JMIR Mental Health

The benefits of physical activity (PA) for both physical and mental health, including major depressive disorder (MDD), are well established. Mobile devices, such as smartphones, offer a scalable way to monitor PA and its relationship with depressive symptoms in daily life.

The mechanisms through which mindfulness and third wave based digital programs exert their effects on stress reduction remain poorly understood. Identifying these mediators is essential to optimize their implementation, particularly in healthcare settings. This approach is particularly relevant for healthcare professionals, who are constantly exposed to high levels of emotional demands, work overload, and risk of burnout, especially in the aftermath of the COVID-19 pandemic. Despite the growing need for scalable and accessible mental health support in this population, such digital programs remain scarce and underutilized.

Patient safety incidents are a leading cause of harm in psychiatric settings, yet early warning systems (EWS) tailored to mental health remain underdeveloped. Traditional risk tools such as the Dynamic Appraisal of Situational Aggression–Inpatient Version (DASA-IV) offer limited predictive accuracy and are reactive rather than proactive.

Suicide is the second-leading cause of U.S. childhood mortality after age nine. Accurate measurement of pediatric emergency service use for self-injurious thoughts and behaviors (SITB) remains challenging, as diagnostic codes undercount children. This measurement gap impedes public health and prevention efforts. Current research has not established which combination of electronic health record (EHR) data elements achieves both high detection accuracy and consistent performance across youth populations.

AVATAR therapy is a novel psychological therapy that aims to reduce distress associated with hearing voices. The approach involves a series of therapist-facilitated dialogues between a voice-hearer and a digital embodiment of their main distressing voice (the avatar), which aim to increase coping and self-empowerment.

Digital mental health interventions (DMHIs) offer scalable and cost-effective support for mental health but are predominantly developed in WEIRD (Western, Educated, Industrialized, Rich, Democratic) contexts, raising questions about their global applicability. Dropout, attrition, and adherence rates critically influence DMHI effectiveness yet remain poorly characterized in culturally adapted formats.

Poor management of mental health conditions leads to reduced adherence to treatment, prolonged illness, unnecessary rehospitalisation and significant financial burden to the health care system. Recognizing this, ecological momentary assessment (EMA) and remote measurement-based care (RMBC) interventions have emerged as promising strategies to address gaps in current care systems. They provide convenient means to continuously monitor patient-reported outcomes, thereby informing clinical decision-making and potentially improving outcomes such as psychopathology, relapse, and quality of life.

Depression and anxiety are prevalent but commonly missed and misdiagnosed, an important concern because many patients do not experience spontaneous recovery and duration of untreated illness is associated with worse outcomes.

Posttraumatic stress disorder (PTSD) is highly prevalent in conflict-affected regions like eastern Democratic Republic of Congo; yet, cultural stigma and lack of psychoeducation limit public understanding and help-seeking behaviors.

University students face high levels of stress with limited support for coping and well-being. Campus mental health services are increasingly using digital resources to support students’ stress-management and coping capacity. However, the effectiveness of providing this support through web-based, self-directed means remains unclear.

This study aims to detect self-harm or suicide (SH-S) ideation language used by youth (aged 13-21 y) in their private Instagram (Meta) conversations. While automated mental health tools have shown promise, there remains a gap in understanding how nuanced youth language around SH-S can be effectively identified.

Depressive disorder affects over 300 million people globally, with only 30-40% of patients achieving remission with initial antidepressant monotherapy. This low response rate highlights the critical need for digital mental health tools that can identify treatment response early in the clinical pathway.