Adverse event monitoring in mHealth for psychosis interventions provides an important opportunity for learning

Developing a process for assessing the safety of a digital mental health intervention and gaining regulatory approval: a case study and academic's guide

BACKGROUND

The field of digital mental health has followed an exponential growth trajectory in recent years. While the evidence base has increased significantly, its adoption within health and care services has been slowed by several challenges, including a lack of knowledge from researchers regarding how to navigate the pathway for mandatory regulatory approval. This paper details the steps that a team must take to achieve the required approvals to carry out a research study using a novel digital mental health intervention. We used a randomised controlled trial of a digital mental health intervention called STOP (Successful Treatment of Paranoia) as a worked example.

METHODS

The methods section explains the two main objectives that are required to achieve regulatory approval (MHRA Notification of No Objection) and the detailed steps involved within each, as carried out for the STOP trial. First, the existing safety of digital mental health interventions must be demonstrated. This can refer to literature reviews, any feasibility/pilot safety data, and requires a risk management plan. Second, a detailed plan to further evaluate the safety of the digital mental health intervention is needed. As part of this we describe the STOP study's development of a framework for categorising adverse events and based on this framework, a tool to collect adverse event data.

RESULTS

We present literature review results, safety-related feasibility study findings and the full risk management plan for STOP, which addressed 26 possible hazards, and included the 6-point scales developed to quantify the probability and severity of typical risks involved when a psychiatric population receives a digital intervention without the direct support of a therapist. We also present an Adverse Event Category Framework for Digital Therapeutic Devices and the Adverse Events Checklist-which assesses 15 different categories of adverse events-that was constructed from this and used in the STOP trial.

CONCLUSIONS

The example shared in this paper serves as a guide for academics and professionals working in the field of digital mental health. It provides insights into the safety assessment requirements of regulatory bodies when a clinical investigation of a digital mental health intervention is proposed. Methods, scales and tools that could easily be adapted for use in other similar research are presented, with the expectation that these will assist other researchers in the field seeking regulatory approval for digital mental health products.

Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context

BACKGROUND

Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.

AIMS

The aim of this study was to generate an experts' consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs.

METHOD

An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health.

RESULTS

Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general.

CONCLUSION

The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk.

Measurement of Adverse Events in Studies of Digital Health Interventions for Psychosis: Guidance and Recommendations Based on a Literature Search and Framework Analysis of Standard Operating Procedures

BACKGROUND

Given the rapid expansion of research into digital health interventions (DHIs) for severe mental illness (SMI; eg, schizophrenia and other psychosis diagnoses), there is an emergent need for clear safety measures. Currently, measurement and reporting of adverse events (AEs) are inconsistent across studies. Therefore, an international network, iCharts, was assembled to systematically identify and refine a set of standard operating procedures (SOPs) for AE reporting in DHI studies for SMI.

DESIGN

The iCharts network comprised experts on DHIs for SMI from seven countries (United Kingdom, Belgium, Germany, Pakistan, Australia, United States, and China) and various professional backgrounds. Following a literature search, SOPs of AEs were obtained from authors of relevant studies, and from grey literature.

RESULTS

A thorough framework analysis of SOPs (n = 32) identified commonalities for best practice for certain domains, along with significant gaps in others; particularly around the classification of AEs during trials, and the provision of training/supervision for research staff in measuring and reporting AEs. Several areas which could lead to the observed inconsistencies in AE reporting and handling were also identified.

CONCLUSIONS

The iCharts network developed best-practice guidelines and a practical resource for AE monitoring in DHI studies for psychosis, based on a systematic process which identified common features and evidence gaps. This work contributes to international efforts to standardize AE measurement and reporting in this emerging field, ensuring that safety aspects of DHIs for SMI are well-studied across the translational pathway, with monitoring systems set-up from the outset to support safe implementation in healthcare systems.

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.

Adverse Events Reporting in Digital Interventions Evaluations for Psychosis: A Systematic Literature Search and Individual Level Content Analysis of Adverse Event Reports

BACKGROUND

Digital health interventions (DHIs) have significant potential to upscale treatment access to people experiencing psychosis but raise questions around patient safety. Adverse event (AE) monitoring is used to identify, record, and manage safety issues in clinical trials, but little is known about the specific content and context contained within extant AE reports. This study aimed to assess current AE reporting in DHIs.

STUDY DESIGN

A systematic literature search was conducted by the iCharts network (representing academic, clinical, and experts by experience) to identify trials of DHIs in psychosis. Authors were invited to share AE reports recorded in their trials. A content analysis was conducted on the shared reports.

STUDY RESULTS

We identified 593 AE reports from 18 DHI evaluations, yielding 19 codes. Only 29 AEs (4.9% of total) were preidentified by those who shared AEs as being related to the intervention or trial procedures. While overall results support the safety of DHIs, DHIs were linked to mood problems and psychosis exacerbation in a few cases. Additionally, 27% of studies did not report information on relatedness for all or at least some AEs; 9.6% of AE reports were coded as unclear because it could not be determined what had happened to participants.

CONCLUSIONS

The results support the safety of DHIs, but AEs must be routinely monitored and evaluated according to best practice. Individual-level analyses of AEs have merit to understand safety in this emerging field. Recommendations for best practice reporting in future studies are provided.

Effectiveness and cost-effectiveness of online recorded recovery narratives in improving quality of life for people with non-psychotic mental health problems: a pragmatic randomized controlled trial

Narratives describing first-hand experiences of recovery from mental health problems are widely available. Emerging evidence suggests that engaging with mental health recovery narratives can benefit people experiencing mental health problems, but no randomized controlled trial has been conducted as yet. We developed the Narrative Experiences Online (NEON) Intervention, a web application providing self-guided and recommender systems access to a collection of recorded mental health recovery narratives (n=659). We investigated whether NEON Intervention access benefited adults experiencing non-psychotic mental health problems by conducting a pragmatic parallel-group randomized trial, with usual care as control condition. The primary endpoint was quality of life at week 52 assessed by the Manchester Short Assessment (MANSA). Secondary outcomes were psychological distress, hope, self-efficacy, and meaning in life at week 52. Between March 9, 2020 and March 26, 2021, we recruited 1,023 participants from across England (the target based on power analysis was 994), of whom 827 (80.8%) identified as White British, 811 (79.3%) were female, 586 (57.3%) were employed, and 272 (26.6%) were unemployed. Their mean age was 38.4±13.6 years. Mood and/or anxiety disorders (N=626, 61.2%) and stress-related disorders (N=152, 14.9%) were the most common mental health problems. At week 52, our intention-to-treat analysis found a significant baseline-adjusted difference of 0.13 (95% CI: 0.01-0.26, p=0.041) in the MANSA score between the intervention and control groups, corresponding to a mean change of 1.56 scale points per participant, which indicates that the intervention increased quality of life. We also detected a significant baseline-adjusted difference of 0.22 (95% CI: 0.05-0.40, p=0.014) between the groups in the score on the "presence of meaning" subscale of the Meaning in Life Questionnaire, corresponding to a mean change of 1.1 scale points per participant. We found an incremental gain of 0.0142 quality-adjusted life years (QALYs) (95% credible interval: 0.0059 to 0.0226) and a £178 incremental increase in cost (95% credible interval: -£154 to £455) per participant, generating an incremental cost-effectiveness ratio of £12,526 per QALY compared with usual care. This was lower than the £20,000 per QALY threshold used by the National Health Service in England, indicating that the intervention would be a cost-effective use of health service resources. In the subgroup analysis including participants who had used specialist mental health services at baseline, the intervention both reduced cost (-£98, 95% credible interval: -£606 to £309) and improved QALYs (0.0165, 95% credible interval: 0.0057 to 0.0273) per participant as compared to usual care. We conclude that the NEON Intervention is an effective and cost-effective new intervention for people experiencing non-psychotic mental health problems.

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.

Young people's experience of online therapy for first-episode psychosis: A qualitative study

OBJECTIVES

This study aimed to understand how young people with first-episode psychosis experienced online therapy on a Moderated Online Social Therapy (MOST) platform known as Horyzons.

METHODS

Semi-structured in-depth qualitative interviews were conducted with 12 young people who had previously participated in Horyzons, a randomized controlled trial (RCT) of a long-term digital intervention for first-episode psychosis. Interviews were analysed using a phenomenological approach.

RESULTS

This study found that the online therapy experience for first-episode psychosis was idiosyncratic, taking on different meaning for different users. The relatively fixed therapeutic content led to experiences that included on-demand help-seeking, positive distraction, revision, generalization and translation, and normalization. We also found that although the experience of online therapy was motivating to some, it was overwhelming for others.

CONCLUSIONS

The self-directed and flexible nature of the Horyzons online therapy gave some young people a sense of welcomed control over their mental health journey, and others felt overwhelmed by the high level of choice. Feeling overwhelmed by the level of choice appeared to interrupt their engagement with the platform, and thus their overall ability to use the intervention meaningfully. We also found that on-demand help-seeking and positive distraction were two functions unique to young people through online therapy and may have been related to the significant reduction in the number of overall presentations by young people to emergency departments and a non-significant trend for lower hospitalizations due to psychosis in the intervention group of the Horyzons RCT.

PRACTITIONER POINTS

Young people used online therapy for on-demand support to help deal with distress. Young people used online therapy to distract themselves from distress in a positive way. Some young people valued the flexibility of online therapy, which increased their motivation to engage with it. Some young people were overwhelmed by the amount of choice available to them via online therapy, which decreased their motivation to engage.

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.

Clinical Utility of Wearable Sensors and Patient-Reported Surveys in Patients With Schizophrenia: Noninterventional, Observational Study

BACKGROUND

Relapse in schizophrenia may be preceded by early warning signs of biological, sensory, and clinical status. Early detection of warning signs may facilitate intervention and prevent relapses.

OBJECTIVE

This study aims to investigate the feasibility of using wearable devices and self-reported technologies to identify symptom exacerbation correlates and relapse in patients with schizophrenia.

METHODS

In this observational study, patients with schizophrenia were provided with remote sensing devices to continuously monitor activity (Garmin vivofit) and sleep (Philips Actiwatch), and smartphones were used to record patient-reported outcomes. Clinical assessments of symptoms (Positive and Negative Syndrome Scale and Brief Psychiatric Rating Scale) were performed biweekly, and other clinical scales on symptoms (Clinical Global Impression-Schizophrenia, Calgary Depression Scale), psychosocial functioning, physical activity (Yale Physical Activity Survey), and sleep (Pittsburgh Sleep Quality Index) were assessed every 4 weeks. Patients were observed for 4 months, and correlations between clinical assessments and aggregated device metrics data were assessed using a mixed-effect model. An elastic net model was used to predict the clinical symptoms based on the device features.

RESULTS

Of the 40 patients enrolled, 1 patient relapsed after being stable with evaluable postbaseline data. Weekly patient-reported outcomes were moderately correlated with psychiatric symptoms (Brief Psychiatric Rating Scale total score, r=0.29; Calgary Depression Scale total score, r=0.37; and Positive and Negative Syndrome Scale total score, r=0.3). In the elastic net model, sleep and activity features derived from Philips Actigraph and Garmin vivofit were predictive of the sitting index of the Yale Physical Activity Survey and sleep duration component of the Pittsburgh Sleep Quality Index. On the basis of the combined patient data, a high percentage of data coverage and compliance (>80%) was observed for each device.

CONCLUSIONS

This study demonstrated that wearable devices and smartphones could be effectively deployed and potentially used to monitor patients with schizophrenia. Furthermore, metrics-based prediction models can assist in detecting earlier signs of symptom changes. The operational learnings from this study may provide insights to conduct future studies.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02224430; https://www.clinicaltrials.gov/ct2/show/NCT02224430.

Using apps for bipolar disorder - An online survey of healthcare provider perspectives and practices

BACKGROUND

Smartphone apps have recognized potential for improving access to evidence-based care in the treatment of bipolar disorder (BD). Healthcare providers are well-positioned to play a role in guiding patients to access safe, evidence-supported, and trustworthy apps. However, little is known about whether and how clinicians use apps with people with BD: understanding practices and attitudes of healthcare providers is essential to support the implementation of mHealth interventions in a real-world context.

METHODS

A web-based survey was used to explore clinicians' attitudes towards, and use of apps when working with people with BD. Descriptive statistics were used to summarize quantitative findings. Free text responses were investigated using qualitative content analysis.

RESULTS

Eighty healthcare providers completed the survey. Approximately half of the respondents reported discussing or recommending apps in clinical practice with BD populations. Recommended apps were most commonly related to mood, sleep, and exercise. Barriers to discussing apps included a lack of healthcare provider knowledge/confidence, concerns about patients' ability to access apps, and beliefs that patients lacked interest in apps.

CONCLUSION

Although research suggests that people with BD are interested in using apps, uptake of such technology among clinicians is more limited. A lack of clinician knowledge regarding apps, combined with concerns about the digital divide and patient interest, may account for this relatively limited integration of apps into the management of BD. These findings emphasise the importance of considering the information needs of healthcare providers when planning dissemination strategies for app-based interventions for BD.

Can digital data diagnose mental health problems? A sociological exploration of 'digital phenotyping'

This paper critically explores the research and development of 'digital phenotyping', which broadly refers to the idea that digital data can measure and predict people's mental health as well as their potential risk for mental ill health. Despite increasing research and efforts to digitally track and predict ill mental health, there has been little sociological and critical engagement with this field. This paper aims to fill this gap by introducing digital phenotyping to the social sciences. We explore the origins of digital phenotyping, the concept of the digital phenotype and its potential for benefit, linking these to broader developments within the field of 'mental health sensing'. We then critically discuss the technology, offering three critiques. First, that there may be assumptions of normality and bias present in the use of algorithms; second, we critique the idea that digital data can act as a proxy for social life; and third that the often biological language employed in this field risks reifying mental health problems. Our aim is not to discredit the scientific work in this area, but rather to call for scientists to remain reflexive in their work, and for more social science engagement in this area.

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

Experiences of a Web-Based Quality of Life Self-Monitoring Tool for Individuals With Bipolar Disorder: A Qualitative Exploration

BACKGROUND

Self-monitoring of symptoms is a cornerstone of psychological interventions in bipolar disorder (BD), but individuals with lived experience also value tracking holistic outcomes, such as quality of life (QoL). Importantly, self-monitoring is not always experienced positively by people with BD and may have lower than expected rates of engagement. Therefore, before progressing into QoL tracking tools, it is important to explore user perspectives to identify possible risks and benefits, optimal methods to support engagement, and possible avenues to integrate QoL self-monitoring practices into clinical work.

OBJECTIVE

This study aimed to conduct a qualitative exploration of how individuals with BD engaged with a Web-based version of a BD-specific QoL self-monitoring instrument, the QoL tool.

METHODS

A total of 43 individuals with BD engaged with a self-management intervention with an optional Web-based QoL self-assessment tool as part of an overarching mixed method study. Individuals were later interviewed about personal experiences of engagement with the intervention, including experiences of gauging their own QoL. A thematic analysis was used to identify salient aspects of the experience of QoL self-monitoring in BD.

RESULTS

In total, 4 categories describing people's experiences of QoL self-monitoring were identified: (1) breadth of QoL monitoring, (2) highlighting the positive, (3) connecting self-monitoring to action, and (4) self-directed patterns of use.

CONCLUSIONS

The findings of this research generate novel insights into ways in which individuals with BD experience the Web-based QoL self-assessment tool. The value of tracking the breadth of domains was an overarching aspect, facilitating the identification of both areas of strength and life domains in need of intervention. Importantly, monitoring QoL appeared to have an inherently therapeutic quality, through validating flourishing areas and reinforcing self-management efforts. This contrasts the evidence suggesting that symptom tracking may be distressing because of its focus on negative experiences and positions QoL as a valuable adjunctive target of observation in BD. Flexibility and personalization of use of the QoL tool were key to engagement, informing considerations for health care providers wishing to support self-monitoring and future research into Web- or mobile phone-based apps.

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.