The Implementation of Recommender Systems for Mental Health Recovery Narratives: Evaluation of Use and Performance.

BACKGROUND: Recommender systems help narrow down a large range of items to a smaller, personalized set. NarraGive is a first-in-field hybrid recommender system for mental health recovery narratives, recommending narratives based on their content and narrator characteristics (using content-based filtering) and on narratives beneficially impacting other similar users (using collaborative filtering). NarraGive is integrated into the Narrative Experiences Online (NEON) intervention, a web application providing access to the NEON Collection of recovery narratives. OBJECTIVE: This study aims to analyze the 3 recommender system algorithms used in NarraGive to inform future interventions using recommender systems for lived experience narratives. METHODS: Using a recently published framework for evaluating recommender systems to structure the analysis, we compared the content-based filtering algorithm and collaborative filtering algorithms by evaluating the accuracy (how close the predicted ratings are to the true ratings), precision (the proportion of the recommended narratives that are relevant), diversity (how diverse the recommended narratives are), coverage (the proportion of all available narratives that can be recommended), and unfairness (whether the algorithms produce less accurate predictions for disadvantaged participants) across gender and ethnicity. We used data from all participants in 2 parallel-group, waitlist control clinical trials of the NEON intervention (NEON trial: N=739; NEON for other [eg, nonpsychosis] mental health problems [NEON-O] trial: N=1023). Both trials included people with self-reported mental health problems who had and had not used statutory mental health services. In addition, NEON trial participants had experienced self-reported psychosis in the previous 5 years. Our evaluation used a database of Likert-scale narrative ratings provided by trial participants in response to validated narrative feedback questions. RESULTS: Participants from the NEON and NEON-O trials provided 2288 and 1896 narrative ratings, respectively. Each rated narrative had a median of 3 ratings and 2 ratings, respectively. For the NEON trial, the content-based filtering algorithm performed better for coverage; the collaborative filtering algorithms performed better for accuracy, diversity, and unfairness across both gender and ethnicity; and neither algorithm performed better for precision. For the NEON-O trial, the content-based filtering algorithm did not perform better on any metric; the collaborative filtering algorithms performed better on accuracy and unfairness across both gender and ethnicity; and neither algorithm performed better for precision, diversity, or coverage. CONCLUSIONS: Clinical population may be associated with recommender system performance. Recommender systems are susceptible to a wide range of undesirable biases. Approaches to mitigating these include providing enough initial data for the recommender system (to prevent overfitting), ensuring that items can be accessed outside the recommender system (to prevent a feedback loop between accessed items and recommended items), and encouraging participants to provide feedback on every narrative they interact with (to prevent participants from only providing feedback when they have strong opinions).

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.

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.

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

BACKGROUND: Paranoia is a highly debilitating mental health condition. One novel intervention for paranoia is cognitive bias modification for paranoia (CBM-pa). CBM-pa comes from a class of interventions that focus on manipulating interpretation bias. Here, we aimed to develop and evaluate new therapy content for CBM-pa for later use in a self-administered digital therapeutic for paranoia called STOP ("Successful Treatment of Paranoia"). OBJECTIVE: This study aimed to (1) take a user-centered approach with input from living experts, clinicians, and academics to create and evaluate paranoia-relevant item content to be used in STOP and (2) engage with living experts and the design team from a digital health care solutions company to cocreate and pilot-test the STOP mobile app prototype. METHODS: We invited 18 people with living or lived experiences of paranoia to create text exemplars of personal, everyday emotionally ambiguous scenarios that could provoke paranoid thoughts. Researchers then adapted 240 suitable exemplars into corresponding intervention items in the format commonly used for CBM training and created 240 control items for the purpose of testing STOP. Each item included newly developed, visually enriching graphics content to increase the engagement and realism of the basic text scenarios. All items were then evaluated for their paranoia severity and readability by living experts (n=8) and clinicians (n=7) and for their item length by the research team. Items were evenly distributed into six 40-item sessions based on these evaluations. Finalized items were presented in the STOP mobile app, which was co-designed with a digital health care solutions company, living or lived experts, and the academic team; user acceptance was evaluated across 2 pilot tests involving living or lived experts. RESULTS: All materials reached predefined acceptable thresholds on all rating criteria: paranoia severity (intervention items: ≥1; control items: ≤1, readability: ≥3, and length of the scenarios), and there was no systematic difference between the intervention and control group materials overall or between individual sessions within each group. For item graphics, we also found no systematic differences in users' ratings of complexity (P=.68), attractiveness (P=.15), and interest (P=.14) between intervention and control group materials. User acceptance testing of the mobile app found that it is easy to use and navigate, interactive, and helpful. CONCLUSIONS: Material development for any new digital therapeutic requires an iterative and rigorous process of testing involving multiple contributing groups. Appropriate user-centered development can create user-friendly mobile health apps, which may improve face validity and have a greater chance of being engaging and acceptable to the target end users.

Impact of receiving recorded mental health recovery narratives on quality of life in people experiencing psychosis, people experiencing other mental health problems and for informal carers: Narrative Experiences Online (NEON) study protocol for three randomised controlled trials.

BACKGROUND: Mental health recovery narratives have been defined as first-person lived experience accounts of recovery from mental health problems which refer to events or actions over a period of time and which include elements of adversity or struggle, and also self-defined strengths, successes or survival. They are readily available in invariant recorded form, including text, audio or video. Previous studies have provided evidence that receiving recorded recovery narratives can provide benefits to recipients. This protocol describes three pragmatic trials that will be conducted by the Narrative Experiences Online (NEON) study using the NEON Intervention, a web application that delivers recorded recovery narratives to its users. The aim of the NEON Trial is to understand whether receiving online recorded recovery narratives through the NEON Intervention benefits people with experience of psychosis. The aim of the NEON-O and NEON-C trials is to evaluate the feasibility of conducting a definitive trial on the use of the NEON Intervention with people experiencing non-psychosis mental health problems and those who care for others experiencing mental health problems respectively. METHODS: The NEON Trial will recruit 683 participants with experience of psychosis. The NEON-O Trial will recruit at least 100 participants with experience of non-psychosis mental health problems. The NEON-C Trial will recruit at least 100 participants with experience of caring for others who have experienced mental health problems. In all three trials, participants will be randomly allocated into one of two arms. Intervention arm participants will receive treatment as usual plus immediate access to the NEON Intervention for 1 year. Control arm participants will receive treatment as usual plus access to the NEON Intervention after 1 year. All participants will complete demographics and outcome measures at baseline, 1 week, 12 weeks and 52 weeks. For the NEON Trial, the primary outcome measure is the Manchester Short Assessment of Quality of Life at 52 weeks, and secondary outcome measures are the CORE-10, Herth Hope Index, Mental Health Confidence Scale and Meaning in Life Questionnaire. A cost-effectiveness analysis will be conducted using data collected through the EQ-5D-5 L and the Client Service Receipt Inventory. DISCUSSION: NEON Trial analyses will establish both effectiveness and cost-effectiveness of the NEON Intervention for people with experience of psychosis, and hence inform future clinical recommendations for this population. TRIAL REGISTRATION: All trials were prospectively registered with ISRCTN. NEON Trial: ISRCTN11152837 . Registered on 13 August 2018. NEON-C Trial: ISRCTN76355273 . Registered on 9 January 2020. NEON-O Trial: ISRCTN63197153 . Registered on 9 January 2020.