Incidental pulmonary nodules (IPNs) are commonly encountered on chest radiographs (CXRs) performed for routine clinical indications and may represent early manifestations of significant pulmonary pathology, including lung cancer. While low-dose CT screening has mortality benefits in selected high-risk populations, its implementation remains limited in many healthcare settings. Artificial intelligence (AI)-assisted CXR interpretation has the potential to enhance pulmonary nodule detection. However, evidence from Malaysian clinical practice is scarce. This study aims to evaluate the diagnostic performance of AI-assisted CXR interpretation for detecting IPNs across healthcare facilities in the Klang Valley, Malaysia.

This prospective, multicentre study will include 2452 CXRs from patients aged ≥35 years over a 6-month period across four Klang Valley healthcare facilities. Each CXR will be independently interpreted by an experienced radiologist (>5 years of experience) and analysed separately using an AI system (qXR-LNMS). An independent thoracic radiologist will determine the final classification for analysis if there is IPN detection discordance. Diagnostic performance metrics (sensitivity, specificity, positive and negative predictive values, and overall accuracy) will be calculated using a 2x2 classification matrix. Agreement between AI-assisted interpretation and radiologist reports will be assessed using Cohen’s kappa statistic. The prevalence of IPNs detected by AI-assisted interpretation and radiologist reporting will be compared using a two-proportion z-test. AI discriminative performance will be evaluated using receiver operating characteristic curve analysis and area under the curve estimation. Statistical analyses will be conducted using Statistical Package for the Social Sciences V.29, with p

Ethical approval has been obtained from the Universiti Kebangsaan Malaysia Research Ethics Committee and the Ministry of Health Malaysia Medical Research and Ethics Committee. Written informed consent will be obtained from all participants. The findings will be disseminated through peer-reviewed publications, scientific conferences and engagement with relevant stakeholders.

The study evaluated the feasibility and efficacy of a non-immersive virtual reality (VR) system on upper extremity (UE) recovery in ischaemic stroke patients in comparison to a conventional physiotherapy.

An open-label, parallel-group, randomised controlled trial randomly assigned the participants to two groups, VR intervention or conventional physiotherapy.

Two tertiary stroke care centres in South India participated in the study.

Sixty first-ever ischaemic stroke patients (1–6 months of stroke onset) having spasticity grades of 1 or 1+ as per Modified Ashworth scale and Brunnstrom recovery stages of 3, 4 or 5 in the UE were included in the intention-to-treat analysis.

High-intensity non-immersive VR-based comprehensive rehabilitation gaming system with a duration of 12 weeks (3 days/week) was compared with equally intensive conventional physiotherapy.

The feasibility outcome was the compliance with the treatment. The primary efficacy outcome was the improvement in the motor function assessed by the Fugl-Meyer assessment (FMA) and Wolf motor function test (WMFT). The secondary outcomes included the performance in activities of daily living by the Barthel index (BI) and the quality of life by the 36-item short form health survey (SF-36).

The treatment compliance was similar in two groups (p=0.19). Both groups improved in motor performance, activities of daily living and quality of life. However, there were no significant differences in the FMA (p=0.58), WMFT (functional ability scale, p=0.33; performance time, p=0.44), BI (p=0.84) and SF-36 (physical, p=0.87; mental, p=0.99) scores between the groups.

The non-immersive VR system was feasible, effective and safe; however, it was not found to be superior to conventional physiotherapy. The trial was stopped early and did not reach its proposed sample size and hence, the findings are to be interpreted cautiously.

Clinical trial registry India: CTRI/2021/11/038339 (https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=NTc1OTI=&Enc=&userName=CTRI/2021/11/038339).

Although timely surgery is essential for improving general health and psychosocial outcomes, delays in cleft surgery remain common in low- and middle-income countries, including Rwanda, where little is known about the underlying causes. This study aimed to explore the factors influencing delays in cleft surgery in Rwanda using the four-delay framework.

A phenomenological qualitative study was conducted between April and July 2024. We conducted 29 in-depth interviews with 15 caregivers of children with orofacial clefts and 14 healthcare providers involved in cleft care. Transcripts were analysed thematically using an inductive–deductive hybrid approach in MAXQDA (V.24), guided by the four-delay framework while allowing themes to emerge from the data.

This qualitative study was conducted across six Operation Smile-supported hospitals in Rwanda. Operation Smile is a non-governmental organisation providing cleft care in several low- and middle-income countries, including Rwanda. Among these facilities, one is a tertiary-level hospital located in Kigali city, while the others are secondary-level hospitals distributed across all provinces of the country.

Participants were purposively selected and comprised caregivers of children who underwent cleft surgery at Operation Smile-supported hospitals between 2023 and 2024, as well as healthcare providers with a minimum of 6 months’ experience delivering cleft care at these facilities.

Six major themes and 15 subthemes emerged. Limited caregiver awareness, cultural beliefs and inconsistent knowledge of clefts among healthcare providers influenced delays in seeking care. Reaching care was impeded by long distances, poor road infrastructure and inadequate transportation options. Receiving care was delayed by patient-related factors such as poor nutritional status of children and systemic issues, including shortages of specialised cleft care workforce (such as plastic surgeons, oral and maxillofacial surgeons, anaesthesiologists, etc) and surgical infrastructure. Remaining in care was affected by the absence of multidisciplinary follow-up services. Despite these barriers, caregivers appreciated the support services provided by Operation Smile, including nutrition, transportation and coverage of surgery costs.

Cleft surgery delays in Rwanda are driven by multifactorial barriers across all stages of care. Strengthening early identification, public awareness, health provider training and post-operative support systems is essential to reducing delays and improving outcomes. Findings support the need for integrated cleft care within national surgical plans and broader health system strengthening efforts, and encourage the social and psychological support to affected children and caregivers.

To determine the prevalence of internet addiction and examine its association with psychological factors specifically depression, anxiety and loneliness among Malaysian public university students.

Cross-sectional study.

All public universities in Malaysia, 20 universities.

The study included 7278 students from 20 public universities in Malaysia.

Statistical analyses were performed usingSTATA V.17 software. Descriptive statistics summarised participants’ demographic characteristics, prevalence of internet addiction and psychological distress (depression, anxiety and loneliness). Pearson’s correlation was used to assess bivariate relationships between internet addiction and psychological variables, while multiple logistic regression identified independent factors associated with internet addiction after adjusting for significant confounders.

The study found that 38.6% of the students showed signs of internet addiction, along with a high level of psychological distress; 24.8% had depressive symptoms, 32.4% experienced anxiety and 35.5% reported loneliness. Moderate positive correlations were observed between internet addiction and depression, anxiety and loneliness (p

The findings indicate significant associations between internet addiction and psychological factors such as depression, anxiety and loneliness. A comprehensive, multifaceted approach is essential to address psychological distress among university students and reduce the risk of internet addiction.

The perspectives of stakeholders directly affected by mental health services for autism spectrum disorder (ASD) are essential for the quality of these services. However, it is crucial that these perspectives are informed by the best available evidence and adapted to the local context. This study aims to analyse barriers related to mental health services for children and adolescents with ASD from the perspective of families and caregivers, considering social, racial and gender aspects.

Three steps will be taken: stakeholder engagement through an online meeting to refine the research question and understand the magnitude of the problem; (b) qualitative evidence synthesis using five databases and grey literature to identify studies that have collected and analysed qualitative data on barriers to mental health services for children and adolescents with ASD in Brazil. Only studies conducted in Brazil that consider the perspectives of family members and caregivers will be included. (c) A citizen panel with families of children and adolescents with ASD will be used to discuss and validate the synthesis findings.

We will provide a set of evidence-informed and stakeholder-experienced barriers to mental health services for children with ASD in Brazil. This represents an effort to engage stakeholders in evidence descriptions to inform policy. We plan to disseminate the findings through various means, including peer-reviewed journal publications, presentations at national conferences, invited workshops and webinars, patient associations and academic social media platforms. The project was approved by the Ethics Committee for Research at the University of Sorocaba (approval number 78747224.7.0000.5500).

Open Science Framework—10.17605/OSF.IO/DVAKG.

Documenting evidence on global health strategies and programmes that provide safeguards for vulnerable populations and strengthen overall pandemic preparedness is essential. This study aimed to identify factors associated with adherence to COVID-19 mitigation measures, COVID-19-related symptoms and testing, as well as pandemic-related income loss among internally displaced persons (IDPs) in urban and remote areas of Burkina Faso, Niger and Mali.

This cross-sectional study used fixed-site respondent-driven sampling (RDS).

Primary care settings across six urban and remote locations in Burkina Faso, Mali and Niger.

4144 internally displaced adults, who had been forced from their homes within 5 years of the survey, participated in the study. The survey was conducted between August and October 2021 in two selected locations in three countries: Kaya (n=700) and Ouahigouya (n=715) in Burkina Faso; Bamako (n=707) and Ménaka (n=700) in Mali; and Niamey (n=733), and Diffa (n=589) in Niger. Participants were included if they were born in the study countries, displaced due to conflict, violence or disaster, aged 18 years or older, and living or working in the study site for at least 1 month.

The primary outcomes measured were adherence to COVID-19 mitigation measures, presence of COVID-19 symptoms, COVID-19 testing and vaccination rates and pandemic-related income loss.

Among 4144 IDPs surveyed across 6 sites in Burkina Faso, Mali and Niger, over half (52%) reported experiencing at least one COVID-19 symptom in the preceding 2 weeks. However, 8% had ever been tested for COVID-19, and fewer than 5% had received a vaccine in all sites except Diffa, where 54% reported vaccination. While willingness to be vaccinated was high (ranging from 56.6% in Bamako to 89.5% in Niamey), access remained limited. Compliance with public health measures varied; for example, 41.7% of IDPs were able to maintain physical distance from non-household members, and just 60.2% reported wearing a mask. Chronic health conditions were consistently associated with higher odds of COVID-19 symptoms (Ménaka OR: 14.65; 95% CI: 7.36 to 29.17). Economic vulnerability was widespread, with more than half of IDPs in Bamako (58.1%) and Niamey (66.4%) reporting income loss due to the pandemic, and average monthly income declining by over 50% in most sites. IDPs in urban areas generally reported greater exposure to COVID-19 risk factors, while those in remote settings reported lower adherence and poorer access to basic preventive measures.

This is the first known RDS study to explore the impact of the COVID-19 pandemic on IDPs. Findings suggest that IDPs in urban areas may face heightened risks of exposure and infection, underscoring the need to prioritise them in public health efforts. Low testing and vaccination rates and significant income loss call for advocacy and economic relief to address these vulnerabilities. Future pandemic responses should integrate health interventions with targeted support, especially mitigating income loss to bolster IDPs’ resilience.

Early childhood development (ECD) lays the foundation for lifelong health, academic success and social well-being, yet over 250 million children in low- and middle-income countries are at risk of not reaching their developmental potential. Traditional measures fail to fully capture the risks associated with a child’s development outcomes. Artificial intelligence techniques, particularly machine learning (ML), offer an innovative approach by analysing complex datasets to detect subtle developmental patterns.

To map the existing literature on the use of ML in ECD research, including its geographical distribution, to identify research gaps and inform future directions. The review focuses on applied ML techniques, data types, feature sets, outcomes, data splitting and validation strategies, model performance, model explainability, key themes, clinical relevance and reported limitations.

Scoping review using the Arksey and O‘Malley framework with enhancements by Levac et al.

A systematic search was conducted on 16 June 2024 across PubMed, Web of Science, IEEE Xplore and PsycINFO, supplemented by grey literature (OpenGrey) and reference hand-searching. No publication date limits were applied.

Included studies applied ML or its variants (eg, deep learning (DL), natural language processing) to developmental outcomes in children aged 0–8 years. Studies were in English and addressed cognitive, language, motor or social-emotional development. Excluded were studies focusing on robotics; neurodevelopmental disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder and communication disorders; disease or medical conditions; and review articles.

Three reviewers independently extracted data using a structured MS Excel template, covering study ML techniques, data types, feature sets, outcomes, outcome measures, data splitting and validation strategies, model performance, model explainability, key themes, clinical relevance and limitations. A narrative synthesis was conducted, supported by descriptive statistics and visualisations.

Of the 759 articles retrieved, 27 met the inclusion criteria. Most studies (78%) originated from high-income countries, with none from sub-Saharan Africa. Supervised ML classifiers (40.7%) and DL techniques (22.2%) were the most used approaches. Cognitive development was the most frequently targeted outcome (33.3%), often measured using the Bayley Scales of Infant and Toddler Development-III (33.3%). Data types varied, with image, video and sensor-based data being most prevalent. Key predictive features were grouped into six categories: brain features; anthropometric and clinical/biological markers; socio-demographic and environmental factors; medical history and nutritional indicators; linguistic and expressive features; and motor indicators. Most studies (74.1%) focused solely on prediction, with the majority conducting predictions at age 2 years and above. Only 41% of studies employed explainability methods, and validation strategies varied widely. Few studies (7.4%) conducted external validation, and only one had progressed to a clinical trial. Common limitations included small sample sizes, lack of external validation and imbalanced datasets.

There is growing interest in using ML for ECD research, but current research lacks geographical diversity, external validation, explainability and practical implementation. Future work should focus on developing inclusive, interpretable and externally validated models that are integrated into real-world implementation.

We aimed to determine the prevalence of hospital discharge communication problems in adults of 10 high-income nations and the associated factors.

Secondary analysis of cross-sectional survey data.

2023 Commonwealth Fund International Health Policy Survey for Adults, including data from residents of Australia, Canada, France, Germany, the Netherlands, New Zealand, Sweden, Switzerland, the UK and the USA.

3763 survey respondents aged 18 and older who reported hospitalisation at least one time in the past 2 years.

Our primary outcome measure is poor discharge communication (PDC), which is a composite variable comprising three questions regarding the provision of written information, follow-up arrangement and discussion of medications at time of discharge.

The overall PDC rate was 17.1%, with the highest in Germany (19.7%) and the lowest in the Netherlands (9.2%). No follow-up arrangement was the most commonly reported problem (22.8%). Respondents who concerned about social service needs and mental health issues were more likely to report PDC.

Providers should consider factors which impact PDC at hospital discharge and tailor communication appropriately. Hospitals, communities and countries should work towards policies that address underlying issues related to social determinants of health, including support for lower-income patients, improved treatment access for patients with physical and mental health conditions, and food and housing stability.

To identify and contextualise evidence-based strategies for implementing deprescribing practices at different levels of healthcare in Brazil, through the development of an evidence brief for policy that includes stakeholder deliberation and considers barriers, facilitators and equity aspects.

This protocol outlines the development of an evidence brief for policy using a mixed-methods design. It involves synthesising evidence for health policies by integrating global research and local evidence through three stages: stakeholder exchange, evidence brief development and external endorsement. The Supporting Policy-Relevant Reviews and Trials tools for evidence-informed health policies will guide both the synthesis of strategies and the facilitation of deliberative dialogues. The synthesis will encompass evidence from systematic reviews and meta-analysis on deprescribing strategies across healthcare levels, focusing on effectiveness, harms, costs, perceptions, barriers, facilitators and equity. Studies proposing strategies not yet implemented will be excluded. Study selection and data extraction will be conducted independently and in duplicate. The methodological quality of included studies will be assessed using the A Measurement Tool for Assessing the Methodological Quality of Systematic Reviews-2 criteria. Synthesised evidence will be used to develop evidence-based strategies, which will then be presented in deliberative dialogues for endorsement by stakeholders and adaptation to the Brazilian context. Endorsement rates will be classified as high, moderate or low based on predefined criteria.

This study was approved by the University of Sorocaba Research Ethics Committee (certificate 82098324.7.0000.5500). Informed consent will be obtained from all participants. Findings will be disseminated through peer-reviewed publications and conference presentations.

CRD42024548845.

The tobacco and nicotine industry fuels tobacco-related addiction, disease and death. Indigenous peoples experience a disproportionate burden of commercial tobacco-related morbidity and mortality. Over the past two decades, significant progress has been made in reducing smoking prevalence among Indigenous peoples; however, smoking remains a leading contributor to the burden of death and disease. This review will summarise evidence on commercial tobacco resistance and/or eradication strategies, including policy reforms, in relation to Indigenous peoples across Oceania, the Pacific Islands and North America.

This review will follow guidelines from the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews and will be conducted in accordance with the Joanna Briggs Institute (JBI) methodology for scoping reviews. This review will consider academic and grey literature published since 1 January 2000. The following electronic databases will be searched for relevant primary research articles and commentaries: PubMed, Scopus, Informit, Web of Science and PsycINFO. Additional searches will be conducted in ProQuest to identify relevant grey literature. Papers will be screened by two reviewers to determine eligibility, followed by full-text data extraction. Findings will be synthesised descriptively for each review question and by region. Studies included in the review will be assessed against criteria for Indigenous engagement in research.

This protocol was led by Indigenous interests, needs and rights of Indigenous peoples, consistent with the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), the WHO’s Framework Convention on Tobacco Control and ethical practice. This review was conceptualised with Indigenous leadership and through engagement, including but not limited to the Indigenous lived experience of the authors (MK, E-ST, HC, PNH, PH, SAM, AW, SW and RM). This review supports the global goal of eradicating commercial tobacco-related harms – reframing commercial tobacco use as a structurally imposed harm sustained by colonial and commercial forces rather than personal choice. Findings from this review will be shared with Indigenous partners and communities who requested this work and will be submitted for peer-reviewed publication.

Open Science Framework https://osf.io/wxqcb