Global discussions surrounding the medical use of marijuana have gained momentum; yet in Malaysia, cannabis remains strictly prohibited under the Dangerous Drugs Act 1952. Despite its legal status, there is growing public discourse on its potential therapeutic benefits. Understanding public acceptance is critical for informing future health policies and public education efforts.

This study used a cross-sectional design, web-based survey among Malaysians aged 18 years and above using convenience and snowball sampling methods. The survey collected data on sociodemographic characteristics, lifestyle factors (eg, smoking and drug use), awareness of medical marijuana and perceived risk. Multivariable logistic regression analysis was performed to identify factors associated with acceptance of medical marijuana decriminalisation.

Out of 2047 respondents, 88.4% supported medical marijuana decriminalisation based on clinical evidence. Key predictors of acceptance included male gender (adjusted OR (AOR) 1.71; 95% CI 1.29 to 2.26), higher education (Bachelor’s degree AOR 1.56; 95% CI 1.09 to 2.23 and Master’s/PhD AOR 2.04; 95% CI 1.34 to 3.10), self-employment (AOR 1.84; 95% CI 1.22 to 2.77) and private sector employment (AOR 1.40; 95% CI 1.03 to 1.89). Behavioural factors, such as smoking (AOR 1.58; 95% CI 1.10 to 2.27), prior drug use (AOR 1.86; 95% CI 1.30 to 2.67) and low perceived risk (AOR 5.82; 95% CI 3.48 to 9.73), were also significantly associated with acceptance.

A large proportion of Malaysian adults supported the clinical use of medical marijuana. Acceptance was strongly associated with demographic and behavioural factors, particularly gender, education and perceived risk. These findings may guide the development of targeted public health education and inform future discussions on regulatory approaches in Malaysia.

To examine the self-reported adherence of ambulance nurses to acute chest pain guidelines and analyse how demographic and professional characteristics influence this adherence.

Cross-sectional study.

Regional ambulance service in southern Sweden (18 ambulance stations).

Ambulance nurses (registered and specialist nurses). Of the 397 ambulance nurses invited, 261 responded (65.7%) in 2023.

Descriptive statistics; independent-samples t-tests and ² tests for group comparisons; Pearson correlation; and stepwise linear regression to identify predictors of adherence.

Primary: adherence to the prehospital acute chest pain guideline, measured with the 5-item Self-Reported Adherence scale (5–25). Secondary: medication-specific adherence; guideline-access sources.

A cross-sectional study involving 261 ambulance nurses from 18 ambulance stations in southern Sweden. Adherence to acute chest pain guidelines was assessed using a validated instrument. Data collected in autumn 2023 were analysed using descriptive and inferential statistics, including stepwise linear regression analysis.

The study revealed an average self-reported adherence score of 19.2 out of 25 for acute chest pain guidelines. Mobile applications were the most commonly used source for accessing acute chest pain guidelines, while ambulance managers were the least used. Notably, older and more experienced ambulance nurses reported higher adherence scores. Additionally, a positive attitude towards the guidelines was correlated with higher adherence. Prioritisation of guidelines and age were predictors of adherence. In contrast, other demographic variables, such as sex and specialist nursing education, were not found to be associated with adherence.

The study indicates that self-reported adherence to acute chest pain guidelines among ambulance nurses is influenced by how highly they prioritise these guidelines and by their attitudes towards them, as well as their age and professional experience. Enhancing educational programmes and digital resources, particularly for younger and less experienced nurses, may improve adherence and patient outcomes in prehospital settings.

Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in the diagnosis of various diseases, including tropical fevers such as dengue and malaria. However, there is a lack of standard guidelines to develop the AI models, the gap between clinical and engineering expertise and clinical validation of the models, and hence there is a critical need for the development of an integrated diagnostic tool which uses demographical, laboratory variables and epidemiological parameters of patient and provides early prediction.

The present study aimed to develop and evaluate a machine-learning (ML) prediction tool for differential diagnosis of tropical fevers for adult patients (>18 years) using a three-phase approach in a tertiary care centre in South India by January 2026. Phase involves identification of the prevalent tropical fevers and associated clinical parameters to develop the AI model through a retrospective audit and qualitative interview. Phase Ⅱ involves retrospective data collection from hospital medical records for finalised diseases (1000 cases per disease) and clinical parameters, with data being used for model development using the Python language. Support vector machine, logistic regression, K-Nearest Neighbors, Naïve Bayes and ensemble models such as decision tree and Random Forest will be employed along with explainable AI techniques. They are used as they are easy to understand and interpret, well established, most effective for structured data, enhancing the transparency and interpretability of the predictive machine learning models, and their use has been widely supported in previous studies across various contexts. Suitable statistical parameters like specificity, sensitivity and area under receiver operating characteristic (AUROC) will be applied to evaluate model performance. In phase , the developed model will be implemented prospectively to assess the feasibility of model implementation. Model performance such as specificity, sensitivity and AUROC will be calculated, and the finally developed model will be implemented in a single tertiary care hospital to evaluate its overall performance.

Ethical approval for the study has been obtained from the institutional ethics committee of the Kasturba Medical College and Kasturba Hospital, Manipal (IEC number: 6/2024). Informed consent will be taken for obtaining the data of the patient for the evaluation of the model in the third phase of the study, and data will be kept confidential. The study results will be disseminated by publishing them in a peer-reviewed journal.

The protocol has been registered with the Clinical Trial Registry of India (CTRI) (CTRI/2024/04/065866) and approved on 16 April 2024.

This study aimed to determine the prevalence of cervical high-risk human papillomavirus (hrHPV) in a community-based setting and its risk factors association in women living in hard-to-reach areas in Bangladesh.

A cross-sectional study

The study was carried out in six subdistricts, located in hard-to-reach and climate-impacted regions of Bangladesh.

A total of 8000 married women aged 30–60 years were invited for screening. Women who were unable to give consent, were pregnant or had a hysterectomy with removal of the cervix, previous screening less than 5 years, or treatment of the cervix or had symptoms of potential cervical cancer were excluded.

A community-based hrHPV self-collected screening for cervical cancer was conducted from June 2022 to July 2023.

Prevalence of cervical hrHPV and risk factor association.

11 127 women were eligible for screening; 7850 women submitted hrHPV self-swabs, 7828 valid HPV test results were reported and 164 women (2.1%) tested hrHPV positive. Women living in the North were 2.1 times more likely to be hrHPV positive compared with women living in the South (adjusted OR (AOR)=2.1, 95% CI: 1.5 to 3.8, p=0.023) and widowed women were 3.0 times more likely to be hrHPV positive than married women (AOR=3.0, 95% CI: 1.7 to 5.3, p=0.001). Another risk factor associated with testing hrHPV positive was the use of hormonal contraceptives for 5 years and above (AOR=7.0, 95% CI: 2.0 to 24.4, p=0.002).

The study identified a low overall prevalence of hrHPV infection (2.1%) among women in hard-to-reach areas in Bangladesh, with some regional variations. Higher prevalence was observed in widowed compared with married women and among women reporting more than 5 years of hormonal contraceptive use. This study shows no evidence of particularly high-risk groups in hard-to-reach areas in Bangladesh. The findings support the feasibility of implementing a nationwide hr-HPV-based self-sampling strategy as a viable approach to reach WHO targets for reducing the burden of cervical cancer. Recommendation for policymakers to support future research to identify hrHPV prevalence among women in comparable groups in other geographically remote areas in Bangladesh.

NCT05234112.