Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia

Using Monte Carlo Simulation to Forecast the Scientific Utility of Psychological App Studies: A Tutorial

Mobile applications offer a wide range of opportunities for psychological data collection, such as increased ecological validity and greater acceptance by participants compared to traditional laboratory studies. However, app-based psychological data also pose data-analytic challenges because of the complexities introduced by missingness and interdependence of observations. Consequently, researchers must weigh the advantages and disadvantages of app-based data collection to decide on the scientific utility of their proposed app study. For instance, some studies might only be worthwhile if they provide adequate statistical power. However, the complexity of app data forestalls the use of simple analytic formulas to estimate properties such as power. In this paper, we demonstrate how Monte Carlo simulations can be used to investigate the impact of app usage behavior on the utility of app-based psychological data. We introduce a set of questions to guide simulation implementation and showcase how we answered them for the simulation in the context of the guessing game app Who Knows (Rau et al., 2023). Finally, we give a brief overview of the simulation results and the conclusions we have drawn from them for real-world data generation. Our results can serve as an example of how to use a simulation approach for planning real-world app-based data collection.

Prescription digital therapeutics: An emerging treatment option for negative symptoms in schizophrenia

Digital therapeutics-web-based programs, smartphone applications, and wearable devices designed to prevent, treat, or manage clinical conditions through software-driven, evidence-based intervention-can provide accessible alternatives and/or may supplement standard care for patients with serious mental illnesses (SMI), including schizophrenia. In this paper we provide a targeted summary of the rapidly growing field of digital therapeutics for schizophrenia and related SMI. We first define digital therapeutics. We then provide a brief summary of the emerging evidence of efficacy of digital therapeutics for improving clinical outcomes, focusing on potential mechanisms of action for addressing some of the most challenging problems, including negative symptoms of psychosis. Our focus on these promising targets for digital therapeutics, including the latest in prescription models in the commercial space, highlights future directions for research and practice in this exciting field.

The role of human involvement and support in digital mental health interventions for people with schizophrenia spectrum disorders: a critical review

PURPOSE OF REVIEW

Schizophrenia spectrum disorders (SDD) are characterized by a complex array of psychosis symptoms, and typically require ongoing and long-term support, including pharmacological and nonpharmacological management. Digital mental health interventions (DMHIs) have been suggested as a novel therapeutic approach to enable low-cost, scalable improvements in quality of care for adults living with SSD. However, the types and role of human involvement and support within DMHIs is currently unknown.

RECENT FINDINGS

Several recent systematic reviews and meta-analyses have investigated the potential efficacy of DMHIs for people with SSD, with scant yet emerging systematic evidence on the effects of human support within DMHIs on mental health outcomes. Further, several recent individual studies examined the efficacy of DMHIs with human support among people with SSD and provided valuable insights into the potential key elements of such support on outcomes relevant to this population.

SUMMARY

The current critical review provides the first narrative synthesis of available evidence to guide clinicians and intervention develops in designing DMHIs with adequate human support that may enhance long-term outcomes of people living with SSD.

A systematic review of users experiences of using digital interventions within psychosis: a thematic synthesis of qualitative research

PURPOSE

Although the development of digital mental health support for people with psychosis has been increasing, the development and opportunities to access this have been more limited compared to other mental health conditions. Qualitative research exploring the experiences of using digital interventions amongst people with psychosis is even less well developed; however, such research is crucial in capturing the experiences of using digital interventions to ensure they are meeting the needs of people with psychosis. This paper aimed to synthesise qualitative data related to the experiences of people with psychosis who have used digital interventions.

METHODS

A systematic literature search was conducted of articles published between 1992 and October 2023 using PubMed, MBase, PsycINFO, & OVID Medline. Two reviewers independently reviewed and screened 268 papers. Papers that met inclusion criteria were quality assessed using The Critical Appraisal Skills Programme (CASP) qualitative studies checklist. The Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) checklist was used to guide the structure of the report.

RESULTS

A thematic synthesis of 19 studies revealed six overarching themes which related to different aspects and features of the digital interventions: participants' relationship with technology; the accessibility of the interventions; how the interventions could impact on individuals' awareness and management of mental health; enhanced communication and relationships; and opportunities for reflection.

CONCLUSIONS

Benefits of using digital interventions are discussed. Areas for development and improvements are highlighted. Finally, recommendations for stakeholders who develop and implement digital interventions for psychosis are made.

Assistive technology services for adults with disabilities in state-federal vocational rehabilitation programs

PURPOSE

Prior research indicates that the provision of assistive technology (AT) services positively predicts successful employment outcomes in vocational rehabilitation (VR) programs. While AT services can be promising, they are underutilized overall, and there are apparent disparities in AT service utilization. The purpose of this study was to identify sociodemographic factors which may act as barriers to receiving AT services in VR programs. Recognizing potential disparities is the first step in improving equity in access to beneficial services.

MATERIALS AND METHODS

This study is a retrospective analysis of national data collected by the Rehabilitation Service Administration's Case Service Report from fiscal years 2017-2019. The sample included 788,173 cases that reported having a disability, were aged ≥18 years old, was deemed eligible for VR services, and had a complete set of data.

RESULTS

Less than 9% of VR clients received AT services. We ran a multiple logistic regression analysis to examine the independent effects of various sociodemographic variables on the likelihood of receiving AT services through VR programs. The following client characteristics were associated with a lower likelihood of receiving AT services: men, unemployed, minority, low income, significant disability, non-enrolled in post-secondary education, mental or cognitive disability, less education, and younger age (all p < .001).

CONCLUSION

The findings emphasize the need for more research to identify underlying mechanisms and potential solutions to these apparent disparities in access to AT services for adults with disabilities. Future research and implications are provided.

Predicting the onset of psychotic experiences in daily life with the use of ambulatory sensor data - A proof-of-concept study

INTRODUCTION

Predictive models of psychotic symptoms could improve ecological momentary interventions by dynamically providing help when it is needed. Wearable sensors measuring autonomic arousal constitute a feasible base for predictive models since they passively collect physiological data linked to the onset of psychotic experiences. To explore this potential, we investigated whether changes in autonomic arousal predict the onset of hallucination spectrum experiences (HSE) and paranoia in individuals with an increased likelihood of experiencing psychotic symptoms.

METHOD

For 24 h of ambulatory assessment, 62 participants wore electrodermal activity and heart rate sensors and were provided with an Android smartphone to answer questions about their HSE-, and paranoia-levels every 20 min. We calculated random forests to detect the onset of HSEs and paranoia. The generalizability of our models was tested using leave-one-assessment-out and leave-one-person-out cross-validation.

RESULTS

Leave-one-assessment-out models that relied on physiological data and participant ID yielded balanced accuracy scores of 80 % for HSE and 66 % for paranoia. Adding baseline information about lifetime experiences of psychotic symptoms increased balanced accuracy to 82 % (HSE) and 70 % (paranoia). Leave-one-person-out models yielded lower balanced accuracy scores (51 % to 58 %).

DISCUSSION

Using passively collectible variables to predict the onset of psychotic experiences is possible and prediction models improve with additional information about lifetime experiences of psychotic symptoms. Generalizing to new individuals showed poor performance, so including personal data from a recipient may be necessary for symptom prediction. Completely individualized prediction models built solely with the data of the person to be predicted might increase accuracy further.

Cost of Implementing mHealth in Community Mental Health Settings: External Versus Internal Facilitation

OBJECTIVE

This study aimed to compare the costs of two implementation models for the mobile health (mHealth) intervention FOCUS in community mental health settings. The external facilitation (EF) approach uses a hub-and-spoke model, in which a central specialist provides support to clinicians and clients at multiple agencies. With the internal facilitation (IF) approach, frontline clinical staff at each center are trained to serve as their organization's local specialists.

METHODS

Financial and economic cost data were collected in the context of a hybrid type 3 effectiveness-implementation trial by using a mixed-methods, top-down expenditure analysis with microcosting approaches. The analysis compared the incremental costs of both models and the costs of successfully engaging clients (N=210) at 20 centers. Costs were characterized as start-up or recurrent (personnel, supplies, contracted services, and indirect costs).

RESULTS

The average annual financial cost per site was $23,517 for EF and $19,118 for IF. EF yielded more FOCUS users at each center, such that the average monthly financial costs were lower for EF ($167 per client [N=129]) than for IF ($177 per client [N=81]). When using a real-world scenario based on economic costs and a lower organizational indirect rate, the average monthly cost per client was $73 for EF and $59 for IF. Both models reflected substantial cost reductions (about 50%) relative to a previous deployment of FOCUS in a clinical trial.

CONCLUSIONS

Compared with IF, EF yielded more clients who received mHealth at community mental health centers and had comparable or lower costs.

A Hybrid Type 1 trial of a multi-component mHealth intervention to improve post-hospital transitions of care for patients with serious mental illness: Study protocol

BACKGROUND

The transition from acute (e.g., psychiatric hospitalization) to outpatient care is associated with increased risk for rehospitalization, treatment disengagement, and suicide among people with serious mental illness (SMI). Mobile interventions (i.e., mHealth) have the potential to increase monitoring and improve coping post-acute care for this population. This protocol paper describes a Hybrid Type 1 effectiveness-implementation study, in which a randomized controlled trial will be conducted to determine the effectiveness of a multi-component mHealth intervention (tFOCUS) for improving outcomes for adults with SMI transitioning from acute to outpatient care.

METHODS

Adults meeting criteria for schizophrenia-spectrum or major mood disorders (n = 180) will be recruited from a psychiatric hospital and randomized to treatment-as-usual (TAU) plus standard discharge planning and aftercare (CHECK-IN) or TAU plus tFOCUS. tFOCUS is a 12-week intervention, consisting of: (a) a patient-facing mHealth smartphone app with daily self-assessment prompts and targeted coping strategies; (b) a clinician-facing web dashboard; and, (c) mHealth aftercare advisors, who will conduct brief post-hospital clinical calls with patients (e.g., safety concerns, treatment engagement) and encourage app use. Follow-ups will be conducted at 6-, 12-, and 24-weeks post-discharge to assess primary and secondary outcomes, as well as target mechanisms. We also will assess barriers and facilitators to future implementation of tFOCUS via qualitative interviews of stakeholders and input from a Community Advisory Board throughout the project.

CONCLUSIONS

Information gathered during this project, in combination with successful study outcomes, will inform a potential tFOCUS intervention scale-up across a range of psychiatric hospitals and healthcare systems.

CLINICALTRIALS

govregistration: NCT05703412.

Stakeholder perspectives on adjunctive mHealth services during transitions of care for patients with schizophrenia-spectrum disorders

BACKGROUND

A growing body of research focuses on developing and testing interventions that leverage mental health-related mobile health (mHealth) services for patients with schizophrenia and other schizophrenia-spectrum disorders. Yet, most formative research has focused on patient perspectives, with little attention paid to clinical stakeholders.

AIMS

This qualitative study aimed to explore clinical stakeholders' (i.e., administrative supervisors, support staff, and clinicians) perspectives on what might help or hinder the use of mHealth, particularly when patients transition from inpatient to outpatient care.

METHODS

In-depth individual qualitative interviews were conducted with 18 stakeholders from inpatient and outpatient psychiatric settings.

RESULTS

Four key themes were identified: (a) adherence challenges; (b) role of mobile technology in patient care; (c) clinical professionals' receptiveness to adjunctive mHealth services; and, (d) costs related to implementation of mHealth services.

CONCLUSIONS

Overall, stakeholders agree with extant data showing that supportive networks are important in facilitating patients' return to the community following hospitalization. Stakeholders welcome mHealth services but suggest they should be appropriately tailored to the population, both in terms of usability and connection to ongoing traditional treatments. Demonstration of added value will likely facilitate wider implementation of mHealth services in the care of patients with schizophrenia and other schizophrenia-spectrum disorders.

Mobile health for mental health support: a survey of attitudes and concerns among mental health professionals in Poland over the period 2020-2023

Introduction

Mobile health (mHealth) has emerged as a dynamic sector supported by technological advances and the COVID-19 pandemic and have become increasingly applied in the field of mental health.

Aim

The aim of this study was to assess the attitudes, expectations, and concerns of mental health professionals, including psychiatrists, psychologists, and psychotherapists, towards mHealth, in particular mobile health self-management tools and telepsychiatry in Poland.

Material and methods

This was a survey conducted between 2020 and 2023. A questionnaire was administered to 148 mental health professionals, covering aspects such as telepsychiatry, mobile mental health tools, and digital devices.

Results

The majority of professionals expressed readiness to use telepsychiatry, with a peak in interest during the COVID-19 pandemic, followed by a gradual decline from 2022. Concerns about telepsychiatry were reported by a quarter of respondents, mainly related to difficulties in correctly assessing the patient's condition, and technical issues. Mobile health tools were positively viewed by professionals, with 86% believing they could support patients in managing mental health and 74% declaring they would recommend patients to use them. Nevertheless, 29% expressed concerns about the effectiveness and data security of such tools. Notably, the study highlighted a growing readiness among mental health professionals to use new digital technologies, reaching 84% in 2023.

Conclusion

These findings emphasize the importance of addressing concerns and designing evidence-based mHealth solutions to ensure long-term acceptance and effectiveness in mental healthcare. Additionally, the study highlights the need for ongoing regulatory efforts to safeguard patient data and privacy in the evolving digital health landscape.

Experiencing hallucinations in daily life: The role of metacognition

BACKGROUND

Hallucinations have been linked to failures in metacognitive reflection suggesting an association between hallucinations and overestimation of performance, although the cross-sectional findings are inconsistent. This inconsistency may relate to the fluctuating hallucinatory experiences that are not captured in cross-sectional studies. Ecological Momentary Assessment (EMA) captures in-the-moment experiences over time so can identify causal relationships between variables such as the associations between metacognition and hallucinatory experience in daily life and overcome problems in cross-sectional designs.

METHODS

Participants (N = 41) experiencing daily hallucinations completed baseline questionnaires and smartphone surveys 7 times per day for 14 days. They were prompted to identify a task they would complete in the next 4 h and to make metacognitive predictions around the likelihood of completing the task, the difficulty of the task, and how well they would complete it (standard of completion).

RESULTS

76 % finished the 14-days of assessment with an average of 42.2 % survey completion. Less accurate metacognition was associated with more hallucinations, but less accurate likelihood and standard of completion was associated with fewer hallucinations. Using a cross-lagged analysis, metacognitive predictions around the likelihood of completion (p < .001) and standard of completion (p = .01) predicted hallucination intensity at the following timepoint, and metacognitive predictions regarding likelihood of completion (p = .02) predicted hallucination control at the following timepoint.

DISCUSSION

Interventions that aim to improve metacognitive ability in-the-moment may serve to reduce the intensity and increase the control of hallucinations.

Just-in-time adaptive ecological momentary assessment (JITA-EMA)

Interest in just-in-time adaptive interventions (JITAI) has rapidly increased in recent years. One core challenge for JITAI is the efficient and precise measurement of tailoring variables that are used to inform the timing of momentary intervention delivery. Ecological momentary assessment (EMA) is often used for this purpose, even though EMA in its traditional form was not designed specifically to facilitate momentary interventions. In this article, we introduce just-in-time adaptive EMA (JITA-EMA) as a strategy to reduce participant response burden and decrease measurement error when EMA is used as a tailoring variable in JITAI. JITA-EMA builds on computerized adaptive testing methods developed for purposes of classification (computerized classification testing, CCT), and applies them to the classification of momentary states within individuals. The goal of JITA-EMA is to administer a small and informative selection of EMA questions needed to accurately classify an individual's current state at each measurement occasion. After illustrating the basic components of JITA-EMA (adaptively choosing the initial and subsequent items to administer, adaptively stopping item administration, accommodating dynamically tailored classification cutoffs), we present two simulation studies that explored the performance of JITA-EMA, using the example of momentary fatigue states. Compared with conventional EMA item selection methods that administered a fixed set of questions at each moment, JITA-EMA yielded more accurate momentary classification with fewer questions administered. Our results suggest that JITA-EMA has the potential to enhance some approaches to mobile health interventions by facilitating efficient and precise identification of momentary states that may inform intervention tailoring.

Developing the Workforce of the Digital Future: mHealth Competency and Fidelity Measurement in Community-Based Care

Integrating mobile health (mHealth) interventions into settings that serve diverse patient populations requires that prerequisite professional competencies are delineated and that standards for clinical quality assurance can be pragmatically assessed. Heretofore, proposed mHealth competencies have been broad and have lacked a framework to support specific applications. We outline the meta-competencies identified in the literature relevant to mHealth interventions and demonstrate how these meta-competencies can be integrated with population- and intervention-related competencies to help guide a pragmatic approach to competency assessment. We present a use case based on FOCUS-an evidence-based mHealth intervention designed for individuals with serious mental illness and currently being implemented in geographically and demographically diverse community behavioral health settings. Subsequent to identifying the cross-cutting competencies relevant to the target population (outpatients experiencing psychotic symptoms), substratal intervention (Cognitive Behavioral Therapy for psychosis), and treatment modality (mHealth), we detail the development process of an mHealth fidelity monitoring system (mHealth-FMS). We adhered to a published sequential 5-step process to design a fidelity monitoring system that aligns with our integrated mHealth competency framework and that was guided by best practices prescribed by the Treatment Fidelity Workgroup of the National Institutes of Health Behavior Change Consortium. The mHealth-FMS is intended to enhance both clinical and implementation outcomes by grounding the mHealth interventionist and the system of care in which they operate in the core functions, tasks, knowledge, and competencies associated with system-integrated mHealth delivery. Future research will explore acceptability and feasibility of the mHealth-FMS.

Prevalence, attitudes and concerns toward telepsychiatry and mobile health self-management tools among patients with mental disorders during and after the COVID-19 pandemic: a nationwide survey in Poland from 2020 to 2023

Introduction

Mobile Health (mHealth) is a rapidly growing field of medicine that has the potential to significantly change everyday clinical practice, including in psychiatry. The COVID-19 pandemic and technological developments have accelerated the adoption of telepsychiatry and mobile solutions, but patient perceptions and expectations of mHealth remain a key factor in its implementation.

Aim

The aim of this study was to assess (1) the prevalence, (2) attitudes, preferences and (3) concerns about mobile mental health, including telepsychiatry and self-management tools, among patients with mental disorders over the period 2020-2023, i.e., at the onset, peak and after the expiration of the COVID-19 pandemic.

Materials and methods

A semi-structured survey was administrated to 354 patients with mental disorders in Poland. The questions were categorized into three section, addressing prevalence, attitudes, and concerns about telepsychiatry and mobile health self-management tools. The survey was conducted continuously from May 2020 to the end of May 2023.

Result

As many as 95.7% of patients with mental disorders used mobile devices at least once a week. Over the course of 3 years (from 2020 to 2023), there was a significant increase in the readiness of patients to embrace new technologies, with the percentage rising from 20% to 40%. In particular, a remarkable growth in patient preferences for telepsychiatry was observed, with a significant increase from 47% in 2020 to a substantial 96% in 2023. Similarly, mHealth self-management tools were of high interest to patients. In 2020, 62% of patients like the idea of using mobile apps and other mobile health tools to support the care and treatment process. This percentage also increased during the pandemic, reaching 66% in 2023. At the same time, the percentage of patients who have concerns about using m-health solutions has gradually decreased, reaching 35% and 28% in 2023 for telepsychiatry and for the reliability and safety of m-health self-management tools, respectively.

Conclusion

This study highlights the growing acceptance of modern technologies in psychiatric care, with patients showing increased readiness to use telepsychiatry and mobile health self-management tools, in particular mobile applications, after the COVID-19 pandemic. This was triggered by the pandemic, but continues despite its expiry. In the face of patient readiness, the key issue now is to ensure the safety and efficacy of these tools, along with providing clear guidelines for clinicians. It is also necessary to draw the attention of health systems to the widespread implementation of these technologies to improve the care of patients with mental disorders.

User-Centered Development of STOP (Successful Treatment for Paranoia): Material Development and Usability Testing for a Digital Therapeutic for Paranoia

BACKGROUND

Paranoia is a highly debilitating mental health condition. One novel intervention for paranoia is cognitive bias modification for paranoia (CBM-pa). CBM-pa comes from a class of interventions that focus on manipulating interpretation bias. Here, we aimed to develop and evaluate new therapy content for CBM-pa for later use in a self-administered digital therapeutic for paranoia called STOP ("Successful Treatment of Paranoia").

OBJECTIVE

This study aimed to (1) take a user-centered approach with input from living experts, clinicians, and academics to create and evaluate paranoia-relevant item content to be used in STOP and (2) engage with living experts and the design team from a digital health care solutions company to cocreate and pilot-test the STOP mobile app prototype.

METHODS

We invited 18 people with living or lived experiences of paranoia to create text exemplars of personal, everyday emotionally ambiguous scenarios that could provoke paranoid thoughts. Researchers then adapted 240 suitable exemplars into corresponding intervention items in the format commonly used for CBM training and created 240 control items for the purpose of testing STOP. Each item included newly developed, visually enriching graphics content to increase the engagement and realism of the basic text scenarios. All items were then evaluated for their paranoia severity and readability by living experts (n=8) and clinicians (n=7) and for their item length by the research team. Items were evenly distributed into six 40-item sessions based on these evaluations. Finalized items were presented in the STOP mobile app, which was co-designed with a digital health care solutions company, living or lived experts, and the academic team; user acceptance was evaluated across 2 pilot tests involving living or lived experts.

RESULTS

All materials reached predefined acceptable thresholds on all rating criteria: paranoia severity (intervention items: ≥1; control items: ≤1, readability: ≥3, and length of the scenarios), and there was no systematic difference between the intervention and control group materials overall or between individual sessions within each group. For item graphics, we also found no systematic differences in users' ratings of complexity (P=.68), attractiveness (P=.15), and interest (P=.14) between intervention and control group materials. User acceptance testing of the mobile app found that it is easy to use and navigate, interactive, and helpful.

CONCLUSIONS

Material development for any new digital therapeutic requires an iterative and rigorous process of testing involving multiple contributing groups. Appropriate user-centered development can create user-friendly mobile health apps, which may improve face validity and have a greater chance of being engaging and acceptable to the target end users.

Smartphone sensor data estimate alcohol craving in a cohort of patients with alcohol-associated liver disease and alcohol use disorder

BACKGROUND

Sensors within smartphones, such as accelerometer and location, can describe longitudinal markers of behavior as represented through devices in a method called digital phenotyping. This study aimed to assess the feasibility of digital phenotyping for patients with alcohol-associated liver disease and alcohol use disorder, determine correlations between smartphone data and alcohol craving, and establish power assessment for future studies to prognosticate clinical outcomes.

METHODS

A total of 24 individuals with alcohol-associated liver disease and alcohol use disorder were instructed to download the AWARE application to collect continuous sensor data and complete daily ecological momentary assessments on alcohol craving and mood for up to 30 days. Data from sensor streams were processed into features like accelerometer magnitude, number of calls, and location entropy, which were used for statistical analysis. We used repeated measures correlation for longitudinal data to evaluate associations between sensors and ecological momentary assessments and standard Pearson correlation to evaluate within-individual relationships between sensors and craving.

RESULTS

Alcohol craving significantly correlated with mood obtained from ecological momentary assessments. Across all sensors, features associated with craving were also significantly correlated with all moods (eg, loneliness and stress) except boredom. Individual-level analysis revealed significant relationships between craving and features of location entropy and average accelerometer magnitude.

CONCLUSIONS

Smartphone sensors may serve as markers for alcohol craving and mood in alcohol-associated liver disease and alcohol use disorder. Findings suggest that location-based and accelerometer-based features may be associated with alcohol craving. However, data missingness and low participant retention remain challenges. Future studies are needed for further digital phenotyping of relapse risk and progression of liver disease.

Digital health interventions to improve adherence to oral antipsychotics among patients with schizophrenia: a scoping review

OBJECTIVES

To assess the current evidence on the potential of digital health interventions (DHIs) to improve adherence to oral antipsychotics among patients with schizophrenia by assessing the methodologies, feasibility and effectiveness of DHIs as well as the perceptions of relevant stakeholders.

DESIGN

The scoping review was conducted based on the methodologies outlined by Levac et al and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.

DATA SOURCES

PubMed, Embase, Web of Science, Scopus, CINAHL, PsycINFO and the Cochrane Library were searched in August 2023 to identify relevant publications from the previous decade.

ELIGIBILITY CRITERIA

Studies published in English focused on improving medication adherence among adult patients with schizophrenia or schizoaffective disorder via DHIs were selected. Protocols, editorials, comments, perspectives, reviews, correspondence and conference abstracts were excluded.

DATA EXTRACTION AND SYNTHESIS

The extracted data included general information about the study, framework, participants, features and strategies of DHIs, measurement tools for adherence used, and main findings.

RESULTS

In total, 64 studies were included in the qualitative synthesis. Features used in DHIs to improve medication adherence included phone calls, text messages, mobile apps, sensors, web-based platforms and electronic devices. Strategies included medication reminders and monitoring, providing medication-related information and suggestions, other illness management suggestions and individual support. Texting and mobile apps were commonly used as medication reminders and monitoring methods. Additionally, the use of sensors combined with other digital technologies has garnered significant attention. All the interventions were considered acceptable and feasible, and several were assessed in pilot trials. Preliminary findings suggest that DHIs could enhance medication adherence in patients with schizophrenia. However, further validation of their effectiveness is required.

CONCLUSION

DHIs are a promising approach to enhancing medication adherence among patients with schizophrenia. Future interventions should be interactive, focusing on user preference, experience and privacy.

Applying the Just-In-Time Adaptive Intervention Framework to the Development of Gambling Interventions

Just-In-Time Adaptive Interventions (JITAIs) are emerging "push" mHealth interventions that provide the right type, timing, and amount of support to address the dynamically-changing needs for each individual. Although JITAIs are well-suited to the delivery of interventions for the addictions, few are available to support gambling behaviour change. We therefore developed GamblingLess: In-The-Moment and Gambling Habit Hacker, two smartphone-delivered JITAIs that differ with respect to their target populations, theoretical underpinnings, and decision rules. We aim to describe the decisions, methods, and tools we used to design these two treatments, with a view to providing guidance to addiction researchers who wish to develop JITAIs in the future. Specifically, we describe how we applied a comprehensive, organising scientific framework to define the problem, define just-in-time in the context of the identified problem, and formulate the adaptation strategies. While JITAIs appear to be a promising design in addiction intervention science, we describe several key challenges that arose during development, particularly in relation to applying micro-randomised trials to their evaluation, and offer recommendations for future research. Issues including evaluation considerations, integrating on-demand intervention content, intervention optimisation, combining active and passive assessments, incorporating human facilitation, adding cost-effectiveness evaluations, and redevelopment as transdiagnostic interventions are discussed.

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

BACKGROUND

Smartphones and wearable biosensors can continuously and passively measure aspects of behavior and physiology while also collecting data that require user input. These devices can potentially be used to monitor symptom burden; estimate diagnosis and risk for relapse; predict treatment response; and deliver digital interventions in patients with obsessive-compulsive disorder (OCD), a prevalent and disabling psychiatric condition that often follows a chronic and fluctuating course and may uniquely benefit from these technologies.

OBJECTIVE

Given the speed at which mobile and wearable technologies are being developed and implemented in clinical settings, a continual reappraisal of this field is needed. In this scoping review, we map the literature on the use of wearable devices and smartphone-based devices or apps in the assessment, monitoring, or treatment of OCD.

METHODS

In July 2022 and April 2023, we conducted an initial search and an updated search, respectively, of multiple databases, including PubMed, Embase, APA PsycINFO, and Web of Science, with no restriction on publication period, using the following search strategy: ("OCD" OR "obsessive" OR "obsessive-compulsive") AND ("smartphone" OR "phone" OR "wearable" OR "sensing" OR "biofeedback" OR "neurofeedback" OR "neuro feedback" OR "digital" OR "phenotyping" OR "mobile" OR "heart rate variability" OR "actigraphy" OR "actimetry" OR "biosignals" OR "biomarker" OR "signals" OR "mobile health").

RESULTS

We analyzed 2748 articles, reviewed the full text of 77 articles, and extracted data from the 25 articles included in this review. We divided our review into the following three parts: studies without digital or mobile intervention and with passive data collection, studies without digital or mobile intervention and with active or mixed data collection, and studies with a digital or mobile intervention.

CONCLUSIONS

Use of mobile and wearable technologies for OCD has developed primarily in the past 15 years, with an increasing pace of related publications. Passive measures from actigraphy generally match subjective reports. Ecological momentary assessment is well tolerated for the naturalistic assessment of symptoms, may capture novel OCD symptoms, and may also document lower symptom burden than retrospective recall. Digital or mobile treatments are diverse; however, they generally provide some improvement in OCD symptom burden. Finally, ongoing work is needed for a safe and trusted uptake of technology by patients and providers.

Relapse prevention through health technology program reduces hospitalization in schizophrenia

BACKGROUND

Psychiatric hospitalization is a major driver of cost in the treatment of schizophrenia. Here, we asked whether a technology-enhanced approach to relapse prevention could reduce days spent in a hospital after discharge.

METHODS

The Improving Care and Reducing Cost (ICRC) study was a quasi-experimental clinical trial in outpatients with schizophrenia conducted between 26 February 2013 and 17 April 2015 at 10 different sites in the USA in an outpatient setting. Patients were between 18 and 60 years old with a diagnosis of schizophrenia, schizoaffective disorder, or psychotic disorder not otherwise specified. Patients received usual care or a technology-enhanced relapse prevention program during a 6-month period after discharge. The health technology program included in-person, individualized relapse prevention planning with treatments delivered via smartphones and computers, as well as a web-based prescriber decision support program. The main outcome measure was days spent in a psychiatric hospital during 6 months after discharge.

RESULTS

The study included 462 patients, of which 438 had complete baseline data and were thus used for propensity matching and analysis. Control participants (N = 89; 37 females) were enrolled first and received usual care for relapse prevention followed by 349 participants (128 females) who received technology-enhanced relapse prevention. During 6-month follow-up, 43% of control and 24% of intervention participants were hospitalized (χ2 = 11.76, p<0.001). Days of hospitalization were reduced by 5 days (mean days: b = -4.58, 95% CI -9.03 to -0.13, p = 0.044) in the intervention condition compared to control.

CONCLUSIONS

These results suggest that technology-enhanced relapse prevention is an effective and feasible way to reduce rehospitalization days among patients with schizophrenia.

m-RESIST, a Mobile Therapeutic Intervention for Treatment-Resistant Schizophrenia: Feasibility, Acceptability, and Usability Study

BACKGROUND

In the European Union, around 5 million people are affected by psychotic disorders, and approximately 30%-50% of people with schizophrenia have treatment-resistant schizophrenia (TRS). Mobile health (mHealth) interventions may be effective in preventing relapses, increasing treatment adherence, and managing some of the symptoms of schizophrenia. People with schizophrenia seem willing and able to use smartphones to monitor their symptoms and engage in therapeutic interventions. mHealth studies have been performed with other clinical populations but not in populations with TRS.

OBJECTIVE

The purpose of this study was to present the 3-month prospective results of the m-RESIST intervention. This study aims to assess the feasibility, acceptability, and usability of the m-RESIST intervention and the satisfaction among patients with TRS after using this intervention.

METHODS

A prospective multicenter feasibility study without a control group was undertaken with patients with TRS. This study was performed at 3 sites: Sant Pau Hospital (Barcelona, Spain), Semmelweis University (Budapest, Hungary), and Sheba Medical Center and Gertner Institute of Epidemiology and Health Policy Research (Ramat-Gan, Israel). The m-RESIST intervention consisted of a smartwatch, a mobile app, a web-based platform, and a tailored therapeutic program. The m-RESIST intervention was delivered to patients with TRS and assisted by mental health care providers (psychiatrists and psychologists). Feasibility, usability, acceptability, and user satisfaction were measured.

RESULTS

This study was performed with 39 patients with TRS. The dropout rate was 18% (7/39), the main reasons being as follows: loss to follow-up, clinical worsening, physical discomfort of the smartwatch, and social stigma. Patients' acceptance of m-RESIST ranged from moderate to high. The m-RESIST intervention could provide better control of the illness and appropriate care, together with offering user-friendly and easy-to-use technology. In terms of user experience, patients indicated that m-RESIST enabled easier and quicker communication with clinicians and made them feel more protected and safer. Patients' satisfaction was generally good: 78% (25/32) considered the quality of service as good or excellent, 84% (27/32) reported that they would use it again, and 94% (30/32) reported that they were mostly satisfied.

CONCLUSIONS

The m-RESIST project has provided the basis for a new modular program based on novel technology: the m-RESIST intervention. This program was well-accepted by patients in terms of acceptability, usability, and satisfaction. Our results offer an encouraging starting point regarding mHealth technologies for patients with TRS.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03064776; https://clinicaltrials.gov/ct2/show/record/NCT03064776.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2017-021346.

Mobile health in the specific management of first-episode psychosis: a systematic literature review

Purpose

The purpose of this systematic literature review is to assess the therapeutic efficacy of mobile health methods in the management of patients with first-episode psychosis (FEP).

Method

The participants are patients with FEP. The interventions are smartphone applications. The studies assess the preliminary efficacy of various types of application.

Results

One study found that monitoring symptoms minimized relapses, visits to A&E and hospital admissions, while one study showed a decrease in positive psychotic symptoms. One study found an improvement in anxiety symptoms and two studies noted an improvement in psychotic symptoms. One study demonstrated its efficacy in helping participants return to studying and employment and one study reported improved motivation.

Conclusion

The studies suggest that mobile applications have potential value in the management of young patients with FEP through the use of various assessment and intervention tools. This systematic review has several limitations due to the lack of randomized controlled studies available in the literature.

Treating depression with a smartphone-delivered self-help cognitive behavioral therapy for insomnia: a parallel-group randomized controlled trial

BACKGROUND

Despite its efficacy in treating comorbid insomnia and depression, cognitive behavioral therapy for insomnia (CBT-I) is limited in its accessibility and, in many countries, cultural compatibility. Smartphone-based treatment is a low-cost, convenient alternative modality. This study evaluated a self-help smartphone-based CBT-I in alleviating major depression and insomnia.

METHODS

A parallel-group randomized, waitlist-controlled trial was conducted with 320 adults with major depression and insomnia. Participants were randomized to receive either a 6-week CBT-I via a smartphone application, proACT-S, or waitlist condition. The primary outcomes included depression severity, insomnia severity, and sleep quality. The secondary outcomes included anxiety severity, subjective health, and acceptability of treatment. Assessments were administered at baseline, post-intervention (week 6) follow-up, and week 12 follow-up. The waitlist group received treatment after the week 6 follow-up.

RESULTS

Intention to treat analysis was conducted with multilevel modeling. In all but one model, the interaction between treatment condition and time at week 6 follow-up was significant. Compared with the waitlist group, the treatment group had lower levels of depression [Center for Epidemiologic Studies Depression Scale (CES-D): Cohen's d = 0.86, 95% CI (-10.11 to -5.37)], insomnia [Insomnia Severity Index (ISI): Cohen's d = 1.00, 95% CI (-5.93 to -3.53)], and anxiety [Hospital Anxiety and Depression Scale - Anxiety subscale (HADS-A): Cohen's d = 0.83, 95% CI (-3.75 to -1.96)]. They also had better sleep quality [Pittsburgh Sleep Quality Index (PSQI): Cohen's d = 0.91, 95% CI (-3.34 to -1.83)]. No differences across any measures were found at week 12, after the waitlist control group received the treatment.

CONCLUSION

proACT-S is an efficacious sleep-focused self-help treatment for major depression and insomnia.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04228146. Retrospectively registered on 14 January 2020. http://www.w3.org/1999/xlink">https://clinicaltrials.gov/ct2/show/NCT04228146.

[Effect of Digital Health Interventions on Psychotic Symptoms among Persons with Severe Mental Illness in Community: A Systematic Review and Meta-Analysis]

PURPOSE

This study aimed to evaluate the effects of digital health interventions on the psychotic symptoms among people with severe mental illness in the community.

METHODS

A systematic review and meta-analysis were conducted in accordance with the Cochrane Intervention Research Systematic Review Manual and PRISMA. A literature search was conducted of published randomized controlled trials (RCTs) for digital health interventions from January 2022 to April 2022. RevMan software 5.3 was used for quality assessment and meta-analysis.

RESULTS

A total 14 studies out of 9,864 studies were included in the review, and 13 were included in meta-analysis. The overall effect size of digital health interventions on psychotic symptoms was -0.21 (95% CI = -0.32 to -0.10). Sub-analysis showed that the reduction of the psychotic symptoms was effective in the schizophrenia spectrum group (SMD = -.0.22; 95% CI = -.0.36 to -0.09), web (SMD = -0.41; 95% CI = -0.82 to 0.01), virtual reality (SMD = -0.33; 95% CI = -0.56 to -0.10), mobile (SMD = -0.15; 95% CI = -0.28 to -0.03), intervention period of less than 3 months (SMD = -0.23; 95% CI = -0.35 to -0.11), and non-treatment group (SMD = -0.23; 95% CI = -0.36 to -0.11).

CONCLUSION

These findings suggest that digital health interventions alleviate psychotic symptoms in patients with severe mental illnesses. However, well-designed digital health studies should be conducted in the future.

Development and Validation of Multivariable Prediction Algorithms to Estimate Future Walking Behavior in Adults: Retrospective Cohort Study

BACKGROUND

Physical inactivity is associated with numerous health risks, including cancer, cardiovascular disease, type 2 diabetes, increased health care expenditure, and preventable, premature deaths. The majority of Americans fall short of clinical guideline goals (ie, 8000-10,000 steps per day). Behavior prediction algorithms could enable efficacious interventions to promote physical activity by facilitating delivery of nudges at appropriate times.

OBJECTIVE

The aim of this paper is to develop and validate algorithms that predict walking (ie, >5 min) within the next 3 hours, predicted from the participants' previous 5 weeks' steps-per-minute data.

METHODS

We conducted a retrospective, closed cohort, secondary analysis of a 6-week microrandomized trial of the HeartSteps mobile health physical-activity intervention conducted in 2015. The prediction performance of 6 algorithms was evaluated, as follows: logistic regression, radial-basis function support vector machine, eXtreme Gradient Boosting (XGBoost), multilayered perceptron (MLP), decision tree, and random forest. For the MLP, 90 random layer architectures were tested for optimization. Prior 5-week hourly walking data, including missingness, were used for predictors. Whether the participant walked during the next 3 hours was used as the outcome. K-fold cross-validation (K=10) was used for the internal validation. The primary outcome measures are classification accuracy, the Mathew correlation coefficient, sensitivity, and specificity.

RESULTS

The total sample size included 6 weeks of data among 44 participants. Of the 44 participants, 31 (71%) were female, 26 (59%) were White, 36 (82%) had a college degree or more, and 15 (34%) were married. The mean age was 35.9 (SD 14.7) years. Participants (n=3, 7%) who did not have enough data (number of days <10) were excluded, resulting in 41 (93%) participants. MLP with optimized layer architecture showed the best performance in accuracy (82.0%, SD 1.1), whereas XGBoost (76.3%, SD 1.5), random forest (69.5%, SD 1.0), support vector machine (69.3%, SD 1.0), and decision tree (63.6%, SD 1.5) algorithms showed lower performance than logistic regression (77.2%, SD 1.2). MLP also showed superior overall performance to all other tried algorithms in Mathew correlation coefficient (0.643, SD 0.021), sensitivity (86.1%, SD 3.0), and specificity (77.8%, SD 3.3).

CONCLUSIONS

Walking behavior prediction models were developed and validated. MLP showed the highest overall performance of all attempted algorithms. A random search for optimal layer structure is a promising approach for prediction engine development. Future studies can test the real-world application of this algorithm in a "smart" intervention for promoting physical activity.

A Mobile Health App (ChillTime) Promoting Emotion Regulation in Dual Disorders: Acceptability and Feasibility Pilot Study

BACKGROUND

A growing number of studies highlight the importance of emotion regulation in the treatment and recovery of individuals with psychosis and concomitant disorders such as substance use disorder (SUD), for whom access to integrated dual-disorder treatments is particularly difficult. In this context, dedicated smartphone apps may be useful tools to provide immediate support to individuals in need. However, few studies to date have focused on the development and assessment of apps aimed at promoting emotional regulation for people with psychosis.

OBJECTIVE

The aim of this study was to evaluate the feasibility, acceptability, and potential clinical impact of a dedicated app (ChillTime) for individuals with psychotic disorders and concurrent SUD. The app design process followed recommendations for reducing cognitive effort on a mobile app. A total of 20 coping strategies regrouped in four categories (behavioral, emotional, cognitive, spiritual) were included in the app.

METHODS

This open pilot study followed a pre-post design. After the initial assessment, researchers asked participants to use the app as part of their treatment over a 30-day period. Feasibility was determined by the frequency of use of the app and measured using the number of completed strategies. Acceptability was determined by measuring ease of use, ease of learning, satisfaction, and perceived utility at the end of the 30-day study period based on responses to satisfaction questionnaires. Clinical scales measuring emotion regulation, substance use (ie, type of substance, amount taken, and frequency of use), and various psychiatric symptoms were administered at the beginning and end of the 30-day period.

RESULTS

A total of 13 participants were recruited from two first-episode psychosis clinics in Montreal, Quebec, Canada. All participants were symptomatically stable, were between 18 and 35 years of age (mostly men; 70% of the sample), and had a schizophrenia spectrum disorder with a comorbid substance use diagnosis. A total of 11 participants completed the study (attrition<20%). Approximately half of the participants used the tool at least 33% of the days (11-21 days). Cognitive and emotion-focused techniques were rated the highest in terms of usefulness and were the most frequently used. The majority of participants gave positive answers about the ease of use and the ease of learning the tool. A nonsignificant association of ChillTime use with negative symptoms and drug use was observed. No other statistically significant changes were observed.

CONCLUSIONS

The ChillTime app showed good feasibility (approximately half of the participants used the tool at least 33% of the days) and acceptability among people with schizophrenia spectrum disorder and SUD. Trends suggesting a potential impact on certain clinical outcomes will need to be replicated in larger-sample studies before any conclusion can be drawn.

User engagement in mobile apps for people with schizophrenia: A scoping review

Over the past decade, there has been an increase in the number of mobile apps designed for mental health proposes and mHealth has been perceived as a promising approach to help people with schizophrenia to manage their condition. However, adoption rates are relatively low and long-term user engagement is a major issue. The aim of this study is to identify and better understand what strategies and factors may influence user engagement and facilitate prolonged use of apps for people with schizophrenia to better manage their illness. A scoping review was conducted in accordance with the Arksey and O'Malley scoping review framework and following PRISMA ScR guidelines. The sources consisted of searching four electronic databases. Rayyan software was used for this study selection process and a narrative approach was used to synthesize the extracted data. A total of 28 studies which met the inclusion criteria were identified. The engagement strategies included push notifications, message prompts, personalization, application customization, goal setting, game-like features, use of different multimedia formats, social connectedness, support (peers and professionals), reliability of content and quality of feedback received. Some demographic factors may influence adherence such as age, gender, education level and socioeconomic status. Other factors also may play a role impacting engagement: health status, data privacy and security, involvement in design process, incentives for participation, app usage fitting in the user routines, initial training, and constant technical support. Included studies present high heterogeneity in outcome measures and thresholds criteria to assess engagement. Understanding what influences engagement and how to measure it is essential to enhance the design of mobile apps and deliver scalable solutions to help people with schizophrenia better manage their illness in their real-world uptake.

Using a complexity science approach to evaluate the effectiveness of just-in-time adaptive interventions: A meta-analysis

Objective

Just-in-time adaptive interventions (JITAIs), which allow individuals to receive the right amount of tailored support at the right time and place, hold enormous potential for promoting behavior change. However, research on JITAIs' implementation and evaluation is still in its early stages, and more empirical evidence is needed. This meta-analysis took a complexity science approach to evaluate the effectiveness of JITAIs that promote healthy behaviors and assess whether key design principles can increase JITAIs' impacts.

Methods

We searched five databases for English-language papers. Study eligibility required that interventions objectively measured health outcomes, had a control condition or pre-post-test design, and were conducted in the real-world setting. We included randomized and non-randomized trials. Data extraction encompassed interventions' features, methodologies, theoretical foundations, and delivery modes. RoB 2 and ROBINS-I were used to assess risk of bias.

Results

The final analysis included 21 effect sizes with 592 participants. All included studies used pre- and post-test design. A three-level random meta-analytic model revealed a medium effect of JITAIs on objective behavior change (g = 0.77 (95% confidence interval (CI); 0.32 to 1.22), p < 0.001). The summary effect was robust to bias. Moderator analysis indicated that design principles, such as theoretical foundations, targeted behaviors, and passive or active assessments, did not moderate JITAIs' effects. Passive assessments were more likely than a combination of passive and active assessments to relate to higher intervention retention rates.

Conclusions

This review demonstrated some evidence for the efficacy of JITAIs. However, high-quality randomized trials and data on non-adherence are needed.

Educational Technologies for Teaching Social Skills to Individuals With Schizophrenia: Scoping Review

Schizophrenia interventions incorporate improving quality of life and social functioning. Educational technologies are a potential treatment method for social skills development among individuals with schizophrenia. The objective of the study is to provide an overview of the characteristics and range of approaches of educational technologies in the context of social skills for individuals with schizophrenia. A scoping review methodological framework was applied. Search strategy was conducted on Ovid MEDLINE® and CINAHL Plus. Data were synthesized using a charting form for a logical, descriptive summary of results. The search yielded 771 results and 23 included studies that met eligibility criteria. The data showed persons with schizophrenia respond well to educational technologies to address illness self-management. Using technology in conjunction with traditional evidence-based interventions demonstrates promising results to improve social skills functioning. Occupational therapists can use educational technologies to decrease the gap in health care services and improve social support for individuals with schizophrenia.

Feasibility and Proof-of-Concept of Delivering an Autonomous Music-Based Digital Walking Intervention to Persons with Parkinson's Disease in a Naturalistic Setting

BACKGROUND

Reduced motor automaticity in Parkinson's disease (PD) negatively impacts the quality, intensity, and amount of daily walking. Rhythmic auditory stimulation (RAS), a clinical intervention shown to improve walking outcomes, has been limited by barriers associated with the need for ongoing clinician input.

OBJECTIVE

To assess the feasibility, proof-of-concept, and preliminary clinical outcomes associated with delivering an autonomous music-based digital walking intervention based on RAS principles to persons with PD in a naturalistic setting.

METHODS

Twenty-three persons with PD used the digital intervention independently for four weeks to complete five weekly 30-minute sessions of unsupervised, overground walking with music-based cues. The intervention progressed autonomously according to real-time gait sensing. Feasibility of independent use was assessed by examining participant adherence, safety, and experience. Intervention proof-of-concept was assessed by examining spatiotemporal metrics of gait quality, daily minutes of moderate intensity walking, and daily steps. Preliminary clinical outcomes were assessed following intervention completion.

RESULTS

Participants completed 86.4% of sessions and 131.1% of the prescribed session duration. No adverse events were reported. Gait speed, stride length, and cadence increased within sessions, and gait variability decreased (p < 0.05). Compared to baseline, increased daily moderate intensity walking (mean Δ= +21.44 minutes) and steps (mean Δ= +3,484 steps) occurred on designated intervention days (p < 0.05). Quality of life, disease severity, walking endurance, and functional mobility were improved after four weeks (p < 0.05).

CONCLUSIONS

Study findings supported the feasibility and potential clinical utility of delivering an autonomous digital walking intervention to persons with PD in a naturalistic setting.

Enhancing Medication Adherence Among Patients With Schizophrenia and Schizoaffective Disorder: Mobile App Intervention Study

Introduction

Technology has permeated every aspect of our existence and the mental health sector is not exempt from this.

Objectives

The aim of this study was to test the impact of using a mobile phone app (MyTherapy pill reminder and medication tracker) on medication adherence in patients with schizophrenia and/or schizoaffective disorder.

Methods

Time series design was used. Fifty-one participants were recruited from tertiary hospitals in Oman. The Medication Adherence Rating Scale was used for assessing medication adherence. The data related to medication adherence were collected at baseline, 3 months later and 3 months after installing the program on participants' smartphones. SPSS data set used to analyze the data.

Results

A repeated-measures ANOVA found no significant change in the level of adherence among patients with schizophrenia and schizoaffective disorders at the start and 12 weeks later when the mobile app was installed (p  =  .371). However, adherence scores improved significantly 12 weeks after installation of mobile app compared with the same group at the baseline and 12 weeks before the installation of mobile app (p < .001).

Conclusion

The mobile phone app was effective in improving the adherence level among patients. Installation of the program and teaching patients how to use it to improve their level of adherence is recommended.

Use of an Interactive Obesity Treatment Approach in Individuals With Severe Mental Illness: Feasibility, Acceptability, and Proposed Engagement Criteria

BACKGROUND

Digital and mobile health interventions are increasingly being used to support healthy lifestyle change, including in certain high-risk populations such as those with severe mental illnesses (SMIs). Life expectancy in this population lags 15 years behind counterparts in the general population, primarily due to obesity-related health conditions.

OBJECTIVE

We tested the feasibility and usability of a 12-week interactive obesity treatment approach (iOTA) to adults with chronic SMIs (depression, bipolar disorder and schizophrenia spectrum disorder) receiving treatment in community settings. The iOTA incorporates short message service (SMS) text messages to supplement monthly in-person health coaching.

METHODS

Factors hypothesized to be associated with weight change were illness severity and treatment engagement. Severe psychiatric symptoms were defined as baseline Clinical Global Impression severity score of >5. Criterion engagement was defined as a text messaging response rate >80% during the first 4 weeks of treatment. Disordered eating, assessed with the Loss of Control Over Eating Scores, was also evaluated. Participants provided qualitative data, further informing assessment of intervention feasibility, usability, and acceptability.

RESULTS

A total of 26 participants were enrolled. The mean age was 48.5 (SD 15.67) years; 40% (10/26) were Black and 60% (15/26) female. Participants with lower symptom severity and adequate engagement demonstrated significantly decreased weight (F1,16=22.54, P<.001). Conversely, high symptom severity and lower text message response rates were associated with trend-level increases in weight (F1,7=4.33, P=.08). Loss-of-control eating was not observed to impact treatment outcome. Participants voiced preference for combination of live health coaching and text messaging, expressing desire for personalized message content.

CONCLUSIONS

These results demonstrate the feasibility of delivering an adapted iOTA to SMI patients receiving care in community settings and suggest testable criteria for defining sufficient treatment engagement and psychiatric symptom severity, two factors known to impact weight loss outcomes. These important findings suggest specific adaptations may be needed for optimal treatment outcomes in individuals with SMI.

Are remote psychotherapy/remediation efforts accessible and feasible in patients with schizophrenia? A narrative review

Background

Cognitive remediation (CR) therapy provides an effective way to improve cognitive impairments in schizophrenia. With the advent of telehealth services, especially during COVID 19 pandemic, a suitable alternative can be found in computer and cell phone-based mental health interventions. Previous studies have proven that remote mental health interventions have by and large been successful. Remote psychotherapy/CR services can now be accessed through smartphone apps, iPads, laptops and wearable devices. This has the advantage of reaching a wider population in resource-limited settings. The lack of access to technology, difficulty in using these online interventions and lack of privacy provide impediments to the delivery of care through these online platforms. Further, as some previous studies have shown, there may be a high rate of dropout in people using remote mental health resources. We aim to look at the factors, which influence the accessibility of remote mental health interventions in schizophrenia. Additionally, we test the feasibility of these interventions and look at how they compare and the potential they hold for implementation in future clinical settings.

Results

We found remote cognitive remediation to be both accessible and feasible. Concerning features, however, are the high attrition rates and the concentration of the studies in Western populations.

Conclusions

Remote interventions are a viable alternative to in-person psychotherapy when in-person resources may not always be present. They are efficacious in improving health outcomes among patients with schizophrenia. Further research into the widespread implementation of remote CR will be beneficial in informing clinical decision-making.

An app-based just-in-time-adaptive self-management intervention for care partners: The CareQOL feasibility pilot study

PURPOSE/OBJECTIVE

The primary objective of this study was to establish the feasibility and acceptability of an intensive data collection protocol that involves the delivery of a personalized just-in-time adaptive intervention (JITAI) in three distinct groups of care partners (care partners of persons with spinal cord injury [SCI], Huntington's disease [HD], or hematopoietic cell transplantation [HCT]).

RESEARCH METHOD/DESIGN

Seventy care partners were enrolled in this study (n = 19 SCI; n = 21 HD, n = 30 HCT). This three-month (90 day) randomized control trial involved wearing a Fitbit to track sleep and steps, providing daily reports of health-related quality of life (HRQOL), and completing end of month HRQOL surveys. Care partners in the JITAI group also received personalized pushes (i.e., text-based phone notifications that include brief tips or suggestions for improving self-care). At the end of three-months, care partners in both groups completed a feasibility and acceptability questionnaire.

RESULTS

Most (98.6%) care partners completed the study, average compliance was 88% for daily HRQOL surveys, 96% for daily steps, and 85% for daily sleep (from wearing the Fitbit), and all monthly surveys were completed with the exception of one missed 3-month assessment. The acceptability of the protocol was high; ratings exceeded 80% agreement for the different elements of the study. Improvements were seen for the majority of the HRQOL measures. There was no evidence of measurement reactivity.

CONCLUSIONS/IMPLICATIONS

Findings provide strong support for the acceptability and feasibility of an intensive data collection protocol that involved the administration of a JITAI. Although this trial was not powered to establish efficacy, findings indicated improvements across a variety of different HRQOL measures (~1/3 of which were statistically significant). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

e-Health for Traumatized Refugees: A Scoping Review

Background: High prevalence of post-traumatic stress disorder (PTSD) is reported among refugees exposed to traumatic experiences, while escaping from their home country, entering a third country, and adjusting to a new society. Electronic health (e-health) treatments have been utilized to overcome challenges such as high costs, limited access to care, and a shortage of resources faced by traumatized refugees. Objective: The aim of this scoping review was to summarize the current science on e-health to screen and treat PTSD in traumatized refugees, examine its benefits and challenges, and suggest strategies for future research. Methods: We conducted a scoping review guided by Arksey and O'Malley's 6-stage scoping review framework. Results: Of the 2,782 articles identified, 8 studies were included for the final analysis. Due to the heterogeneity of studies, the synthesis of results was not feasible. However, the findings of individual studies were examined. The most commonly used technology modality was the smartphone (n = 5). One study revealed the possibility of telephonic screening of PTSD to be equally efficacious as in-person screening, and all interventions through smartphone and the internet reported high feasibility and acceptability. Conclusion: e-Health is suggested to be a novel and scalable platform to provide mental health care in settings with limited resources. Larger and highly robust studies in refugee populations with PTSD-targeted, theory-based approaches and diverse technological formats such as video conferencing and virtual reality are warranted.

A novel smartphone-based intervention targeting sleep difficulties in individuals experiencing psychosis: A feasibility and acceptability evaluation

OBJECTIVES

Cognitive Behavioural Therapy (CBT) is an effective psychological intervention for sleep difficulties and has been used successfully in individuals with psychosis. However, access is restricted due to lack of resources and staff training. Delivering CBT for sleep problems using smartphone technology may facilitate wider access. This study aimed to evaluate the feasibility, acceptability and potential usefulness of a guided, smartphone-based CBT intervention targeting sleep disturbance for individuals with psychosis.

DESIGN

Participants with psychosis spectrum diagnoses were recruited to a single-arm, uncontrolled study and engaged with the seven-module programme via smartphone app for six weeks with therapist support.

METHOD

Feasibility was assessed by rates of referral, recruitment and completion. Acceptability was assessed by app usage, a satisfaction questionnaire and qualitative analysis of participants' semi-structured interview. Pre- and post-intervention assessment of sleep, psychotic experiences, mood, well-being and functioning was conducted. Mean change confidence intervals were calculated and reported as an indication of usefulness.

RESULTS

Fourteen individuals consented to participation, and eleven completed the post-intervention assessment. On average, each participant engaged with 5.6 of 7 available modules. Qualitative feedback indicated the intervention was considered helpful and would be recommended to others. Suggested improvements to app design were provided by participants. Potential treatment benefits were observed for sleep difficulties, and all outcomes considered, except frequency of hallucinatory experiences.

CONCLUSIONS

It is feasible and acceptable to deliver therapist-guided CBT for sleep problems by smartphone app for individuals with psychosis. This method provides a low-intensity, accessible intervention, which could be offered more routinely. Further research to determine treatment efficacy is warranted.

The service user experience of SlowMo therapy: A co-produced thematic analysis of service users' subjective experience

OBJECTIVES

SlowMo is the first blended digital therapy for paranoia, showing significant small-moderate reductions in paranoia in a recent large-scale randomized controlled trial (RCT). This study explored the subjective service-user experience of the SlowMo therapy content and design; the experience of the blended therapy approach, including the triangle of the therapeutic alliance; and the experience of the digital aspects of the intervention.

DESIGN

Qualitative co-produced sub-study of an RCT.

METHODS

Participants were 22 adult service users with schizophrenia-spectrum psychosis and persistent distressing paranoia, who completed at least one SlowMo therapy session and a 24-week follow-up, at one of 3 sites in Oxford, London, and Sussex, UK. They were interviewed by peer researchers, using a topic guide co-produced by the Patient and Public Involvement (PPI) team. The transcribed data were analysed thematically. Multiple coding and triangulation, and lay peer researcher validation were used to reach a consensus on the final theme structure.

RESULTS

Six core themes were identified: (i) starting the SlowMo journey; (ii) the central role of the supportive therapist; (iii) slowing things down; (iv) value and learning from social connections; (v) approaches and challenges of technology; and (vi) improvements in paranoia and well-being.

CONCLUSIONS

For these service users, slowing down for a moment was helpful, and integrated into thinking over time. Learning from social connections reflected reduced isolation, and enhanced learning through videos, vignettes, and peers. The central role of the supportive therapist and the triangle of alliance between service user, therapist, and digital platform were effective in promoting positive therapeutic outcomes.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force

BACKGROUND

The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established.

OBJECTIVES

To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators.

METHODS

We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668).

RESULTS

The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators.

CONCLUSION

We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

Developing the Workforce of the Digital Future: Leveraging Technology to Train Community-Based Mobile Mental Health Specialists

Challenges in training, dissemination, and implementation have impeded the ability of providers to integrate promising digital health tools in real-world services. There is a need for generalizable strategies to rapidly train real-world providers at scale to support the adoption of digital health. This study describes the development of principles guiding rapid training of community-based clinicians in the support of digital health. This training approach was developed in the context of an ongoing trial examining implementation strategies for FOCUS, a mobile mental health intervention designed for people with serious mental illness. The SAIL (Simple, Accessible, Inverted, Live) model introduces how digital tools can be leveraged to facilitate rapid training of community agency-based personnel to serve as digital mental health champions, promoters, and providers. This model emphasizes simple and flexible principles of intervention delivery, accessible materials in a virtual learning environment, inverted or "flipped" live training structure, and live consultation calls for ongoing support. These initial insights lay the groundwork for future work to test and replicate generalizable training strategies focused on real-world delivery of digital mental health services. These strategies have the potential to remove key obstacles to the implementation and dissemination of digital health interventions for mental health.

Health Consumer Engagement, Enablement, and Empowerment in Smartphone-Enabled Home-Based Diagnostic Testing for Viral Infections: Mixed Methods Study

Background

Health consumers are increasingly taking a more substantial role in decision-making and self-care regarding their health. A range of digital technologies is available for laypeople to find, share, and generate health-related information that supports their health care processes. There is also innovation and interest in home testing enabled by smartphone technology (smartphone-supported home testing [smart HT]). However, few studies have focused on the process from initial engagement to acting on the test results, which involves multiple decisions.

Objective

This study aimed to identify and model the key factors leading to health consumers’ engagement and enablement associated with smart HT. We also explored multiple levels of health care choices resulting from health consumer empowerment and activation from smart HT use. Understanding the factors and choices associated with engagement, enablement, empowerment, and activation helps both research and practice to support the intended and optimal use of smart HT.

Methods

This study reports the findings from 2 phases of a more extensive pilot study of smart HT for viral infection. In these 2 phases, we used mixed methods (semistructured interviews and surveys) to shed light on the situated complexities of health consumers making autonomous decisions to engage with, perform, and act on smart HT, supporting the diagnostic aspects of their health care. Interview (n=31) and survey (n=282) participants underwent smart HT testing for influenza in earlier pilot phases. The survey also extended the viral infection context to include questions related to potential smart HT use for SARS-CoV-2 diagnosis.

Results

Our resulting model revealed the smart HT engagement and enablement factors, as well as choices resulting from empowerment and activation. The model included factors leading to engagement, specifically various intrinsic and extrinsic influences. Moreover, the model included various enablement factors, including the quality of smart HT and the personal capacity to perform smart HT. The model also explores various choices resulting from empowerment and activation from the perspectives of various stakeholders (public vs private) and concerning different levels of impact (personal vs distant).

Conclusions

The findings provide insight into the nuanced and complex ways health consumers make decisions to engage with and perform smart HT and how they may react to positive results in terms of public-private and personal-distant dimensions. Moreover, the study illuminates the role that providers and smart HT sources can play to better support digitally engaged health consumers in the smart HT decision process.

A systematic review of engagement reporting in remote measurement studies for health symptom tracking

Remote Measurement Technologies (RMTs) could revolutionise management of chronic health conditions by providing real-time symptom tracking. However, the promise of RMTs relies on user engagement, which at present is variably reported in the field. This review aimed to synthesise the RMT literature to identify how and to what extent engagement is defined, measured, and reported, and to present recommendations for the standardisation of future work. Seven databases (Embase, MEDLINE and PsycINFO (via Ovid), PubMed, IEEE Xplore, Web of Science, and Cochrane Central Register of Controlled Trials) were searched in July 2020 for papers using RMT apps for symptom monitoring in adults with a health condition, prompting users to track at least three times during the study period. Data were synthesised using critical interpretive synthesis. A total of 76 papers met the inclusion criteria. Sixty five percent of papers did not include a definition of engagement. Thirty five percent included both a definition and measurement of engagement. Four synthetic constructs were developed for measuring engagement: (i) engagement with the research protocol, (ii) objective RMT engagement, (iii) subjective RMT engagement, and (iv) interactions between objective and subjective RMT engagement. The field is currently impeded by incoherent measures and a lack of consideration for engagement definitions. A process for implementing the reporting of engagement in study design is presented, alongside a framework for definition and measurement options available. Future work should consider engagement with RMTs as distinct from the wider eHealth literature, and measure objective versus subjective RMT engagement.Registration: This review has been registered on PROSPERO [CRD42020192652].

Improving outcomes for care partners of persons with traumatic brain injury: Protocol for a randomized control trial of a just-in-time-adaptive self-management intervention

Informal family care partners of persons with traumatic brain injury (TBI) often experience intense stress resulting from their caregiver role. As such, there is a need for low burden, and easy to engage in interventions to improve health-related quality of life (HRQOL) for these care partners. This study is designed to evaluate the effectiveness of a personalized just-in-time adaptive intervention (JITAI) aimed at improving the HRQOL of care partners. Participants are randomized either to a control group, where they wear the Fitbit® and provide daily reports of HRQOL over a six-month (180 day) period (without the personalized feedback), or the JITAI group, where they wear the Fitbit®, provide daily reports of HRQOL and receive personalized self-management pushes for 6 months. 240 participants will be enrolled (n = 120 control group; n = 120 JITAI group). Outcomes are collected at baseline, 1-, 2-, 3-, 4-, 5- & 6-months, as well as 3- and 6-months post intervention. We hypothesize that the care partners who receive the intervention (JITAI group) will show improvements in caregiver strain (primary outcome) and mental health (depression and anxiety) after the 6-month (180 day) home monitoring period. Participant recruitment for this study started in November 2020. Data collection efforts should be completed by spring 2025; results are expected by winter 2025. At the conclusion of this randomized control trial, we will be able to identify care partners at greatest risk for negative physical and mental health outcomes, and will have demonstrated the efficacy of this JITAI intervention to improve HRQOL for these care partners. Trial registration: ClinicalTrial.gov NCT04570930; https://clinicaltrials.gov/ct2/show/NCT04570930.

Pilot Randomized Control Trial of an App-Based CBT Program for Reducing Anxiety in Individuals with ASD without Intellectual Disability

This study developed and tested the effectiveness of an app-based cognitive behavioral therapy (CBT) program in alleviating anxiety among adolescents and adults with autism without co-occurring intellectual disability. Thirty participants from 15 to 35 years old were randomly assigned to either the intervention or waitlist control group, and self- and caregiver proxy report questionnaires were administered, accompanied by direct behavior observation before and after the intervention period. There was a significant decrease in anxiety level, an increase in positive affect, and a decline in stereotypic behaviors, hyperactivity, noncompliance, and inappropriate speech in proxy reports for the intervention group, compared to the control group. A significant rise in passive response in the direct observation was also seen in the intervention group.

Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT

BACKGROUND

Relapse is a major determinant of outcome for people with a diagnosis of schizophrenia. Early warning signs frequently precede relapse. A recent Cochrane Review found low-quality evidence to suggest a positive effect of early warning signs interventions on hospitalisation and relapse.

OBJECTIVE

How feasible is a study to investigate the clinical effectiveness and cost-effectiveness of a digital intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse?

DESIGN

A multicentre, two-arm, parallel-group cluster randomised controlled trial involving eight community mental health services, with 12-month follow-up.

SETTINGS

Glasgow, UK, and Melbourne, Australia.

PARTICIPANTS

Service users were aged > 16 years and had a schizophrenia spectrum disorder with evidence of a relapse within the previous 2 years. Carers were eligible for inclusion if they were nominated by an eligible service user.

INTERVENTIONS

The Early signs Monitoring to Prevent relapse in psychosis and prOmote Wellbeing, Engagement, and Recovery (EMPOWER) intervention was designed to enable participants to monitor changes in their well-being daily using a mobile phone, blended with peer support. Clinical triage of changes in well-being that were suggestive of early signs of relapse was enabled through an algorithm that triggered a check-in prompt that informed a relapse prevention pathway, if warranted.

MAIN OUTCOME MEASURES

The main outcomes were feasibility of the trial and feasibility, acceptability and usability of the intervention, as well as safety and performance. Candidate co-primary outcomes were relapse and fear of relapse.

RESULTS

We recruited 86 service users, of whom 73 were randomised (42 to EMPOWER and 31 to treatment as usual). Primary outcome data were collected for 84% of participants at 12 months. Feasibility data for people using the smartphone application (app) suggested that the app was easy to use and had a positive impact on motivations and intentions in relation to mental health. Actual app usage was high, with 91% of users who completed the baseline period meeting our a priori criterion of acceptable engagement (> 33%). The median time to discontinuation of > 33% app usage was 32 weeks (95% confidence interval 14 weeks to ∞). There were 8 out of 33 (24%) relapses in the EMPOWER arm and 13 out of 28 (46%) in the treatment-as-usual arm. Fewer participants in the EMPOWER arm had a relapse (relative risk 0.50, 95% confidence interval 0.26 to 0.98), and time to first relapse (hazard ratio 0.32, 95% confidence interval 0.14 to 0.74) was longer in the EMPOWER arm than in the treatment-as-usual group. At 12 months, EMPOWER participants were less fearful of having a relapse than those in the treatment-as-usual arm (mean difference -4.29, 95% confidence interval -7.29 to -1.28). EMPOWER was more costly and more effective, resulting in an incremental cost-effectiveness ratio of £3041. This incremental cost-effectiveness ratio would be considered cost-effective when using the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year gained.

LIMITATIONS

This was a feasibility study and the outcomes detected cannot be taken as evidence of efficacy or effectiveness.

CONCLUSIONS

A trial of digital technology to monitor early warning signs that blended with peer support and clinical triage to detect and prevent relapse is feasible.

FUTURE WORK

A main trial with a sample size of 500 (assuming 90% power and 20% dropout) would detect a clinically meaningful reduction in relapse (relative risk 0.7) and improvement in other variables (effect sizes 0.3-0.4).

TRIAL REGISTRATION

This trial is registered as ISRCTN99559262.

FUNDING

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879).

The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia

BACKGROUND

Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia.

METHODS

This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262).

FINDINGS

We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Aug 8, 2018; 73 were randomised (42 [58%] to EMPOWER and 31 [42%] to treatment as usual). There were 37 (51%) men and 36 (49%) women. At 12 months, main outcomes were collected for 32 (76%) of service users in the EMPOWER group and 30 (97%) of service users in the treatment as usual group. Of those randomised to EMPOWER, 30 (71%) met our a priori criterion of more than 33% adherence to daily monitoring that assumed feasibility. Median time to discontinuation of these participants was 31·5 weeks (SD 14·5). There were 29 adverse events in the EMPOWER group and 25 adverse events in the treatment as usual group. There were 13 app-related adverse events, affecting 11 people, one of which was serious. Fear of relapse was lower in the EMPOWER group than in the treatment as usual group at 12 months (mean difference -7·53 (95% CI -14·45 to 0·60; Cohen's d -0·53).

INTERPRETATION

A trial of digital technology to monitor early warning signs blended with peer support and clinical triage to detect and prevent relapse appears to be feasible, safe, and acceptable. A further main trial is merited.

FUNDING

UK National Institute for Health Research Health Technology Assessment programme and the Australian National Health and Medical Research Council.

Can cognitive remediation therapy be delivered remotely? A review examining feasibility and acceptability of remote interventions

Cognitive remediation (CR) is an effective treatment for schizophrenia. However, issues such as motivational impairments, geographic limitations, and limited availability of specialized clinicians to deliver CR, can impede dissemination. Remote delivery of CR provides an opportunity to implement CR on a broader scale. While empirical support for the efficacy of in-person CR is robust, the evidence-base for virtual delivery of CR is limited. Thus, in this review we aimed to evaluate the feasibility and acceptability of remote CR interventions. Nine (n = 847) fully remote and one hybrid CR intervention were included in this review. Attrition rates for remote CR were generally high compared to control groups. Acceptability rates for remote CR interventions were high and responses from caregivers were positive. Further research using more methodologically rigorous designs is required to evaluate appropriate adaptations for remote treatment and determine which populations may benefit more from remote CR.

A Smartphone-Based Intervention as an Adjunct to Standard-of-Care Treatment for Schizophrenia: Randomized Controlled Trial

Background

Antipsychotic medications have limited benefits in schizophrenia, and cognitive behavioral therapy may be beneficial as an adjunct. There may be potential for implementing mobile cognitive behavioral therapy–based treatment for schizophrenia in addition to standard antipsychotic medications.

Objective

This study aims to determine whether PEAR-004, a smartphone-based investigational digital therapeutic, improves the symptoms of an acute psychotic exacerbation of schizophrenia when it is added to standard treatments.

Methods

This was a 12-week, multicenter, randomized, sham-controlled, rater-blinded, parallel group proof‑of‑concept study of 112 participants with moderate acute psychotic exacerbation in schizophrenia. This study was conducted in 6 clinical trial research sites in the United States from December 2018 to September 2019. The primary outcome, change in Positive and Negative Syndrome Scale (PANSS) from baseline to week 12 or the last available visit, was analyzed using the mixed-effects regression model for repeated measures, applied to an intent-to-treat sample.

Results

The total PANSS scores slightly decreased from baseline over the study period in both groups; the treatment difference at day 85 between PEAR-004 and sham was 2.7 points, in favor of the sham (2-sided P=.09). The secondary scales found no benefit, except for transient improvement in depressive symptoms with PEAR-004. Application engagement was good, and patient and clinical investigator satisfaction was high. No safety concerns were observed. There was some evidence of study site heterogeneity for the onboarding processes and directions on PEAR-004 product use at baseline and throughout the study. However, these differences did not affect the efficacy results.

Conclusions

In the largest-to-date randomized, sham-controlled study of a digital therapeutic in schizophrenia, PEAR-004 did not demonstrate an effect on the primary outcome—total PANSS scores—when compared with a nonspecific digital sham control. The secondary and exploratory results also did not demonstrate any notable benefits, except for possible temporary improvement in depressive symptoms. This study provided many useful scientific and operational insights that can be used in the further clinical development of PEAR-004 and other investigational digital therapeutics.

Trial Registration

ClinicalTrials.gov NCT03751280; https://clinicaltrials.gov/ct2/show/NCT03751280

Effectiveness of mobile applications for patients with severe mental illness: A meta-analysis of randomized controlled trials

BACKGROUND

A systematic review and meta-analysis was conducted to evaluate the effectiveness of mobile applications used by patients diagnosed with mental disorders.

METHODS

An electronic literature search in five databases including PubMed, Embase, the Cochrane Library, CINAHL, and PsychInfo was conducted. The keywords used were "mental disorder," "mental illness," "mobile phone," "smartphone," "mHealth," "application," and "app". The search was restricted to randomized controlled trials (RCTs) written in English and Korean.

RESULTS

Fourteen RCTs, involving 1307 patients diagnosed with depression, schizophrenia, and bipolar disorder were included in the analysis. The included studies were published between 2012 and 2020 and used mobile applications. The risk of bias tool was used to assess methodological quality and the overall risk of bias of the included studies was moderate. The pooled data favored mobile application interventions in reducing the disease-related symptoms of depression (standardized mean difference [SMD] = -0.255, 95% CI: -0.370 to -0.141), mania symptoms (SMD = -0.279, 95% CI: -0.456 to -0.102), and positive (SMD = -0.205, 95% CI: -0.388 to -0.022) and negative psychotic symptoms (SMD = -0.406, 95% CI: -0.791 to -0.020). In subgroup analysis, the incorporation of feedback, notification, and data tracking features in the mobile application intervention produced better outcomes.

CONCLUSION

This review provided evidence that mobile applications could well-assist patients diagnosed with mental disorders. Greater benefits could be achieved by well-designed interventions incorporating strategies with thoughtful consideration of the disease characteristics. Mobile applications present the potential to be effective supplements to clinical treatment.

Acceptability of Texting 4 Relapse Prevention, Text Messaging-Based Relapse Prevention Program for People With Schizophrenia and Schizoaffective Disorder

ABSTRACT

We report process outcomes of the pilot randomized controlled trial of Texting 4 Relapse Prevention (T4RP), a text messaging-based relapse prevention program for people with schizophrenia or schizoaffective disorder (SAD). Forty people were randomized to either the intervention or treatment as usual control group at a 2:1 ratio. Process indicators were collected at 6 months post enrollment.Over 90% of patients agreed or strongly agreed that the text messages were easy to understand, easy to answer, positive, and helped them feel supported. Patient acceptability was positively associated with recovery (β = 0.29, p = <0.001) and patient-provider communication scores (β = 1.04, p < 0.001), and negatively associated with symptoms of the disorder (β = -0.27, p = 0.07). Acceptability was similar by diagnosis (β, SAD diagnosis = 0.40, p = 0.90) and age (β = 0.05, p = 0.67). Findings suggest that a text messaging intervention aimed at preventing relapse is feasible and perceived as beneficial in individuals with schizophrenia and SAD. Future research might include a targeted study of T4RP within the context of hospital discharge when people with schizophrenia/SAD are at highest risk of relapse.