation at three FQHCs (Midwest city in WI vs. rural town in MT vs. metropolitan NY), interviews, meetings, and focus groups were conducted with 53 clinicians to identify core themes of initial expectations about implementation. One year into implementation at Site 1, clinicians there were re-interviewed. Their reports were supplemented by quantitative data on clinician and patient use of Seva.

Results

Clinicians anticipated that Seva could help patients and make behavioral health appointments more efficient, but they were skeptical that physicians would engage with Seva (given high caseloads), and they were uncertain whether patients would use Seva. They were concerned about legal obligations for monitoring patients’ interactions online, including possible “cries for help” or inappropriate interactions. One year later at Site 1, behavioral health care providers, rather than physicians, had incorporated Seva into patient care, primarily by discussing it during appointments. Given workflow/load concerns, only a few key clinicians monitored health tracking/relapses and prompted outreach when needed; two researchers monitored the discussion board and alerted the clinic as needed. Clinician turnover/leave complicated this approach. Contrary to clinicians’ initial concerns, patients showed sustained, mutually supportive use of Seva, with few instances of misuse.

Conclusions

Results suggest the value of (a) focusing implementation on behavioral health care providers rather than physicians, (b) assigning a few individuals (not necessarily clinicians) to monitor health tracking, relapses, and the discussion board, (c) anticipating turnover/leave and having designated replacements. Patients showed sustained, positive use of Seva.

Trial registration

ClinicalTrials.gov (NCT01963234).

Development and Test of a Model to Predict Adherence to a Medical Regimen

Objective:

To develop a predictive model that projects patient adherence to new and existing medication regimens.

Methods:

A panel of adherence experts was convened to develop a decision theoretic model to predict and explain patient medication adherence behavior. Two predictive models were developed: one for patients new to their regimen and one for patients on an existing regimen. The models have 12 and 13 predictive factors of adherence, respectively. The panel developed levels for each factor and diagnostic value estimates for each level.

Results:

Both models were tested by having randomly generated hypothetical patient medication adherence profiles scored by the model developers and a separate panel of healthcare practitioners. These scores were then compared with predictions made by the model. For the new-to-regimen model, the correlations were 0.86 for the development panel and 0.68 for the healthcare practitioner panel. Only the practitioner panel scored the existing medication model. The model's correlation with their scores was 0.88.

Conclusions:

The medication adherence model seems to have promise as an approach to predicting the likelihood of medication adherence. The model has the benefit of considering many factors of adherence simultaneously. It can also highlight areas that may result in patient nonadherence and suggest potential intervention strategies to enhance patient adherence to a medication regimen.

A Pilot Test of a Mobile App for Drug Court Participants

The U.S. criminal justice system refers more people to substance abuse treatment than any other system. Low treatment completion rates and high relapse rates among addicted offenders highlight the need for better substance use disorder treatment and recovery tools. Mobile health applications (apps) may fill that need by providing continuous support. In this pilot test, 30 participants in a Massachusetts drug court program used A-CHESS, a mobile app for recovery support and relapse prevention, over a four-month period. Over the course of the study period, participants opened A-CHESS on average of 62% of the days that they had the app. Social networking tools were the most utilized services. The study results suggest that drug court participants will make regular use of a recovery support app.

This pilot study sought to find out if addicted offenders in a drug court program would use a mobile application to support and manage their recovery.

Using the NIATx Model to Implement User-Centered Design of Technology for Older Adults

What models can effectively guide the creation of eHealth and mHealth technologies? This paper describes the use of the NIATx model as a framework for the user-centered design of a new technology for older adults. The NIATx model is a simple framework of process improvement based on the following principles derived from an analysis of decades of research from various industries about why some projects fail and others succeed: (1) Understand and involve the customer; (2) fix key problems; (3) pick an influential change leader; (4) get ideas from outside the field; (5) use rapid-cycle testing. This paper describes the use of these principles in technology development, the strengths and challenges of using this approach in this context, and lessons learned from the process. Overall, the NIATx model enabled us to produce a user-focused technology that the anecdotal evidence available so far suggests is engaging and useful to older adults. The first and fourth principles were especially important in developing the technology; the fourth proved the most challenging to use.

Successful Organizational Strategies to Sustain Use of A-CHESS: A Mobile Intervention for Individuals With Alcohol Use Disorders

Background

Mobile health (mHealth) services are growing in importance in health care research with the advancement of wireless networks, tablets, and mobile phone technologies. These technologies offer a wide range of applications that cover the spectrum of health care delivery. Although preliminary experiments in mHealth demonstrate promising results, more robust real-world evidence is needed for widespread adoption and sustainment of these technologies.

Objective

Our aim was to identify the problems/challenges associated with sustained use of an mHealth addiction recovery support app and to determine strategies used by agencies that successfully sustained client use of A-CHESS.

Methods

Qualitative inquiry assessed staff perceptions about organizational attributes and strategies associated with sustained use of the mobile app, A-CHESS. A total of 73 interviews of clinicians and administrators were conducted. The initial interviews (n=36) occurred at the implementation of A-CHESS. Follow-up interviews (n=37) occurred approximately 12 and 24 months later. A coding scheme was developed and Multiuser NVivo was used to manage and analyze the blinded interview data.

Results

Successful strategies used by treatment providers to sustain A-CHESS included (1) strong leadership support, (2) use of client feedback reports to follow up on non-engaged clients, (3) identify passionate staff and incorporate A-CHESS discussions in weekly meetings, (4) develop A-CHESS guidelines related to client use, (5) establish internal work groups to engage clients, and (6) establish a financial strategy to sustain A-CHESS use. The study also identified attributes of A-CHESS that enhanced as well as inhibited its sustainability.

Conclusions

Mobile apps can play an important role in health care delivery. However, providers will need to develop strategies for engaging both staff and patients in ongoing use of the apps. They will also need to rework business processes to accommodate the changes in communication frequency and style, learn to use app data for decision making, and identify financing mechanisms for supporting these changes.

The effect of an information and communication technology (ICT) on older adults' quality of life: study protocol for a randomized control trial

BACKGROUND

This study investigates the use of an information and communication technology (Elder Tree) designed for older adults and their informal caregivers to improve older adult quality of life and address challenges older adults face in maintaining their independence (for example, loneliness and isolation, falling, managing medications, driving and transportation).

METHODS/DESIGN

This study, an unblinded randomized controlled trial, will evaluate the effectiveness and cost of Elder Tree. Older adults who are at risk for losing their independence - along with their informal caregivers, if they name them - are randomized to two groups. The intervention group has access to their usual sources of information and communication as well as to Elder Tree for 18 months while the control group uses only their usual sources of information and communication. The primary outcome of the study is older adult quality of life. Secondary outcomes are cost per Quality-Adjusted Life Year and the impact of the technology on independence, loneliness, falls, medication management, driving and transportation, and caregiver appraisal and mastery. We will also examine the mediating effect of self-determination theory. We will evaluate the effectiveness of Elder Tree by comparing intervention- and control-group participants at baseline and months 6, 12, and 18. We will use mixed-effect models to evaluate the primary and secondary outcomes, where pretest score functions as a covariate, treatment condition is a between-subjects factor, and the multivariate outcome reflects scores for a given assessment at the three time points. Separate analyses will be conducted for each outcome. Cost per Quality-Adjusted Life Year will be compared between the intervention and control groups. Additional analyses will examine the mediating effect of self-determination theory on each outcome.

DISCUSSION

Elder Tree is a multifaceted intervention, making it a challenge to assess which services or combinations of services account for outcomes in which subsets of older adults. If Elder Tree can improve quality of life and reduce healthcare costs among older adults, it could suggest a promising way to ease the burden that advancing age can place on older adults, their families, and the healthcare system.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02128789 . Registered on 26 March 2014.

Communication competence, psychological well-being, and the mediating role of coping efforts among women with breast cancer: cross-sectional and longitudinal evidence

Despite existing research identifying psychological benefits of patients' interpersonal competence in various contexts, little longitudinal research has addressed underlying mechanism(s). To address this limitation, we examined both the cross-sectional and longitudinal associations between cancer patients' communication competence in close relationships and psychological well-being, as well as the mediating role of coping efforts. Data came from a larger project with women with breast cancer (N = 661), recruited from April 2005 to May 2007 at three large university-affiliated cancer centers in the U.S. to study the effects of an Internet-based system providing patients and families with a range of services. The present study focused on survey data at baseline, 6 weeks, and 12 weeks after the intervention (controlling for the possible effects of the intervention). Results from both cross-sectional and longitudinal analyses indicated that competence in open communication between patients and their close support persons had a positive association with patients' psychological well-being and that approach coping efforts partially mediated this association. We discussed the implications and limitations of the study.

Social support and responsiveness in online patient communities: impact on service quality perceptions

BACKGROUND

Hospitals frequently evaluate their service quality based on the care and services provided to patients by their clinical and non-clinical staff.(1,2) However, such evaluations do not take into consideration the many interactions that patients have in online patient communities with the health-care organization (HCO) as well as with peer patients. Patients' interactions in these online communities could impact their perceptions regarding the HCO's service quality.

PURPOSES

The objective of this pilot study was to evaluate the impact of social support and responsiveness that patients experience in an HCO's online community on patients' perceptions regarding the HCO's service quality.

METHOD

The study data are collected from CHESS, a health-care programme (Comprehensive Health Enhancement Support System) run by the Centre for Health Enhancement System Studies at the University of Wisconsin-Madison.

FINDINGS

Findings show that the social support and the responsiveness received from peer patients in the online patient communities will impact patients' perceptions regarding the service quality of the HCO even when the organizational members themselves do not participate in the online discussions.

PRACTICE IMPLICATIONS

The results indicate that interactions in such HCO-provided online patient communities should not be ignored as they could translate into patients' perceptions regarding HCOs' service quality. Ways to improve responsiveness and social support in an HCO's online patient community are discussed.

Patient-clinician mobile communication: analyzing text messaging between adolescents with asthma and nurse case managers

BACKGROUND

With the increasing penetration of digital mobile devices among adolescents, mobile texting messaging is emerging as a new channel for patient-clinician communication for this population. In particular, it can promote active communication between healthcare clinicians and adolescents with asthma. However, little is known about the content of the messages exchanged in medical encounters via mobile text messaging. Therefore, this study explored the content of text messaging between clinicians and adolescents with asthma.

MATERIALS AND METHODS

We collected a total of 2,953 text messages exchanged between 5 nurse case managers and 131 adolescents with asthma through a personal digital assistant. The text messages were coded using a scheme developed by adapting categories from the Roter Interaction Analysis System.

RESULTS

Nurse case managers sent more text messages (n=2,639) than adolescents with asthma. Most messages sent by nurse case managers were targeted messages (n=2,475) directed at all adolescents with asthma, whereas there were relatively few tailored messages (n=164) that were created personally for an individual adolescent. In addition, both targeted and tailored messages emphasized task-focused behaviors over socioemotional behaviors. Likewise, text messages (n=314) sent by adolescents also emphasized task-focused over socioemotional behaviors.

CONCLUSIONS

Mobile texting messaging has the potential to play an important role in patient-clinician communication. It promotes not only active interaction, but also patient-centered communication with clinicians. In order to achieve this potential, healthcare clinicians may need to focus on socioemotional communication as well as task-oriented communication.