Frontiers in Public Health

Background: Skin-related neglected tropical diseases (skin NTDs) continue to affect people living in remote communities of endemic countries, particularly in regions with limited access to dermatological care. This operational research evaluated the impact of the eSkinHealth app, a digital health tool designed to enhance case management of skin NTDs and other skin diseases in Cote d'Ivoire. The eSkinHealth app functions as a portable electronic medical record and a platform for teledermatology, connecting frontline healthcare workers to remote specialists. Methodology/Principal Findings: The study was conducted across sixteen primary health centers (PHCs) in the Sinfra and Bouafle districts, regions endemic for skin NTDs. Using a before-and-after implementation design, baseline data were collected from paper registries and compared with data captured through the app. The primary objective was to assess changes in skin disease detection and diagnosis, while also evaluating usability, acceptability, and feasibility of the tool among healthcare workers. A total of 1,766 patients were included in the analysis (mean age 22.8 years; 55% male). During the intervention period, skin NTD registrations increased significantly from 30 to 91 cases (p < 0.01). Buruli ulcer cases rose from 6 to 14 (p = 0.05), scabies from 24 to 70 (p = 0.13), and other NTDs such as leprosy, lymphatic filariasis, and yaws were newly detected and documented. In contrast, registrations of non-NTD skin diseases decreased from 662 to 472 cases (p < 0.01); however, the proportion of non-NTD cases which received diagnostic confirmation increased markedly, from 0% at baseline to 94% during the intervention period (p < 0.01). Qualitative interviews with nurses and community health workers highlighted improvements in diagnostic accuracy, patient engagement, and confidence in daily practice, while also noting persistent challenges such as stigma, transportation barriers, technical difficulties, and patient concerns about privacy. Conclusions/Significance: The integration of the eSkinHealth app into routine PHC services proved effective in enhancing diagnostic capacity for skin NTDs in resource-limited settings. However, capturing other skin diseases proved more difficult given their high prevalence. While the app demonstrated clear benefits in improving diagnostic rates and healthcare worker confidence, persistent challenges such as technical issues and patient concerns about privacy need to be addressed for future scalability. As with many digital tools, further refinement will be an ongoing process, and the lessons learnt from this study may provide valuable guidance for similar initiatives in comparable settings.

Introduction Gender norms and roles are important determinants of physical and mental health in the key period of adolescence. Yet, the gendered pathways to mental health in adolescents are not fully understood. Using a conceptual framework for global adolescent mental health that we developed based on a Delphi process, we empirically investigated the associations between six gender-related constructs and adolescent mental health. Methods We used cross-sectional Gender and Adolescence: Global Evidence (GAGE) data from Ethiopia (2020) to explore the associations between sex, gender norms, psychological competencies, gender attitudes, gender roles, with the latter two also serving as mediators, and psychological distress (GHQ-12), using Structural Equation Modelling (SEM). Results The SEM model contained measurements from 1,584 adolescents, including 843 girls and 741 boys, with a median age of 13 years. Out of 14 pathways tested, we found statistically significant associations between psychological competencies and psychological distress; sex and gender attitudes; and between gender norms and psychological competencies, gender attitudes, and gender roles. Hence, the gender-related constructs were mostly associated with each other, rather than with psychological distress. Conclusion The gender-related constructs are strongly interrelated, thereby attenuating their individual effects on psychological distress. The interplay of gender-related constructs should be considered when developing interventions to promote mental health in adolescents.

Background: In crises, hospitals must rapidly shift from routine operations to structured crisis management, requiring the activation of an incident command system. However, empirical insight into their operational functioning during activation remains limited. Goal: to identify operational enablers and barriers influencing effective crisis response. Methods: Prospective cross-sectional, qualitative, single-center study conducted after a table-top exercise within a hospital incident command system at a tertiary care university hospital (NCT06913010). Data was collected through semi-structured interviews, participant observation, and document analysis, and analyzed using a narrative-phenomenological approach. Results: Nineteen participants were included. Analysis identified nine thematic clusters shaping operational performance: (1) structure and roles; (2) communication; (3) decision-making and prioritization; (4) information management; (5) infrastructure and technology; (6) personnel and organization; (7) training, exercises, and team dynamics; (8) documentation; and (9) external communication and media. Enablers included clear role definition, structured communication, phased decision-making, and regular training. Barriers included role ambiguity, fragmented communication, insufficient prioritization, infrastructure limitations, and staffing constraints. Conclusion: Preparedness frameworks are necessary but insufficient as stand-alone approaches, as operational execution determines real-world performance. Recurring deficits included unclear roles, inconsistent communication, weak prioritization, and gaps in infrastructure and personnel. A limited set of standardized practices - including a clear separation od roles, leadership intent, closed-loop communication, explicit decision cycles from information gathering to structuring to decision-making, checklists, visualization, central information management, and rapid "80% decisions"-substantially enhanced performance. Mission command (Auftragstaktik) further enabled adaptive, coordinated action. Strengthening hospital incident command is a key lever for achieving system-level resilience in crises.

Introduction -- Emergency Medical Dispatch Systems (EMDS) can reduce delays in accessing emergency care by providing structured communication, triage, and coordination. However, such systems remain absent or underdeveloped in most low- or middle-income countries (LMICs). This study aimed to establish international consensus on essential EMDS components to inform global guidance. Methods -- We convened a multidisciplinary expert group to draft a preliminary list of essential components for three EMDS levels reflecting resource availability and system maturity. We then conducted a three-round Delphi with international experts to reach consensus on core EMDS components. Components which had [&ge;]75% agreement were included, those with [&ge;]75% disagreement were excluded. Components not achieving consensus by Round 3 were removed. Results were analysed overall and stratified by respondents' country income level. A subsequent online expert meeting resolved inconsistencies and finalised the component list. Results -- The expert group generated 111 components for each of three EMDS levels (Foundational, Emerging, and Established) spanning 11 operational domains. Of the 68 experts invited to the Delphi, 43 participated in Round 1 and 30 in Round 3. Across all Delphi rounds, 289 components reached consensus for inclusion. The consensus resulted in a final list of 227 components (63 Foundational, 84 Emerging, and 80 Established). Consensus agreement clustered around core EMDS domains including communication, structured call-taking and prioritisation, advice-giving, resource dispatch and tracking, and foundational governance and data functions, whereas items showing either non-consensus or consensus disagreement were typically technology-dependent or context-specific. Conclusions -- This international consensus offers guidance for EMDS development across diverse resource settings and provides a scalable roadmap to strengthen emergency care systems.

Since the U.S. 2013/14 influenza season, the CDC's FluSight Challenge has provided a platform for evaluating influenza forecasting models and fostering collaboration across institutions. The Challenge aims to improve the science and enhance the utility of infectious disease forecasts for public health decision making. We analyzed ten years of submitted forecasts (2014/15-2019/20 (influenza-like illness seasons) and 2021/22-2024/25 (hospital admissions seasons)) across a range of model types, including statistical, mechanistic, machine learning, and hybrid models. Influenza-like illness (ILI) forecasts were evaluated using the exponentiated logarithmic score (skill metric) while hospital admissions forecasts were evaluated using the log transformed relative Weighted Interval Score. Corresponding potential performance differences were assessed using Wilcoxon rank-sum tests, and associations with team participation history were evaluated using Spearman's rank correlation. Model performance varied by season, and no single model type consistently outperformed others. In ILI seasons, statistical models generally performed better than mechanistic and machine learning models, though consistent differences were not observed in more recent hospital admissions seasons. Ensemble forecasts showed better overall performance across seasons, and the CDC's FluSight ensemble ranked among the top-performing forecasts every year. We also found a positive correlation between forecast accuracy and the number of years a team participated in the Challenge, with statistically significant associations in four seasons. These findings highlight the benefits of ensemble approaches and sustained engagement in improving forecasting performance, while also underscoring the continued value of forecast evaluation before and following the COVID-19 pandemic. Insights from the FluSight Challenge can guide future infectious disease forecasting efforts and support more effective public health preparedness.

Aims Moral distress has been studied across many health arenas; however, public health has often been overlooked. Canada is facing a healthcare crisis with a significant number of staff leaving the healthcare field. This study explores the experiences of moral distress in public healthcare practitioners across Canada. Better understanding these experiences can provide insights into how to support staff and prevent attrition in public health. Methods This was a cross-sectional qualitative study. Fifteen in-depth interviews were conducted between May and July 2023, through remote and in person methods. Participants were from nursing, social work, medicine, and dietetics, all working in public health across Canada. Iterative thematic analysis was used. Emergent themes were compared within and across data sets and by participant age and years of experience. Results/Findings Experiences that contributed to moral distress included systemic powerlessness, political and ideological overreach, unethical work environments and undervalued expertise. Years of experience and diversity in gender and ethnicity impacted how practitioners navigated moral distress. Experiences where practitioners felt actions went against their values increased during the pandemic, contributing to moral injury. Conclusions This study situates the unique position of public health within the health system and explores experiences of moral distress both during and outside the COVID-19 pandemic. While the pandemic brought the concept of moral distress to the forefront of many peoples minds, these experiences existed prior. Addressing the underlying causes will contribute to establishing approaches to support public health practitioners suffering from moral distress and injury.

Background: Higher education has been transformed by the rapid integration of generative artificial intelligence (GenAI) tools into academia. The objective of the present study was to examine how and for what purposes senior undergraduate dental students use GenAI tools in academic assignments. Methods: This cross-sectional study uses data from three written assignments submitted by two consecutive cohorts of graduating fourth-year dental students at the Faculty of Dentistry at the University of British Columbia, for a total of 120 students. The assignments focused on different subjects where students had to offer their views, including community water fluoridation. When using GenAI, students were asked to disclose whether and how such tools were used, and for what purpose. Descriptive statistics (e.g., means, frequencies, and proportions) were conducted via IBM SPSS Statistics (Version 27.0). Results: From the two cohort of students, 102 (85%) disclosed the use of GenAI tools in at least one assignment; of these, 69 (67.6%) reported using these tools in all three assignments. ChatGPT was by far the most frequently used GenAI tool, reported by 89 students (87.2%). Nine students (8.8%) did not specify which tool they had used. The majority of the students (91.2%, n = 93) reported using GenAI for proofreading or grammatical editing. About 9.8% of the students (n = 10) reported more substantive uses, such as relying on GenAI to generate in part or in full the assignment, and/or assessing the credibility of references. Conclusions: In our study, the use of GenAI tools was highly prevalent among senior undergraduate dental students for editorial purposes. A smaller but notable proportion of students engaged in more substantive uses that may carry academic and ethical risks. There is a need for structured AI literacy training and clear, dentistry-specific guidelines to promote responsible and transparent use while safeguarding critical thinking, academic integrity, and professional judgment in dental education.

Essential medicines are one of the cornerstones of financial protection and health equity. The REMEDIAR Program is an initiative of the Argentine Ministry of Health aimed at ensuring free access to essential medicines for the uninsured at the point of care in primary healthcare centers (PHC). This study analyzes the financing, procurement, and distribution of this program over two decades (2002 to 2024). It evaluates how the program's capacity to navigate economic and political challenges ensured an uninterrupted supply of essential drugs at the primary healthcare level in a federal country where health services are devolved to provinces. We adopted a mixed-methods approach to examine the duality between international concessional loans and domestic treasury funding. Findings reveal that while international financing enhanced predictability and efficiency, reducing procurement timelines from 458 to 235 days, it also constrained domestic planning through external conditionalities. Conversely, while national centralized procurement achieved superior price efficiency and lower dispersion, it faced rigidities in adapting to local needs. Territorial distribution analysis confirms that REMEDIAR reduced access barriers for vulnerable households without formal insurance. However, the program entered a stabilization phase, failing to consolidate robust coordination with subnational policies, becoming entrenched in its own operational logic. The study concludes that program effectiveness depends not only on resource volume but on management quality. To guarantee long-term sustainability, transition to national financing requires profound institutional redesign. This must integrate operational capacities with federal coordination and domestic regulations, ensuring that the primary healthcare supply chain remains resilient to macroeconomic volatility and political shifts, aligned with sub-national strategies.

Strengthening the resilience and inclusivity of primary health care (PHC) systems during crises is critical to achieving equitable access to health care in low-income countries. The COVID-19 pandemic exposed significant weaknesses in PHC systems, highlighting gaps in inclusivity and resilience, particularly for persons with disabilities (PWDs). Although studies have examined PWDs, few have applied systems thinking approaches such as Group Model Building (GMB). This study aimed to develop a resilient and inclusive PHC system to improve access to services and vaccine uptake among PWDs during pandemics. A mixed-methods design incorporating GMB was employed in three phases. First, quantitative and qualitative data were collected to identify barriers and facilitators to PHC access and vaccine uptake. Second, a stakeholder GMB workshop was conducted in Monze to map system dynamics and develop causal loop diagrams. Third, validation and refinement meetings were held, including a final workshop in Lusaka. Findings identified key endogenous system drivers influencing vaccine uptake and access to PHC services and consumables, including financing mechanisms, human resources, outreach services, transport, staff commitment, and availability of accessible information such as Braille materials. These interact through reinforcing and balancing feedback mechanisms. In addition, critical contextual (exogenous) drivers such as political will, health insurance, community gatekeepers, and road networks shape system performance and influence access and service delivery. Strengthening both endogenous system drivers and contextual factors through inclusive strategies, coordinated financing, and supportive governance is essential for building resilient PHC systems that improve equitable access and vaccine uptake among PWDs during health crises. These findings contribute to Universal Health Coverage and equity by showing that strengthening both health systems drivers and contextual drivers is essential to ensure inclusive, accessible, and fair delivery of PHC services for all populations, including persons with disabilities.

In spite of well-established global immune landscape, SARS-CoV-2 is still able to further spread and continue causing infection waves. The current understanding about the reason behind is limited, and it is still difficult to predict the evolution or spreading tread of SARS-CoV-2. Therefore, it is necessary to investigate whether the establishment of population immunity has changed the virus evolution or spreading pattern. In this investigation, one overall analysis of the SARS-CoV-2 spreading in the past several years have been carried out through one thorough genomic epidemiology study, with Germany being chosen as one representative location in view of the systemic efforts for genomic surveillance. The growth advantage of a few predominant variants in its early spreading period has been evaluated through a logistic regression model. The results have revealed that the major circulating SARS-CoV-2 variants since 2023 are mainly derived from the Omicron BA.2 family. Since middle of 2024, most predominant variants were produced primarily through recombination, indicating that the evolution derived from recombination might be the major driving force for the continuous spread of SARS-CoV-2 despite the existence of population immunity. Furthermore, the lower growth advantage of recently emerged variants might possibly lead to a tread of reduction in the frequency of infection wave. The information revealed from this investigation suggests that although short-term spreading tread can be affected by specific virus feature as well as local immunity landscape, the long-term spreading tread is mainly decided by the genomic diversity of the viruses, and can be predicted through phylogenetic and genomic epidemiology investigation. The results have emphasized the importance of maintaining the efforts for genomic surveillance of SARS-CoV-2, which is essential from both medical and research perspectives.

Youth in the United States are experiencing growing mental health challenges, yet many face barriers to accessing timely, affordable, and stigma-free support. At the same time, artificial intelligence (AI) chatbots have become widely available and are increasingly being used by young people as tools for information seeking, coping, and self-reflection. This brief report explores how youth are engaging with AI chatbots for mental health support, drawing from qualitative interviews conducted in New Jersey. Nine semi-structured interviews were completed with participants ages 19-22. Thematic analysis revealed five core themes: (1) generational change, peer communication, and humor as coping and normalization tools; (2) internal and external barriers to self-recognition and help-seeking; (3) AI chatbots as a safe and accessible first step; (4) AI chatbots as a tool for filling information gaps; and (5) limits of AI chatbots and the preference for human connection. These findings indicate that young people see AI chatbots as private, judgment-free starting points for exploring their emotions and seeking early support. However, they also recognize that these tools cannot replace human connection or professional care. For public health, this presents both challenges and opportunities in utilizing the accessibility of AI chatbots while ensuring ethical design, cultural responsiveness, and protections that safeguard youth privacy and equity.

Background: Many mental health problems originate in childhood, highlighting the need for early preventive approaches. Preventive services to promote children's mental health are offered in the health, education, and social sectors (H-E-S) but are often not used by certain at-risk groups or early enough. To identify children at-risk and provide needs-oriented support, professionals from all sectors must be well trained, collaborate closely to refer to specialized services for specific mental health problems or risk factors, and understand the regional psychosocial support system and its services. A comprehensive approach to preventing mental health problems requires structured planning and a systematic overview of all institutions and services in the region and their collaboration. This study aims to map the preventive mental health and psychosocial support service system and the collaboration between institutions across three sectors (H-E-S) in two exemplary city districts. The study is integrated into a whole-district approach to child mental health promotion that is being implemented in one of the researched city districts, and its results will inform further activities there. Methods: We use a mixed-methods approach, combining qualitative interviews with a quantitative survey to map psychosocial services for children aged 4 to 10 and their families across the H-E-S sectors in two socioeconomically disadvantaged city districts in East and West Germany. All institutions that potentially offer psychosocial services for children and families will be approached to recruit professionals (e.g., schools, practices, counseling centers). To understand the regional psychosocial support system, we will analyze existing services and their characteristics (e.g., target groups, intervention types) descriptively. Social network analysis will be applied to gain an in-depth understanding of collaboration between institutions, to identify potential gaps in services and pathways, and to inform an intervention aimed at improving interinstitutional and intersectoral collaboration. Discussion: To our knowledge, this is the first study to comprehensively analyze regional preventive psychosocial support systems for children and families across sectors at the community level. Previous mappings of psychosocial services have focused on a single sector (e.g., health) or specific diagnoses only. The psychosocial preventive landscape spanning the H-E-S sectors involves complex financing structures and referral logics. Understanding the characteristics of the existing support landscape requires a systematic and comprehensive approach. Our study advances service mapping and operationalization methods in public health research. Additionally, the findings will inform recommendations for improving comprehensive prevention approaches in the selected city districts.

Objectives and study: This study aimed to examine predictors of post-partum maternal mental health (MMH) and coping during COVID-19 lockdown across seven countries (the UK, China, Japan, Malaysia, Mexico, Argentina, and Thailand). Methods: An anonymous questionnaire, developed in the UK in English and translated into local languages, was used in 2021-2022 to collect data on MMH and perceived coping ability from women aged [&ge;]18 years with an infant born before or during lockdowns. Five MMH components (worry, sadness, loneliness, difficulty relaxing, annoyance) and coping were assessed on a 4-point Likert scale, then dichotomised. MMH and coping were compared across countries using Chi-square tests with post-hoc pairwise comparisons conducted via Bonferroni-adjusted z-tests. Predictors of MMH and coping were examined using multivariable logistic regression. Results: A total of 7,650 women were analysed. Younger infant age, higher income, walking and exercise, and level of support were associated with better MMH and coping, whereas higher education was associated with better coping but poorer MMH. MMH and coping differed across countries (all p<0.001), which remained after adjusting for covariates: mothers in Asian countries reported better MMH, while those in the UK and Thailand reported better coping. Conclusions: Postpartum MMH and coping during lockdown were shaped by both individual and contextual factors. Findings highlight cross-country differences and underscore the need to strengthen maternal support system during future disruptions to perinatal care. Keywords: Mental Health, COVID-19, Postpartum Period, Coping Behaviour, Social Support, Cross-Cultural Comparison

Abstract Background: Artificial Intelligence (AI) is increasingly integrated into healthcare systems worldwide and medical schools worldwide have begun integrating AI into their curricula. The healthcare system in Iraq is currently undergoing development and AI has not yet been adopted in clinical practice in Erbil; in addition, no formal AI instruction has been incorporated into the medical education curriculum. The aim of this study was to assess knowledge levels, attitudes, and perceptions regarding AI among medical students and healthcare professionals in Erbil, Kurdistan Region of Iraq. Methods: A mixed-methods survey was distributed to medical students and residents in Erbil, Kurdistan Region of Iraq. The survey was adapted from Teng et al, and modified to reflect the local context. The survey was translated into Kurdish and Arabic. Convenience sampling was used. Statistical analysis was conducted using IBM SPSS (Statistical Package for Social Sciences), Version 26.0. Chi-square and Fishers exact tests were used to test associations between categorical variables. Mann Whitney U test was used to compare mean ranks between groups in the non-normally distributed data. A P value <0.05 was considered statistically significant. Thematic analysis was applied to open-ended qualitative responses by two independent reviewers. Results: A total of 368 participants participated in this study. The majority (85.6%) of participants felt that AI should be taught in schools and universities, and 90.8% reported using AI. ChatGPT was by far the most commonly used AI tool (85.3%). Participants aged 20-24 years (93.2%) and 25-29 years (90.2%) showed the highest prevalence of using AI. Participants that used AI previously, had higher scores for support for AI development in their field (U = 3744.5, P=0.001), feelings of hope towards AI in their field (U = 4406.5, P = 0.004) and thinking that students should learn the basics of AI (U = 4022.5, P = 0.03). Male participants were more likely to use AI in comparision with women (P=0.045). The most common concern regarding AI was loss of jobs (33.0%), followed by overreliance on AI (22.8%). Qualitative analysis revealed themes of guarded optimism, and concerns regarding the ethical implications of AI use in medicine. Conclusion: Medical students and physicians in Erbil are early adopters of AI in spite of any formal training. In parralel, most participants expressed dissatisfaction with their understanding of the ethical implications of AI in healthcare and emphasized the need for formal AI education in healthcare curricula. The majority of participants expressed guarded optimism regarding the future of AI in healthcare. A gender gap in AI was identified, consistent with global trends with implications for professional equity.

Abstract Background: Emergency Department (ED) populations are a high-risk group that are opportune for interventions targeting NCDs and NCD risk factors, like tobacco use. Mobile health (mHealth)interventions such as Text2Quit, a novel text message-based mHealth tool addressing tobacco cessation in the US, have demonstrated effectiveness for tobacco cessation and for ED-based mHealth interventions in High Income Countries (HIC). To successfully adapt and implement such mHealth interventions in limited resource settings like African EDs, it is essential to examine the implementation climate and engage key stakeholders. These implementers provide invaluable insight to understand healthcare system level factors that affect adoption, implementation and maintenance of the interventions. Methods: We conducted 12 semi-structured key informant interviews (KIIs) with ED administrators and staff including 2 departmental heads, 5 medical doctors, 3 nurses, and 2 clinical officers at a national referral hospital in Kenya. This was guided by RE-AIM framework indicators of Adoption, Implementation, and Maintenance (eg feasibility of intervention integration, and suggestions to improve implementation). Interviews were conducted in English, recorded, professionally transcribed and translated, and analyzed using a constant comparative analysis approach, according to grounded theory principles. Findings: Key informants were positive about the adoption of them Health intervention in Kenyan EDs and across different health facility levels in Kenya due to the perceived need for the program, facility and staff receptiveness and existing healthcare infrastructure to leverage. Recommended implementation strategies included follow-up mechanisms for program participants, inclusion of all healthcare cadres in implementation and increased sensitization and the use of champions. Barriers to Implementation in the ED included competing clinical priorities with emergency cases, limited staffing and shame associated with smoking. Conclusion: Implementing a mobile health tobacco cessation program like Text2Quit is feasible and acceptable in Kenyan EDs when supported by targeted strategies.

Background: Microbiota dysbiosis of the skin has been implicated in ulcer formation. Individuals with diabetes remain at high risk for diabetic foot ulcers (DFUs) even after ulcer healing. Topical chlorhexidine gluconate (CHG) is a broad-spectrum antiseptic commonly used to reduce microbial burden. In a prior randomized clinical trial comparing daily CHG foot treatment with soap-and-water treatment, no statistically significant reduction in new DFUs was observed, prompting evaluation of whether CHG produced durable changes in the skin microbiota. Objective: To compare changes in foot skin microbiota (including bacterial bioburden, diversity, and community composition) associated with daily CHG versus soap-and-water use over one year in people with diabetes and prior foot complications. Methods: In a single-center, double-blind, placebo-controlled randomized trial, 87 participants were randomized to daily CHG wipes or soap-and-water wipes for 12 months. Foot swabs were collected at baseline, 3 and 12 months, and 4 weeks post-treatment. Bacterial bioburden was quantified. Microbiota composition was assessed using 16S rRNA and ITS amplicon sequencing. Key Results: CHG treatment significantly reduced bacterial bioburden, increased microbial diversity, and altered community composition, including sustained reductions in Staphylococcus abundance. Several microbiota changes persisted more than 4 weeks after treatment cessation. Soap-and-water treatment showed similar but smaller and largely nonsignificant trends. Conclusions: Daily CHG use durably modifies foot skin microbiota in high-risk individuals with diabetes. However, this alone may be insufficient to prevent new foot complications, highlighting the need for additional interventions. These findings have implications for long-term CHG use in populations at risk for staphylococcal infections.

Background As lockdown measures was eased, pregnant women faced an elevated risk of COVID-19 infection, potentially impacting their mental health. This study aimed to investigate the prevalence of antenatal depression (AD) post-lockdown and develop predictive models for AD risk using machine learning. Methods A cross-sectional study utilizing the Edinburgh Postnatal Depression Scale was conducted in Beijing and Guizhou, China, from January to August 2023. Data was randomly split into training and test datasets (6:4 ratio), with logistic regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Gradient Boosting Decision Tree (GBDT) models trained and compared. The best model underwent further examination, including SHapley Additive exPlanations (SHAP) for feature importance, calibration curve (CC) for discrimination, and decision curve analysis (DCA) for clinical benefit. Results The effective response rate was 91.07% (459/504), with 25.7% (118/459) testing positive for AD. Multivariate analysis identified "sleep disorders," "family support level," and "COVID-19 symptom severity" as independent predictors. RF model showed the highest area under the curve in both training (0.842) and testing (0.724) datasets, with SHAP emphasizing the greatest impact of "sleep disorders" on AD. The RF model's calibration (P > 0.05) and clinical utility across thresholds (8%-95% and 10%-58%) were confirmed by CC and DCA, respectively. Conclusions AD strongly correlated with "sleep disorders," "family support level," and "COVID-19 symptom severity" post-lockdown, and the EPDS-based RF model effectively predicted AD risk.

Tacrolimus is an immunosuppressant drug commonly used in transplantation. Although multiple studies have demonstrated that polymorphisms in the CYP3A5 gene impact the metabolism of tacrolimus, routine pre-transplant testing for these markers is still not broadly implemented. TacroType - a new laboratory developed test implemented by One Lambda Laboratories - utilizes a qPCR-based six-plex assay for CYP3A5 genotyping and detects the three most common genetic variants (*3, *6 and *7) associated with loss of CYP3A5 protein function and reduced tacrolimus metabolism. TacroType was optimized to address known sources of protocol, technical or sample variability to achieve accurate and reproduceable genotyping results. An analytical performance study was completed following CLSI guidelines. Accuracy was confirmed for each possible CYP3A5 genotype involving 6 target alleles using 32 well-characterized reference samples. TacroType exhibited accurate performance within a broad range of DNA concentrations and quality. Precision studies indicated consistent genotyping results across 4 operators, 2 instrument types and 5 lots of reagents. Accurate and reproducible assay performance was demonstrated using whole blood from 100 and buccal swabs from 70 donors. The analytical performance of TacroType was evaluated in 4014 total qPCR reactions, with a report rate of 99.8% and genotyping accuracy of 100% (95% confidence interval of 99.9%).

Purpose: The purpose of this study was to examine the barriers and facilitators experienced by non-U.S. born persons during the diagnosis and treatment of latent tuberculosis infection (LTBI) in primary care settings, including the impact of culturally and linguistically congruent care navigation. Design: 25 interviews with non-U.S. born patients, along with focus groups and surveys with 31 primary care team members and leadership, were conducted. Setting: The study was conducted within a network of Federally Qualified Health Center (FQHC) clinics. Participants: Participants were adult non-U.S. born patients with LTBI and FQHC care team members. A purposefully selected subsample of randomized participants was interviewed. Intervention: Care navigators followed participants randomized to receive care navigation after a positive test for tuberculosis (TB) infection and offered health navigation and education about the importance of TB screening and treatment. Method: Data collection was followed by thematic analysis guided by a critical ideological paradigm. Results: Culturally and linguistically congruent navigation emerged as central to potentially reducing barriers, fostering trust, and improving treatment continuity. Participants without navigation support reported confusion and disengagement from care, while those with culturally aligned navigators described clarity and comfort, with influence overall by intrinsic motivation, relational support, and culturally shaped beliefs about care. Conclusion: Care navigation that includes culturally and linguistically congruent navigators whenever possible may help increase LTBI treatment completion among non-U.S. born populations. Limitations of the study include the potential influence of cultural norms, power dynamics, and selection bias.

Background: Medical and doctoral students in health sciences represent a strategic public health lever as future professionals who will have a lasting influence on healthcare practices and the overall quality of health systems. Impaired quality of life and mental health issues among these students, coupled with scarce prevention programmes, led us to develop PROMESS-Group, an innovative multimodal programme designed to promote healthier lifestyle habits among university students. Methods: We will conduct a 2-arm randomised, controlled, superiority monocentric trial to assess the effect of this programme on medical and doctoral students compared to a control group. The intervention will consist of six sessions covering stress, sleep and physical activity domains. Each session will include group and individual meetings led by trained peer experts, focusing on needs assessment, self-care education, and personalised goals setting. Students' quality of life, academic self-efficacy, and broader health outcomes will be assessed using validated questionnaires and objective tools at baseline, during, and post-intervention. Data will be analysed according to the intention-to-treat principle and presented in accordance with CONSORT guidelines. Ethical approval was obtained from the institutional review board (IRB2025021802). All procedures will be performed in adherence to the Helsinki Declaration. Discussion: This study will enable the generation of high-quality evidence to evaluate the programme's effects on students' quality of life and related psychosocial outcomes, and may inform evidence-based health promotion strategies in university settings. Trial registration: ClinicalTrials.gov: NCT07030751 (https://clinicaltrials.gov/study/NCT07030751?locStr=Lyon,%20France&country=FR&state=Auvergne-Rh%C3%B4ne-Alpes&city=Lyon&cond=promess%20group&rank=1), 06.12.2025 - retrospectively registered. This protocol study follows the SPIRIT guidelines (Appendix 1). Keywords: Doctoral student, health behaviour, medical student, quality of life, physical activity, sleep, stress