Development and Long-Term Acceptability of ExPRESS, a Mobile Phone App to Monitor Basic Symptoms and Early Signs of Psychosis Relapse

Developing a qualitative and quantitative ambulatory assessment-based feedback system within cognitive behavioural interventions for people with persecutory beliefs

Background

Although the application of self-monitoring (ambulatory assessment) and visual feedback in psychological interventions has yielded promising results, there are currently no reports on using self-monitoring and feedback during a complete therapy. The online m-Path platform provides a tailorable framework for integrating self-monitoring and visual feedback within different psychological interventions.

Methods

Therapy-specific questionnaires and visual feedback were developed within the online m-Path platform as part of the Feeling Safe-NL trial (registration number: ISRCTN25766661) for regular CBT for psychosis (CBTp) and the Feeling Safe Programme combined with peer counselling (the Feeling Safe-NL Programme). The design process involved people with lived experience, psychologists, peer counsellors, researchers, and software developers. The design principles included that the system should be 1) easy to use, 2) suitable for use during a six-month therapy, 3) focussed on positive and goal-aligned outcomes, 4) understandable by patients and professionals, and 5) informing, guiding, and promoting therapy. Design principles were evaluated using compliance data and a patient questionnaire.

Results

The system was used by 21 patients, of which nine completed the questionnaires for the full therapy period, 168 days on average. Usability data from patients revealed that the system was easy to use, well-explained, and suitable for use over six months of therapy. The patients also reported that the questions overall positively affected their emotions and that the feedback was insightful.

Conclusion

The results support the successful application of the design principles to promote the integration of the self-monitoring and visual feedback system within specific CBTp interventions.

Early psychosis service user views on digital remote monitoring: a qualitative study

BACKGROUND

Current approaches to mental healthcare for people with severe mental health problems are limited by sporadic monitoring and symptom recall bias. Emotional and behavioural markers generated by digital health technologies (DHTs) offer the potential to enhance quality of care and clinical decision-making. This study explored early psychosis service users' views and experiences of using a digital remote monitoring tool (ClinTouch app).

METHODS

Qualitative framework analysis was undertaken with interview data collected from participants who took part in the Actissist proof-of-concept and subsequent randomised controlled trial studies to understand the experiences of participants using the ClinTouch app (n = 8).

RESULTS

Data were summarised into four key themes. The following three themes were established a priori: (1) awareness of mood and symptoms; (2) acceptability of ClinTouch; and (3) improvements and recommendations. The fourth theme was established a posteriori: (4) integrating ClinTouch into clinical practice. More specifically, participants felt ClinTouch was an acceptable and useful tool for symptom monitoring. ClinTouch facilitated an increased awareness of mood and symptoms, which enabled participants to self-reflect and develop understanding of their own experiences.

CONCLUSIONS

This study shed light on early psychosis service users' experiences with using the ClinTouch digital remote monitoring app. ClinTouch was viewed as acceptable for monitoring symptoms, safe and easy to use, showed potential of integration with clinical care, and facilitated increased awareness and understanding of symptoms. Improvements including personalised question items and interactive features were suggested. Future developments of digital remote monitoring apps should include a more refined item set and personalisation features.

CLINICAL TRIAL NUMBER

ISRCTN34966555, Registration Date: 12/06/2014; ISRCTN76986679, Registration Date: 07/02/2018.

Digital Assessment of Wellbeing in New Parents (DAWN-P): protocol of a randomised feasibility trial comparing digital screening for maternal postnatal depression with usual care screening

BACKGROUND

Meta-analyses indicate that 17% of mothers experience postnatal depression (PND) in the year following childbirth, with suicide the leading cause of direct maternal death between 6 weeks and 12 months postpartum. The consequences and costs of PND are particularly high due to impacts on infants as well as parents. If detected, PND usually responds well to psychological treatment and/or medication but national reports indicate > 50% of cases are undetected. To improve detection, we developed a digital screening system (CareLoop PND) whereby mothers use an app to monitor their mood daily using a validated measure (Edinburgh Postnatal Depression Scale; EPDS), with real-time responses uploaded to a secure server. In this paper, we describe the protocol of a study to determine feasibility of delivering a full-scale RCT comparing digital screening with standard NHS practice.

METHODS

In this single-blind randomised feasibility trial, participants (n = 80) will be recruited during late pregnancy from two NHS maternity services and randomised (1:1) to receive CareLoop PND alongside their usual NHS care, or usual care alone. Those in the experimental arm will use the CareLoop PND app daily from ≥ 36 weeks' pregnancy until 8 weeks postpartum. During this period, participants scoring above EPDS screening thresholds (via the app or standard care) will be assessed to confirm diagnosis. True positive PND cases identified by digital screening will be referred to services for support. A blinded researcher will conduct follow-up assessments using clinical and health economic measures at 8 weeks and 6 months postpartum. At 8 weeks postpartum, experimental arm participants will also provide qualitative and quantitative feedback exploring app usability, acceptability, and implementation. Feasibility of delivering a full-scale RCT will be evaluated using a priori criteria relating to app engagement, study retention and completion of candidate primary outcome measures.

CONCLUSIONS

Digital screening could increase appropriate referral to perinatal mental health care. However, prior to roll out in NHS services, evidence of efficacy and cost-effectiveness is needed. The current study protocol will determine whether a full-scale RCT examining efficacy and cost-effectiveness is feasible and will inform the design of such a trial.

TRIAL REGISTRATION

Prospective ISRCTN registration (03/07/23): ISRCTN10781027; https://www.isrctn.com/ISRCTN10781027 .

Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review

OBJECTIVES

We aimed to examine the predictive accuracy of functioning, relapse or remission among patients with psychotic disorders, using machine learning methods. We also identified specific features that were associated with these clinical outcomes.

DESIGN

The methodology of this review was guided by the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy.

DATA SOURCES

CINAHL, EMBASE, PubMed, PsycINFO, Scopus and ScienceDirect were searched for relevant articles from database inception until 21 November 2024.

ELIGIBILITY CRITERIA

Studies were included if they involved the use of machine learning methods to predict functioning, relapse and/or remission among individuals with psychotic spectrum disorders.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers screened the records from the database search. Risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies tool from Cochrane. Synthesised findings were presented in tables.

RESULTS

23 studies were included in the review, which were mostly conducted in the west (91%). Predictive summary area under the curve values for functioning, relapse and remission were 0.63-0.92 (poor to outstanding), 0.45-0.95 (poor to outstanding), 0.70-0.79 (acceptable), respectively. Logistic regression and random forest were the best performing algorithms. Factors influencing outcomes included demographic (age, ethnicity), illness (duration of untreated illness, types of symptoms), functioning (baseline functioning, interpersonal relationships and activity engagement), treatment variables (use of higher doses of antipsychotics, electroconvulsive therapy), data from passive sensor (call log, distance travelled, time spent in certain locations) and online activities (time of use, use of certain words, changes in search frequencies and length of queries).

CONCLUSION

Machine learning methods show promise in the prediction of prognosis (specifically functioning, relapse and remission) of mental disorders based on relevant collected variables. Future machine learning studies may want to focus on the inclusion of a broader swathe of variables including ecological momentary assessments, with a greater amount of good quality big data covering longer longitudinal illness courses and coupled with external validation of study findings.

PROSPERO REGISTRATION NUMBER

The review was registered on PROSPERO, ID: CRD42023441108.

Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis

BACKGROUND

Digital mental health interventions (DMHIs) to monitor and improve the health of people with psychosis or bipolar disorder show promise; however, user engagement is variable, and integrated clinical use is low.

OBJECTIVE

This prospectively registered systematic review examined barriers and facilitators of clinician and patient engagement with DMHIs, to inform implementation within real-world settings.

METHODS

A systematic search of 7 databases identified empirical studies reporting qualitative or quantitative data about factors affecting staff or patient engagement with DMHIs aiming to monitor or improve the mental or physical health of people with psychosis or bipolar disorder. The Consolidated Framework for Implementation Research was used to synthesize data on barriers and facilitators, following a best-fit framework synthesis approach.

RESULTS

The review included 175 papers (150 studies; 11,446 participants) describing randomized controlled trials; surveys; qualitative interviews; and usability, cohort, and case studies. Samples included people with schizophrenia spectrum psychosis (98/150, 65.3% of studies), bipolar disorder (62/150, 41.3% of studies), and clinicians (26/150, 17.3% of studies). Key facilitators were a strong recognition of DMHIs' relative advantages, a clear link between intervention focus and specific patient needs, a simple, low-effort digital interface, human-supported delivery, and device provision where needed. Although staff thought patients would lose, damage, or sell devices, reviewed studies found only 11% device loss. Barriers included intervention complexity, perceived risks, user motivation, discomfort with self-reflection, digital poverty, symptoms of psychosis, poor compatibility with existing clinical workflows, staff and patient fears that DMHIs would replace traditional face-to-face care, infrastructure limitations, and limited financial support for delivery.

CONCLUSIONS

Identified barriers and facilitators highlight key considerations for DMHI development and implementation. As to broader implications, sustainable business models are needed to ensure that evidence-based DMHIs are maintained and deployed.

TRIAL REGISTRATION

PROSPERO CRD42021282871; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282871.

Current Implementation of Digital Health in Chronic Disease Management: Scoping Review

BACKGROUND

Approximately 1 in 3 adults live with multiple chronic diseases. Digital health is being harnessed to improve continuity of care and management of chronic diseases. However, meaningful uptake of digital health for chronic disease management remains low. It is unclear how these innovations have been implemented and evaluated.

OBJECTIVE

This scoping review aims to identify how digital health innovations for chronic disease management have been implemented and evaluated: what implementation frameworks, methods, and strategies were used; how successful these strategies were; key barriers and enablers to implementation; and lessons learned and recommendations shared by study authors.

METHODS

We used the Joanna Briggs Institute methodology for scoping reviews. Five databases were searched for studies published between January 2015 and March 2023: PubMed, Scopus, CINAHL, PsycINFO, and IEEE Xplore. We included primary studies of any study design with any type of digital health innovations for chronic diseases that benefit patients, caregivers, or health care professionals. We extracted study characteristics; type of digital health innovation; implementation frameworks, strategies, and outcome measures used; barriers and enablers to implementation; lessons learned; and recommendations reported by study authors. We used established taxonomies to synthesize extracted data. Extracted barriers and enablers were grouped into categories for reporting. Descriptive statistics were used to consolidate extracted data.

RESULTS

A total of 252 studies were included, comprising mainly mobile health (107/252, 42.5%), eHealth (61/252, 24.2%), and telehealth (97/252, 38.5%), with some studies involving more than 1 innovation. Only 23 studies (23/252, 9.1%) reported using an implementation science theory, model, or framework; the most common were implementation theories, classic theories, and determinant frameworks, with 7 studies each. Of 252 studies, 144 (57.1%) used 2 to 5 implementation strategies. Frequently used strategies were "obtain and use patient or consumer feedback" (196/252, 77.8%); "audit and provide feedback" (106/252, 42.1%); and piloting before implementation or "stage implementation scale-up" (85/252, 33.7%). Commonly measured implementation outcomes were acceptability, feasibility, and adoption of the digital innovation. Of 252 studies, 247 studies (98%) did not measure service outcomes, while patient health outcomes were measured in 89 studies (35.3%). The main method used to assess outcomes was surveys (173/252, 68.7%), followed by interviews (95/252, 37.7%). Key barriers impacting implementation were data privacy concerns and patient preference for in-person consultations. Key enablers were training for health care workers and personalization of digital health features to patient needs.

CONCLUSIONS

This review generated a summary of how digital health in chronic disease management is currently implemented and evaluated and serves as a useful resource for clinicians, researchers, health system managers, and policy makers planning real-world implementation. Future studies should investigate whether using implementation science frameworks, including how well they are used, would yield better outcomes compared to not using them.

Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis: Qualitative Study

BACKGROUND

Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences.

OBJECTIVE

This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS).

METHODS

A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17).

RESULTS

Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features.

CONCLUSIONS

When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.

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.

Co-Production of a Flexibly Delivered Relapse Prevention Tool to Support the Self-Management of Long-Term Mental Health Conditions: Co-Design and User Testing Study

BACKGROUND

Supported self-management interventions, which assist individuals in actively understanding and managing their own health conditions, have a robust evidence base for chronic physical illnesses, such as diabetes, but have been underused for long-term mental health conditions.

OBJECTIVE

This study aims to co-design and user test a mental health supported self-management intervention, My Personal Recovery Plan (MyPREP), that could be flexibly delivered via digital and traditional paper-based mediums.

METHODS

This study adopted a participatory design, user testing, and rapid prototyping methodologies, guided by 2 frameworks: the 2021 Medical Research Council framework for complex interventions and an Australian co-production framework. Participants were aged ≥18 years, self-identified as having a lived experience of using mental health services or working in a peer support role, and possessed English proficiency. The co-design and user testing processes involved a first round with 6 participants, focusing on adapting a self-management resource used in a large-scale randomized controlled trial in the United Kingdom, followed by a second round with 4 new participants for user testing the co-designed digital version. A final round for gathering qualitative feedback from 6 peer support workers was conducted. Data analysis involved transcription, coding, and thematic interpretation as well as the calculation of usability scores using the System Usability Scale.

RESULTS

The key themes identified during the co-design and user testing sessions were related to (1) the need for self-management tools to be flexible and well-integrated into mental health services, (2) the importance of language and how language preferences vary among individuals, (3) the need for self-management interventions to have the option of being supported when delivered in services, and (4) the potential of digitization to allow for a greater customization of self-management tools and the development of features based on individuals' unique preferences and needs. The MyPREP paper version received a total usability score of 71, indicating C+ or good usability, whereas the digital version received a total usability score of 85.63, indicating A or excellent usability.

CONCLUSIONS

There are international calls for mental health services to promote a culture of self-management, with supported self-management interventions being routinely offered. The resulting co-designed prototype of the Australian version of the self-management intervention MyPREP provides an avenue for supporting self-management in practice in a flexible manner. Involving end users, such as consumers and peer workers, from the beginning is vital to address their need for personalized and customized interventions and their choice in how interventions are delivered. Further implementation-effectiveness piloting of MyPREP in real-world mental health service settings is a critical next step.

Systematic review of early warning signs of relapse and behavioural antecedents of symptom worsening in people living with schizophrenia spectrum disorders

BACKGROUND

Identification of the early warning signs (EWS) of relapse is key to relapse prevention in schizophrenia spectrum disorders, however, limitations to their precision have been reported. Substantial methodological innovations have recently been applied to the prediction of psychotic relapse and to individual psychotic symptoms. However, there has been no systematic review that has integrated findings across these two related outcomes and no systematic review of EWS of relapse for a decade.

METHOD

We conducted a systematic review of EWS of psychotic relapse and the behavioural antecedents of worsening psychotic symptoms. Traditional EWS and ecological momentary assessment/intervention studies were included. We completed meta-analyses of the pooled sensitivity and specificity of EWS in predicting relapse, and for the prediction of relapse from individual symptoms.

RESULTS

Seventy two studies were identified including 6903 participants. Sleep, mood, and suspiciousness, emerged as predictors of worsening symptoms. Pooled sensitivity and specificity of EWS in predicting psychotic relapse was 71% and 64% (AUC value = 0.72). There was a large pooled-effect size for the model predicting relapse from individual symptom which did not reach statistical significance (d = 0.81, 95%CIs = -0.01, 1.63).

CONCLUSIONS

Important methodological advancements in the prediction of psychotic relapse in schizophrenia spectrum disorders are evident with improvements in the precision of prediction. Further efforts are required to translate these advances into effective clinical innovations.

Digital tools to support mental health: a survey study in psychosis

BACKGROUND

There is a notable a gap between promising research findings and implementation of digital health tools. Understanding and addressing barriers to use is key to widespread implementation.

METHODS

A survey was administered to a self-selecting sample in-person (n = 157) or online (n = 58), with questions examining: i) ownership and usage rates of digital devices among people with psychosis; ii) interest in using technology to engage with mental health services; and iii) facilitators of and barriers to using digital tools in a mental healthcare context.

RESULTS

Device ownership: Virtually all participants owned a mobile phone (95%) or smartphone (90%), with Android phones slightly more prevalent than iPhones. Only a minority owned a fitness tracker (15%) or smartwatch (13%). Device ownership was significantly lower in unemployed people and those without secondary education. Device cost and paranoid ideation were barriers to ownership. Technology and mental health services: Most participants (88%) said they would willingly try a mental health app. Symptom monitoring apps were most popular, then appointment reminders and medication reminders. Half the sample would prefer an app alongside face-to-face support; the other half preferred remote support or no other mental health support. Facilitators: Participants thought using a mental health app could increase their understanding of psychosis generally, and of their own symptoms. They valued the flexibility of digital tools in enabling access to support anywhere, anytime. Barriers: Prominent barriers to using mental health apps were forgetting, lack of motivation, security concerns, and concerns it would replace face-to-face care. Overall participants reported no substantial effects of technology on their mental health, although a quarter said using a phone worsened paranoid ideation. A third used technology more when psychotic symptoms were higher, whereas a third used it less. Around half used technology more when experiencing low mood.

CONCLUSIONS

Our findings suggest rapidly increasing device ownership among people with psychosis, mirroring patterns in the general population. Smartphones appear appropriate for delivering internet-enabled support for psychosis. However, for a sub-group of people with psychosis, the sometimes complex interaction between technology and mental health may act as a barrier to engagement, alongside more prosaic factors such as forgetting.

Digital intervention for public health: searching for implementing characteristics, concepts and recommendations: scoping review

Studying the impact of digital interventions on public health can help ensure that the offered services produce the desired results. In order to address these factors, the subsequent study uses a scope review to evaluate the state of the field while concentrating on ideas and suggestions that represent factors that have been crucial in the management of digital intervention for public health. To shed light on the traits, ideas and suggestions related to public health digital intervention, a scoping review was carried out. Five electronic databases were used to locate pertinent research that were published before February 2022. All texts were examined, and study abstracts were scrutinized to determine their eligibility. The last analysis of this study included fifteen publications; five reviews, four qualitative studies, two quantitative studies, one viewpoint study, one mixed-method study, one perspective study, and one interventional study. The key ideas for digital interventions in population management and health studies are presented in this overview. Many concepts, implementation characteristics and recommendations have been raised which highlight the future role of these interventions to enhance public engagement and health equity.

Using EMPOWER in daily life: a qualitative investigation of implementation experiences

BACKGROUND

Digital self-management tools blended with clinical triage and peer support have the potential to improve access to early warning signs (EWS) based relapse prevention in schizophrenia care. However, the implementation of digital interventions in psychosis can be poor. Traditionally, research focused on understanding how people implement interventions has focused on the perspectives of mental health staff. Digital interventions are becoming more commonly used by patients within the context of daily life, which means there is a need to understand implementation from the perspectives of patients and carers.

METHODS

Semi-structured one-on-one interviews with 16 patients who had access to the EMPOWER digital self-management intervention during their participation in a feasibility trial, six mental health staff members who supported the patients and were enrolled in the trial, and one carer participant. Interviews focused on understanding implementation, including barriers and facilitators. Data were coded using thematic analysis.

RESULTS

The intervention was well implemented, and EMPOWER was typically perceived positively by patients, mental health staff and the carer we spoke to. However, some patients reported negative views and reported ideas for intervention improvement. Patients reported valuing that the app afforded them access to things like information or increased social contact from peer support workers that went above and beyond that offered in routine care. Patients seemed motivated to continue implementing EMPOWER in daily life when they perceived it was creating positive change to their wellbeing, but seemed less motivated if this did not occur. Mental health staff and carer views suggest they developed increased confidence patients could self-manage and valued using the fact that people they support were using the EMPOWER intervention to open up conversations about self-management and wellbeing.

CONCLUSIONS

The findings from this study suggest peer worker supported digital self-management like EMPOWER has the potential to be implemented. Further evaluations of these interventions are warranted, and conducting qualitative research on the feasibility gives insight into implementation barriers and facilitators, improving the likelihood of interventions being usable. In particular, the views of patients who demonstrated low usage levels would be valuable.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Exploring digital cognitive behavioural therapy for insomnia in an early intervention in psychosis service - A study protocol for an initial feasibility study with process evaluation

AIM

Early psychosis may be a critical time at which clinical trajectories are still evolving, and sleep interventions hold promise to improve outcomes at this stage. Although cognitive behavioural therapy (CBT) for insomnia shows promise in psychosis, there has been limited evaluation of delivery within current care. This study aims to evaluate the feasibility and acceptability of providing fully-automated digital CBT for insomnia (CBT-I) within an early intervention in psychosis service.

METHODS

We will conduct a single-arm feasibility trial within an early psychosis intervention service, and up to 40 individuals experiencing a first episode of psychosis and with evidence of insomnia can be enrolled (May 2021 - August 2022). Additional service user inclusion criteria are capacity to consent and access to a suitable technological device to access digital CBT. Participants will be offered access to a fully-automated digital CBT-I program (Sleepio) delivered using web and/or mobile app. The study comprises pre- and post- intervention questionnaire assessments and interviews with service users and staff to provide initial outcome signals.

RESULTS

Quantitative questionnaire data will be analysed descriptively, alongside rates of eligibility, consent, uptake and completion. Qualitative data will be analysed using thematic analysis. Results will be used to develop a logic model describing feasibility and implementation.

CONCLUSIONS

From this study, we hope to better understand how to deliver digital CBT for insomnia within an early intervention in psychosis service. This study will help inform further research, including how best to support staff in using Sleepio, and inform the design of subsequent trials in this area.

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.

Digital Phenotyping for Mental Health: Reviewing the Challenges of Using Data to Monitor and Predict Mental Health Problems

PURPOSE OF REVIEW

We review recent developments within digital phenotyping for mental health, a field dedicated to using digital data for diagnosing, predicting, and monitoring mental health problems. We especially focus on recent critiques and challenges to digital phenotyping from within the social sciences.

RECENT FINDINGS

Three significant strands of criticism against digital phenotyping for mental health have been developed within the social sciences. This literature problematizes the idea that digital data can be objective, that it can be unbiased, and argues that it has multiple ethical and practical challenges. Digital phenotyping for mental health is a rapidly growing and developing field, but with considerable challenges that are not easily solvable. This includes when, and if, data from digital phenotyping is actionable in practice; the involvement of user and patient perspectives in digital phenotyping research; the possibility of biased data; and challenges to the idea that digital phenotyping can be more objective than other forms of psychiatric assessment.

Feasibility, Acceptability, and Potential Utility of Peer-supported Ecological Momentary Assessment Among People with Serious Mental Illness: a Pilot Study

To examine the feasibility, acceptability, and initial validity of using smartphone-based peer-supported ecological momentary assessment (EMA) as a tool to assess loneliness and functioning among adults with a serious mental illness diagnosis. Twenty-one adults with a diagnosis of a serious mental illness (i.e., schizophrenia, schizoaffective disorder, bipolar disorder, or treatment-refractory major depressive disorder) and at least one medical comorbidity (i.e., cardiovascular disease, obesity, diabetes, chronic obstructive pulmonary disease, hypertension, and/or high cholesterol) aged 18 years and older completed EMA surveys via smartphones once per day for 12-weeks. Nine peer support specialists prompted patients with SMI to complete the EMA surveys. Data were collected at baseline and 12-weeks. EMA acceptability (15.9%) was reported, and participants rated their experience with EMA methods positively. EMA responses were correlated with higher social support at 3 months. Higher levels of EMA-measured loneliness were significantly correlated with levels of social support, less hope, and less empowerment at 3 months. Lastly, those who contacted their peer specialist reported higher levels of loneliness and lower levels of functioning on that day suggesting that participants were able to use their peers for social support. Peer-supported EMA via smartphones is a feasible and acceptable data collection method among adults with SMI and appears to be a promising mobile tool to assess loneliness and functioning. These preliminary findings indicate EMA-measured loneliness and functioning are significantly predicted by baseline variables and such variables may impact engagement in EMA. EMA may contribute to future research examining the clinical utility of peer support specialists to alleviate feelings of loneliness and improve functioning.

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).

Digital screening for postnatal depression: mixed methods proof-of-concept study

Background

Depression during the postnatal year is prevalent in mothers (17%) and fathers (9%), and suicide is the leading cause of maternal death in this period. Lifelong costs and consequences of untreated postnatal depression (PND) are high due to impacts on infants as well as parents. We aimed to improve access to PND treatment using digital screening. We developed a smartphone app (ClinTouch DAWN-P) that allows parents to monitor their mood daily with the Edinburgh Postnatal Depression Scale (EPDS), uploading responses in real-time to a secure server. We evaluated the app’s feasibility, acceptability, validity and safety in a proof-of-concept study.

Methods

Pregnant women (≥ 36 weeks gestation) and partners were recruited from antenatal services and invited to complete daily EPDS assessments via the ClinTouch DAWN-P app until 6 weeks postpartum. Participants completed standard paper-based EPDS at two time points for validity comparisons. We examined app acceptability and usability at 6 weeks postpartum with qualitative interviews, examined using framework analysis, and the abridged Mobile App Rating Scale (convergent mixed methods design).

Results

Most (96%) eligible pregnant women approached were keen to try the app. Participating mothers (n = 15) and partners/fathers (n = 8) found the app easy to use, and 91% continued to use it for the full study period. Overall, 67% of daily app-based assessments were completed, with a history of depression predicting lower app usage. Participants suggested modifications to the app and its deployment to improve usability (e.g., extending the response window and including feedback and parenting advice). The validity of app-based responses was confirmed by high agreement with standard EPDS. App-based and paper-based ratings showed perfect agreement in identifying cases of likely PND. There were no serious adverse events relating to app use.

Conclusions

Digital PND screening appears feasible, acceptable, valid and safe. It also benefits from being remotely delivered: we enrolled all participants remotely during the first COVID-19 lockdown. Use of digital screening could address known shortcomings of conventional health visitor-delivered screening such as limited staff time, parental unwillingness to disclose difficulties to a professional, lack of partner/father screening, and language barriers.

Trial registration

The study was prospectively registered (Clinicaltrials.gov: NCT04279093).

Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives

BACKGROUND

Remote measurement technologies (RMT) such as mobile health devices and apps are increasingly used by those living with chronic neurological and mental health conditions. RMT enables real-world data collection and regular feedback, providing users with insights about their own conditions. Data visualizations are an integral part of RMT, although little is known about visualization design preferences from the perspectives of those living with chronic conditions.

OBJECTIVE

The aim of this review was to explore the experiences and preferences of individuals with chronic neurological and mental health conditions on data visualizations derived from RMT to manage health.

METHODS

In this systematic review, we searched peer-reviewed literature and conference proceedings (PubMed, IEEE Xplore, EMBASE, Web of Science, Association for Computing Machinery Computer-Human Interface proceedings, and the Cochrane Library) for original papers published between January 2007 and September 2021 that reported perspectives on data visualization of people living with chronic neurological and mental health conditions. Two reviewers independently screened each abstract and full-text article, with disagreements resolved through discussion. Studies were critically appraised, and extracted data underwent thematic synthesis.

RESULTS

We identified 35 eligible publications from 31 studies representing 12 conditions. Coded data coalesced into 3 themes: desire for data visualization, impact of visualizations on condition management, and visualization design considerations. Data visualizations were viewed as an integral part of users' experiences with RMT, impacting satisfaction and engagement. However, user preferences were diverse and often conflicting both between and within conditions.

CONCLUSIONS

When used effectively, data visualizations are valuable, engaging components of RMT. They can provide structure and insight, allowing individuals to manage their own health more effectively. However, visualizations are not "one-size-fits-all," and it is important to engage with potential users during visualization design to understand when, how, and with whom the visualizations will be used to manage health.

Investigating characteristics of idiopathic inflammatory myopathy flares using daily symptom data collected via a smartphone app

OBJECTIVE

The objective of this study was to use daily data collected via a smartphone app for characterization of patient-reported and symptom-based (using an a priori definition) flares in an adult idiopathic inflammatory myopathy (IIM) cohort.

METHODS

UK adults with an IIM answered patient-reported outcome measurements (PROMs) daily via a smartphone app during a 91-day study. Daily symptom PROMs addressed global activity, overall pain, myalgia, fatigue, and weakness (on a 0-100 visual analogue scale). Patient-reported flares were recorded via a weekly app question. Symptom-based flares were defined via an a priori definition related to increase in daily symptom data from the previous 4-day mean.

RESULTS

Twenty participants (65% female) participated. Patient-reported flares occurred on a median of 5 weeks (IQR 3, 7) per participant, out of a possible 13. The mean of each symptom score was significantly higher in flare weeks, compared with non-flare weeks (e.g. mean flare week myalgia score 34/100, vs 21/100 during non-flare week, t test P-value <0.01). Fatigue accounted for the most symptom-based flares [incidence-rate 23/100 person-days (95% CI 19, 27)], and myalgia the fewest [incidence rate 13/100 person-days (95% CI 11, 16)]. Symptom-based flares typically resolved after 3 days, although fatigue-predominant flares lasted 2 days. The majority (69%) of patient-reported flare weeks coincided with at least one symptom-based flare.

CONCLUSIONS

IIM flares are frequent and associated with increased symptom scores. This study has demonstrated the ability to identify and characterize patient-reported and symptom-based flares (based on an a priori definition), using daily app-collected data.

User perceptions of mobile digital apps for mental health: Acceptability and usability - An integrative review

WHAT IS KNOWN ON THE SUBJECT?: Mobile mental health apps are increasingly being used by both mental health nurses to promote individual self-managemental of mental health conditions and by consumers. Perceptions about specific apps are known, but the overarching acceptability and usability of mental health apps in general less understood. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: This paper identified consumer perceptions of mobile mental health apps. Six key areas were identified that future mobile app developers should consider to maximize consumer engagement with mental health apps. Consumers also highlighted that apps do not replace traditional mental health nursing-rather these supplement existing care. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: This review found that mental health apps are generally viewed positively by consumers; however, factors such as ease of use, usefulness of content and privacy need to be considered to maximise and sustain app engagement. ABSTRACT: Introduction There is increasing interest in the use of mobile mental health applications (apps) to manage mental health conditions. Understanding user perceptions is key to maximise app engagement and inform how apps can be used to support mental health nursing care. Aim This integrative review explores consumers' perceptions of mobile mental health apps to gain insight into user preferences and acceptability. Methods This integrative review was based on searching four databases: CINAHL, EMBASE, Medline, PsycInfo. Inclusion criteria were: (i) articles published after 2000; (ii) focused on apps for mental health disorders; (iii) explored consumers' perception of using a mental health app. Abstracts were screened and eligible papers reviewed. Data on user perceptions were extracted and analysed thematically. Results Seventeen articles were identified. Overall, consumers did not feel that app use replaced traditional health care. Six themes were identified: "Helpfulness," "Improvements/enhancements," "Technical issues," "Easy to use," "Satisfaction with the app" and "Perceived issues." Consumers indicated a preference for personalization for the app to meet individual needs. Discussion and Implications for Practice Mental health apps are generally viewed positively by consumers; however, factors such as ease of use, usefulness of content and privacy need to be considered to maximise and sustain app engagement.

ReMind, a smartphone application for psychotic relapse prediction: A longitudinal study protocol

BACKGROUND

Psychotic disorders are associated with a high rate of relapse. In addition to medication non-adherence, some psychosocial factors have been found to be predictive of relapse (e.g., poor premorbid adjustment, high expressed emotion and substance misuse). Impairments in cognitive functions including general memory functioning, set shifting, attention, processing speed and working memory have also been indicative of a subsequent psychotic episode. As clinical appointments do not always allow for timely or accurate detection of these early warning signs, the ReMind app is developed to explore potential relapse predictors and enhance the process of relapse monitoring.

AIM

The ReMind app aims (1) to assess whether verbal or visual working memory predicts psychotic relapse in 1 year and (2) to determine whether social factors such as stressful life events, level of expressed emotion and medication adherence also predict relapse in 1 year.

METHODS

This is a one-year prospective follow-up study involving 176 remitted patients diagnosed with schizophrenia or non-affective psychoses. Monthly relapse predictor assessments will be conducted via ReMind throughout the one-year study duration. These assessments include neurocognitive tasks and psychosocial questionnaires.

RESULTS

Recruitment began in August 2017 and is still ongoing. Preliminary user feedback suggested an overall positive experience with the app.

CONCLUSION

The ReMind app presents a step forward to the identification and sensitive detection of reliable psychosis relapse predictors. With its anticipated success, it may offer an alternative means of monitoring relapse for the Chinese-speaking population in the future.

Threats to Global Mental Health From Unregulated Digital Phenotyping and Neuromarketing: Recommendations for COVID-19 Era and Beyond

The new era of digitalized knowledge and information technology (IT) has improved efficiency in all medical fields, and digital health solutions are becoming the norm. There has also been an upsurge in utilizing digital solutions during the COVID-19 pandemic to address the unmet mental healthcare needs, especially for those unable to afford in-person office-based therapy sessions or those living in remote rural areas with limited access to mental healthcare providers. Despite these benefits, there are significant concerns regarding the widespread use of such technologies in the healthcare system. A few of those concerns are a potential breach in the patients' privacy, confidentiality, and the agency of patients being at risk of getting used for marketing or data harnessing purposes. Digital phenotyping aims to detect and categorize an individual's behavior, activities, interests, and psychological features to properly customize future communications or mental care for that individual. Neuromarketing seeks to investigate an individual's neuronal response(s) (cortical and subcortical autonomic) characteristics and uses this data to direct the person into purchasing merchandise of interest, or shaping individual's opinion in consumer, social or political decision making, etc. This commentary's primary concern is the intersection of these two concepts that would be an inevitable threat, more so, in the post-COVID era when disparities would be exaggerated globally. We also addressed the potential "dark web" applications in this intersection, worsening the crisis. We intend to raise attention toward this new threat, as the impacts might be more damming in low-income settings or/with vulnerable populations. Legal, health ethics, and government regulatory processes looking at broader impacts of digital marketing need to be in place.

A qualitative study of stakeholder views on the use of a digital app for supported self-management in early intervention services for psychosis

BACKGROUND

Digital tools such as Smartphones have the potential to increase access to mental health support including self-management interventions for individuals with psychosis, and ultimately to improve outcomes. Self-management strategies, including relapse prevention and crisis planning and setting personal recovery goals, are intended to assist people with long-term conditions to take an active role in their recovery, with evidence for a range of benefits. However, their implementation is inconsistent, and access and uptake need to be improved. The current study explores the acceptability of a Smartphone app (My Journey 3) that has been developed to facilitate supported self-management in Early Intervention in Psychosis (EIP) services.

METHODS

Semi-structured one-to-one interviews were conducted with twenty-one EIP service users who had access to My Journey 3 as part of a feasibility trial, and with thirteen EIP service clinicians who were supporting service users with the app. Interviews focused on the acceptability and usability of My Journey 3. Data was coded to themes based on the Acceptability of Healthcare Interventions framework.

RESULTS

Many service user participants found My Journey 3 to be acceptable. The symptom and medication trackers in particular were described as helpful. A smaller number of service users disliked the intervention. Individual-level factors that appeared to influence acceptability and engagement included recovery stage and symptom severity. Clinicians tended to report that My Journey 3 was a potentially positive addition to service users' care, but they often felt unable to provide support due to competing demands in their work, which in turn may have impacted acceptability and usage of the app.

CONCLUSIONS

Our findings suggest that the app is perceived as having potential to improve users' capacity to self-manage and work towards recovery goals, but barriers prevented many clinicians providing consistent and effective support as intended. Further evaluation of supported self-management apps in psychosis is warranted but needs to address implementation challenges from the start.

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.

Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Background

Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions.

Objective

This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs.

Methods

A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included.

Results

A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health.

Conclusions

Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.

Perspectives of Trial Staff on the Barriers to Recruitment in a Digital Intervention for Psychosis and How to Work Around Them: Qualitative Study Within a Trial

BACKGROUND

Recruitment processes for clinical trials of digital interventions for psychosis are seldom described in detail in the literature. Although trial staff have expertise in describing barriers to and facilitators of recruitment, a specific focus on understanding recruitment from the point of view of trial staff is rare, and because trial staff are responsible for meeting recruitment targets, a lack of research on their point of view is a key limitation.

OBJECTIVE

The primary aim of this study was to understand recruitment from the point of view of trial staff and discover what they consider important.

METHODS

We applied pluralistic ethnographic methods, including analysis of trial documents, observation, and focus groups, and explored the recruitment processes of the EMPOWER (Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-being, Engagement, and Recovery) feasibility trial, which is a digital app-based intervention for people diagnosed with schizophrenia.

RESULTS

Recruitment barriers were categorized into 2 main themes: service characteristics (lack of time available for mental health staff to support recruitment, staff turnover, patient turnover [within Australia only], management styles of community mental health teams, and physical environment) and clinician expectations (filtering effects and resistance to research participation). Trial staff negotiated these barriers through strategies such as emotional labor (trial staff managing feelings and expressions to successfully recruit participants) and trying to build relationships with clinical staff working within community mental health teams.

CONCLUSIONS

Researchers in clinical trials for digital psychosis interventions face numerous recruitment barriers and do their best to work flexibly and to negotiate these barriers and meet recruitment targets. The recruitment process appeared to be enhanced by trial staff supporting each other throughout the recruitment stage of the trial.

Elevated environmental PM2.5 increases risk of schizophrenia relapse: Mediation of inflammatory cytokines

BACKGROUND

Ecological epidemiology suggests that hospital admissions for schizophrenia are associated with an increased environmental PM_2.5, but no prospective study has verified this result, and the physiological mechanism is not clear.

METHODS

We used a repeated-measures design to prospectively assess the association of environmental PM_2.5 and the risk of relapse in schizophrenia, and used two linear mixed-effects models to explore possible mediating effects of immune cytokines on the premise of controlling confounders.

RESULTS

We import the data using EpiData software, and collate and analyze of the data using R software. The increase of PM_2.5 at lag0 had the greatest impact on the relapse of schizophrenia (for each 10 μg/m³ increase in PM_2.5, the relapse risk score increased by 1.504, that is to say, odds ratio (OR) = 4.500 (95% confidence interval (CI): 2.849-7.106，P < 0.001)), and cumulative effects lasted for four days with the maximum at the second day (for each 10 μg/m³ increase in PM_2.5, the relapse risk score increased by 1.301, OR = 3.673 (95%CI: 1.962-6.876，P < 0.001)). PM_2.5 exposure was statistically related to four symptom dimensions of early signs scale (ESS), and the symptoms most affected by the increased PM_2.5 were depression/withdrawal (ESSN) (OR = 1.990, 95%CI: 1.701-2.328), anxiety/agitation (ESS-A) (OR = 1.537, 95%CI: 1.340-1.763), initial psychosis (ESS-IP) (OR = 1.398, 95%CI: 1.151-1.697), and disinhibition (ESS-D) (OR = 1.235, 95%CI: 1.133-1.347). Furthermore, there are three statistically significant pathways in intermediary analysis: of PM_2.5 and relapse risk: "PM_2.5 → IL-17 → ESS", "PM_2.5 → IL-17 → ESS-A", and "PM_2.5 → IL-17 → ESS-N", and the intermediary ratio of IL-17 was 11.66%, 16.37% and 22.55%, respectively.

CONCLUSIONS

Increased environmental PM_2.5 is a risk factor for the relapse of schizophrenia. Early relapse identification and intervention based on clinical characteristics are of great significance for timely termination of relapse and slowing down of relapse.

mHealth-Assisted Detection of Precursors to Relapse in Schizophrenia

Theoretical views and a growing body of empirical evidence suggest that psychiatric relapses in schizophrenia-spectrum disorders (SSDs) have measurable warning signs. However, because they are time- and resource-intensive, existing assessment approaches are not well-suited to detect these warning signs in a timely, scalable fashion. Mobile technologies deploying frequent measurements-i.e., ecological momentary assessment-could be leveraged to detect increases in symptoms that may precede relapses. The present study examined EMA measurements with growth curve models in the 100 days preceding and following 27 relapses (among n = 20 individuals with SSDs) to identify (1) what symptoms changed in the periods gradually preceding, following, and right as relapses occur, (2) how large were these changes, and (3) on what time scale did they occur. Results demonstrated that, on average, participants reported elevations in negative mood (d = 0.34), anxiety (d =0.49), persecutory ideation (d =0.35), and hallucinations (d =0.34) on relapse days relative to their average during the study. These increases emerged gradually on average from significant and steady increases (d = 0.05 per week) in persecutory ideation and hallucinations over the 100-day period preceding relapse. This suggests that brief (i.e., 1-2 item) assessments of psychotic symptoms may detect meaningful signals that precede psychiatric relapses long before they occur. These assessments could increase opportunities for relapse prevention as remote measurement-based care management platforms develop.

Assessing the relationship between routine and schizophrenia symptoms with passively sensed measures of behavioral stability

Increased stability in one's daily routine is associated with well-being in the general population and often a goal of behavioral interventions for people with serious mental illnesses like schizophrenia. Assessing behavioral stability has been limited in clinical research by the use of retrospective scales, which are susceptible to reporting biases and memory inaccuracies. Mobile passive sensors, which are less susceptible to these sources of error, have emerged as tools to assess behavioral patterns in a range of populations. The present study developed and examined a metric of behavioral stability from data generated by a passive sensing system carried by 61 individuals with schizophrenia for one year. This metric-the Stability Index-appeared orthogonal from existing measures drawn from passive sensors and matched the predictive performance of state-of-the-art features. Specifically, greater stability in social activity (e.g., calls and messages) were associated with lower symptoms, and greater stability in physical activity (e.g., being still) appeared associated with elevated symptoms. This study provides additional support for the predictive value of individualized over population-level data in psychiatric populations. The Stability Index offers also a promising tool for generating insights about the impact of behavioral stability in schizophrenia-spectrum disorders.

ReMindCare App for Early Psychosis: Pragmatic Real World Intervention and Usability Study

Background

eHealth interventions are widely used in clinical trials and increasingly in care settings as well; however, their efficacy in real-world contexts remains unknown. ReMindCare is a smartphone app that has been systematically implemented in a first episode of psychosis program (FEPP) for patients with early psychosis since 2018.

Objective

The objective of this study was to assess the efficacy of ReMindCare after 19 months of use in the clinic and varying use by individual patients.

Methods

The integration of the ReMindCare app into the FEPP started in October 2018. Patients with early psychosis self-selected to the app (ReMindCare group) or treatment as usual (TAU group). The outcome variables considered were adherence to the intervention and number of relapses, hospital admissions, and visits to urgent care units. Data from 90 patients with early psychosis were analyzed: 59 in the ReMindCare group and 31 in the TAU group. The mean age of the sample was 32.8 (SD 9.4) years, 73% (66/90) were males, 91% (83/90) were White, and 81% (74/90) were single.

Results

Significant differences between the ReMindCare and TAU groups were found in the number of relapses, hospitalizations, and visits to urgent care units, with each showing benefits for the app. Only 20% (12/59) of patients from the ReMindCare group had a relapse, while 58% (18/31) of the TAU patients had one or more relapses (χ²=13.7, P=.001). Moreover, ReMindCare patients had fewer visits to urgent care units (χ²=7.4, P=.006) and fewer hospitalizations than TAU patients (χ²=4.6, P=.03). The mean of days using the app was 352.2 (SD 191.2; min/max: 18-594), and the mean of engagement was 84.5 (SD 16.04).

Conclusions

To our knowledge, this is the first eHealth intervention that has preliminarily proven its benefits in the real-world treatment of patients with early psychosis.

International Registered Report Identifier (IRRID)

RR2-10.1111/eip.12960

Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study

BACKGROUND

Smartphone-based ecological momentary assessment (EMA) is a promising methodology for mental health research. The objective of this study is to determine the feasibility of smartphone-based active and passive EMA in psychiatric outpatients and student controls.

METHODS

Two smartphone applications -MEmind and eB²- were developed for behavioral active and passive monitoring. The applications were tested in psychiatric patients with a history of suicidal thoughts and/or behaviors (STB), psychiatric patients without a history of STB, and student controls. Main outcome was feasibility, measured as response to recruitment, retention, and EMA compliance. Secondary outcomes were patterns of smartphone usage.

RESULTS

Response rate was 87.3% in patients with a history of STB, 85.1% in patients without a history of STB, and 75.0% in student controls. 457 participants installed the MEmind app (120 patients with a history of STB and 337 controls) and 1,708 installed the eB² app (139 patients with a history of STB, 1,224 patients with no history of STB and 346 controls). For the MEmind app, participants were followed-up for a median of 49.5, resulting in 22,622 person-days. For the eB² application, participants were followed-up for a median of 48.9 days, resulting in 83,521 person-days. EMA compliance rate was 65.00% in suicidal patients and 75.21% in student controls. At the end of the follow-up, over 60% of participants remained in the study.

LIMITATIONS

Cases and controls were not matched by age and sex. Cases were patients who were receiving adequate psychopharmacological treatment and attending their appointments, which may result in an overstatement of clinical compliance.

CONCLUSIONS

Smartphone-based active and passive monitoring are feasible methods in psychiatric patients in real-world settings. The development of applications with friendly interfaces and directly useful features can help increase engagement without using incentives. The MEmind and eB² applications are promising clinical tools that could contribute to the management of mental disorders. In the near future, these applications could serve as risk monitoring devices in the clinical practice.

Engaging With a Web-Based Psychosocial Intervention for Psychosis: Qualitative Study of User Experiences

BACKGROUND

Web-based interventions are increasingly being used for individuals with serious mental illness, including psychosis, and preliminary evidence suggests clinical benefits. To achieve such benefits, individuals must have some level of engagement with the intervention. Currently, little is known about what influences engagement with web-based interventions for individuals with psychotic disorders.

OBJECTIVE

This study aimed to explore users' perspectives on what influenced engagement with a web-based intervention for psychosis.

METHODS

A qualitative design was employed using semistructured telephone interviews. Participants were 17 adults with psychosis who had participated in a trial examining engagement with a self-guided, web-based intervention promoting personal recovery and self-management of mental health.

RESULTS

We identified 2 overarching themes: challenges to using the website and factors supporting persistence. Both of the main themes included several subthemes related to both user-related factors (eg, mental health, personal circumstances, approach to using the website) and users' experience of the intervention (eg, having experienced similar content previously or finding the material confronting).

CONCLUSIONS

Individuals with psychosis experienced several challenges to ongoing engagement with a web-based intervention. Adjunctive emails present an important design feature to maintain interest and motivation to engage with the intervention. However, fluctuations in mental health and psychosocial difficulties are a significant challenge. Design and implementation considerations include flexible interventions with tailoring opportunities to accommodate changeable circumstances and individual preferences.

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

Understanding Implementation of a Digital Self-Monitoring Intervention for Relapse Prevention in Psychosis: Protocol for a Mixed Method Process Evaluation

Background

Relapse is common in people who experience psychosis and is associated with many negative consequences, both societal and personal. People who relapse often exhibit changes (early warning signs [EWS]) in the period before relapse. Successful identification of EWS offers an opportunity for relapse prevention. However, several known barriers impede the use of EWS monitoring approaches. Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) is a complex digital intervention that uses a mobile app to enhance the detection and management of self-reported changes in well-being. This is currently being tested in a pilot cluster randomized controlled trial. As digital interventions have not been widely used in relapse prevention, little is known about their implementation. Process evaluation studies run in parallel to clinical trials can provide valuable data on intervention feasibility.

Objective

This study aims to transparently describe the protocol for the process evaluation element of the EMPOWER trial. We will focus on the development of a process evaluation framework sensitive to the worldview of service users, mental health staff, and carers; the aims of the process evaluation itself; the proposed studies to address these aims; and a plan for integration of results from separate process evaluation studies into one overall report.

Methods

The overall process evaluation will utilize mixed methods across 6 substudies. Among them, 4 will use qualitative methodologies, 1 will use a mixed methods approach, and 1 will use quantitative methodologies.

Results

The results of all studies will be triangulated into an overall analysis and interpretation of key implementation lessons. EMPOWER was funded in 2016, recruitment finished in January 2018. Data analysis is currently under way and the first results are expected to be submitted for publication in December 2019.

Conclusions

The findings from this study will help identify implementation facilitators and barriers to EMPOWER. These insights will inform both upscaling decisions and optimization of a definitive trial.

Trial Registration

ISRCTN Registry ISRCTN99559262; http://www.isrctn.com/ISRCTN99559262

International Registered Report Identifier (IRRID)

DERR1-10.2196/15634

Developing a Hypothetical Implementation Framework of Expectations for Monitoring Early Signs of Psychosis Relapse Using a Mobile App: Qualitative Study

Background

Relapse is a common experience for people diagnosed with psychosis, which is associated with increased service costs and profound personal and familial distress. EMPOWER (Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery) is a peer worker–supported digital intervention that aims to enable service users to self-monitor their mental health with the aim of encouraging self-management and the shared use of personal data to promote relapse prevention. Digital interventions have not been widely used in relapse prevention and, therefore, little is currently known about their likely implementation—both within trials and beyond.

Objective

Seeking the perspectives of all relevant stakeholder groups is recommended in developing theories about implementation because this can reveal important group differences in understandings and assumptions about whether and for whom the intervention is expected to work. However, the majority of intervention implementation research has been retrospective. This study aimed to discover and theoretically frame implementation expectations in advance of testing and synthesize these data into a framework.

Methods

To develop a hypothetical implementation framework, 149 mental health professionals, carers, and people diagnosed with psychosis participated in 25 focus groups in both Australia and the United Kingdom. An interview schedule informed by the normalization process theory was used to explore stakeholders’ expectations about the implementation of the EMPOWER intervention. Data were analyzed using thematic analysis and then theoretically framed using the Medical Research Council guidelines for understanding the implementation of complex interventions.

Results

All groups expected that EMPOWER could be successfully implemented if the intervention generated data that were meaningful to mental health staff, carers, and service users within their unique roles. However, there were key differences between staff, carers, and service users about what facilitators and barriers that stakeholders believe exist for intervention implementation in both the cluster randomized controlled trial stage and beyond. For example, service user expectations mostly clustered around subjective user experiences, whereas staff and carers spoke more about the impact upon staff interactions with service users.

Conclusions

A hypothetical implementation framework synthesized from stakeholder implementation expectations provides an opportunity to compare actual implementation data gathered during an ongoing clinical trial, giving valuable insights into the accuracy of these stakeholders’ previous expectations. This is among the first studies to assess and record implementation expectations for a newly developed digital intervention for psychosis in advance of testing in a clinical trial.

Trial Registration

ISRCTN Registry ISRCTN99559262; http://www.isrctn.com/ISRCTN99559262

Feasibility of using a smartphone app to assess early signs, basic symptoms and psychotic symptoms over six months: A preliminary report

BACKGROUND

Psychosis relapses are common, have profound adverse consequences for patients, and are costly to health services. 'Early signs' have been used to predict relapse, in the hope of prevention or mitigation, with moderate sensitivity and specificity. We investigated the feasibility and validity of adding 'basic symptoms' to conventional early signs and monitoring these using a smartphone app.

METHODS

Individuals (n = 18) experiencing a relapse within the past year were asked to use a smartphone app ('ExPRESS') weekly for six months to report early signs, basic symptoms and psychotic symptoms. Above-threshold increases in app-reported psychotic symptoms prompted a telephone interview (PANSS positive items) to assess relapse.

RESULTS

Participants completed 65% app assessments and 58% telephone interviews. App items showed high concurrent validity with researcher-rated psychotic symptoms and basic symptoms over six months. There was excellent agreement between telephone call and face-to-face assessed psychotic symptoms. The primary relapse definition, based on telephone assessment and casenotes, compared well with a casenote-only definition but had better specificity. Mixed-effects models provided preliminary evidence of concurrent and predictive validity: early signs and basic symptoms were associated with most app-assessed psychotic symptom variables the same week and with a number of psychotic symptoms variables three weeks later; adding basic symptoms to early signs improved model fit in most of these cases.

CONCLUSIONS

This is the first study to test a smartphone app for monitoring early signs and basic symptoms as putative relapse predictors. It demonstrates that weekly app-based monitoring is feasible, valid and acceptable over six months.