JMIR Mental Health

The global demand for mental health services has significantly increased over the past decade, exacerbated by the COVID-19 pandemic. Digital resources, particularly smartphone apps, offer a flexible and scalable means of addressing the research-to-practice gap in mental health care. Clinicians play a crucial role in integrating these apps into mental health care, although practitioner-guided digital interventions have traditionally been considered more effective than stand-alone apps.

Ambulatory assessment and mood monitoring are different methods that can use novel technology to deliver a more efficient, flexible and usable method of clinical outcome assessment compared to established measures of behavior and mood. Concerns have been raised around attrition in and adherence to these new protocols, particularly over the medium to long term in people with mood disorders.

The Safety Planning Intervention (SPI) is a suicide prevention intervention that results in a written plan to help patients reduce suicide risk. High-quality safety plans – that is, those that are most complete, personalized, and specific – are more effective in reducing suicide risk. Measuring SPI quality is labor intensive, which means that clinicians rarely get specific, actionable feedback on their use of the SPI.

Household chaos is an emerging risk factor for childhood obesity development, especially in families with lower socioeconomic status (SES). It is unclear if changes in household chaos, especially in pregnancy, may mediate the effectiveness of weight-related behavioral interventions.

Mood monitoring is widely used by people with depression and bipolar disorder (BD) to prevent relapse and improve insight into their condition but it is unclear if these interventions have an impact on symptoms and for whom. As the capacity for passive mood monitoring increases it is vital to improve our understanding of frequent mood assessment.

The high number of mental disorders poses challenges for healthcare systems. In 2020, digital health applications (DHA) were introduced in Germany as a new form of healthcare financed by the statutory health insurance. They aim to detect, monitor, treat, or alleviate disease, injury, or disability. DHA for mental disorders (DHA-MD) intend to improve outpatient care for patients with mental disorders. However, evidence on general practitioners (GP) perspectives on DHA-MD and their prescribing behavior is limited.

Digital interventions play an innovative role in the treatment of mental health disorders, offering evidence-based solutions across a wide range of conditions. Blended therapy (BT) - which integrates digitally delivered interventions with face-to-face therapy - has shown promise. However, challenges such as low uptake hinder widespread implementation. Mental health professionals are key stakeholders for the adoption of BT in routine care settings.

Cyberchondria, a combination of the words “cyber” and “hypochondriasis”, is a condition that is receiving increasing attention by clinicians and researchers globally. Researchers are currently using multiple instruments to quantify it. Furthermore, the instruments have been translated into multiple languages.

The availability of telebehavioral health care dramatically increased in response to the COVID-19 pandemic among both civilian and military populations. After restrictions were lifted, telebehavioral health use decreased but remained elevated compared to before the pandemic. Examining the use of treatment modalities and how it relates to care metrics can inform the future delivery of behavioral health care.

The growing global burden of mental health disorders has intensified the search for scalable, accessible, and cost-effective interventions. Conversational agents in the form of digital humans have emerged as promising tools to deliver mental health support across diverse populations and settings.

Computer perception (CP) technologies—including digital phenotyping, affective computing, and related passive sensing approaches—offer unprecedented opportunities to personalize health care, especially mental health care, yet they also provoke concerns about privacy, bias, and the erosion of empathic, relationship-centered practice. At present, it remains elusive what stakeholders who design, deploy, and experience these tools in real-world settings perceive as the risks and benefits of CP technologies.

The therapeutic relationship is the professional partnership between clinicians and patients that supports open communication and clinical decision-making. This relationship is critical to the delivery of effective mental health care. Integration of artificial intelligence (AI) into mental health care has the potential to support accessibility and personalized care; however, less is known about how AI might affect the dynamic of the therapeutic relationship.