JMIR Formative Research

The use of virtual mental healthcare increased rapidly in 2020 as a critical response to the COVID-19 pandemic, serving as an effective contact-free alternative to treatment. Today, virtual care remains a viable option for individuals with geographic and physical barriers to treatment. However, there are several potential therapeutic disadvantages to virtual care (e.g., missing nonverbal signals, handling crises, confidentiality, weakened social connection in group therapy) that should be evaluated. While published literature has explored client satisfaction within virtual therapy and the effect of using technology for virtual care demands, there is a need for published surveys that evaluate the therapeutic experience in virtual and in-person mediums of care.

Cognitive control training (CCT) has gained attention in recent years as a preventative intervention in the context of major depressive disorder. To date, uncertainty exists around the working mechanisms of CCT and how its effects unfold overtime.

Artificial intelligence (AI) tools hold much promise for mental healthcare by increasing the scalability and accessibility of care. However, current development and evaluation practices of AI tools limit their meaningfulness for healthcare contexts and thereby, the practical usefulness of such tools for professionals and clients alike.

Artificial intelligence (AI) has become increasingly important in health care, generating both curiosity and concern. With a doctor-patient ratio of 1:834 in India, AI has the potential to alleviate a significant health care burden. Public perception plays a crucial role in shaping attitudes that can facilitate the adoption of new technologies. Similarly, the acceptance of AI-driven mental health interventions is crucial in determining their effectiveness and widespread adoption. Therefore, it is essential to study public perceptions and usage of existing AI-driven mental health interventions by exploring user experiences and opinions on their future applicability, particularly in comparison to traditional, human-based interventions.

Intensive care unit (ICU) residents are exposed to high stress levels due to the intense nature of their work, which can impact their mental health and job performance. Heart rate measured through wearable devices has the potential to provide insights into residents’ self-reported stress and aid in developing targeted interventions.

Diagnostic errors involve significant problems in medical care. Despite the usefulness of artificial intelligence (AI)-based diagnostic decision-support systems, the over-reliance of physicians on AI-generated diagnoses may lead to diagnostic errors.

Inexperienced adolescent drivers are particularly susceptible to engaging in distracted driving behaviors (DDBs) such as texting while driving (TWD). Traditional driver education approaches have shown limited success in reducing motor vehicle crashes among young drivers.

Orthopedic trauma care encounters challenges in follow-up treatment due to limited patient information provision, treatment variation, and chaotic settings in which it is provided. Additionally, pressure on healthcare resources is rising globally. In response, digital follow-up treatment pathways were implemented for orthopedic trauma patients, aiming to optimize healthcare resource utilization and enhance patient experiences.

Health-system fragmentation in Quebec significantly impacts care coordination, leading to interruptions in patients’ care pathways and adverse effects on their health. Coordinating interfacility service corridors is complex and requires collaboration between multiple health care providers (HCPs) and care settings. Effective care coordination is essential to ensure optimal patient management at transition points.

Assessing changes in quality of life in patients with hay fever–related allergic conjunctivitis requires validated and clinically meaningful metrics. A minimal clinically important difference (MCID) that can be applied to assess Domain II of the Japanese Allergic Conjunctival Disease Quality of Life Questionnaire (JACQLQ) in a smartphone app setting has yet to be determined.

Young Black male individuals are 24 times more likely to be impacted by firearm injuries and homicides but encounter significant barriers to care and service disengagement, even in program-rich cities across the United States, leaving them worryingly underserved. Existing community-based interventions focus on secondary and tertiary prevention after firearm violence has occurred and are typically deployed in emergency settings. To address these service and uptake issues, we developed BrotherlyACT—a nurse-led, culturally tailored, multicomponent app—to reduce the risk and effects of firearm injuries and homicides and to improve access to precrisis and mental health resources for young Black male individuals (aged 15-24 years) in low-resource and high-violence settings. Grounded in Acceptance and Commitment Therapy, the app provides life skills coaching, safety planning, artificial intelligence–powered talk therapy, and zip code–based service connections directly to young Black male individuals at risk for violence and substance use.

While structured compassion training programs have shown promise for increasing compassion among medical trainees, a major challenge is applying the concepts and practices taught during the program into the complex, dynamic, time-pressured, and often hectic hospital workplace.