BACKGROUND: Artificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. Understanding and optimizing the interaction between individuals and AI-driven mHealth apps is essential for achieving the desired outcomes.
OBJECTIVE: This study aims to review and describe the current evidence on the HFs in AI-driven digital solutions for increasing PA.
METHODS: We conducted a scoping review by searching for publications containing terms related to PA, HFs, and AI in the titles and abstracts across 3 databases-PubMed, Embase, and IEEE Xplore-and Google Scholar. Studies were included if they were primary studies describing an AI-based solution aimed at increasing PA, and results from testing the solution were reported. Studies that did not meet these criteria were excluded. Additionally, we searched the references in the included articles for relevant research. The following data were extracted from included studies and incorporated into a qualitative synthesis: bibliographic information, study characteristics, population, intervention, comparison, outcomes, and AI-related information. The certainty of the evidence in the included studies was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation).
RESULTS: A total of 15 studies published between 2015 and 2023 involving 899 participants aged approximately between 19 and 84 years, 60.7% (546/899) of whom were female participants, were included in this review. The interventions lasted between 2 and 26 weeks in the included studies. Recommender systems were the most commonly used AI technology in digital solutions for PA (10/15 studies), followed by conversational agents (4/15 studies). User acceptability and satisfaction were the HFs most frequently evaluated (5/15 studies each), followed by usability (4/15 studies). Regarding automated data collection for personalization and recommendation, most systems involved fitness trackers (5/15 studies). The certainty of the evidence analysis indicates moderate certainty of the effectiveness of AI-driven digital technologies in increasing PA (eg, number of steps, distance walked, or time spent on PA). Furthermore, AI-driven technology, particularly recommender systems, seems to positively influence changes in PA behavior, although with very low certainty evidence.
CONCLUSIONS: Current research highlights the potential of AI-driven technologies to enhance PA, though the evidence remains limited. Longer-term studies are necessary to assess the sustained impact of AI-driven technologies on behavior change and habit formation. While AI-driven digital solutions for PA hold significant promise, further exploration into optimizing AI\'s impact on PA and effectively integrating AI and HFs is crucial for broader benefits. Thus, the implications for innovation management involve conducting long-term studies, prioritizing diversity, ensuring research quality, focusing on user experience, and understanding the evolving role of AI in PA promotion.

BACKGROUND: The COVID-19 pandemic placed an additional mental health burden on individuals and families, resulting in widespread service access problems. Digital mental health interventions suggest promise for improved accessibility. Recent reviews have shown emerging evidence for individual use and early evidence for multiusers. However, attrition rates remain high for digital mental health interventions, and additional complexities exist when engaging multiple family members together.
OBJECTIVE: As such, this scoping review aims to detail the reported evidence for digital mental health interventions designed for family use with a focus on the build and design characteristics that promote accessibility and engagement and enable cocompletion by families.
METHODS: A systematic literature search of MEDLINE, Embase, PsycINFO, Web of Science, and CINAHL databases was conducted for articles published in the English language from January 2002 to March 2024. Eligible records included empirical studies of digital platforms containing some elements designed for cocompletion by related people as well as some components intended to be completed without therapist engagement. Platforms were included in cases in which clinical evidence had been documented.
RESULTS: Of the 9527 papers reviewed, 85 (0.89%) met the eligibility criteria. A total of 24 unique platforms designed for co-use by related parties were identified. Relationships between participants included couples, parent-child dyads, family caregiver-care recipient dyads, and families. Common platform features included the delivery of content via structured interventions with no to minimal tailoring or personalization offered. Some interventions provided live contact with therapists. User engagement indicators and findings varied and included user experience, satisfaction, completion rates, and feasibility. Our findings are more remarkable for what was absent in the literature than what was present. Contrary to expectations, few studies reported any design and build characteristics that enabled coparticipation. No studies reported on platform features for enabling cocompletion or considerations for ensuring individual privacy and safety. None examined platform build or design characteristics as moderators of intervention effect, and none offered a formative evaluation of the platform itself.
CONCLUSIONS: In this early era of digital mental health platform design, this novel review demonstrates a striking absence of information about design elements associated with the successful engagement of multiple related users in any aspect of a therapeutic process. There remains a large gap in the literature detailing and evaluating platform design, highlighting a significant opportunity for future cross-disciplinary research. This review details the incentive for undertaking such research; suggests design considerations when building digital mental health platforms for use by families; and offers recommendations for future development, including platform co-design and formative evaluation.

UNASSIGNED: Large language model (LLM)-powered services are gaining popularity in various applications due to their exceptional performance in many tasks, such as sentiment analysis and answering questions. Recently, research has been exploring their potential use in digital health contexts, particularly in the mental health domain. However, implementing LLM-enhanced conversational artificial intelligence (CAI) presents significant ethical, technical, and clinical challenges. In this viewpoint paper, we discuss 2 challenges that affect the use of LLM-enhanced CAI for individuals with mental health issues, focusing on the use case of patients with depression: the tendency to humanize LLM-enhanced CAI and their lack of contextualized robustness. Our approach is interdisciplinary, relying on considerations from philosophy, psychology, and computer science. We argue that the humanization of LLM-enhanced CAI hinges on the reflection of what it means to simulate \"human-like\" features with LLMs and what role these systems should play in interactions with humans. Further, ensuring the contextualization of the robustness of LLMs requires considering the specificities of language production in individuals with depression, as well as its evolution over time. Finally, we provide a series of recommendations to foster the responsible design and deployment of LLM-enhanced CAI for the therapeutic support of individuals with depression.

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Telemedicine is a promising solution to the challenges of delivering equitable and quality primary healthcare, especially in LMICs. This review evaluated peer-reviewed literature on telehealth interventions in Indian primary care published from Jan 1, 2011 to Dec 31, 2021, from PubMed, Scopus, TRIP, Google Scholar, Indian Kanoon, and Cochrane database The majority of Indian studies focus on key health issues like maternal and child health, mental health, diabetes, infectious diseases, and hypertension, mainly through patient education, monitoring, and diagnostics. Yet, there\'s a lack of research on telemedicine\'s cost-effectiveness, communication among providers, and the role of leadership in its quality and accessibility. The current research has gaps, including small sample sizes and inconsistent methodologies, which hamper the evaluation of telemedicine\'s effectiveness. India\'s varied healthcare landscape, technological limitations, and social factors further challenge telemedicine\'s adoption. Despite regulatory efforts, issues like the digital divide and data privacy persist. Addressing these challenges with a context-aware, technologically driven approach is crucial for enhancing healthcare through telemedicine in India.

BACKGROUND: Deaths due to drug overdose are an international issue, causing an estimated 128,000 global deaths in 2019. Scotland has the highest rate of drug-related deaths in Europe, with those in the most deprived areas at greater risk than those in affluent areas. There is a paucity of research on digital solutions, particularly from the perspective of those who use drugs who additionally access harm reduction and homelessness support services. The Digital Lifelines Scotland programme (DLS) provides vulnerable people who use/d drugs with digital devices to connect with services.
METHODS: This paper reports on the evaluation of the DLS from the perspective of service users who accessed services for those at risk of drug-related harms. A mixed methods approach was used including an online-survey (n = 19) and semi-structured interviews (n = 21). Survey data were analysed descriptively and interview data through inductive coding, informed by the Technology, People, Organisations and Macroenvironmental factors (TPOM) framework, to investigate the use, access, and availability of devices, and people\'s experiences and perceptions of them.
RESULTS: Most participants lived in social/council housing (63.2%, n = 12), many lived alone (68.4%, n = 13). They were mainly over 40 years old and lived in a city. Participants described a desire for data privacy, knowledge, and education, and placed a nascent social and personal value on digital devices. Participants pointed to the person-centred individuality of the service provision as one of the reasons to routinely engage with services. Service users experienced an increased sense of value and there was a palpable sense of community, connection and belonging developed through the programme, including interaction with services and devices.
CONCLUSIONS: This paper presents a unique perspective which documents the experiences of service users on the DLS. Participants illustrated a desire for life improvement and a collective and individual feeling of responsibility towards themselves and digital devices. Digital inclusion has the potential to provide avenues by which service users can safely and constructively access services and society to improve outcomes. This paper provides a foundation to further cultivate the insight of service users on digital solutions in this emerging area.

Physical activity is essential to interrupt the cycle of deconditioning associated with chronic kidney disease (CKD). However, access to targeted physical activity interventions remain under-supported due to limited funding and specialised staff. Digital interventions may address some of these factors. This systematic review sought to examine the evidence base of digital interventions focused on promoting physical activity or exercise and their effect on health outcomes for people living with CKD. Electronic databases (PubMed, CINAHL, Embase, Cochrane) were searched from 1 January 2000 to 1 December 2023. Interventions (smartphone applications, activity trackers, websites) for adults with CKD (any stage, including transplant) which promoted physical activity or exercise were included. Study quality was assessed, and a narrative synthesis was conducted. Of the 4057 records identified, eight studies (five randomised controlled trials, three single-arm studies) were included, comprising 550 participants. Duration ranged from 12-weeks to 1-year. The findings indicated acceptability and feasibility were high, with small cohort numbers and high risk of bias. There were inconsistent measures of physical activity levels, self-efficacy, body composition, physical function, and psychological outcomes which resulted in no apparent effects of digital interventions on these domains. Data were insufficient for meta-analysis. The evidence for digital interventions to promote physical activity and exercise for people living with CKD is limited. Despite popularity, there is little evidence that current digital interventions yield the effects expected from traditional face-to-face interventions. However, 14 registered trials were identified which may strengthen the evidence-base.

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