The feasibility and validity of ambulatory self-report of psychotic symptoms using a smartphone software application

Effects of Actissist, a digital health intervention for early psychosis: A randomized clinical trial

Schizophrenia affects 24 million people worldwide. Digital health interventions drawing on psychological principles have been developed, but their effectiveness remains unclear. This parallel, assessor-blinded, randomized clinical trial aimed to investigate whether a cognitive behaviour therapy-informed digital health intervention (Actissist app) confers added benefit on psychotic symptoms over and above remote symptom monitoring (ClinTouch app). Participants recruited from UK community health services were randomized 1:1 to receive either Actissist plus treatment as usual (TAU) or ClinTouch plus TAU. Eligible participants were adults with schizophrenia-spectrum psychosis within five years of first episode onset meeting a criterion level of positive symptoms severity. The primary outcome was Positive and Negative Syndrome Scale (PANSS) symptoms total score at 12 weeks post-randomization. Intention-to-treat analysis included 172 participants, with 149 participants (86.6 %) providing primary outcome data. Actissist plus TAU was not associated with greater reduction than an active control remote symptom monitoring app (ClinTouch) in PANSS total score at post-randomization. There were no significant effects between groups across secondary measures. There were no serious adverse reactions. Both groups improved on the primary psychotic symptoms measure at primary end-point and on secondary measures over time. The Actissist app is safe but not superior to digital symptom monitoring.

Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study

BACKGROUND

Access to high-quality mental healthcare remains challenging for people with psychosis globally, including China. Smartphone-based symptom monitoring has the potential to support scalable mental healthcare. However, no such tool, until now, has been developed and evaluated for people with psychosis in China. This study investigated the acceptability and the experience of using a symptom self-monitoring smartphone app (YouXin) specifically developed for people with psychosis in China.

METHODS

Semi-structured interviews were conducted with 10 participants with psychosis to explore the acceptability of YouXin. Participants were recruited from the non-randomised feasibility study that tested the validity, feasibility, acceptability and safety of the YouXin app. Data analysis was guided by the theoretical framework of acceptability.

RESULTS

Most participants felt the app was acceptable and easy to use, and no unbearable burdens or opportunity costs were reported. Participants found completing the self-monitoring app rewarding and experienced a sense of achievement. Privacy and data security were not major concerns for participants, largely due to trust in their treating hospital around data protection. Participants found the app easy to use and attributed this to the training provided at the beginning of the study. A few participants said they had built some form of relationship with the app and would miss the app when the study finished.

CONCLUSIONS

The YouXin app is acceptable for symptom self-monitoring in people with experience of psychosis in China. Participants gained greater insights about their symptoms by using the YouXin app. As we only collected retrospective acceptability in this study, future studies are warranted to assess hypothetical acceptability before the commencement of study to provide a more comprehensive understanding of implementation.

Cognitive behavioural therapy added to standard care for first-episode and recent-onset psychosis

BACKGROUND

Cognitive behavioural therapy (CBT) can be effective in the general population of people with schizophrenia. It is still unclear whether CBT can be effectively used in the population of people with a first-episode or recent-onset psychosis.

OBJECTIVES

To assess the effects of adding cognitive behavioural therapy to standard care for people with a first-episode or recent-onset psychosis.

SEARCH METHODS

We conducted a systematic search on 6 March 2022 in the Cochrane Schizophrenia Group's Study-Based Register of Trials, which is based on CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, PubMed, ClinicalTrials.gov, ISRCTN, and WHO ICTRP.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) comparing CBT added to standard care vs standard care in first-episode or recent-onset psychosis, in patients of any age.

DATA COLLECTION AND ANALYSIS

Two review authors (amongst SFM, CC, LK and IB) independently screened references for inclusion, extracted data from eligible studies and assessed the risk of bias using RoB2. Study authors were contacted for missing data and additional information. Our primary outcome was general mental state measured on a validated rating scale. Secondary outcomes included other specific measures of mental state, global state, relapse, admission to hospital, functioning, leaving the study early, cognition, quality of life, satisfaction with care, self-injurious or aggressive behaviour, adverse events, and mortality.

MAIN RESULTS

We included 28 studies, of which 26 provided data on 2407 participants (average age 24 years). The mean sample size in the included studies was 92 participants (ranging from 19 to 444) and duration ranged between 26 and 52 weeks. When looking at the results at combined time points (mainly up to one year after start of the intervention), CBT added to standard care was associated with a greater reduction in overall symptoms of schizophrenia (standardised mean difference (SMD) -0.27, 95% confidence interval (CI) -0.47 to -0.08, 20 RCTs, n = 1508, I2 = 68%, substantial heterogeneity, low certainty of the evidence), and also with a greater reduction in positive (SMD -0.22, 95% CI -0.38 to -0.06, 22 RCTs, n = 1565, I² = 52%, moderate heterogeneity), negative (SMD -0.20, 95% CI -0.30 to -0.11, 22 RCTs, n = 1651, I² = 0%) and depressive symptoms (SMD -0.13, 95% CI -0.24 to -0.01, 18 RCTs, n = 1182, I² = 0%) than control. CBT added to standard care was also associated with a greater improvement in the global state (SMD -0.34, 95% CI -0.67 to -0.01, 4 RCTs, n = 329, I² = 47%, moderate heterogeneity) and in functioning (SMD -0.23, 95% CI -0.42 to -0.05, 18 RCTs, n = 1241, I² = 53%, moderate heterogeneity, moderate certainty of the evidence) than control. We did not find a difference between CBT added to standard care and control in terms of number of participants with relapse (relative risk (RR) 0.82, 95% CI 0.57 to 1.18, 7 RCTs, n = 693, I² = 48%, low certainty of the evidence), leaving the study early for any reason (RR 0.87, 95% CI 0.72 to 1.05, 25 RCTs, n = 2242, I² = 12%, moderate certainty of the evidence), adverse events (RR 1.29, 95% CI 0.85 to 1.97, 1 RCT, n = 43, very low certainty of the evidence) and the other investigated outcomes.

AUTHORS' CONCLUSIONS

This review synthesised the latest evidence on CBT added to standard care for people with a first-episode or recent-onset psychosis. The evidence identified by this review suggests that people with a first-episode or recent-onset psychosis may benefit from CBT additionally to standard care for multiple outcomes (overall, positive, negative and depressive symptoms of schizophrenia, global state and functioning). Future studies should better define this population, for which often heterogeneous definitions are used.

Methodological Characteristics and Feasibility of Ecological Momentary Assessment Studies in Psychosis: a Systematic Review and Meta-Analysis

BACKGROUND

Ecological momentary assessment (EMA) involves completing multiple surveys over time in daily life, capturing in-the-moment experiences in real-world contexts. EMA use in psychosis studies has surged over several decades. To critically examine EMA use in psychosis research and assist future researchers in designing new EMA studies, this systematic review aimed to summarize the methodological approaches used for positive symptoms in psychosis populations and evaluate feasibility with a focus on completion rates.

METHODS

A systematic review of PubMed, PsycINFO, MEDLINE, Web of Science, EBSCOhost, and Embase databases using search terms related to EMA and psychosis was conducted. Excluding duplicate samples, a meta-analysis was conducted of EMA survey completion rates and meta-regression to examine predictors of completion.

RESULTS

Sixty-eight studies were included in the review. Characteristics and reporting of EMA methodologies were variable across studies. The meta-mean EMA survey completion computed from the 39 unique studies that reported a mean completion rate was 67.15% (95% CI = 62.3, 71.9), with an average of 86.25% of the sample meeting a one-third EMA completion criterion. No significant predictors of completion were found in the meta-regression. A variety of EMA items were used to measure psychotic experiences, of which few were validated.

CONCLUSIONS

EMA methods have been widely applied in psychosis studies using a range of protocols. Completion rates are high, providing clear evidence of feasibility in psychosis populations. Recommendations for reporting in future studies are provided.

Mobile-based ecological momentary assessment and intervention: bibliometric analysis

Objective

The aim of this article was to review existing documents in the field of mobile-based EMA and EMI, provide an overview of current hot topics, and predict future development trends.

Methods

We conducted a bibliometric study on mobile-based EMA and EMI publications that were collected from the Web of Science Core Collection database. Biblioshiny and CiteSpace were utilized to analyze scientific productions, leading sources, authors, affiliations, documents, research hot topics, keywords, and trend topics.

Results

A total of 2222 documents related to EMA and EMI published between 1992 and 2023 were retrieved. In recent years, scholarly publications have generally increased in mobile-based EMA and EMI research, particularly in the last decade. JMIR mHealth and uHealth (n=86), as well as JMIR (n=73), showed the highest number of publications. The United States (n=1038), Germany (n=218) and Netherlands (n=175) were leading countries. Regarding keyword co-occurrence and trend topics analysis, mental health, health behaviors, and feasibility were hot topics in mobile-based EMA and EMI research. Future research trends included using EMA for tailoring EMI, just-in-time adaptive interventions (JITAI), and digital phenotyping.

Conclusion

This bibliometric study on mobile-based EMA and EMI is a valuable resource for understanding the field's evolution and future trends. Our analysis indicates that EMA and EMI have great potential in health behaviors and mental health, but implementation should consider feasibility and reactivity issues carefully. Emerging trends include EMA-tailored EMI, JITAI, and digital phenotyping. In the future, strengthening multidisciplinary cooperation will be necessary to promote the continued development of the field.

Assessing the Influence of Patient Empowerment Gained Through Mental Health Apps on Patient Trust in the Health Care Provider and Patient Compliance With the Recommended Treatment: Cross-sectional Study

BACKGROUND

In chronic mental illness, noncompliance with treatment significantly worsens the illness course and outcomes for patients. Considering that nearly 1 billion people worldwide experience mental health issues, including 1 of 5 Canadians in any given year, finding tools to lower noncompliance in these populations is critical for health care systems. A promising avenue is apps that make mental health services more accessible to patients. However, little is known regarding the impact of the empowerment gained from mental health apps on patient compliance with recommended treatment.

OBJECTIVE

This study aimed to investigate the impact of patient empowerment gained through mental health apps on patient trust in the health care provider and patient compliance with the recommended treatment.

METHODS

A cross-sectional web-based survey was conducted in Canada. Eligible participants were Canadian adults diagnosed with chronic mental health disorders who were using at least one of the following apps: Dialogue, MindBeacon, Deprexis, Ginger, Talkspace, BetterHelp, MindStrong, Mindshift, Bloom, Headspace, and Calm. A total of 347 valid questionnaires were collected and analyzed using partial least-squares structural equation modeling. Trust in the health care provider and patient compliance were measured with multiple-item scales adapted from existing scales. Patient empowerment was conceived and measured as a higher-order construct encompassing the following 2 dimensions: patient process and patient outcome. All the items contributing to the constructs in the model were measured with 7-point Likert scales. The reliability and validity of the measurement model were assessed, and the path coefficients of the structural model were estimated.

RESULTS

The results clearly show that patient empowerment gained through mental health apps positively influenced patient trust in the health care provider (β=.306; P<.001). Patient trust in the health care provider had a positive effect on patient compliance (β=.725; P<.001). The direct relationship between patient empowerment and patient compliance was not significant (β=.061, P=.23). Interestingly, the data highlight that the effect of patient empowerment on patient compliance was fully mediated by trust in the health care provider (β=.222; P<.001). The results show that patient empowerment gained through the mental health app involves 2 dimensions: a process and an outcome.

CONCLUSIONS

This study shows that for individuals living with mental health disorders, empowerment gained through mental health apps enhances trust in the health care provider. It reveals that patient empowerment impacts patient compliance but only through the full mediating effect of patient trust in the health care provider, indicating that patient trust is a critical variable to enhance patient compliance. Hence, our results confirm that health care systems could encourage the use of mental health apps to favor a climate that facilitates patients' trust in health care provider recommendations, possibly leading to better compliance with the recommended treatment.

Evaluating a smartphone-based symptom self-monitoring app for psychosis in China (YouXin): A non-randomised validity and feasibility study with a mixed-methods design

Background

Psychosis causes a significant burden globally, including in China, where limited mental health resources hinder access to care. Smartphone-based remote monitoring offers a promising solution. This study aimed to assess the validity, feasibility, acceptability, and safety of a symptom self-monitoring smartphone app, YouXin, for people with psychosis in China.

Methods

A pre-registered non-randomised validity and feasibility study with a mixed-methods design. Participants with psychosis were recruited from a major tertiary psychiatric hospital in Beijing, China. Participants utilised the YouXin app to self-monitor psychosis and mood symptoms for four weeks. Feasibility outcomes were recruitment, retention and outcome measures completeness. Active symptom monitoring (ASM) validity was tested against corresponding clinical assessments (PANSS and CDS) using Spearman correlation. Ten participants completed qualitative interviews at study end to explore acceptability of the app and trial procedures.

Results

Feasibility parameters were met. The target recruitment sample of 40 participants was met, with 82.5% completing outcome measures, 60% achieving acceptable ASM engagement (completing >33% of all prompts), and 33% recording sufficient passive monitoring data to extract mobility indicators. Five ASM domains (hallucinations, suspiciousness, guilt feelings, delusions, grandiosity) achieved moderate correlation with clinical assessment. Both quantitative and qualitative evaluation showed high acceptability of YouXin. Clinical measurements indicated no symptom and functional deterioration. No adverse events were reported, suggesting YouXin is safe to use in this clinical population.

Conclusions

The trial feasibility, acceptability and safety parameters were met and a powered efficacy study is indicated. However, refinements are needed to improve ASM validity and increase passive monitoring data completeness.

User engagement in a randomised controlled trial for a digital health intervention for early psychosis (Actissist 2.0 trial)

Digital Health Interventions (DHIs) can help support people with mental health problems. Achieving satisfactory levels of patient engagement is a crucial, yet often underexplored, pre-requisite for health improvement. Actissist is a co-produced DHI delivered via a smartphone app for people with early psychosis, based on Cognitive Behaviour Therapy principles. This study describes and compares engagement patterns among participants in the two arms of the Actissist 2.0 randomised controlled trial. Engagement frequency and duration were measured among participants using the Actissist app in the intervention arm (n = 87) and the ClinTouch symptom monitoring only app used as the control condition (n = 81). Overall, 47.1 % of Actissist and 45.7 % of ClinTouch users completed at least a third of scheduled alerts while active in the study. The mean frequency (77.1 versus 60.2 total responses) and the median duration (80 versus 75 days until last response) of engagement were not significantly higher among Actissist users compared to ClinTouch users. Older age, White ethnicity, using their own smartphone device and, among Actissist users, an increased sense of therapeutic alliance were significantly associated with increased engagement. Through exploiting detailed usage data, this study identifies possible participant-level and DHI-level predictors of engagement to inform the practical implementation of future DHIs.

A Digital System (YouXin) to Facilitate Self-Management by People With Psychosis in China: Protocol for a Nonrandomized Validity and Feasibility Study With a Mixed Methods Design

BACKGROUND

Psychosis is one of the most disabling mental health conditions and causes significant personal, social, and economic burden. Accurate and timely symptom monitoring is critical to offering prompt and time-sensitive clinical services. Digital health is a promising solution for the barriers encountered by conventional symptom monitoring approaches, including accessibility, the ecological validity of assessments, and recall bias. However, to date, there has been no digital health technology developed to support self-management for people with psychosis in China.

OBJECTIVE

We report the study protocol to evaluate the validity, feasibility, acceptability, usability, and safety of a symptom self-monitoring smartphone app (YouXin; Chinese name ) for people with psychosis in China.

METHODS

This is a nonrandomized validity and feasibility study with a mixed methods design. The study was approved by the University of Manchester and Beijing Anding Hospital Research Ethics Committee. YouXin is a smartphone app designed to facilitate symptom self-monitoring for people with psychosis. YouXin has 2 core functions: active monitoring of symptoms (ie, smartphone survey) and passive monitoring of behavioral activity (ie, passive data collection via embedded smartphone sensors). The development process of YouXin utilized a systematic coproduction approach. A series of coproduction consultation meetings was conducted by the principal researcher with service users and clinicians to maximize the usability and acceptability of the app for end users. Participants with psychosis aged 16 years to 65 years were recruited from Beijing Anding Hospital, Beijing, China. All participants were invited to use the YouXin app to self-monitor symptoms for 4 weeks. At the end of the 4-week follow-up, we invited participants to take part in a qualitative interview to explore the acceptability of the app and trial procedures postintervention.

RESULTS

Recruitment to the study was initiated in August 2022. Of the 47 participants who were approached for the study from August 2022 to October 2022, 41 participants agreed to take part in the study. We excluded 1 of the 41 participants for not meeting the inclusion criteria, leaving a total of 40 participants who began the study. As of December 2022, 40 participants had completed the study, and the recruitment was complete.

CONCLUSIONS

This study is the first to develop and test a symptom self-monitoring app specifically designed for people with psychosis in China. If the study shows the feasibility of YouXin, a potential future direction is to integrate the app into clinical workflows to facilitate digital mental health care for people with psychosis in China. This study will inform improvements to the app, trial procedures, and implementation strategies with this population. Moreover, the findings of this trial could lead to optimization of digital health technologies designed for people with psychosis in China.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45170.

Inspire self report scale (ISRS): A feasibility study of a Novel self report scale for people with schizophrenia spectrum disorders

Clinician-rated symptom scales are the current standard for outcome measures in Schizophrenia Spectrum Disorders (SSD) research. There has been growing interest in the development of self-report measures for people with SSD to support measurement-based care and inclusive research. We developed the Inspire Self Report Scale (ISRS), which measures the current magnitude of well-being, mood symptoms, psychosis, negative symptoms and cognition using 10 questions on a Likert or Visual analogue scale (VAS). The main aim of this report was to investigate the correlation and concordance between patient self-report and clinician ratings on the ISRS during a clinical encounter. When ratings were discordant, we sought to identify whether the participant's or psychiatrist's rating was more accurate. The results indicated a moderately strong statistically significant correlation between participant and clinician ratings. There was a moderate concordance between participant and clinician ratings on the ISRS. When the results were discordant, the participant ratings were assessed to be more accurate than the clinician rating over 70% of the time. The ISRS has distinct utility compared to existing scales due to the measurement of present symptom severity, capturing multiple clinical domains, and time efficiency and ease of use. Thus, it may be useful in clinical and research settings.

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.

Exploring engagement with the CBT-informed Actissist smartphone application for early psychosis

BACKGROUND

Individuals with psychosis report favourable attitudes towards psychological interventions delivered via smartphone apps. Evidence for acceptability, safety, feasibility and efficacy is promising but in-depth reporting of app engagement in trials is sparse.

AIMS

To examine how people with psychosis engaged with the cognitive behaviour therapy (CBT)-informed Actissist app over a 12-week intervention period, and to examine factors associated with app engagement.

METHODS

Secondary data from participants in the intervention arm (n = 24) of a proof-of-concept randomised controlled trial of the Actissist app were analysed. The app prompted participants to engage with app-based CBT-informed material in five domains (voices, socialization, cannabis use, paranoia, perceived criticism) at pseudo-random intervals (three notifications per day, six days per week). Participants could self-initiate use any time. App use was financially incentivised.

RESULTS

Participants responded to 47% of app notifications. Most app engagements (87%) were app-initiated rather than self-initiated. Participants engaged most with the voices domain, then paranoia. Age and employment status were significantly associated with overall app engagement.

CONCLUSION

Individuals with psychosis engaged well with Actissist, particularly with areas focussing on voice-hearing and paranoia. App-generated reminders successfully prompted app engagement. As financial incentives may have increased app engagement, future studies of non-incentivized engagement in larger samples are needed.

A digital patient-reported outcome (electronic patient-reported outcome) system for patients with severe psychiatric disorders: User-centered development study and study protocol of a multicenter-controlled trial

Background

The effective treatment of patients with severe psychiatric disorders primarily relies on subjective reporting of symptoms and side-effects. This information is crucial for a clinician's decision regarding medication adjustment. Treatment adjustment usually happens at a low frequency (∼4-8 weeks). In between points of care, patients are left alone with their symptoms and side-effects. This leads to uncertainty regarding the treatment, non-adherence, possible relapse, and rehospitalization.

Objectives

We aim to design a flexible electronic patient-reported outcome (ePRO) system, which allows patients with severe psychiatric disorders to: (a) record their symptoms using an app; (b) share the data with the clinical team at points of care; and (c) utilize the data to support therapy decisions.

Methods

In this article, we describe the development process which included the following steps: (a) formation of a co-design team; (b) stakeholder interviews with patients, practitioners, and digital health experts to access needs, requirements, and barriers; (c) prototype conceptualization and design; (d) user acceptance testing and refinement; and (e) finalization of the system for testing in a pilottrial.

Results

We included input from patients with lived experience of psychiatric disorders, clinical team members, software engineers, and researchers. A prototype system was refined, and iterative changes were made before finalization during a series of operational meetings. The system allows patients to digitally self-report their symptoms and provides longitudinal ePRO symptom data for export into the electronic health record.

Conclusions

Routine ePRO collection has the potential to improve outcomes and hereby also reduce health service costs. We have successfully developed a trial-ready ePRO system for severe psychiatric disorders. The findings were incorporated in the planning of a feasibility pilot trial. Assuming feasibility will be established, the system might be subjected to a certification process evaluation of safety and efficacy including a randomized controlled trial.

Study protocol: understanding pain after dental procedures, an observational study within the National Dental PBRN

BACKGROUND

Patient-reported outcome measures provide an essential perspective on the quality of health care provided. However, how data are collected, how providers value and make sense of the data, and, ultimately, use the data to create meaningful impact all influence the success of using patient-reported outcomes.

OBJECTIVES

The primary objective is to assess post-operative pain experiences by dental procedure type through 21 days post-procedure as reported by patients following dental procedures and assess patients' satisfaction with pain management following dental surgical procedures. Secondary objectives are to: 1) assess post-operative pain management strategies 1 week following dental surgical procedures, as recommended by practitioners and reported by patients, and 2) evaluate practitioner and patient acceptance of the FollowApp.Care post visit patient monitoring technology (FollowApp.Care). We will evaluate FollowApp.Care usage, perceived usefulness, ease of use, and impact on clinical workload.

DESIGN AND METHODS

We describe the protocol for an observational study involving the use of the FollowApp.Care platform, an innovative mobile application that collects dental patients' assessments of their post-operative symptoms (e.g., pain). The study will be conducted in collaboration with the National Dental Practice-based Research Network, a collective Network of dental practices that include private and group practices, public health clinics, community health centers and Federal Qualified Health Centers, academic institutional settings, and special patient populations. We will recruit a minimum of 150 and up to 215 dental providers and up to 3147 patients who will receive push notifications through text messages FollowApp.Care on their mobile phones at designated time intervals following dental procedures. This innovative approach of implementing an existing and tested mobile health system technology into the real-world dental office setting will actively track pain and other complications following dental procedures. Through patients' use of their mobile phones, we expect to promptly and precisely identify specific pain levels and other issues after surgical dental procedures. The study's primary outcome will be the patients' reported pain experiences. Secondary outcomes include pain management strategies and medications implemented by the patient and provider and perceptions of usefulness and ease of use by patients and providers.

Accessibility and availability of smartphone apps for schizophrenia

App-based interventions have the potential to enhance access to and quality of care for patients with schizophrenia. However, less is known about the current state of schizophrenia apps in research and how those translate to publicly available apps. This study, therefore, aimed to review schizophrenia apps offered on marketplaces and research literature with a focus on accessibility and availability. A search of recent reviews, gray literature, PubMed, and Google Scholar was conducted in August 2022. A search of the U.S. Apple App Store and Google Play App Store was conducted in July 2022. All eligible studies and apps were systematically screened/reviewed. The academic research search produced 264 results; 60 eligible studies were identified. 51.7% of research apps were built on psychosis-specific platforms and 48.3% of research apps were built on non-specific platforms. 83.3% of research apps offered monitoring functionalities. Only nine apps, two designed on psychosis-specific platforms and seven on non-specific platforms were easily accessible. The search of app marketplaces uncovered 537 apps; only six eligible marketplace apps were identified. 83.3% of marketplace apps only offered psychoeducation. All marketplace apps lacked frequent updates with the average time since last update 1121 days. There are few clinically relevant apps accessible to patients on the commercial marketplaces. While research efforts are expanding, many research apps are unavailable today. Better translation of apps from research to the marketplace and a focus on sustainable interventions are important targets for the field.

The temporal dynamics of sleep disturbance and psychopathology in psychosis: a digital sampling study

BACKGROUND

Sleep disruption is a common precursor to deterioration and relapse in people living with psychotic disorders. Understanding the temporal relationship between sleep and psychopathology is important for identifying and developing interventions which target key variables that contribute to relapse.

METHODS

We used a purpose-built digital platform to sample self-reported sleep and psychopathology variables over 1 year, in 36 individuals with schizophrenia. Once-daily measures of sleep duration and sleep quality, and fluctuations in psychopathology (positive and negative affect, cognition and psychotic symptoms) were captured. We examined the temporal relationship between these variables using the Differential Time-Varying Effect (DTVEM) hybrid exploratory-confirmatory model.

RESULTS

Poorer sleep quality and shorter sleep duration maximally predicted deterioration in psychosis symptoms over the subsequent 1-8 and 1-12 days, respectively. These relationships were also mediated by negative affect and cognitive symptoms. Psychopathology variables also predicted sleep quality, but not sleep duration, and the effect sizes were smaller and of shorter lag duration.

CONCLUSIONS

Reduced sleep duration and poorer sleep quality anticipate the exacerbation of psychotic symptoms by approximately 1-2 weeks, and negative affect and cognitive symptoms mediate this relationship. We also observed a reciprocal relationship that was of shorter duration and smaller magnitude. Sleep disturbance may play a causal role in symptom exacerbation and relapse, and represents an important and tractable target for intervention. It warrants greater attention as an early warning sign of deterioration, and low-burden, user-friendly digital tools may play a role in its early detection.

Developing "MinDag" - an app to capture symptom variation and illness mechanisms in bipolar disorder

Introduction

The illness course of bipolar disorder (BD) is highly heterogeneous with substantial variation between individuals with the same BD subtype and within individuals over time. This heterogeneity is not well-delineated and hampers the development of more targeted treatment. Furthermore, although lifestyle-related behaviors are believed to play a role in the illness course, such mechanisms are poorly understood. To address some of these knowledge gaps, we aimed to develop an app for collection of multi-dimensional longitudinal data on BD-relevant symptoms and lifestyle-related behaviors.

Methods

An app named MinDag was developed at the Norwegian Center for Mental Disorders Research in Oslo, Norway. The app was designed to tap into selected areas: mood, sleep, functioning/activities (social, occupational, physical exercise, leisure), substance use, emotional reactivity, and psychotic experiences. Ethical, security and usability issues were highly prioritized throughout the development and for the final app solution. We conducted beta- and pilot testing to eliminate technical problems and enhance usability and acceptability.

Results

The final version of MinDag comprises six modules; three which are presented for the user once daily (the Sleep module in the morning and the Mood and Functoning/Activities modules in the evening) and three which are presented once weekly (Substance Use, Emotional Reactivity, and Psychotic Experiences modules). In general, MinDag was well received in both in the beta-testing and the pilot study, and the participants provided valuable feedback that was taken into account in the final development. MinDag is now in use as part of the research protocol at the NORMENT center and in a specialized treatment unit for BD at Oslo University Hospital in Norway.

Discussion

We believe that MinDag will generate unique longitudinal data well suited for capturing the heterogeneity of BD and clarifying important unresolved issues such as how life-style related behavior may influence BD symptoms. Also, the experiences and knowledge derived from the development of MinDag may contribute to improving the security, acceptability, and benefit of digital tools in mental health.

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.

Accounting for Patient Engagement in Randomized Controlled Trials Evaluating Digital Cognitive Behavioral Therapies

Background: Cognitive behavioral therapy (CBT) can be a useful treatment option for various mental health disorders. Modern advances in information technology and mobile communication enable delivery of state-of-the-art CBT programs via smartphones, either as stand-alone or as an adjunct treatment augmenting traditional sessions with a therapist. Experimental CBTs require careful assessment in randomized clinical trials (RCTs). Methods: We investigate some statistical issues for an RCT comparing efficacy of an experimental CBT intervention for a mental health disorder against the control. Assuming a linear model for the clinical outcome and patient engagement as an influential covariate, we investigate two common statistical approaches to inference—analysis of covariance (ANCOVA) and a two-sample t-test. We also study sample size requirements for the described experimental setting. Results: Both ANCOVA and a two-sample t-test are appropriate for the inference on treatment difference at the average observed level of engagement. However, ANCOVA produces estimates with lower variance and may be more powerful. Furthermore, unlike the t-test, ANCOVA allows one to perform treatment comparison at the levels of engagement other than the average level observed in the study. Larger sample sizes may be required to ensure experiments are sufficiently powered if one is interested in comparing treatment effects for different levels of engagement. Conclusions: ANCOVA with proper adjustment for engagement should be used for the for the described experimental setting. Uncertainty on engagement patterns should be taken into account at the study design stage.

Examining relationships between state and trait psychotic symptoms and quality of life in schizophrenia spectrum disorders

Positive and negative symptoms are core aspects of schizophrenia and have been shown to influence patient quality of life (QOL). Previous studies have largely focused on current or state symptoms, with limited work on the contributions of trait symptoms to QOL. This study sought to examine the relationship between both state and trait symptoms and objective and subjective QOL. Fifty-three schizophrenia spectrum disorder patients and 47 healthy controls were recruited. State symptomatology was assessed using the Positive and Negative Syndrome Scale in the patients only. In all participants, trait symptoms were assessed using the Oxford-Liverpool Inventory of Feelings and Experiences, and QOL using Lehman's QOL Interview. Hierarchical linear regression analyses, controlling for depression and neurocognition, revealed that negative state symptoms were related to objective QOL within the patients, while negative trait symptoms were associated with both objective and subjective QOL in patients and healthy controls. No relationships were observed with positive state or trait symptoms and either QOL measure. The findings suggest a degree of complexity in the associations between symptoms and QOL, with primacy for negative symptoms at both state and trait levels. A greater appreciation of trait symptoms may help explain non-complementary QOL changes following symptom remission.

Reliability and Confirmatory Factor Analysis (CFA) of a Paper- Versus App-Administered Resilience Scale in Scottish Youths: Comparative Study

Background

Adequately measuring resilience is important to support young people and children who may need to access resources through social work or educational settings. A widely accepted measure of youth resilience has been developed previously and has been shown to be suitable for vulnerable youth. While the measure is completed by the young person on paper, it has been designed to be worked through with a teacher or social worker in case further clarification is required. However, this method is time consuming and, when faced with large groups of pupils who need assessment, can be overwhelming for schools and practitioners. This study assesses app software with a built-in avatar that can guide young persons through the assessment and its interpretation.

Objective

Our primary objective is to compare the reliability and psychometric properties of a mobile software app to a paper version of the Child and Youth Resilience measure (CYRM-28). Second, this study assesses the use of the CYRM-28 in a Scottish youth population (aged 11-18 years).

Methods

Following focus groups and discussion with teachers, social workers, and young people, an avatar was developed by a software company and integrated into an android smartphone app designed to ask questions via the device’s inbuilt text-to-voice engine. In total, 714 students from 2 schools in North East Scotland completed either a paper version or app version of the CYRM-28. A cross-sectional design was used, and students completed their allocated version twice, with a 2-week period in between each testing. All participants could request clarification either from a guidance teacher (paper version) or from the in-built software glossary (app version).

Results

Test and retest correlations showed that the app version performed better than the paper version of the questionnaire (paper version: r₃₀₃=0.81; P<.001; 95% CI 0.77-0.85; app version: r₄₁₃=0.84; P<.001; 95% CI 0.79-0.89). Fisher r to z transformation revealed a significant difference in the correlations (Z=–2.97, P<.01). Similarly, Cronbach α in both conditions was very high (app version: α=.92; paper version: α=.87), suggesting item redundancy. Ordinarily, this would lead to a possible removal of highly correlated items; however, our primary objective was to compare app delivery methods over a pen-and-paper mode and was hence beyond the scope of the study. Fisher r to z transformation revealed a significant difference in the correlations (Z=–3.69, P<.01). A confirmatory factor analysis supported the 3-factor solution (individual, relational, and contextual) and reported a good model fit (χ²₁₅=27.6 [n=541], P=.24).

Conclusions

ALEX, an avatar with an integrated voice guide, had higher reliability when measuring resilience than a paper version with teacher assistance. The CFA reports similar structure using the avatar when compared against the original validation.

'Care co-ordinator in my pocket': a feasibility study of mobile assessment and therapy for psychosis (TechCare)

OBJECTIVES

The aim of the project was to examine the acceptability and feasibility of a mobile phone application-based intervention 'TechCare', for individuals with psychosis in the North West of England. The main objectives were to determine whether appropriate individuals could be identified and recruited to the study and whether the TechCare App would be an acceptable intervention for individuals with psychosis.

METHODS

This was a mixed methods feasibility study, consisting of a test-run and feasibility evaluation of the TechCare App intervention.

SETTING

Early Intervention Services (EIS) for psychosis, within an NHS Trust in the North West of England.

PARTICIPANTS

Sixteen participants (test-run n=4, feasibility study n=12) aged between 18 and 65 years recruited from the East, Central and North Lancashire EIS.

INTERVENTION

A 6-week intervention, with the TechCare App assessing participants' symptoms and responses in real-time and providing a personalised-guided self-help-based psychological intervention based on the principles of Cognitive Behaviorual Therapy (CBT).

RESULTS

A total of 83.33% (n=10) of participants completed the 6-week feasibility study, with 70% of completers achieving the set compliance threshold of ≥33% engagement with the TechCare App system. Analysis of the qualitative data suggested that participants held the view that the TechCare was both an acceptable and feasible means of delivering interventions in real-time.

CONCLUSION

Innovative digital clinical technologies, such as the TechCare App, have the potential to increase access to psychological interventions, reduce health inequality and promote self-management with a real-time intervention, through enabling access to mental health resources in a stigma-free, evidence-based and time-independent manner.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT02439619.

Clinical validation of ratings on the six-item Positive and Negative Syndrome Scale obtained via the Simplified Negative and Positive Symptoms Interview

BACKGROUND

The six-item version of the Positive and Negative Syndrome Scale (PANSS-6) has shown promise as a brief measure of the severity of core symptoms of schizophrenia. However, since all prior analyses of the PANSS-6 were based on data extracted from studies using the full 30-item PANSS (PANSS-30), it remains unknown whether it is possible to obtain valid information for the PANSS-6 ratings via a brief interview, such as the Simplified Negative and Positive Symptoms Interview (SNAPSI).

AIMS

We aimed to validate the PANSS-6 ratings obtained via the SNAPSI using the PANSS-6 scores extracted from the PANSS-30 ratings obtained via the comprehensive Structured Clinical Interview for PANSS (SCI-PANSS) as the gold-standard reference.

METHODS

The PANSS-6 ratings based on the SNAPSI and the PANSS-30 ratings based on the SCI-PANSS were conducted by independent raters with established inter-rater reliability.

RESULTS

Seventy-seven inpatients with schizophrenia (M_age = 35.1 ± 11.7 years; males = 57%; paranoid schizophrenia = 75%) participated in the study. The intraclass correlation coefficient (ICC) of the PANSS-6 total scores obtained using the SNAPSI and the PANSS-30-derived PANSS-6 total scores via the SCI-PANSS was 0.77 (p < 0.001). The ICC for the PANSS-6 total score and the PANSS-30-derived PANSS-8 (Andreasen's remission criteria) was 0.75 (p < 0.001). Spearman's rank correlation coefficient for changes in PANSS-6 total scores via the SNAPSI and changes in PANSS-30-derived PANSS-6 total scores was 0.70 (p < 0.001).

CONCLUSIONS

Using the SNAPSI to rate the PANSS-6 enables a focused and brief assessment of the severity of core symptoms of schizophrenia, which facilitates measurement-based care and clinical decision making in the treatment of schizophrenia.

Clinical validation of the Symptom Self-rating Scale for Schizophrenia (4S) among inpatients

PURPOSE

Self-reports of psychosis-related symptoms may be a valuable supplement to clinician-ratings, but more validation studies are required. The aim of this study was to conduct clinical validation for the Symptom Self-rating Scale for Schizophrenia (4S) in an inpatient setting.

MATERIALS AND METHODS

Inpatients diagnosed with schizophrenia were invited to participate in the study. The participants completed the 4S, the 5-item World Health Organization Wellbeing Index (WHO-5) and the Sheehan Disability Scale (SDS) at two time points. Trained raters assessed participants using the 6-item Positive And Negative Syndrome Scale (PANSS-6). The relationship between the 4S and PANSS-6, self-reported side effects, functioning and wellbeing was assessed using Spearman's correlation coefficient (rho).

RESULTS

Sixty-one participants completed the 4S at least once (yielding a total of 91 completed 4S questionnaires). The 4S total score was weakly correlated with the PANSS-6 total score (rho = 0.37, p < 0.001). The rho's for individual 4S and PANSS-6 subscales and item comparisons ranged from -0.24 (thought disorder) to 0.69 (hallucinations). Finally, the 4S hallucination subscale was also sensitive to change. The 4S was strongly inversely correlated with wellbeing (WHO-5) and moderately inversely correlated with functioning (SDS total score).

CONCLUSION

The 4S holds promise as a valid self-report of core schizophrenia symptoms among inpatients. While the hallucination subscale seems superior to existing scales, the thought disorder subscale needs to be re-developed.

Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study

Background

Ecological momentary assessment (EMA) tools appear to be useful interventions for collecting real-time data on patients’ behavior and functioning. However, concerns have been voiced regarding the acceptability of EMA among patients with schizophrenia and the factors influencing EMA acceptability.

Objective

The aim of this study was to investigate the acceptability of a passive smartphone-based EMA app, evidence-based behavior (eB2), among patients with schizophrenia spectrum disorders and the putative variables underlying their acceptance.

Methods

The participants in this study were from an ongoing randomized controlled trial (RCT) of metacognitive training, consisting of outpatients with schizophrenia spectrum disorders (F20-29 of 10th revision of the International Statistical Classification of Diseases and Related Health Problems), aged 18-64 years, none of whom received any financial compensation. Those who consented to installation of the eB2 app (users) were compared with those who did not (nonusers) in sociodemographic, clinical, premorbid adjustment, neurocognitive, psychopathological, insight, and metacognitive variables. A multivariable binary logistic regression tested the influence of the above (independent) variables on “being user versus nonuser” (acceptability), which was the main outcome measure.

Results

Out of the 77 RCT participants, 24 (31%) consented to installing eB2, which remained installed till the end of the study (median follow-up 14.50 weeks) in 14 participants (70%). Users were younger and had a higher education level, better premorbid adjustment, better executive function (according to the Trail Making Test), and higher cognitive insight levels (measured with the Beck Cognitive Insight Scale) than nonusers (univariate analyses) although only age (OR 0.93, 95% CI 0.86-0.99; P=.048) and early adolescence premorbid adjustment (OR 0.75, 95% CI 0.61-0.93; P=.01) survived the multivariable regression model, thus predicting eB2 acceptability.

Conclusions

Acceptability of a passive smartphone-based EMA app among participants with schizophrenia spectrum disorders in this RCT where no participant received financial compensation was, as expected, relatively low, and linked with being young and good premorbid adjustment. Further research should examine how to increase EMA acceptability in patients with schizophrenia spectrum disorders, in particular, older participants and those with poor premorbid adjustment.

Trial Registration

ClinicalTrials.gov NCT04104347; https://clinicaltrials.gov/ct2/show/NCT04104347

Engagement with online psychosocial interventions for psychosis: A review and synthesis of relevant factors

BACKGROUND

Little is known about factors associated with engagement with online interventions for psychosis. This review aimed to synthesise existing data from relevant literature to develop a working model of potential variables that may impact on engagement with online interventions for psychosis.

METHODS

Online databases were searched for studies relevant to predictors of engagement with online interventions for psychosis; predictors of Internet use amongst individuals with psychosis; and predictors of engagement with traditional psychosocial treatments for psychosis. Data were synthesised into a conceptual model highlighting factors relevant to engagement with online interventions for psychosis.

RESULTS

Sixty-one studies were identified. Factors relevant to engagement related directly to the impact of psychosis, response to psychosis, integration of technology into daily lives and intervention aspects.

CONCLUSION

While several candidate predictors were identified, there is minimal research specifically investigated predictors of engagement with online interventions for psychosis. Further investigation examining both individual- and intervention-related factors is required to inform effective design and dissemination of online interventions for psychosis.

Adaptive Symptom Monitoring Using Hidden Markov Models - An Application in Ecological Momentary Assessment

Wearable and mobile technology provides new opportunities to manage health conditions remotely and unobtrusively. For example, healthcare providers can repeatedly sample a person's condition to monitor progression of symptoms and intervene if necessary. There is usually a utility-tolerability trade-off between collecting information at sufficient frequencies and quantities to be useful, and over-burdening the user or the underlying technology, particularly when active input is required from the user. Selecting the next sampling time adaptively using previous responses, so that people are only sampled at high frequency when necessary, can help to manage this trade-off. We present a novel approach to adaptive sampling using clustered continuous-time hidden Markov models. The model predicts, at any given sampling time, the probability of moving to an 'alert' state, and the next sample time is scheduled when this probability has exceeded a given threshold. The clusters, each representing a distinct sub-model, allow heterogeneity in states and state transitions. The work is illustrated using longitudinal mental-health symptom data in 49 people collected using ClinTouch, a mobile app designed to monitor people with a diagnosis of schizophrenia. Using these data, we show how the adaptive sampling scheme behaves under different model parameters and risk thresholds, and how the average sampling can be substantially reduced whilst maintaining a high sampling frequency during high-risk periods.

Development and Validation of a Computerized Adaptive Assessment Tool for Discrimination and Measurement of Psychotic Symptoms

OBJECTIVE

Time constraints limit the use of measurement-based approaches in research and routine clinical management of psychosis. Computerized adaptive testing (CAT) can reduce administration time, thus increasing measurement efficiency. This study aimed to develop and test the capacity of the CAT-Psychosis battery, both self-administered and rater-administered, to measure the severity of psychotic symptoms and discriminate psychosis from healthy controls.

METHODS

An item bank was developed and calibrated. Two raters administered CAT-Psychosis for inter-rater reliability (IRR). Subjects rated themselves and were retested within 7 days for test-retest reliability. The Brief Psychiatric Rating Scale (BPRS) was administered for convergent validity and chart diagnosis, and the Structured Clinical Interview (SCID) was used to test psychosis discriminant validity.

RESULTS

Development and calibration study included 649 psychotic patients. Simulations revealed a correlation of r = .92 with the total 73-item bank score, using an average of 12 items. Validation study included 160 additional patients and 40 healthy controls. CAT-Psychosis showed convergent validity (clinician: r = 0.690; 95% confidence interval [95% CI]: 0.610-0.757; self-report: r = .690; 95% CI: 0.609-0.756), IRR (intraclass correlation coefficient [ICC] = 0.733; 95% CI: 0.611-0.828), and test-retest reliability (clinician ICC = 0.862; 95% CI: 0.767-0.922; self-report ICC = 0.815; 95%CI: 0.741-0.871). CAT-Psychosis could discriminate psychosis from healthy controls (clinician: area under the receiver operating characteristic curve [AUC] = 0.965, 95% CI: 0.945-0.984; self-report AUC = 0.850, 95% CI: 0.807-0.894). The median length of the clinician-administered assessment was 5 minutes (interquartile range [IQR]: 3:23-8:29 min) and 1 minute, 20 seconds (IQR: 0:57-2:09 min) for the self-report.

CONCLUSION

CAT-Psychosis can quickly and reliably assess the severity of psychosis and discriminate psychotic patients from healthy controls, creating an opportunity for frequent remote assessment and patient/population-level follow-up.

Using ecological momentary assessment for patients with psychosis posthospitalization: Opportunities for mobilizing measurement-based care

OBJECTIVE

Ecological momentary assessment (EMA) via mobile devices offers a promising approach for collecting real-time data from psychiatric patients, potentially as an augment to traditional measurement-based care strategies. This study examined whether EMA had added value in collecting clinically important data from recently hospitalized adults with psychosis, relative to traditional assessments.

METHOD

In a sample of 24 adults with psychosis, EMA data regarding psychotic symptoms, affect, alcohol and drug use, functioning, quality of life, and social support were collected starting immediately posthospital discharge and extending for up to one month during their transition to outpatient care. EMA data were compared with traditional retrospective assessments of the same constructs, administered at a 1-month follow-up assessment.

RESULTS

Data from EMA and traditional retrospective assessments were correlated with each other in most cases. However, in some cases, participants were more likely to report drug use, medication nonadherence, and psychotic symptoms via EMA compared with traditional retrospective assessments.

CONCLUSIONS AND IMPLICATIONS FOR PRACTICE

Results suggest that the additional information obtained via frequent in-the-moment self-reports collected using smartphones can provide an expanded picture of individuals' symptomatic and functional experiences. Thus, monitoring patients' progress posthospitalization could be improved through the use of EMA. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Examining a Digital Health Approach for Advancing Schizophrenia Illness Self-Management and Provider Engagement: Protocol for a Feasibility Trial

Background

In schizophrenia spectrum populations, adherence to treatment is poor, community-based supports are limited, and efforts to foster illness self-management have had limited success. These challenges contribute to frequent, lengthy, and costly hospital readmissions and poor functional outcomes. Digital health strategies, in turn, hold considerable promise in the effort to address these problems.

Objective

This feasibility trial will examine a digital health platform called App4Independence (A4i), which was designed to enhance illness self-management and treatment engagement for individuals with schizophrenia.

Methods

Feasibility metrics in this single-blind, randomized trial include study recruitment and retention, rate of technology use, safety, and utility in clinical interactions. Other outcome metrics include symptomatology, treatment adherence, patient-provider alliance, and quality of life. In this trial, 160 study participants with schizophrenia spectrum diagnoses will be randomized to either treatment or control conditions, with pretest-posttest outcomes measured over a 6-month period.

Results

This study was funded by the Canadian Institutes of Health Research in January 2020 and received Institutional Review Board approval on August 13, 2020. This study plans to begin recruiting in January 2021 and will be completed within 3 years. Data collection is projected to begin in January 2021.

Conclusions

This research will provide critical information for the development of this new technology in the larger effort to address a key problem in the schizophrenia field—how to leverage technology to enhance illness self-management and care engagement in resource-limited service contexts.

International Registered Report Identifier (IRRID)

PRR1-10.2196/24736

Possibilities, Problems, and Perspectives of Data Collection by Mobile Apps in Longitudinal Epidemiological Studies: Scoping Review

Background

The broad availability of smartphones and the number of health apps in app stores have risen in recent years. Health apps have benefits for individuals (eg, the ability to monitor one’s health) as well as for researchers (eg, the ability to collect data in population-based, clinical, and observational studies). Although the number of health apps on the global app market is huge and the associated potential seems to be great, app-based questionnaires for collecting patient-related data have not played an important role in epidemiological studies so far.

Objective

This study aims to provide an overview of studies that have collected patient data using an app-based approach, with a particular focus on longitudinal studies. This literature review describes the current extent to which smartphones have been used for collecting (patient) data for research purposes, and the potential benefits and challenges associated with this approach.

Methods

We conducted a scoping review of studies that used data collection via apps. PubMed was used to identify studies describing the use of smartphone app questionnaires for collecting data over time. Overall, 17 articles were included in the summary.

Results

Based on the results of this scoping review, there are only a few studies that integrate smartphone apps into data-collection approaches. Studies dealing with the collection of health-related data via smartphone apps have mainly been developed with regard to psychosomatic, neurodegenerative, respiratory, and cardiovascular diseases, as well as malign neoplasm. Among the identified studies, the duration of data collection ranged from 4 weeks to 12 months, and the participants’ mean ages ranged from 7 to 69 years. Potential can be seen for real-time information transfer, fast data synchronization (which saves time and increases effectivity), and the possibility of tracking responses longitudinally. Furthermore, smartphone-based data-collection techniques might prevent biases, such as reminder bias or mistakes occurring during manual data transfers. In chronic diseases, real-time communication with physicians and early detection of symptoms enables rapid modifications in disease management.

Conclusions

The results indicate that using mobile technologies can help to overcome challenges linked with data collection in epidemiological research. However, further feasibility studies need to be conducted in the near future to test the applicability and acceptance of these mobile apps for epidemiological research in various subpopulations.

Mobile RDoC: Using Smartphones to Understand the Relationship Between Auditory Verbal Hallucinations and Need for Care

Objective

Auditory verbal hallucinations (AVH) are common in multiple clinical populations but also occur in individuals who are otherwise considered healthy. Adopting the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, the aim of the current study was to integrate a variety of measures to evaluate whether AVH experience varies across clinical and nonclinical individuals.

Methods

A total of 384 people with AVH from 41 US states participated in the study; 295 participants (77%) who received inpatient, outpatient, or combination treatments for AVH and 89 participants (23%) who never received care. Participants used a multi-modal smartphone data collection system to report on their AVH experiences and co-occurring psychological states multiple times daily, over 30 days. In parallel, smartphone sensors recorded their physical activity, geolocation, and calling and texting behavior continuously.

Results

The clinical sample experienced AVH more frequently than the nonclinical group and rated their AVH as significantly louder and more powerful. They experienced more co-occurring negative affect and were more socially withdrawn, spending significantly more time at home and significantly less time near other people. Participants with a history of inpatient care also rated their AVH as infused with significantly more negative content. The groups did not differ in their physical activity or use of their smartphones for digital communication.

Conclusion

Smartphone-assisted remote data collection revealed real-time/real-place phenomenological, affective, and behavioral differences between clinical and nonclinical samples of people who experience AVH. The study provided strong support for the application of RDoC-informed approaches in psychosis research.

Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial

Background

Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity.

Objective

To assess (i) acceptability of continuous monitoring to SMI patients and health professionals over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; and (iii) the feasibility of detecting early warning signs of relapse.

Methods

The active symptom monitoring smartphone app was built into an end-to-end system in two NHS Trusts to enable real-time symptom self-monitoring and detection by the clinical team of early signs of relapse in people with severe mental illness. We conducted an open randomized controlled trial of active symptom monitoring compared to usual management to assess: (i) acceptability and safety of continuous monitoring over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; (iii) feasibility of detecting early warning signs of relapse communicated to the healthcare staff via an app streaming data to the electronic health record. Eligible participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of schizophrenia and related disorders, and a history of relapse within the previous two years were enrolled from an early intervention team and a community mental health team.

Results

Of 181 eligible patients, 81 (45%) consented and were randomized to either active symptom monitoring or management as usual. At 12 weeks, 90% (33/36) of those in the active monitoring group continued to use the system and exhibited an adherence rate (defined as responding to >33% of alerts) of 84% (30/36}. Active symptom monitoring was associated with no difference on the empowerment scale in comparison to the usual management group at 12 weeks. The pre-planned intent-to-treat analysis of the primary outcome, a positive score on the Positive and Negative Syndrome Scale (PANSS) scale, showed a significant reduction in the active symptom monitoring group over 12 weeks in the early intervention center. Alerts for personalized early warning signs of relapse were built into the workflows of both NHS Trusts, and 100% of health professional staff used the system in a new digital workflow. Qualitative analyses supported the acceptability of the system to participants and staff.

Conclusions

The active smartphone monitoring system is feasible and was accepted by users in a 3-month study of people with severe mental illness, with surprisingly high levels of adherence. App use was associated with psychotic symptom improvement in recent-onset participants, but not those with longstanding illness, supporting the notion of improved self-management. When built into clinical management workflows to enable personalized alerts of symptom deterioration, the app has demonstrated utility in promoting earlier intervention for relapse.

Trial Registration

ISRCTN Registry ISRCTN88145142; http://www.isrctn.com/ISRCTN88145142

Progress in Characterizing the Human Exposome: a Key Step for Precision Medicine

OBJECTIVE

Most diseases result from the complex interplay between genetic and environmental factors. The exposome can be defined as a systematic approach to acquire large data sets corresponding to environmental exposures of an individual along her/ his life. The objective of this contribution is to raise awareness within the health informatics community about the importance of dealing with data related to the contribution of environmental factors to individual health, particularly in the context of precision medicine informatics.

METHODS

This article summarizes the main findings after a panel organized by the International Medical Informatics Association - Exposome Informatics Working Group held during the last MEDINFO, in Lyon (France) in August 2019.

RESULTS

The members of our community presented four initiatives (PULSE, Digital exposome, Cloudy with a chance of pain, Wearable clinics), providing a detailed view of current challenges and accomplishments in processing environmental and social data from a health research perspective. Projects illustrate a wide range of research methods, digital data collection technologies, and analytics and visualization tools. This reinforces the idea that this area is now ready for health informaticians to step in and contribute their expertise, leading the application of informatics strategies to understand environmental health problems.

CONCLUSIONS

The featured projects illustrate applications that use exposome data for the investigation of the causes of diseases, health care, patient empowerment, and public health. They offer a rich overview of the expanding range of applications that informatics is finding in the field of environmental health, with potential impact in precision medicine.

Terminology and assessment tools of psychosis: A systematic narrative review

AIM

Phenomena within the psychosis continuum that varies in frequency/duration/intensity have been increasingly identified. Different terms describe these phenomena, however there is no standardization within the terminology. This review evaluated the definitions and assessment tools of seven terms - (i) 'psychotic experiences'; (ii) 'psychotic-like experiences'; (iii) 'psychotic-like symptoms'; (iv) 'attenuated psychotic symptoms'; (v) 'prodromal psychotic symptoms'; (vi) 'psychotic symptomatology'; and (vii) 'psychotic symptoms'.

METHODS

EMBASE, MEDLINE, and CINAHL were searched during February-March 2019. Inclusion criteria included 1989-2019, full text, human, and English. Papers with no explicit definition or assessment tool, duplicates, conference abstracts, systematic reviews, meta-analyses, or no access were excluded.

RESULTS

A total of 2238 papers were identified and of these, 627 were included. Definitions and assessment tools varied, but some trends were found. Psychotic experiences and psychotic-like experiences were transient and mild, found in the general population and those at-risk. Psychotic-like symptoms were subthreshold and among at-risk populations and non-psychotic mental disorders. Attenuated psychotic symptoms were subthreshold but associated with distress, risk, and help-seeking. Prodromal psychotic symptoms referred to the prodrome of psychotic disorders. Psychotic symptomatology included delusions and hallucinations within psychotic disorders. Psychotic symptoms was the broadest term, encompassing a range of populations but most commonly involving hallucinations, delusions, thought disorder, and disorganization.

DISCUSSION

A model for conceptualizing the required terms is proposed and future directions needed to advance this field of research are discussed.

Pilot randomised controlled trial of a brief coping-focused intervention for hearing voices blended with smartphone-based ecological momentary assessment and intervention (SAVVy): Feasibility, acceptability and preliminary clinical outcomes

BACKGROUND

Voice-hearing experiences can be distressing and impairing, and existing psychological treatments show modest effectiveness. Ecological momentary assessment and intervention (EMA/I) are two promising approaches which may be used as digital tools to support and enhance existing psychological therapies. The aim of this study was to investigate the potential clinical utility of smartphone-based EMA/I in a blended, coping focused therapy for voice-hearing experiences.

METHOD

This pilot RCT focused on feasibility, acceptability and preliminary estimations of efficacy. Thirty-four participants with persisting and distressing voices were randomised to receive the four-session intervention along-side treatment-as-usual (TAU) or TAU-only.

RESULTS

Findings supported the feasibility and acceptability of the approach, with good engagement and satisfaction rates, and clinical outcomes showed the intervention holds promise for improving coping, overall severity of voices and to some degree their negative impact.

CONCLUSION

This is the first examination of the use of EMA/I in a blended therapy for psychotic experiences, with findings suggesting these technologies show promise as clinical tools.

Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support

Background

Relapse in schizophrenia is a major cause of distress and disability and is predicted by changes in symptoms such as anxiety, depression, and suspiciousness (early warning signs [EWSs]). These can be used as the basis for timely interventions to prevent relapse. However, there is considerable uncertainty regarding the implementation of EWS interventions.

Objective

This study was designed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) against treatment as usual (TAU). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, safety, and outcome signals of a digital health intervention as an adjunct to usual care that is deliverable in the UK National Health Service and Australian community mental health service (CMHS) settings. We will assess the feasibility of candidate primary outcomes, candidate secondary outcomes, and candidate mechanisms for a definitive trial.

Methods

We will randomize CMHSs to EMPOWER or TAU. We aim to recruit up to 120 service user participants from 8 CMHSs and follow them for 12 months. Eligible service users will (1) be aged 16 years and above, (2) be in contact with local CMHSs, (3) have either been admitted to a psychiatric inpatient service or received crisis intervention at least once in the previous 2 years for a relapse, and (4) have an International Classification of Diseases-10 diagnosis of a schizophrenia-related disorder. Service users will also be invited to nominate a carer to participate. We will identify the feasibility of the main trial in terms of recruitment and retention to the study and the acceptability, usability, safety, and outcome signals of the EMPOWER intervention. EMPOWER is a mobile phone app that enables the monitoring of well-being and possible EWSs of relapse on a daily basis. An algorithm calculates changes in well-being based on participants’ own baseline to enable tailoring of well-being messaging and clinical triage of possible EWSs. Use of the app is blended with ongoing peer support.

Results

Recruitment to the trial began September 2018, and follow-up of participants was completed in July 2019. Data collection is continuing. The database was locked in July 2019, followed by analysis and disclosing of group allocation.

Conclusions

The knowledge gained from the study will inform the design of a definitive trial including finalizing the delivery of our digital health intervention, sample size estimation, methods to ensure successful identification, consent, randomization, and follow-up of participants, and the primary and secondary outcomes. The trial will also inform the final health economic model to be applied in the main trial.

Trial Registration

International Standard Randomized Controlled Trial Number (ISRCTN): 99559262; http://isrctn.com/ISRCTN99559262

International Registered Report Identifier (IRRID)

DERR1-10.2196/15058

Exacerbation of Psychosis During the Perimenstrual Phase of the Menstrual Cycle: Systematic Review and Meta-analysis

Psychotic disorders can be exacerbated by the hormonal changes associated with childbirth, but the extent to which exacerbations occur with the menstrual cycle is unclear. We addressed this issue by conducting a systematic review. Embase, Medline, and PsychINFO databases were searched for studies that measured exacerbations of psychotic disorders in relation to the menstrual cycle. We extracted exacerbation measure, definition of menstrual cycle phase, and measurement of menstrual cycle phase. Standard incidence ratios were calculated for the perimenstrual phase based on the observed admissions during this phase divided by the expected number of admissions if the menstrual cycle had no effect. Random effects models were used to examine pooled rates of psychiatric admission in the perimenstrual phase. Nineteen studies, comprising 1193 participants were eligible for inclusion. Eleven studies examined psychiatric admission rates, 5 examined symptoms scores, 2 examined self-reported exacerbation, and 1 examined both admission rates and symptom scores. A random effects model demonstrated the rate of admissions during the perimenstrual phase was 1.48 times higher than expected (95% CI: 1.31-1.67), with no significant heterogeneity detected. Four of six symptom score studies reported perimenstrual worsening, but lack of consistency in timepoints precluded meta-analysis. Two studies examining self-reported menstrual exacerbations reported prevalences ranging from 20% to 32.4%. Psychiatric admission rates are significantly higher than expected during the perimenstrual phase. There is some evidence that a worsening of psychotic symptoms also occurs during this phase, but further research with more precise measurement of the menstrual cycle and symptomatology is required.

Client experiences of blending a coping-focused therapy for auditory verbal hallucinations with smartphone-based ecological momentary assessment and intervention

This study explored participants' experiences of a novel intervention blending ecological momentary assessment and intervention (EMA/I) digital technologies with four face-to-face therapy sessions to improve coping in people who experience persisting auditory verbal hallucinations (hear voices). A smartphone app was used to deliver prompts to facilitate both self-monitoring and self-management of voices. Analysis of data recorded by the app was also used in-session to develop an idiographic formulation of antecedents of and responses to voice-hearing episodes. Semi-structured interviews were conducted with 12 participants who completed the blended therapy. A thematic approach was used to analyse the data, generating four main themes, with associated subthemes: (1) Therapy experience changed by digital technology; (2) Valuing face-to-face component; (3) Preference for different phases of the digital technology; (4) Not as bothered by voices. Key findings revealed that participants perceived EMA/I technology as helping capture their experience more accurately and communicate this more effectively to the therapist, which, in combination with coping prompts developed in-session, deepened the therapeutic relationship. These findings add to the emerging literature that shows blended therapy can play an important role in the treatment of people with psychosis, and suggest potential of EMA/I as a technology for other clinical populations.

Smartphone Apps to Support Coordinated Specialty Care for Prodromal and Early Course Schizophrenia Disorders: Systematic Review

Background

Demand for mental health services, especially for clinical high-risk and early psychosis, has increased, creating a need for new solutions to increase access to and quality of care. Smartphones and mobile technology are potential tools to support coordinated specialty care for early psychosis, given their potential to augment the six core roles of care: case management and team leadership, recovery-oriented psychotherapy, medication management, support for employment and education, coordination with primary care services, and family education and support. However, the services smartphones are actually offering specifically for coordinated specialty care and the level of evidence are unknown.

Objective

This study aimed to review the published literature on smartphone technology to enhance care for patients with prodromal and early course psychosis and schizophrenia and to analyze studies by type, aligned with coordinated specialty care domains.

Methods

A systematic literature search was conducted on August 16 and 17, 2019, using the PubMed, EMBASE, Web of Sciences, and PsycINFO electronic databases. The eligible studies were reviewed and screened based on inclusion and exclusion criteria.

Results

The search uncovered 388 unique results, of which 32 articles met the initial inclusion criteria; 21 eligible studies on 16 unique app platforms were identified. Feasibility studies showed a high user engagement and interest among patients, monitoring studies demonstrated a correlation between app assessments and clinical outcomes, and intervention studies indicated that these apps have the potential to advance care. Eighteen studies reported on app use for the case management roles of coordinated specialty care. No app studies focused on employment and education, coordination with primary care services, and family education and support.

Conclusions

Although the published literature on smartphone apps for prodromal and first-episode psychosis is small, it is growing exponentially and holds promise to augment both monitoring and interventions. Although the research results and protocols for app studies are not well aligned with all coordinated specialty care roles today, high rates of adoption and feasibility suggest the potential for future efforts. These results will be used to develop coordinated specialty care–specific app evaluation scales and toolkits.

Mental Health Apps in China: Analysis and Quality Assessment

BACKGROUND

Mental disorders have been a great burden on health care systems, affecting the quality of life of millions of people worldwide. Developing countries, including China, suffer from the double burden of both the increasing mental health issues in population and the deficiency in mental health care resources. The use of mobile health technologies, especially for mobile phone apps, can be a possible solution.

OBJECTIVE

This review aimed to describe the features and assess the quality of mental health apps in major mobile phone app markets in China and further discuss the priorities for mental health app development.

METHODS

Keywords including psychology, psychological health, psychological hygiene, psychological health service(s), mental, mental health, mental hygiene, mental health service(s), depression, and anxiety were searched in Chinese in 3 Android app markets (Baidu Mobile Assistant, Tencent MyApp, and 360 Mobile Assistant) and iOS App Store independently. Mental health apps were then selected according to established criteria for in-depth analysis and quality assessment by the Mobile App Rating Scale.

RESULTS

In total, 63 of 997 mental health apps were analyzed in depth, of which 78% (49/63) were developed by commercial entities for general population, 17% (11/63) were for patients or clients of specialized psychiatric hospitals or counseling agencies, 3% (2/63) were by government or local Centers for Disease Control and Prevention for general information, and 2% (1/63) for students of a university. Major built-in features of the apps included counseling services, mental health education, and self-assessment of mental health status by validated self-rating scales. The overall quality score of the MH apps was acceptable.

CONCLUSIONS

Mental health apps are emerging in the area of mobile health in China. Popular mental health apps usually provide a synthetic platform organizing resources of information, knowledge, counseling services, self-tests, and management for the general population with mental health-related inquiries. The quality of the apps was rated as acceptable on average, suggesting some space for improvement. Official guidelines and regulations are urgently required for the field in the future.

E-Clinical High Risk for Psychosis: Viewpoint on Potential of Digital Innovations for Preventive Psychiatry

E-mental health is an emerging area of research that has the potential to overcome some of the current barriers to progress in working with people at clinical high risk for psychosis (CHR-P). This article provides an overview of how e-mental health could be used in the detection, prediction, and treatment in the CHR-P population. Specifically, we evaluate e-detection, e-prediction, and e-therapeutics for this clinical population. E-mental health holds great promise to improve current management of CHR-P individuals.

Blending active and passive digital technology methods to improve symptom monitoring in early psychosis

AIMS

Psychotic symptoms fluctuate over time and effective and regular monitoring may contribute to relapse prevention and improve long-term outcomes. In this proof-of-concept study we test the feasibility, acceptability and potential usefulness of a novel digital method assessing the association between physiological signals and psychotic symptom distress.

METHODS

Fifteen participants with first episode psychosis were asked to use a self-assessment mobile phone application for psychotic symptom monitoring for 10 days while using a wrist worn device continuously recording heart rate variability (HRV) and electrodermal activity (EDA). We compared physiological activity when participants reported experiencing distressing and non-distressing psychotic symptoms.

RESULTS

Participants completed on average 76% of the mobile phone symptom assessments. When reporting distressing hallucinations and delusions participants had significantly higher EDA levels and non-significant lower HRV values compared to when these symptoms were non-distressing.

CONCLUSIONS

This study provides further evidence linking psychotic symptom's distress, as experienced in everyday life, and autonomic deregulation. This proof-of-concept study may lead to further longer-term efforts to identify relapse biosignatures using automated methods based on passive monitoring. This method may allow for earlier interventions, contribute to improve relapse prevention and reduce symptoms interfering with recovery.

Feasibility and outcomes of a multi-function mobile health approach for the schizophrenia spectrum: App4Independence (A4i)

Relative to the large investments in mobile health (mHealth) strategies for mental illnesses such as anxiety and depression, the development of technology to facilitate illness self-management for people with schizophrenia spectrum illnesses is limited. This situation falls out of step with the opportunity mHealth represents for providing inexpensive and accessible self-care resources and the routine use of mobile technologies by people with schizophrenia. Accordingly, the focus of this study was upon the feasibility of a schizophrenia-focused mobile application: App4Independence (A4i). A4i is a multi-feature app that uses feed, scheduling, and text-based functions co-designed with service users to enhance illness self-management. This study was completed in a large urban Canadian centre and employed pre-post assessments over a 1-month period that examined medication adherence, personal recovery, and psychiatric symptomatology. App use metrics were assessed as was qualitative feedback through semi-structured interview. Findings are reported in line with the World Health Organization mHealth Evidence and Assessment (mERA) checklist. Among the 38 individuals with a primary psychosis who participated, there was no research attrition and classic retention on the app was 52.5%. Significant improvement was observed in some psychiatric symptom domains with small-medium effects. Significant change in recovery engagement and medication adherence were not observed after controlling for multiple comparisons. Those who interacted with the app more frequently were more depressed and had higher hostility and interpersonal sensitivity at baseline. Satisfaction with the app was high and qualitative feedback provided insights regarding feature enhancements. This research suggested that A4i is feasible in terms of outcome and process indicators and is a technology that is ready to move on to clinical trial and validation testing. This study contributes to the small but emergent body of work investigating digital health approaches in severe mental illness populations.