To examine which information sources medical specialists use to answer clinical questions in daily practice and to describe the relative frequency of use for each source.

Systematic review with narrative synthesis and meta-analysis.

Academic Search Premier, APA PsycINFO, CINAHL, Emcare, Cochrane Library, Web of Science, Embase and PubMed were searched for relevant studies published from 2000 to 1 June 2025.

We included peer-reviewed English-language studies reporting on the frequency of information source usage by medical specialists when addressing clinical questions. Studies reporting usage on a continuous (0–100%) scale were eligible for meta-analysis.

Two reviewers independently screened studies. Data were extracted by one reviewer and checked by a second. Study quality was assessed using the Quality Assessment tool with Diverse Studies tool. A narrative synthesis was conducted for studies that were not eligible for quantitative pooling to summarise patterns in information-seeking behaviour and reported barriers. A random-effects meta-analysis was performed for studies reporting continuous usage percentages and assessing at least four information sources. Sensitivity analyses were conducted using a leave-one-out approach. Potential publication bias was explored descriptively using funnel plots.

25 studies were included, of which 6 (with 8641 participants) were eligible for meta-analysis. The narrative synthesis of non-pooled studies showed a consistent reliance on standalone information sources and identified barriers to the use of aggregated sources. In the meta-analysis, digital databases such as PubMed were the most frequently used information source (74%, 95% CI 63% to 85%), followed by textbooks (71%, 95% CI 57% to 85%) and consultation with colleagues (43%, 95% CI 15% to 71%). Systematically aggregated sources, including clinical practice guidelines (38%, 95% CI 27% to 49%) and point-of-care websites (49%, 95% CI 17% to 81%), were used less frequently. Sensitivity analyses indicated that pooled estimates were generally robust, although results should be interpreted cautiously given methodological variability across studies.

Medical specialists predominantly rely on standalone information sources when addressing clinical questions, while systematically aggregated and interpreted sources such as clinical practice guidelines and point-of-care tools are used less frequently. These findings highlight the need to better understand and address barriers to the use of aggregated information sources in clinical practice.

CRD42022267431.

National cross-sectional survey.

Hospitals delivering orthopaedic and trauma services across all levels of care and ownership categories in Tanzania.

Licensed orthopaedic and trauma surgeons practising in Tanzania served as key informants for their respective hospitals. A total of 171 surgeons provided data on 92 unique hospitals nationwide.

Primary outcomes included orthopaedic departmental structural capacity, availability of multidisciplinary specialist support, external support mechanisms and in-hospital orthopaedic training activities.

A response rate of 77.7% yielded data on 92 hospitals delivering orthopaedic and trauma services nationwide. Structural capacity varied widely, with only 19.6% of hospitals reporting more than 50 orthopaedic beds, 43.5% relying on a single orthopaedic surgeon, and 47.8% operating with one or two functional theatres. Access to specialist support was limited, with vascular trauma surgeons available in 9.8% of hospitals and plastic and reconstructive surgeons in 8.7%. Intensivists were available in 41.3% of facilities and anaesthesiologists in 57.6%, while physiotherapists were present in 90.2% of hospitals but occupational therapists in only 28.3%. External dependence was common, with 41.3% of hospitals relying on donated implants and 29.3% participating in outreach programmes. In-hospital orthopaedic training opportunities were limited, with seminars or workshops available in 25.0% of hospitals. Across domains, higher-tier hospitals demonstrated significantly greater structural capacity and specialist availability.

Orthopaedic and trauma services in Tanzania are available across multiple levels of the health system but are characterised by inequitable workforce distribution, limited capacity at lower-tier hospitals and substantial reliance on external assistance. Integrated strategies linking infrastructure development, multidisciplinary workforce expansion, sustainable procurement and decentralised training are essential to strengthen the organisation and resilience of orthopaedic and trauma services nationwide.

Disasters can have a disproportionate impact on highly vulnerable hospitalised patients. Managers preparing hospital networks for disasters play an important role in enhancing networks’ readiness by creating disaster plans and imparting that knowledge through training and simulation exercises. The objective of this research was to uncover how those working in disaster preparedness roles in Australian hospital networks perceived the challenges that they face while ensuring adequate preparation for disasters.

A qualitative study design was employed which involved purposive sampling of Australian hospital network professionals responsible for disaster preparedness. Thematic analysis of data collected through individual online interviews generated prominent challenges of disaster preparedness in Australian hospital networks.

Local hospital networks across Australia

Twenty-six disaster preparedness managers, including hospital executives, disaster managers, emergency management coordinators and business continuity managers from 23 hospital networks located in five Australian states and one territory, participated in semi-structured online interviews. Interview transcripts were coded through an iterative inductive thematic analysis process to synthesise the predominant challenges faced by these participants when preparing their hospital networks for disasters.

Participants reported four challenges: staff’s limited interest in preparedness, budgetary constraints, staffing issues and ambiguous relationships with state and national health departments. They also presented four related solutions: capitalising on interest after disasters, attracting funding with evidence from prior disasters, facilitating staff’s availability for disaster training and specifying network-government relationships for accountability.

Disasters, although infrequent, are known to occur and can be catastrophic, yet those working in hospital network disaster preparedness roles encounter limited availability of wider staff for training and low interest in disaster planning. The sudden onset of a disaster can take a heavy toll on patients if hospitals’ staff are not sufficiently trained in disaster response or are not aware of the disaster plan. By identifying the perceptions of managers to disaster preparedness, this research presents specific challenges that hospital networks can address to improve awareness and preparation.

Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to validate these clusters in newly diagnosed T2D patients without any complications and determine whether severe and mild phenotypes are detectable early in the disease course.

Retrospective, cross-sectional, non-interventional study.

Primary healthcare centres in Dubai, UAE.

A total of 451 adults, including both Emiratis and expatriates, diagnosed with T2D in the last 5 years and without T2D-related complications at the time of visit, were enrolled. Patients with complications, incomplete clinical data or higher duration of T2D were excluded from the study.

Identification of distinct T2D clusters using machine learning-based clustering analysis. Five clinical variables: age at diagnosis, body mass index, glycated haemoglobin, fasting serum insulin and fasting blood glucose served as predictors. Overlap between clusters was assessed via the Silhouette Index and Bayesian probability.

Five clusters were identified, replicating prior findings: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild age-related diabetes (MARD), mild obesity-related diabetes (MOD) and mild early-onset diabetes (MEOD). As confirmed by a Silhouette Index and Bayesian probability of 1, 55.43% of the patients showed cluster-exclusiveness, while 44.56% of the cohort showed overlap between clusters. The highest overlap was recorded for mild forms of T2D in the order MOD>MARD>MEOD.

The study confirms that both severe and mild T2D phenotypes are present in newly diagnosed, complication-free patients, supporting the applicability of cluster-based classification early in disease. These results highlight the potential for personalised treatment strategies to optimise management and prevent complications. Future studies should investigate longitudinal outcomes and therapeutic response across clusters.

Health systems must guarantee access to quality, safe and effective medicines. Essential medicine lists (EMLs) are crucial prioritisation tools to inform coverage decisions and steward limited health resources under the context of universal healthcare. This study aims to develop a consolidated framework for prioritising the assessment of health technologies to review and update EML for treating diseases or health problems managed in primary healthcare (PHC).

A mixed-methods approach was designed to validate the framework. An initial scoping systematic review will be conducted to search for studies that describe criteria used to prioritise the assessment of health technologies for PHC. The relevant studies will be examined using the Joanna Briggs Institute methodological framework for scoping review studies. A comprehensive search was conducted in the following sources: PubMed, Embase, Cochrane Library, Virtual Health Library (LILACS, WHO IRIS, IBECS, PAHO-IRIS, PAHO, LIS, BRISA), Health System Evidence, Global Healths, Health Evidence and Epistemonikos from the inception until February 2025. Two review authors will screen and extract data independently. The extracted data will be qualitatively analysed and presented in a diagrammatic or tabular form, alongside a narrative summary, in line with Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Extension for Scoping Reviews reporting guidelines. An iterative process online using the Delphi hybrid with stakeholders through predetermined consensus thresholds, a combination of a four-point Likert scale and open-ended questions will be conducted to select and validate the criteria identified in the scoping review.

We will provide a consolidated framework to inform decision-makers for prioritising the assessment of health technologies for the national EML for PHC. This is an important step in using evidence to inform public health policies. We plan to share findings through a variety of means, including publications in peer-reviewed journals, presentations at national conferences, invited workshops and webinars, email discussion lists affiliated with our institutions and professional associations, and academic social media.

Ensuring gender equity in leadership is crucial for fair representation and diversity in academic medicine. This study aims to investigate the representation of women in leadership positions in Turkish academic medicine, including medical schools, specialty boards, conferences and medical journals.

A cross-sectional study was conducted between August and December 2023. The study analysed data from members of medical faculties, specialty boards, medical conferences and medical journals across Turkey. The source of information was publicly accessible websites.

The study included data from 17 939 members of 113 medical faculties, 112 specialty boards, 73 medical conferences and 246 medical journals in Turkey.

This study has no interventions.

Women made up 40.4% of all medical-school faculty but only 22.5% of deans (95% CI 15.5 to 31.6; p

Turkey’s academic medicine pipeline contains substantial numbers of women, yet marked gaps persist in senior positions. Bridging these gaps will require targeted policies that look beyond overall workforce proportions to the specific decision-making roles where shortfalls remain.

Polypharmacy, defined as the concurrent use of multiple medications, is a growing concern among the elderly, especially in low-income and middle-income countries such as Iran. This study aims to explore the prevalence and patterns of polypharmacy among the elderly in Iran, using health insurance claims data to identify common drug classes and coprescribed medications, with a focus on informing policy decisions and improving medication management.

Retrospective population-based observational study.

Nationwide data from the Iran Health Insurance Organization (IHIO) across 24 provinces.

1 876 527 individuals aged 65 years and older, insured by the IHIO from 2014 to 2017. Individuals with incomplete demographic information or lacking medication records in the database were excluded from the analysis.

Prevalence and patterns of polypharmacy, demographic factors associated with polypharmacy, and common drug classes used. Medications were classified using the Anatomical Therapeutic Chemical system. Polypharmacy was defined as the use of five or more medications, with cumulative polypharmacy considering total drug use over time, and consecutive polypharmacy focusing on the frequency of monthly drug use. Logistic regression and association rule mining were applied to explore demographic factors and medication patterns associated with polypharmacy.

Of the study population, 74.9% experienced cumulative polypharmacy over 6 months and 64.6% over 1 month, with 7.6% experiencing consecutive polypharmacy. Females and those aged 75–79 were more prone to polypharmacy. Systemic glucocorticoids were the most commonly used medications (50.02%), followed by HMG-CoA reductase inhibitors (42.73%) and platelet aggregation inhibitors (41.92%). Polypharmacy was most strongly associated with medications related to the alimentary tract and metabolism, cardiovascular system, nervous system and blood and blood-forming organs.

Polypharmacy is highly prevalent among the elderly in Iran, with significant variations by gender, age, insurance fund and region. The findings highlight the need for targeted interventions to manage polypharmacy and improve medication safety in this population.

We calculate positive predictive values (PPVs) of patients presenting with unexpected weight loss (UWL) being diagnosed with cancer within 6 months, using data from a population of Australian primary care patients to replicate results from a previous UK study.

A diagnostic accuracy study involving calculation of the PPV for any cancer using retrospective data from routinely collected electronic healthcare records. The index date is defined as the first recorded UWL presentation and the reference standard is cancer diagnosis within 6 months of the index date.

This study uses primary care data from the Patron primary care database, linked to hospital admissions data and the Victorian Cancer Registry. We include only patients who presented to their General Practitioners (GPs) at least once between 1 July 2007 and 1 February 2022.

Patients were included if they were at least 18 years of age at the index date, had no previous diagnosis of cancer or previous weight loss intervention, including being prescribed medications for weight loss. 13 306 patients out of a primary care population of 1 791 051 patients were identified that met the eligibility criteria.

When stratified by age, sex and smoking status, we found PPVs lower than those derived in a previous UK primary care study, though still above 3% for male non-smokers over 60, female smokers over 70 and all males over 70. Patients from ages 60–79 with at least one abnormal blood test result had PPVs consistently above 3%, while overall, patients with abnormal blood test results have PPVs of up to 35%.

We confirmed that many PPVs, while consistently below those derived in the UK study, are above clinically significant thresholds and increasing with age and the number of different abnormal blood test results.

Non-communicable diseases (NCDs), such as diabetes, cardiovascular diseases and cancer, are major global public health concerns. Diet quality—particularly the consumption of ultra-processed foods—has been associated with increased risk of NCDs. Traditional cohort studies are often expensive and logistically complex. The NutriNet-Brasil cohort leverages a web-based approach, offering a cost-effective and practical solution for comprehensive data collection and long-term follow-up.

Recruitments began in January 2020 through mass media, social media campaigns and collaborations with health organisations. Eligible participants are adults (aged ≥18 years) living in Brazil with internet access. Participants complete self-administered online questionnaires covering dietary intake, health status and other health determinants. Dietary assessment is based on the Nova classification system, which categorises foods by their level of processing.

Over 88 000 participants have completed the initial questionnaire. The cohort is predominantly women (79.9%) and highly educated (67.9% had completed higher education). The web-based design enabled the development and application of innovative dietary assessment tools, including the Nova24h and the Nova24hScreener, specifically designed to evaluate food processing levels. These tools have shown good performance in capturing dietary patterns and are central to the cohort’s aim. The online platform facilitates efficient recruitment, data collection and participant retention.

NutriNet-Brasil is pioneering the development of web-based cohort methodologies and instruments tailored to food processing research. Future work includes leveraging collaborations with national and international research centres to conduct multidisciplinary analyses and inform public health policies.