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Background: Older adults with mental illness face specific physical and psychosocial challenges and inequities, reflected in limited access to advanced technology. This #Digital divide is alarming as #MentalHealth interventions increasingly depend on both patients’ and clinicians’ access to technology. However, #Digitalized treatments also present opportunities to enhance accessibility, effectiveness, and equity across age groups. Objective: This scoping review charted the state of quantitative research on #Digitalized treatment options for older people with mental illness. We focused specifically on how technology is integrated into existing nonpharmacological #MentalHealth interventions or leveraged to create new ones. We also summarized the state of the art on the feasibility and effectiveness of these interventions for various mental illnesses. Methods: This review was conducted in compliance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for systematic scoping reviews. A PubMed search conducted in April 2024 and updated in April 2025 identified 64 studies (15,644 participants; aged 40-97 years). Included studies were original quantitative studies or reviews of these studies looking into nonpharmacological treatments for older adults with a psychiatric diagnosis using any kind of technology. Results: The technologies examined ranged from web-based psychotherapy platforms and #Digital devices for daily challenges to robots for social interaction. Few studies (5/64, 7%) examined the newest advances in #Digital #MentalHealth, such as artificial intelligence or virtual reality. Most studies (37/64, 58%) evaluated dementia-related interventions using small, nonrandomized samples and uncontrolled designs. Conclusions: The current state of the field, despite the promises of technology to reduce inequities between age groups, still largely excludes older adults from research on technological advances in #MentalHealth and their benefits. The field needs to overcome this selective bias and fight the “#Digital gray divide” in #MentalHealth. Trial Registration:

Background: Access to mental health care is critical for the effective management of serious mental illness (SMI), but consumers with low socioeconomic status (SES) have lower rates of service usage and worse retention in care. Digital technologies are often lauded as a way to bridge access gaps; however, little is known about how technology-mediated care may influence care access among low-SES consumers and how consumers use technology in care access. Objective: This study aimed to examine the applicability of Levesque et al’s access framework to technology-mediated care for SMI and analyze how low-SES consumers use technology to facilitate care access. Furthermore, the study assesses whether and how technologies are involved in care access at multiple points within the process of accessing care. Methods: This study used 2 qualitative methods: ethnographic observations at a mental health treatment court and interviews with low-SES consumers with SMI using community mental health care (n=14) and key informant interviews with health and service providers working with this population (n=14). Observations occurred from July 2022 through September 2023, and interviews occurred between January 2022 and May 2024. Data analysis involved both inductive and deductive coding approaches. Data from both the interviews and observations were analyzed in NVivo and further triangulated through analytic memos. Results: Levesque et al’s framework required several extensions to accommodate technology-mediated care related to SMI for low-SES consumers: (1) a cyclical rather than linear trajectory; (2) simultaneous care acquisition from multiple health and service providers; (3) staying in care long-term; (4) identification of both one-time and ongoing health needs; and (5) an emergency pathway for entering care. Consumers often faced challenges related to the varied digital requirements of each provider and a dearth of integrative, patient-facing tools like portals. Within this context, some consumers use mobile apps, communication, and telehealth technologies across various care access stages. Consumers used technology by figuring out how to navigate technology-mediated care, especially by leaning on others, such as case managers, for support. These others provided consumers with temporary technologies, showed them how to use technologies, and accompanied them through the process of using technology for accessing care. Conclusions: This study highlights that accessing care is iterative and ongoing, involving multiple forms of co-occurring service provision. A theoretical contribution of this work is its extension of Levesque et al’s care access framework to better reflect technology-mediated care for SMI among low-SES consumers. This work also underscores ongoing challenges for accessing technology-mediated care and the importance of human support in addressing access difficulties. Clinical implications include incorporating digital readiness assessments and providing comprehensive guidance on how consumers can effectively use technologies for care. Future work should investigate how technology-mediated care can make care access easier rather than harder.

Background: Digital phenotyping (DP), the process of using data from digital devices, like smartphones and wearable technology to understand and monitor people's behaviour, health, and daily activities, has shown significant promise in mental health care within high-income countries (HICs). However, its application in lower and middle-income countries (LMICs) is limited, particularly among impoverished populations such as slum residents. Objective: This study investigates the awareness, knowledge, acceptance, and implementation of DP, including willingness to share data, and concerns regarding privacy and data security, among residents of Dhaka's Korail slum, one of Bangladesh's largest and most densely populated informal settlements. Understanding awareness, acceptance, and privacy concerns surrounding DP in these settings is critical for its effective implementation. Methods: We conducted eight focus group discussions (FGDs) with 38 participants (79% female, mean age 37 ± 13.7 years). Participants included 20 individuals diagnosed with serious mental disorders (SMDs) and 18 caregivers. The FGDs also included a section explaining what DP is. Results: Smartphone ownership was reported by 45% of participants, while 92% had access to a smartphone through family members. There was a general lack of awareness about DP among the participants. Initially, 92% (35/38) of participants had no prior knowledge of DP, but after receiving an explanation, they acknowledged its potential applications and benefits. Participants recognized the utility of DP for health monitoring, particularly in managing mental health conditions. Participants expressed willingness to share certain types of data, particularly phone usage and location data, provided that content-level information remained private. Despite these perceived benefits, significant concerns about privacy and data security emerged. Participants expressed fears about the potential misuse of their personal information, with some feeling resigned to the idea of already being constantly monitored. Trust in DP tools emerged as a critical factor for adoption, highlighting the need for transparent data protection policies and user control over data sharing. Additionally, participants emphasized the importance of adapting DP tools to local contexts, including cultural considerations and technological literacy. Conclusions: While DP presents a promising avenue for mental health support in underserved urban populations, its adoption in LMIC slum settings requires targeted educational initiatives, robust privacy safeguards, and community involvement to ensure trust and #usability. DP tools should be adapted to fit the cultural context of the target population, possibly involving modifications to the types of data collected or the way data is interpreted. In conclusion, while DP holds potential to improve mental health care in underserved communities, addressing barriers related to awareness, privacy, culture and #usability is crucial. Focusing on educational initiatives, robust data protection, cultural adaptation, user-friendly design, and community engagement, DP can become a valuable tool in bridging the mental health care gap in LMICs.

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A study by Baylor University and Dell Medical School reveals a surprising link between technology use and a reduced risk of dementia in older adults. As the first generation to grow up with digital technology...