Background: Access to health care, especially in low-resource settings, remains a critical challenge for marginalized and underserved populations. Telemedicine, delivering medical advice remotely, has the potential to improve access to health care by reducing geographic and economic barriers. Its adoption, however, especially in low-resource settings, remains limited. Frugal innovation, characterized by solutions developed under tremendous resource constraints and prioritizing affordability, accessibility, and simplicity, offers valuable insights for enhancing telemedicine adoption. Rooted in a sociocultural approach, it is particularly relevant in low-resource health systems where complex, intersectoral challenges occur. Despite this potential, insights from frugal innovation have not been compared, contrasted, or studied alongside telemedicine in a systematic way. Objective: Our review aims to examine how frugal innovation contributes to the adoption of telemedicine in low-resource settings, with a particular focus on identifying frugal innovation characteristics that facilitate telemedicine adoption. Methods: Our PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-guided systematic review will examine case studies of adopted telemedicine applications in low-resource settings. Eligible studies need to demonstrate evidence of adoption and use in real-world health care settings. We will examine functions and features of telemedicine, along with frugal innovation characteristics, as demonstrated by each telemedicine application. The following databases were searched: MEDLINE ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, CINAHL, PsycInfo, Scopus, Dimensions, IEEE Xplore Digital Library, EconLit, the International HTA Database, LILACS (Latin American and Caribbean Literature on Health Sciences), the World Health Organization (WHO) Global Index Medicus, and the WHO Global Health Observatory. Results: Insights from our review will deepen the understanding of how health care technologies such as telemedicine can be positioned and configured to improve adoption in low-resource settings. Search results, delivered in February 2025, were followed by title and abstract screening in March 2025, full-text screening in April 2025, and final study selection and quality appraisal by November 2025. With dataset updates requested in December 2025, the data synthesis remains ongoing. The expected results will be published in 2026. Conclusions: This combined assessment will examine how frugal innovation can contribute to the adoption of telemedicine in low-resource settings. As a result, we expect that our findings will contribute to the development of frugal telemedicine as a sociotechnical artifact. The protocol is submitted to enhance transparency and rigor.

BACKGROUND: Maternal obesity affects approximately 16% of pregnancies worldwide and is a major concern for public health. This condition is associated with elevated risks of adverse outcomes, such as gestational diabetes, hypertensive disorders of pregnancy, and cardiovascular and metabolic disease (CVMD) during the life course. Our long-term experience with the (cost-)effective web-based Smarter Pregnancy coaching program is promising to mitigate these risks and improve lifestyle behaviours as well as maternal and neonatal health outcomes. Here our aim is to describe the rationale and study protocol for a randomised controlled trial (RCT) to investigate the clinical and cost-effectiveness, and implementation potential of Smarter Pregnancy Plus (SP+) from early pregnancy onwards in women with obesity. METHODS: The HYGEIA study is designed as a multicentre, two-armed RCT. A total of 930 women with a body mass index ≥30 kg/m² and a singleton pregnancy of ≤14 weeks gestation will be recruited and randomised 1:1 to the intervention (n=465) and control group (n=465). The intervention group will receive six months of digital lifestyle coaching via the SP+ application, supported by at least one video consultation. SP+ is an extended, co-designed and tailored app version for pregnant women with obesity based on the validated SP program. It provides evidence-based coaching on nutrition, physical activity, mental health, folic acid and vitamin D supplement use, and smoking and alcohol cessation. The control group will receive usual care. Data will be collected through validated questionnaires, electronic medical records, financial records, and qualitative stakeholder sessions, guided by the Non adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS)-framework. The primary outcome is the incidence of maternal CVMD during pregnancy, assessed using a composite measure that includes gestational diabetes, hypertensive disorders of pregnancy, and worsening of pre-existing hypertension or diabetes. Secondary outcomes include changes in lifestyle behaviours, maternal and neonatal outcomes, quality of life, and cost-effectiveness. Tertiary outcomes involve patient satisfaction, provider feasibility and a roadmap for nationwide implementation. DISCUSSION: The HYGEIA study will provide evidence on the clinical impact, cost-effectiveness, and implementation potential of SP+ as a digital lifestyle intervention for pregnant women with obesity. If successful, SP+ could further enhance routine obstetric care and contribute to improving maternal and neonatal health while reducing healthcare costs. TRIAL REGISTRATION: Dutch Trial Registration number NL-OMON57196 (URL: https://onderzoekmetmensen.nl/nl/node/57196/pdf ), date of registration 19-12-2024.

Background: Women face unique and diverse mental health challenges and therefore require tailored interventions that address their specific needs and lived realities. Research has shown a lack of digital interventions designed for and with women from marginalized backgrounds, such as minority racial/ethnic backgrounds or with low socioeconomic status. If Digital Mental Health Interventions (DMHI) are not designed with active involvement of women from diverse backgrounds, they may fail to reach their public health objectives, which potentially exacerbates existing health disparities. How Human-Centered design methods are applied and reported, and whether women from diverse backgrounds are involved in the design and development of Digital Mental Health Interventions (DMHI), is under-researched. Objective: This study examined the methods and frameworks used in the design and development processes of DMHIs, whether and how studies include women from diverse backgrounds, and whether they tailor to their diverse needs related to intersectional identities (e.g., race/ethnicity, socioeconomic status, age) in the design and development process. Methods: We conducted a scoping review following the PRISMA-ScR guidelines. The databases included are Scopus, PubMed and IEEE Xplore, and the databases are searched from the inception until the 31st of May 2026. We included 77 articles that described the design process of digital mental health solutions for women. Results: Among the 77 reviewed studies, 18 (23.4%) did not explicitly state their design methods, and most of them provided limited information on the characteristics of the included populations. Only 16 (20.8%) studies consistently involved users across all design stages. Intersectional identities were considered in only 26 (33.8%) studies. We observed an overrepresentation of research in higher-income countries, an underrepresentation of women from racial/ethnic minority backgrounds, a narrow age range of participants, and a lack of consideration of intersectional identities. Conclusions: Our findings reveal critical gaps in the development of DMHIs for women, including the superficial reporting and application of Human-Centered Design methods in the design process, limited user involvement, and a lack of consideration of diversity, inclusivity and intersectionality. Future research should emphasize active involvement of end-users from the earliest design phases onwards and adopting an intersectional lens in their design processes. We propose a research agenda for better reporting and applying HCD methods in future DMHI research, towards designing diverse, inclusive and equitable digital solutions for all women. Registry and registry number for systematic reviews or meta-analyses: A protocol of this study is pre-registered at Open Science Framework (DOI 10.17605/OSF.IO/WC79P).

Large language model (LLM)-based conversational systems are increasingly proposed as personalized digital well-being tools (DWTs) for youth, yet current personalization approaches often fail to reflect heterogeneous lived experiences. We present a participatory approach for eliciting personalization requirements for LLM-based DWTs, with youth well-being as a case study. In a multi-stage co-creation study with youth, parents, and youth care professionals (N=38), we combined data-driven personas with participatory persona co-creation and follow-up stakeholder interviews to examine what meaningful LLM-based DWT personalization should entail. Our preliminary findings suggest that stakeholders prioritize person-centered personalization beyond demographic or clinical labels, emphasizing identity, relational dynamics, routines, literacy needs, and changing lived context. Participants also highlighted the importance of dialogic mechanisms, particularly reflective questioning and ongoing updating of contextual representations over time. We argue that participatory personas can serve as reflexive scaffolds for surfacing community-grounded personalization needs and translating them into emerging design requirements for adaptive LLM systems. These findings position personalization in DWTs as an ongoing dialogic, person-centered process that warrants further investigation in research on human-AI personalization.

Background: Maternal obesity increases risks of adverse pregnancy outcomes and long-term diseases for mothers and child. Digital lifestyle interventions show promise, but their effectiveness depends on meeting the specific needs of pregnant women with obesity and healthcare providers (HCPs). Objectives: To explore perspectives and practices on healthy lifestyle and care for pregnant women with obesity, and to identify needs and preferences for digital lifestyle intervention development and implementation. Methods: A qualitative study using focus groups and interviews was conducted with 13 HCPs and 13 pregnant women with obesity. Sessions were audio-recorded, transcribed and analysed thematically. Women viewed a healthy lifestyle as multidimensional, encompassing nutrition, physical activity, mental well-being, and rest, but faced barriers such as pregnancy discomfort, limited knowledge, and stigma. Both women and HCPs emphasized child health as a motivator and valued goal setting and practical advice. Existing care was seen as inconsistent and generic, with HCPs constrained by time and unclear roles. Participants preferred a personalized, user-friendly mobile app with modular, evidence-based content tailored to individual goals, pregnancy stage, and medical status. Features such as self-monitoring, goal setting, and a supportive, non-judgmental tone were important. Integration into routine obstetric care was considered key for engagement and effectiveness. If designed accordingly, such tools could provide accessible, tailored support between appointments, reinforce positive behaviour change, improve patient-provider communication, and reduce HCP time pressures. Conclusions: Co-designing digital lifestyle tools with women and HCPs is vital. Personalized, feasible interventions integrated in obstetric care can support behaviour change and improve outcomes for mothers and children. Trial registration number: not applicable.

Background: The transition from adolescence to young adulthood (age 10‐25 years) constitutes a sensitive developmental period marked by rapid biological, psychological, and social change, during which preventive health interventions can shape long-term outcomes. Mobile health tools offer accessible opportunities for tailored support for this population, but often adapt poorly to dynamic contexts, resulting in inconsistent engagement and effects. Just-in-time adaptive interventions (JITAIs), which tailor support in real time using ongoing data, are increasingly explored as precision health strategies. However, how these mechanisms are designed, implemented, and evaluated for adolescents and young adults (AYAs) has not been systematically reviewed. Objective: This review aimed to synthesize the evidence on JITAIs developed for AYAs, examine how their adaptive mechanisms have been designed to support specific health goals and changing AYA contexts, and assess methodological reporting quality to inform future precision health intervention development. Methods: We conducted a systematic review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and SWiM (Synthesis Without Meta-Analysis) reporting guidelines. Twelve databases were searched for peer-reviewed studies published from 2013 to 2025. Eligible studies focused on participants aged 10 to 25 years and reported real-time adaptive mobile health interventions consistent with JITAI design principles. Two reviewers independently conducted screening, data extraction, and methodological quality appraisal using the Joanna Briggs Institute checklists. AYA coauthors contributed to all phases. Due to substantial heterogeneity in study populations, intervention content, adaptive mechanisms, comparators, and outcome measurements, findings were synthesized narratively, and no meta-analysis was conducted. Results: A total of 61 unique interventions were included. JITAIs for AYAs addressed substance use (n=24, 39.3%), mental health (n=23, 37.7%), and physical health or chronic conditions (n=14, 23%). JITAI tailoring mechanisms relied predominantly on self-reported behavioral data. Decision rules were typically symptom threshold–based, and decision points were commonly daily or event-triggered. Methodological concerns with reporting on intervention administration, participant selection, and outcome measurement reliability were pervasive across all studies, limiting the interpretability of observed effects and cross-study comparisons. Ethical considerations, including researcher positioning and reflexivity, alongside the depth of reporting around participatory AYA engagement in design and implementation, were also inconsistent. Conclusions: This review contributes a novel perspective to AYA digital health by moving beyond intervention outcomes to examine how core adaptive mechanisms are operationalized for AYAs across multiple health domains, while also integrating AYA perspectives into the interpretation of findings and recommendations. Unlike prior reviews focused primarily on adults or specific conditions, it identifies broader contextual, methodological, and ethical considerations relevant to AYA precision health. These findings highlight the need for more transparent, contextually responsive, and youth-centered adaptive interventions, alongside more rigorous designs for evaluating adaptive intervention components in daily life contexts.

Youth are increasingly using large language models (LLMs) for well-being support, yet existing governance guidelines provide limited interaction-level requirements and empirical work rarely centers lived experience from youth and the communities that support them. We report a participatory study with 38 stakeholders (youth, parents, youth care workers). Using reflexive thematic analysis, we identify three stakeholder-derived governance domains for youth-facing LLM support: Interaction, Context, and Escalation. Stakeholders aligned on Governance of Interaction and Context but diverged on Escalation, particularly acceptable transitions to external support, with youth proposing intermediary peer referral mechanisms via personalized information retrieval. We translate these stakeholder accounts into preliminary normative requirements and dialogue inspection examples that can be used to guide model fine-tuning and post hoc evaluation. We further discuss how our formative findings expand upon major artificial intelligence guidelines by surfacing where existing frameworks remain underspecified for conversational governance and evaluation.

Introduction: Mental health issues among young people have surged post-COVID-19. Mental health apps can offer accessible preventive support on a large scale, yet the perspective of minoritized youth–such as those from low socioeconomic and ethnic/racial backgrounds–are underexplored. This risks low uptake and effectiveness, and exacerbating health inequities. This study aimed to understand the needs and concerns of minoritized youth in the Netherlands using a participatory approach. Methods: We conducted 3 co-creation sessions with 17 adolescents (16 females, majority Dutch Moroccan background) aged 11–22 years, recruited through community centers in lower-income neighborhoods in The Netherlands, with the help of community workers. We also organized a discussion session with 26 preventive youth workers to explore their perspectives regarding implementation. A subset of youth (n = 10) analyzed the data in 2 co-thematic analysis workshops. We compared youth and researcher themes. Results: Youth saw data-driven mental health apps as useful for short-term stress relief through motivational quotes, social activity suggestions, and homework support, but unable to solve more severe issues. In the co-analysis, youth analyzed based on emotion and functions, whereas researchers employed a more technical lens. Key themes included identity-based (such as religion, gender, and age) and contextual tailoring (to school/home schedules), compassionate communication as opposed to fake support (robots), safety, and the role of social media. Conclusion: These findings highlight the need to examine how app design for young people can prioritize authentic, compassionate communication, safety–including transparency about data–tailoring to identify aspects, adapting the timing and frequency of notifications, and integrating social connections and social media. Participatory approaches are promising to better understand the needs of youth from minoritized backgrounds for digital mental health technologies, with the aim of equitable digital solutions.

Background: Hypersensitivity to punishment is one of the core features of major depressive disorder (MDD). Hypersensitivity to punishment has been proposed to originate from aberrant aversive learning. One of the key areas in aversive learning is the habenula. Although evidence for dysfunctional aversive learning in patients with depression is well established, whether this dysfunction and its neural correlates persist during symptomatic remission of depression remains largely unexplored. Methods: Functional magnetic resonance imaging data from 36 medication-free remitted patients with recurrent MDD and 27 healthy control participants participating in a Pavlovian classical conditioning task were assessed within a computational modeling framework to evaluate temporal difference–related activation of the habenula during aversive learning. Furthermore, generalized psychophysiological interaction analyses were performed to assess functional connectivity of the temporal difference signal with the habenula as an a priori region of interest. Results: Relative to healthy control participants, patients showed significantly increased temporal difference–related aversive learning activation in the bilateral habenula. This activation was correlated with residual symptoms in the remitted MDD group. Furthermore, patients exhibited decreased functional connectivity between the habenula and the ventral tegmental area compared with control participants. Conclusions: The increased habenula activity during aversive learning, particularly during the expectation of punishment, together with decreased functional habenula–ventral tegmental area connectivity in remitted patients with MDD, reflect hypersensitivity to and/or inability to regulate the impact of aversive environmental cues and punishment.

Adolescents and young adults (AYA) often face mental health challenges and are heavily influenced by technology. Digital health interventions (DHIs), leveraging smartphone data and artificial intelligence, offer immense potential for personalized and accessible mental health support. However, ethical guidelines for DHI research fail to address AYA’s unique developmental and technological needs and leave crucial ethical questions unanswered. This gap creates risks of either over- or under-protecting AYA in DHI research, slowing progress and causing harm. This Perspective examines ethical gaps in DHI research for AYA, focusing on three critical domains: challenges of passive data collection and artificial intelligence, consent practices, and risks of exacerbating inequities. We propose an agenda for ethical guidance based on bioethical principles autonomy, respect for persons, beneficence and justice, developed through participatory research with AYA, particularly marginalized groups. We discuss methodologies to achieve this agenda, ensuring ethical, youth-focused and equitable DHI research for the mental health of AYA.

StayWell is a 60-day CBT/DBT-based text messaging intervention which leverages reinforcement learning algorithms to support mental health. Participants were randomly assigned to receiving personalized messaging (adaptive arm), static messaging (random arm) or mood-monitoring only messages (control arm). A diverse sample of 1121 adults participated in a fully remote trial between December 2021 and July 2022. Across study arms, participants showed a 25% reduction in depression symptoms (PHQ-8) and 24% reduction in anxiety symptoms (GAD-7) following the intervention. We did not find statistically significant differences in PHQ-8 and GAD-7 reductions between intervention arms. Participants in the control arm had higher mood-monitoring messages response rates than those in other conditions. Finally, post-hoc exploratory analysis assessing outcomes by condition indicated that patients with minimal to mild depression symptoms (PHQ-8 < 10) benefitted from the reinforcement learning algorithm. The results of this trial suggest that StayWell is a promising text-messaging intervention to achieve reductions in depression and anxiety among diverse populations.