Testosterone deficiency in middle-aged men is associated with a wide range of adverse health outcomes, including metabolic disorders, reduced physical performance, sarcopenia, impaired sexual function, psychological distress and decreased quality of life. Despite its growing clinical and public health importance, early identification of men at increased risk remains challenging. Current diagnostic approaches rely primarily on laboratory assessment of testosterone levels, which may not adequately reflect symptom burden and are often inaccessible in resource-limited settings. There is therefore a need for comprehensive and practical approaches that integrate anthropometric, functional and lifestyle-related factors associated with serum total testosterone levels.

This population-based analytical cross-sectional study will be conducted among middle-aged men aged 35–59 years residing in the Andijan region of Uzbekistan. Approximately 600 participants will be recruited through community-based screening programmes, primary healthcare institutions, workplace outreach and public announcements. Data collection will include anthropometric measurements, assessment of muscle strength and physical performance, lifestyle characteristics, dietary habits, sleep quality, symptoms suggestive of testosterone deficiency, lower urinary tract symptoms, muscle function and laboratory evaluation of serum total testosterone concentrations. Standardised questionnaires and validated clinical assessment tools will be used. The primary outcome is serum total testosterone concentration. Secondary outcomes include identification of anthropometric, functional and lifestyle-related factors associated with serum total testosterone levels and development of a multivariable predictive model for the early identification of testosterone deficiency. Statistical analyses will include correlation analyses, multivariable linear and logistic regression models and receiver operating characteristic curve analysis to evaluate model performance.

The study was approved by the Ethics Committee of the Ministry of Health of the Republic of Uzbekistan (Approval No. 4/26-2380, 13 May 2026) and registered at ClinicalTrials.gov (NCT07476222). Written informed consent will be obtained from all participants before enrolment. Study findings will be disseminated through peer-reviewed publications, scientific conferences and academic networks. The results are expected to contribute to the development of accessible screening strategies for the early identification of testosterone deficiency among middle-aged men.

NCT07476222.

Diabetes has reached epidemic proportions in Pakistan. This study applied machine learning (ML) techniques to identify comorbidity-based and diabetic complications-based clusters in hospitalised patients with diabetes and examine their association with in-hospital mortality.

Retrospective cross-sectional study.

Aga Khan University Hospital, Pakistan.

Adult patients (≥18 years) with diabetes admitted between 2008 and 2021.

Diagnoses were extracted using International Classification of Diseases (ICD-9 and ICD-10) codes. Data was integrated from the Hospital Information Management Systems (HIMS). The K-Modes clustering algorithm was applied to categorical diagnostic data, with the optimal number of clusters determined using elbow curve and silhouette score analysis. Latent-Dirichlet Allocation and Term Frequency-Inverse Document Frequency were applied to identify frequent terms from each cluster followed by expert validation. Logistic regression was performed to assess the association between cluster membership and in-hospital mortality.

Among 78 271 patients, four clusters were identified with varying mortality risks: (1) cardio, tumour and tobacco (CTT), (2) renal complication cluster (RCC), (3) cardiovascular cluster (CVC) and (4) uncontrolled diabetes mellitus, hypertension, stroke and kidney (HSK). The within cluster mortality was highest in the RCC cluster (682; 18.1%), followed by CVC (543; 4.4%), HSK (1,379; 4%) and CTT (603; 2.2%). Compared with CTT, the unadjusted odds of in-hospital mortality were significantly higher in RCC (OR=9.9, 95% CI 8.9 to 11.2, p

Among hospitalised patients with diabetes, the RCC cluster demonstrated the highest mortality risk, comprising predominantly older patients with severe complications. These findings highlight the utility of unsupervised ML approaches for identifying high-risk clinical phenotypes and informing risk stratification in resource-constrained settings. Longitudinal studies are warranted to evaluate progression and long-term outcomes across clusters.

Dissemination of study results to research participants is an ethical imperative, yet it is rarely implemented in resource-limited settings partly due to a lack of clear guidance. The purpose of this study was to evaluate and explore dissemination activities that were conducted as part of a multi-site clinical trial of Plasmodium vivax treatment options, informing future dissemination strategies in similar resource-limited settings.

Qualitative study using focus group discussions (FGDs) and an inductive–deductive thematic analysis approach.

Clinical trial study site catchment areas in Cambodia, Ethiopia and Pakistan.

Dissemination attendees were invited to participate in FGDs, a subset agreeing and able to participate. There were 25 participants in Cambodia, 34 in Ethiopia and 23 in Pakistan.

The dissemination activities were well accepted by participants despite some expectations in receiving individual results rather than only aggregated trial results and suggestions for broader community dissemination. Dissemination participants perceived having learnt from the dissemination, demonstrating their knowledge of the trial and its results and attributing it to the dissemination. Dissemination activities may have failed to correct certain misconceptions, including the blurred distinction between clinical care and trial-related care; however, the dissemination had positive impacts, including making participants feel part of a larger endeavour.

Contributing to the limited data on dissemination in resource-limited settings, our findings provide context-informed recommendations that can be applied to similar settings. Our recommendations underscore the importance of tailoring activities according to participant preferences, such as potentially providing individual results and implementing broader community dissemination.

NCT04411836.

Information anxiety (IA) describes the distress caused by the gap between the information individuals have and what they feel they should possess. In the current digital environment—marked by volatility, uncertainty, complexity and ambiguity—IA has expanded beyond traditional academic and workplace contexts to become a pervasive concern across populations. Mapping the empirical evidence on IA is critical to understanding its prevalence, determinants, impacts and coping strategies.

This protocol outlines a scoping review guided by the Joanna Briggs Institute methodology and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). We will systematically search EBSCOhost, Scopus and Web of Science for peer-reviewed empirical studies published from 1 January 2000 to the planned end date of 5 November 2025. Two reviewers will independently screen records, with a third resolving discrepancies. Data extraction will be conducted using a customised tool, and results will be synthesised narratively and visually, structured around bibliometric characteristics, the Population, Concept, Context framework and a Stimulus-Organism-Response model. Subgroup analyses will be conducted across populations, disciplines and regions.

As this study is based on secondary analysis of published data, ethical approval is not required. Findings will be disseminated through peer-reviewed journals and academic conferences.

Although the association between obesity and health-related quality of life (HRQoL) is well-documented, studies on the association between weight trajectories and HRQoL among spouses are limited. This longitudinal study aimed to characterise distinct body mass index (BMI) trajectories and their association with HRQoL at individual and spousal levels.

The total sample of 773 couples was followed for an average of 15 years. Univariate group–based trajectory models and multi-trajectory group–based models were used to identify latent classes of individual and couple BMI trajectories, respectively. Linear regression analyses were applied to investigate the associations between identified BMI trajectories and HRQoL at the individual level and at the spousal level, where spousal HRQoL refers to the association between both partners’ BMI trajectories and each individual’s HRQoL.

Based on BMI changes over the life course, four trajectories were identified in wives and husbands at both individual and couple levels, ranging from stable healthy weight to progressively increasing overweight and obesity, with all trajectories showing an overall rise in BMI with age. In the fully adjusted model, compared with wives in the mild progressive overweight group, the mean score of physical HRQoL in women in the progressive obesity group (β=–2.14, p=0.02) and severe progressive obesity group (β=–2.55, p=0.03) was significantly lower. Moreover, compared with husbands with stable healthy weight status, those in the progressive obesity group had lower physical HRQoL (β=–2.67, p=0.02). At the spousal level, lower physical HRQoL was observed in individuals whose BMI trajectories, together with their partner’s trajectory, indicated higher risk (eg, wives with severe progressive obesity and husbands with stable overweight) compared with couples with both partners in lower-risk BMI trajectories (β=–3.61, p=0.01). A similar effect was observed only in severe progressive obese women whose husbands were of stable healthy weight during their lifespan. None of the BMI trajectories at either individual or spousal levels affected mental HRQoL.

Our findings indicate a significant effect of individuals’ BMI patterns on the physical domain of HRQoL. Spousal HRQoL associations reflect how both partners’ BMI trajectories are jointly associated with individual HRQoL. Clinically, these results highlight the potential importance of early weight management, particularly in women, in relation to long-term physical HRQoL and possible benefits for both partners. Further investigation is required to assess the role of potential confounders in BMI–HRQoL associations.