To determine the risk perception, health-related adaptive behaviours and associated factors related to climate change among high school students in Thiruvananthapuram district, Kerala, India.

A cross-sectional study with multistage cluster sampling was conducted among high school students from Neyyatinkara Taluk in the Thiruvananthapuram district of Kerala, India. After identifying the taluk, 10 schools were chosen using probability proportionate to size to ensure adequate representation.

The study was conducted among 600 high school students (mean age 14 years, SD 0.75) from Neyyatinkara Taluk in the Thiruvananthapuram district of Kerala.

Neyyattinkara taluk was randomly selected from the six taluks in Thiruvananthapuram district. From each of the 10 selected schools, students from classes 8 to 10, section A, formed the study clusters, with cluster sizes ranging from 45 to 60 students. All students from classes 8 to 10 (section A) who were present on the day of the survey and had obtained informed consent from their parents or guardian were considered eligible to participate in the study. Risk perception and health-related adaptive behaviour scores for children were calculated using a pretested structured questionnaire with 8 and 17 questions, respectively. All questions were designed on a 5-point scale. For positively worded questions, scores ranged from 5 to 1 (strongly agree to strongly disagree), and for negatively worded questions, the scoring was reversed. Binary logistic regression analysis was used to determine the independent factors associated with risk perception and health-related adaptive behaviour.

Nearly three in four study participants (72.1%) were aware of the term climate change. The median risk perception score and health-related adaptive behaviour scores were 28 (IQR 26–30) and 52 (IQR 47–57), respectively. Study participants from urban areas had significantly better risk perception compared with rural counterparts (AOR 2.42; 95% CI 1.54 to 3.78). Similarly, children from above poverty line (APL) households demonstrated markedly higher risk perception than those from below poverty line households (AOR 28.77; 95% CI 16.84 to 45). Participation in a climate change awareness programme was also associated with higher risk perception (AOR 1.98; 95% CI 1.23 to 3.19). Positive health-related adaptive behaviour was more likely among children aged 14–16 years compared with those younger than 14 (AOR 1.92; 95% CI 1.3 to 2.84). Urban residence (AOR 20.72; 95% CI 5.04 to 85.17), higher paternal education (AOR 1.91; 95% CI 1.15 to 3.13) and APL household status (AOR 2.50; 95% CI 1.57 to 3.93) were also significantly associated with better adaptive behaviour.

Climate change interventions and awareness programmes should prioritise rural, lower socioeconomic and younger populations and equip them with practical life skills for adaptive behaviour.

Dysphagia, or difficulty in swallowing, significantly impacts the quality of life of the affected individuals. Diagnostic approaches, including video fluoroscopic swallowing studies and flexible endoscopic evaluation of swallowing, are the most commonly used methods for assessing swallowing function. Recent advancements have led to the development of artificial intelligence (AI), including machine learning (ML) and deep learning (DL), which will provide innovative approaches to dysphagia diagnosis and treatment planning. There is a limited synthesis of literature on AI tools in dysphagia. There is an urgent need for a more rigorous and structured scoping review that can address the existing gaps, provide a more comprehensive evidence synthesis, and establish clearer guidelines for the clinical implementation of AI in assessments and management of dysphagia. This review will include studies focusing on AI tools such as ML, DL and computer vision for assessing and managing dysphagia. The context will be clinical or therapeutic settings, and all language articles will be considered for the review. Studies not involving AI technologies, those without clinical outcomes and ethical approval, and those focusing solely on the paediatric population will be excluded. This scoping review will systematically map and synthesise the existing literature on the use of AI tools for the assessment and management of dysphagia.

This scoping review will follow JBI methodology and PRISMA ScR guidelines. Information to be searched from January 2000 to May 2025 will include MEDLINE (via Ovid), Scopus, CINAHL (via EBSCOhost), Cochrane Library, JBI Evidence Synthesis, ProQuest and Google Scholar. The titles, abstracts and full texts will be screened by two independent reviewers. Data extraction will use a study-specific customised form, with descriptive analysis employed to categorise studies by AI tools and outcomes.

Ethical approval is not mandatory for this scoping review as it does not entail the collection of any individual patient data. Secondary data from publicly accessible research papers will be used. All the data sources will be appropriately cited. The findings will be propagated through peer-reviewed publications and scientific presentations.

Open Science Framework: DOI 10.17605/OSF.IO/DYCE9.

This study aimed to analyse the number of myocardial infarction (MI) admissions during the COVID-19 lockdown periods of 2020 and 2021 (March 15th to June 15th) and compare them with corresponding pre-pandemic period in 2019. The study also evaluated changes in critical treatment intervals: onset to door (O2D), door to balloon (D2B) and door to needle (D2N) and assessed 30-day clinical outcomes. This study examined MI care trends in India during the COVID-19 lockdown period, irrespective of patients’ COVID-19 infection status.

Multicentre retrospective cohort study

Twenty-three public and private hospitals across multiple Indian states, all with 24/7 interventional cardiology facilities.

All adults (>18 years) admitted with acute myocardial infarction between March 15 and June 15 in 2019 (pre-pandemic), 2020 (first lockdown) and 2021 (second lockdown). A total of 3614 cases were analysed after excluding duplicates and incomplete data.

Number of MI admissions, median O2D, D2B and D2N times.

30-day outcomes including death, reinfarction and revascularisation.

MI admissions dropped from 4470 in year 2019 to 2131 (2020) and 1483 (2021). The median O2D increased from 200 min (IQR 115–428) pre-COVID-19 to 390 min (IQR 165–796) in 2020 and 304 min (IQR 135–780) in 2021. The median D2B time reduced from 225 min (IQR 120–420) in 2019 to 100 min (IQR 53–510) in 2020 and 130 min (IQR 60–704) in 2021. Similarly, D2N time decreased from 240 min (IQR 120–840) to 35 min (IQR 25–69) and 45 min (IQR 24–75), respectively. The 30-day outcome of death, reinfarction and revascularisation was 4.25% in 2020 and 5.1% in 2021, comparable to 5.8% reported in the Acute Coronary Syndrome Quality Improvement in Kerala study.

Despite the expansion of catheterisation facilities across India, the country continues to fall short of achieving international benchmarks for optimal MI care.