AI-Led Mental Health Support (Wysa) for Health Care Workers During COVID-19: Service Evaluation.

BACKGROUND: The impact that the COVID-19 pandemic has had on health care workers' mental health, in particular, cannot be ignored. Not only did the pandemic exacerbate mental health challenges through elevated stress, anxiety, risk of infection, and social isolation, but regulations to minimize infection additionally hindered the conduct of traditional in-person mental health care. OBJECTIVE: This study explores the feasibility of using Wysa, an artificial intelligence-led mental health app, among health care workers. METHODS: A national tertiary health care cluster in Singapore piloted the use of Wysa among its own health care workers to support the management of their mental well-being during the pandemic (July 2020-June 2022). The adoption of this digital mental health intervention circumvented the limitations of in-person contact and enabled large-scale access to evidence-based care. Rates and patterns of user engagement were evaluated. RESULTS: Overall, the opportunity to use Wysa was well-received. Out of the 527 staff who were onboarded in the app, 80.1% (422/527) completed a minimum of 2 sessions. On average, users completed 10.9 sessions over 3.80 weeks. The interventions most used were for sleep and anxiety, with a strong repeat-use rate. In this sample, 46.2% (73/158) of health care workers reported symptoms of anxiety (Generalized Anxiety Disorder Assessment-7 [GAD-7]), and 15.2% (24/158) were likely to have symptoms of depression (Patient Health Questionnaire-2 [PHQ-2]). CONCLUSIONS: Based on the present findings, Wysa appears to strongly engage those with none to moderate symptoms of anxiety. This evaluation demonstrates the viability of implementing Wysa as a standard practice among this sample of health care workers, which may support the use of similar digital interventions across other communities.

A Systematic Review and Lived Experience Synthesis of Self-disclosure as an Active Ingredient in Interventions for Adolescents and Young Adults with Anxiety and Depression.

Self-disclosure, referring to the ability to communicate and share intimate personal feelings, has strong face validity for many young people as a way of improving anxiety and depression outcomes. The current review aimed to generate the first comprehensive evidence synthesis of self-disclosure interventions involving young people aged 14-24 years who are either disclosers or recipients of personal information about living with anxiety and/or depression. A systematic review of quantitative and qualitative data was combined with new insights from an adolescents and young adults lived-experience panel (n = 7) with the intention to combine rigorous systematic review methods and experiential knowledge. Six studies of variable quality were included in this review, five were quantitative and one was qualitative. Findings suggest that self-disclosure may be effective at reducing symptoms for adolescents and young adults with established depression; effects were not apparent when delivered as early prevention. No evidence for impacts on anxiety was found. The potential for negative effects like bullying or harassment was identified. Findings were limited by a small number of studies; low representation of peer-reviewed studies from low-or middle-income countries; and varied interventions in terms of format, participants' context, and nature of delivery. Self-disclosure may be of value in the context of interventions intended explicitly to reduce depression for those already showing symptoms. Delivery by non-specialists (such as peers and teachers) in addition to mental health professionals can help build capacity in community health systems. Self-disclosure may also be helpful at reducing stigma and stimulating help-seeking at earlier stages of mental health problems.

Evaluating a Digital Mental Health Intervention (Wysa) for Workers' Compensation Claimants: Pilot Feasibility Study.

OBJECTIVE: This study examines the feasibility and acceptability of an AI-led digital mental health intervention in a Workers' Compensation (WC) program, Wysa for Return to Work. METHODS: Self-reported demographic data and responses to psychosocial screening questions were analyzed alongside participants' app usage through which four key outcomes were measured: recruitment rate, onboarding rate, retention, and engagement. RESULTS: The data demonstrated a high need for psychosocial interventions among injured workers, especially women, young adults, and those with high severity injuries. Those with more psychosocial risk factors had a higher rate of onboarding, retention, and engagement, and those with severe injuries had higher retention. CONCLUSIONS: Our study concluded that Wysa for Return to Work, the AI-led digital mental health intervention that delivers a recovery program using a digital conversational agent, is feasible and acceptable for a return-to-work population.