This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in “Guttmann, Neuro Personal Trainer” (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services.

In this article, we described a new mobile-Health (mHealth) supported clinical pathway of care for people living with medically stable HIV in terms of platform acceptability, usability and technical feasibility. The EmERGE mHealth platform was codesigned with clinicians and the community, developed using Scrum agile methodology, integrated with hospital information systems and validated in a large prospective cohort study of 2251 participants. The evaluation of this new paradigm of care was conducted using a tailored Health Technology Assessment: the Model for Assessment of Telemedicine Applications. Usability and acceptability were assessed through the System Usability Score and a Patient Reported Experience Measure. The EmERGE platform was successfully deployed across diverse care settings in five European countries and used by 2251 patients and more than 20 clinicians for up to 30 months. Results from the formal evaluation demonstrated that the EmERGE platform is feasible and acceptable, with a high level of usability (median System Usability Score (SUS) 85.0%) and very positive patient-reported experiences (94.2% would recommend to a friend). The EmERGE platform is a secure and General Data Protection Regulation (GDPR)-compliant system with a complete set of functionalities that could be easily adapted to other clinical conditions, clinical sites and health systems thanks to its modular technical architecture.

Digital health innovation can fail to move beyond prototype or pilot stages or achieve intended outcomes due to a lack of involvement and attunement to local context. This article shares the potential of place-based co-production to support the development, acceptability and usability of context-attuned, digital health service innovation for young people. To illustrate the approach, we report on a collaborative, interdisciplinary project involving a Zambian public health research partner based in Lusaka, Zambia, three European universities and a not-for-profit digital innovation partner. Our youth-led, co-production process involved 6 stages: recruitment of youth Co-design Leaders; role play-based care pathway co-design; app co-design; digital prototype development; stakeholder consultation; and digital pathway testing. We used a combination of qualitative social science research, community and arts-based, human-centred design and digital innovation methods. Young people traced the digital testing and sampling process from accessing self-testing and sampling kits to laboratory processing of results through to how results should be communicated. They were encouraged to evaluate how these processes would work in the context of their everyday lives. We systematically embedded this ideation work into a technically functional ‘eHealth Yabwela’ app and clinical or laboratory worker-facing web application which young people user tested. Our place-based focus encouraged elicitation of whole pathway, in situ, logistical feasibility alongside social and technical concerns, enabling us to engage with potential adoption and accessibility barriers during the design process. Youth-led co-production created the conditions for participants to lead discussions, voice requirements and hold the project team accountable. Young people recognised that advocacy, overcoming digital inequalities, and further co-production with healthcare workers already facilitating youth-friendly healthcare provision would be needed to integrate the pathway within local systems.

BACKGROUND Digital phenotyping, the real-time quantification of human phenotype in situ via digital devices, offers new opportunities to understand how behavior change interventions influence brain health. This approach has gained increasing interest in recent years, especially in brain health research. Interoception, chronic stress, and self-regulation are key domains, and benefit from real- world, continuous assessment beyond what traditional methods can provide. OBJECTIVE The aim of this scoping review was to map and synthesize the literature of the last five years on the use of digital phenotyping to measure or predict interoception, chronic stress, and self-regulation in adults. The review addressed specific questions concerning the types of devices and sensors used, the psychological domains targeted, the nature of the data collected, feature extraction and intended targets, data processing methods, and the technological platforms utilized. METHODS We conducted a scoping review following the Joanna Briggs Institute (JBI) methodology and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Eligibility criteria included studies using digital phenotyping to assess or predict interoception, chronic stress, or self-regulation in adults aged 21–65 years, based on data collected via smartphones or commercial wearable devices. Studies published since 2018 were considered. A systematic search of PubMed, Web of Science, and Scopus retrieved 850 records; one additional study was identified through Google Scholar. Two reviewers independently screened titles, abstracts, and full texts. Eighteen studies met the inclusion criteria. Results were synthesized narratively. RESULTS Of the 18 studies included, 11 addressed chronic stress or stress reactivity, 5 self-regulation, and 2 interoception. To gather physiological and behavioral data, 13 used wearable devices, 3 smartphones, and 2 both; 8 used smartphones for ecological momentary assessment (EMA). Heart rate variability (HRV) was the most common physiological measure (n=14), followed by electrodermal activity (EDA) and heart rate (HR) (n=4 each). Behavioral data (e.g., smartphone use, sleep, activity) was analyzed in 9 studies. Six studies used machine learning models, but only 3 reported classification accuracy (56.8–79%). Eight applied statistical methods to link features with stress or interoception, while 4 assessed self-regulation using predefined features without identifying new biomarkers. CONCLUSIONS This scoping review highlights that research on digital phenotyping for interoception, chronic stress, and self-regulation is still in its early stages, with most studies focusing on chronic stress and relying primarily on wearable devices. Integration of smartphone sensing and long-term monitoring remains limited, and reported analytical performance is generally modest. Despite these challenges, the widespread use of smartphones and wearables positions digital phenotyping as a promising and scalable approach for assessing brain health in daily life. Future research should emphasize longer-term, multimodal data collection, innovative analytical methods, and transparent reporting to advance the field. CLINICALTRIAL