Feasibility of a Mobile Phone App to Support Recovery From Addiction in China: Secondary Analysis of a Pilot Study

Closing the Digital Divide in Interventions for Substance Use Disorder

Digital health interventions are exploding in today's medical practice and have tremendous potential to support the treatment of substance use disorders (SUD). Developers and healthcare providers alike must be cognizant of the potential for digital interventions to exacerbate existing inequities in SUD treatment, particularly as they relate to Social Determinants of Health (SDoH). To explore this evolving area of study, this manuscript will review the existing concepts of the digital divide and digital inequities, and the role SDoH play as drivers of digital inequities. We will then explore how the data used and modeling strategies can create bias in digital health tools for SUD. Finally, we will discuss potential solutions and future directions to bridge these gaps including smartphone ownership, Wi-Fi access, digital literacy, and mitigation of historical, algorithmic, and measurement bias. Thoughtful design of digital interventions is quintessential to reduce the risk of bias, decrease the digital divide, and create equitable health outcomes for individuals with SUD.

Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study

BACKGROUND

Artificial intelligence (AI)-powered digital therapies that detect methamphetamine cravings via consumer devices have the potential to reduce health care disparities by providing remote and accessible care solutions to communities with limited care solutions, such as Native Hawaiian, Filipino, and Pacific Islander communities. However, Native Hawaiian, Filipino, and Pacific Islander communities are understudied with respect to digital therapeutics and AI health sensing despite using technology at the same rates as other racial groups.

OBJECTIVE

In this study, we aimed to understand the feasibility of continuous remote digital monitoring and ecological momentary assessments in Native Hawaiian, Filipino, and Pacific Islander communities in Hawaii by curating a novel data set of longitudinal Fitbit (Fitbit Inc) biosignals with the corresponding craving and substance use labels. We also aimed to develop personalized AI models that predict methamphetamine craving events in real time using wearable sensor data.

METHODS

We will develop personalized AI and machine learning models for methamphetamine use and craving prediction in 40 individuals from Native Hawaiian, Filipino, and Pacific Islander communities by curating a novel data set of real-time Fitbit biosensor readings and the corresponding participant annotations (ie, raw self-reported substance use data) of their methamphetamine use and cravings. In the process of collecting this data set, we will gain insights into cultural and other human factors that can challenge the proper acquisition of precise annotations. With the resulting data set, we will use self-supervised learning AI approaches, which are a new family of machine learning methods that allows a neural network to be trained without labels by being optimized to make predictions about the data. The inputs to the proposed AI models are Fitbit biosensor readings, and the outputs are predictions of methamphetamine use or craving. This paradigm is gaining increased attention in AI for health care.

RESULTS

To date, more than 40 individuals have expressed interest in participating in the study, and we have successfully recruited our first 5 participants with minimal logistical challenges and proper compliance. Several logistical challenges that the research team has encountered so far and the related implications are discussed.

CONCLUSIONS

We expect to develop models that significantly outperform traditional supervised methods by finetuning according to the data of a participant. Such methods will enable AI solutions that work with the limited data available from Native Hawaiian, Filipino, and Pacific Islander populations and that are inherently unbiased owing to their personalized nature. Such models can support future AI-powered digital therapeutics for substance abuse.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46493.

Telehealth interventions for substance use disorders in low- and- middle income countries: A scoping review

The increasing prevalence and magnitude of harmful effects of substance use disorders (SUDs) in low- and middle-income countries (LMICs) make it imperative to embrace interventions which are acceptable, feasible, and effective in reducing this burden. Globally, the use of telehealth interventions is increasingly being explored as possible effective approaches in the management of SUDs. Using a scoping review of literature, this article summarizes and evaluates evidence for the acceptability, feasibility, and effectiveness of telehealth interventions for SUDs in LMICs. Searches were conducted in five bibliographic databases: PubMed, Psych INFO, Web of Science, Cumulative Index of Nursing and Allied Professionals and the Cochrane database of systematic review. Studies from LMICs which described a telehealth modality, identified at least one psychoactive substance use among participants, and methods that either compared outcomes using pre- and post-intervention data, treatment versus comparison groups, post-intervention data, behavioral or health outcome, and outcome of either acceptability, feasibility, and/or effectiveness were included. Data is presented in a narrative summary using charts, graphs, and tables. The search produced 39 articles across 14 countries which fulfilled our eligibility criteria over a period of 10 years (2010 to 2020). Research on this topic increased remarkably in the latter five years with the highest number of studies in 2019. The identified studies were heterogeneous in their methods and various telecommunication modalities were used to evaluate substance use disorder, with cigarette smoking as the most assessed. Most studies used quantitative methods. The highest number of included studies were from China and Brazil, and only two studies from Africa assessed telehealth interventions for SUDs. There has been an increasingly significant body of literature which evaluates telehealth interventions for SUDs in LMICs. Overall, telehealth interventions showed promising acceptability, feasibility, and effectiveness for SUDs. This article identifies gaps and strengths and suggests directions for future research.

Digital Help for Substance Users (SU): A Systematic Review

The estimated number of Substance Users (SU) globally has currently reached a very high number and is still increasing. This aspect necessitates appropriate interventions for prevention and specific treatments. The literature shows that digital treatments can be useful in the context of health services and substance abuse. This systematic review focuses mainly on research on the effectiveness of digital treatments for SU. Data sources included studies found on PsycINFO, PubMed, SCOPUS, and WebOfScience (WOS) database searches. The following keywords were used: TITLE (digital OR computer OR software OR tablet OR app OR videogame OR seriousgame OR virtualreality) AND ABSTRACT((mental AND health) AND (addiction OR dependence OR substance OR drug)). We focused on peer-reviewed articles published from 2010 through 2021 using PRISMA guidelines. A total of 18 studies met the inclusion criteria (i.e., type of intervention, efficacy in terms of misuse of substances and scored outcomes from questionnaire or toxicology tests, study methodology). The studies included investigations of specific digital treatments for SU of various kinds of drugs. The interventions were administered using personal computers, smartphones, or, in a few cases, tablets. Most of the interventions focused on the cognitive behavior therapy (CBT) model and/or on the use strategies, tips, or feedback. A minority provided information or training programs. The current review shows that digital treatments and interventions are effective in reducing the frequency of use, augmenting abstinence, or reducing the gravity of dependence for most of the studies at post-treatment. However, due to the heterogeneity of the variables (i.e., substance type, digital tool used, and treatment administered), there was a reduced generalizability of the results. This review highlights the need to continue the research in this field, and above all, to create effective digital protocols.

Ecological Momentary Assessment: A Systematic Review of Validity Research

Ecological momentary assessment (EMA) is a self-report method that involves intensive longitudinal assessment of behavior and environmental conditions during everyday activities. EMA has been used extensively in health and clinical psychology to investigate a variety of health behaviors, including substance use, eating, medication adherence, sleep, and physical activity. However, it has not been widely implemented in behavior analytic research. This is likely an example of the empirically based skepticism with which behavioral scientists view self-report measures. We reviewed studies comparing electronic, mobile EMA (mEMA) to more objective measures of health behavior to explore the validity of mEMA as a measurement tool, and to identify procedures and factors that may promote the accuracy of mEMA. We identified 32 studies that compared mEMA to more objective measures of health behavior or environmental events (e.g., biochemical measures or automated devices such as accelerometers). Results showed that the correspondence rates varied considerably across individuals, behavior, and studies (agreement rates ranged from 1.8%-100%), and no unifying variables could be identified across the studies that found high correspondence. The findings suggest that mEMA can be an accurate measurement tool, but further research should be conducted to identify procedures and variables that promote accurate responding.

Clear the fog of negative emotions: A new challenge for intervention towards drug users

BACKGROUND

The psychological and emotional problems of drug users are a focus of research. However, quick and effective emotion assessment tools were scarce. We aimed to use facial expression recognition to assess the emotional states of drug users.

METHODS

Our study was conducted in Chengdu City, Sichuan Province, China from January 1, 2020 to June 30, 2020. The 69 drug users who were undergoing community-based treatment were recruited. We developed an app to collect their images and videos, and trained the deep learning model to assess their emotional states. We also explored the correlation between emotional changes and treatment time, and investigated the impact factors associated with emotional changes.

RESULTS

Based on the continuous 6-month follow-up study, the emotional distribution of drug users was still dominated by negative emotions during community treatment (72.85%). Nevertheless, with the increase of treatment time, 17.39% of drug users' emotions were changing better. Results also showed that compared with the females, males were less likely to have positive emotion change. In addition, the females were more willing to read reply messages from social workers.

LIMITATIONS

The relatively short observation period could be extended, and voice data should be considered for analysis in the future.

CONCLUSIONS

Social workers should pay attention to emotional states of drug users, and provide effective and gender-specific psychological interventions for them. In addition, as a more powerful "medicine", it is essential to strengthen the accessibility of humanistic care and services to help drug users maintain a positive attitude.

Digital mental health in China: a systematic review

Mental health problems are highly prevalent in China; however, China's mental health services lack resources to deliver high-quality care to people in need. Digital mental health is a promising solution to this short-fall in view of the population's digital literacy. In this review, we aim to: (i) investigate the effectiveness, acceptability, usability, and safety of digital health technologies (DHTs) for people with mental health problems in China; (ii) critically appraise the literature; and (iii) make recommendations for future research directions. The databases MEDLINE, PsycINFO, EMBASE, Web of Science, CNKI, WANFANG, and VIP were systemically searched for English and Chinese language articles evaluating DHTs for people with mental health problems in mainland China. Eligible studies were systematically reviewed. The heterogeneity of studies included precluded a meta-analysis. In total, 39 articles were retrieved, reporting on 32 DHTs for various mental health problems. Compared with the digital mental health field in the West, the Chinese studies targeted schizophrenia and substance use disorder more often and investigated social anxiety mediated by shame and culturally specific variants, DHTs were rarely developed in a co-production approach, and methodology quality was less rigorous. To our knowledge, this is the first systematic review focused on digital mental health in the Chinese context including studies published in both English and the Chinese language. DHTs were acceptable and usable among Chinese people with mental health problems in general, similar to findings from the West. Due to heterogeneity across studies and a paucity of robust control trial research, conclusions about the efficacy of DHTs are lacking.

PSIXPORT: Mobile App for Ecological Momentary Assessment of Psychological Dimensions in Sport Injury

Retrospective self-reports have been commonly used to assess psychological variables such as feelings, thoughts, or emotions. Nevertheless, this method presents serious limitations to gather accurate information about variables that change over time. The Ecological Momentary Assessment (EMA) approach has been used to deal with some of the limitations these retrospective assessment methods present, and for gathering real-time information about dynamic psychological variables, such as feelings, thoughts, or behaviors. In the sports injury rehabilitation context, athletes' thoughts, feelings, behaviors, and pain perceptions during the rehabilitation process can influence the outcomes of this process. These responses change over different stages of the rehabilitation and taking them into account can help therapists to adapt the rehabilitation process and increasing their effectiveness. With this aim, an EMA mobile app (PSIXPORT) was designed to gather real-time information about severely injured athletes' cognitive appraisals, emotional responses, behaviors, and pain perceptions during their rehabilitation process. The goals of this study were to evaluate Psixport's ability to gather real-time information about injured athletes' psychological responses during the rehabilitation, to test the users' perceived usability of Psixport, and to compare the reliability and differences between real-time data gathered with Psixport and the data gathered through the one-time retrospective method. Twenty-eight severely injured athletes (10 men and 18 women) were assessed using Psixport, a retrospective questionnaire, and the uMARS usability test. Results showed that Psixport can be considered as a good tool to gather information about injured athletes' cognitive appraisals, emotional responses, behaviors, and pain perceptions. Moreover, multiple data assessments gathered with the app showed to be more accurate information about injured athletes' psychological responses than one-time retrospective reports.

Feasibility and Preliminary Efficacy of a Community-Based Addiction Rehabilitation Electronic System in Substance Use Disorder: Pilot Randomized Controlled Trial

BACKGROUND

Drug use disorder has high potential for relapse and imposes an enormous burden on public health in China. Since the promulgation of the Anti-drug law in 2008, community-based rehabilitation has become the primary approach to treat drug addiction. However, multiple problems occurred in the implementation process, leading to a low detoxification rate in the community. Mobile health (mHealth) serves as a promising tool to improve the effectiveness and efficiency of community-based rehabilitation. Community-based addiction rehabilitation electronic system (CAREs) is an interactive system for drug users and their assigned social workers.

OBJECTIVE

The study aimed to examine the feasibility and preliminary efficacy of CAREs in community-based rehabilitation from the perspective of drug users and social workers in Shanghai, China.

METHODS

In this pilot randomized controlled trial, 40 participants were recruited from the community in Shanghai from January to May 2019. Participants randomized to the intervention group (n=20) received CAREs + community-based rehabilitation, while participants in the control group (n=20) received community-based rehabilitation only for 6 months. CAREs provided education, assessment, and SOS (support) functions for drug users. The assigned social workers provided service and monitored drug use behavior as usual except that the social workers in the intervention group could access the webpage end to obtain drug users' information and fit their routine workflow into CAREs. The primary outcome was the feasibility of CAREs, reflected in the overall proportion and frequency of CAREs features used in both app and webpage end. The secondary outcomes were the effectiveness of CAREs, including the percentage of drug-positive samples, longest period of abstinence, contact times with social workers, and the change of Addiction Severity Index (ASI) from baseline to the 6-month follow-up.

RESULTS

The number of participants logged in to the app ranged from 7 to 20 per week, and CAREs had relatively high levels of continued patient use. Drug users preferred assessment and education features in the app end while their social workers showed high levels of use in urine results record and viewing assessment results on the webpage end. After the 6-month intervention, 3.3% (17/520) of samples in the intervention group and 7.5% (39/520) in the control group were drug-positive (F=4.358, P=.04). No significant differences were noted between the control and intervention groups in terms of longest duration of abstinence, number of contact times and ASI composite scores.

CONCLUSIONS

The study preliminarily demonstrated that with relatively good feasibility and acceptability, CAREs may improve the effectiveness and efficiency of the community-based rehabilitation, which provided instruction for further improvement of the system.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03451344; https://clinicaltrials.gov/ct2/show/NCT03451344.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.3389/fpsyt.2018.00556.

The emergence of digital mental health in low-income and middle-income countries: A review of recent advances and implications for the treatment and prevention of mental disorders

In low-income and middle-income countries (LMICs), emerging digital mental health interventions should be accompanied by regular and comprehensive assessment of available scientific evidence. This review aims to support efforts to monitor progress in digital mental health research, ensuring new evidence can guide researchers, clinicians, policymakers and program managers positioned to adopt and implement these digitally-enabled treatments. In accordance with PRISMA guidelines, an electronic database search from 2016 to 2020 yielded 37 digital intervention studies for detection, diagnosis, prevention, treatment, and/or management of a broad range of mental disorders in 13 LMICs. This date range was selected to update previous reviews. Most studies involved online interventions and many reported feasibility and acceptability, reflected by participant satisfaction or program adherence. About half the studies (N = 23) reported clinical benefits based on changes in mental health. For depression and mood disorders, some digital interventions showed improvements in depressive symptoms, quality of life, treatment adherence, and recovery. However, sample sizes were small and studies focused primarily on adults. Further limiting generalizability was the lack of consistency in clinical assessment and measurement tools between studies. No studies reported worsening symptoms, negative acceptability or dissatisfaction with digital interventions, suggesting possible publication bias. While digital interventions show promise, it remains difficult to conclude that digital interventions are effective from these studies, as it is prudent to exercise caution before drawing conclusions about clinical effectiveness. This review reflects continued growth in digital mental health research in LMICs and further highlights the need for rigorous evaluation of effectiveness and cost-effectiveness.

Current reporting of usability and impact of mHealth interventions for substance use disorder: A systematic review

BACKGROUND

Connected interventions use data collected through mobile/wearable devices to trigger real-time interventions and have great potential to improve treatment for substance use disorder (SUD). This review aims to describe the current landscape, effectiveness and usability of connected interventions for SUD.

METHODS

A systematic review was conducted to identify articles evaluating connected health interventions for SUD in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three databases (PubMed, IEEE, and Scopus) were searched over a five-year period. Included articles described a connected health intervention targeting SUD and provided outcomes data. Data were extracted using a standardized reporting tool.

RESULTS

A total of 1676 unique articles were identified during the initial search, with 32 articles included in the final analysis. Seven articles of the 32 were derived from two large studies. The most commonly studied SUD was alcohol use disorder. Sixteen articles reported at least one statistically significant result with respect to reduced craving and/or substance use. The majority of articles used ecological momentary assessment to trigger interventions, while four used biologic/physiologic data. Two articles used a wearable device. Common intervention types included craving management, coping assistance, and tailored feedback. Twenty-three articles measured usability factors, and acceptability was generally reported as high.

CONCLUSION

Identified themes included a focus on AUD, use of smart phones, use of EMA for intervention delivery, positive effects on SUD related outcomes, and overall high acceptability. Wearables that directly monitor biologic data and predictive analytics using integrated data streams represent understudied opportunities for new research.

Mobile health interventions in developing countries: A systematic review

This study reviews the quality of evidence reported in mobile health intervention literature in the context of developing countries. A systematic search of renowned databases was conducted to find studies related to mobile health applications published between a period of 2013 and 2018. After a methodological screening, a total of 31 studies were included for data extraction and synthesis. The mobile health Evidence Reporting and Assessment checklist developed by the World Health Organization was then used to evaluate the rigor and completeness in evidence reporting. We report several important and interesting findings. First, there is a very low level of familiarity with the mobile health Evidence Reporting and Assessment checklist among the researchers and mobile health intervention designers from developing countries. Second, most studies do not adequately meet the essential criteria of evidence reporting mentioned in the mobile health Evidence Reporting and Assessment checklist. Third, there is a dearth of application of design science-based methods and theory-based frameworks in developing mobile health interventions. Fourth, most of the mobile health interventions are not ready for interoperability and to be integrated into the existing health information systems. Based on these findings, we recommend for robust and inclusive study plans to deliver highly evidence-based reports by mobile health intervention studies that are conducted in the context of developing countries.

Impact of Mobile Phone-Based Interventions on Methamphetamine Use and High-risk Sexual Behaviors in Men Who Have Sex with Men (MSM): A Systematic Review

Background

Today, increased use of methamphetamine in homosexual men is associated with high-risk sexual behaviors and (HIV) epidemic. Mobile phone-based interventions are an accessible and rapid method to provide healthcare services to this population. This study aimed to systematically review the effects of mobile phone-based interventions on methamphetamine use and high-risk sexual behaviors in homosexual men.

Methods

This systematic review was conducted by two researchers via searching in PubMed, Google Scholar, Web of Science, Scopus, and PsycINFO databases to retrieve the published articles regarding the effects of mobile phone-based interventions on the control of methamphetamine use and high-risk sexual behaviors.

Findings

Among 250 unique articles that were retrieved, only five cases met all the inclusion criteria of the study. Accordingly, some of the applied interventions included text messaging (n = 4) and mobile apps (n = 1). In this regard, the use of text messaging significantly decreased the rates of methamphetamine use, condomless anal intercourse (CAI), and HIV transmission among homosexual men.

Conclusion

According to the results, short-term interventions based on text messaging could decrease the rates of methamphetamine use and the high-risk sexual behaviors associated with HIV infection in homosexual men. Despite the positive impact of these interventions, long-term follow-ups are required for individuals using methamphetamine in different communities.

Review and Implementation of Self-Help and Automated Tools in Mental Health Care

Self-help and automated technologies can be useful for behavioral and mental health education and interventions. These technologies include interactive media, online courses, artificial intelligence-powered chatbots, voice assistants, and video games. Self-help media can include books, videos, audible media like podcasts, blog and print articles, and self-contained Internet sites. Social media, online courses, and mass-market mobile apps also can include such media. These technologies serve to decrease geospatial, temporal, and financial barriers. This article describes different self-help and automated technologies, how to implement such technologies in existing clinical services, and how to implement according to patient needs.

Common themes and emerging trends for the use of technology to support mental health and psychosocial well-being in limited resource settings: A review of the literature

There are significant disparities in access to mental health care. With the burgeoning of technologies for health, digital tools have been leveraged within mental health and psychosocial support programming (eMental health). A review of the literature was conducted to understand and identify how eMental health has been used in resource-limited settings in general. PubMed, Ovid Medline and Web of Science were searched. Six-hundred and thirty full-text articles were identified and assessed for eligibility; of those, 67 articles met the inclusion criteria and were analyzed. The most common mental health use cases were for depression (n = 25) and general mental health and well-being (n = 21). Roughly one-third used a website or Internet-enabled intervention (n = 23) and nearly one-third used an SMS intervention (n = 22). Technology was applied to enhance service delivery (n = 32), behavior change communication (n = 26) and data collection (n = 8), and specifically dealt with adherence (n = 7), ecological momentary assessments (n = 7), well-being promotion (n = 5), education (n = 8), telemedicine (n = 28), machine learning (n = 5) and games (n = 2). Emerging trends identified wearables, predictive analytics, robots and virtual reality as promising areas. eMental health interventions that leverage low-tech tools can introduce, strengthen and expand mental health and psychosocial support services and can be a starting point for future, advanced tools.

A systematic review of mobile health interventions in China: Identifying gaps in care

INTRODUCTION

Mobile health has a promising future in the healthcare system in most developed countries. China's rapidly developing mobile technology infrastructure offers an unprecedented opportunity for wide adoption of mobile health interventions in the delivery of effective and timely healthcare services. However, there is little data on the current extent of the mobile health landscape in China. The aim of this study was to systematically review the existing mobile health initiatives in China, characterise the technology used, disease categories targeted, location of the end user (urban versus rural), and examine the potential effects of mobile health on health system strengthening in China. Furthermore, we identified gaps in development and evaluation of the effectiveness of mobile health interventions.

METHODS

A systematic review of the literature published from 18 December 2015 - 3 April 2019 was conducted and yielded 2863 articles from English and Chinese retrieval database and trial registries, including PubMed, EMBASE, China National Knowledge of Infrastructure and World Health Organization International Clinical Trials Registry Platform. Studies were included if they used mobile health to support patient healthcare outcomes.

RESULTS

A total of 1129 full-text articles were assessed and 338 were included in this study. The review found that most studies targeted client education and behaviour change via applications (apps) (65.4%), including WeChat, and text messaging (short text messages) (19.8%) to improve patient medical treatment outcomes such as compliance and appointment reminders. The most common disease-specific mobile health interventions focused primarily on chronic disease management and behaviour change in cardiology (13.3%), endocrinology/diabetes (12.1%), behavioural health (11.8%), oncology (11.2%) and neurology (6.8%). The mobile health interventions related to nutrition (0.6%) and chronic respiratory diseases (1.6%) are underrepresented in mobile health in comparison to the burden of disease in China. The majority (90.0%) of the mobile health interventions were conducted exclusively in urban areas, with few opportunities reaching rural populations.

CONCLUSIONS

Overall, mobile health has a promising future in China, with recent rapid growth in initiatives. The majority are focused on education and behaviour change in the realm of chronic diseases and target patients in urban areas. The imbalance in mobile health between the urban and rural areas, as well as between population disease spectrum and health service delivery, pose substantial dilemmas. However, mobile health may be redirected to correct this imbalance, possibly improving access to healthcare services, and filling the gaps in order to improve health equity for the underserved populations in China.