Growing evidence supports integrating occupational health and safety (OHS) and workplace health promotion (WHP) to enhance worker health, safety and wellbeing. This study aimed to explore in Australia: (1) the reasons for implementing OHS and WHP separately or concurrently/jointly; and (2) potential preferences and implementation contexts of integrated OHS-WHP approaches.

This qualitative study involved focus groups (n = 3) and individual interviews (n = 40) with 47 OHS professionals, health promotion (HP) professionals, occupational health professionals and employers in Australia. Data were collected between October 2024 and March 2025. A thematic inductive analysis was employed.

Several important insights include: (1) knowledge and attitudes of professionals towards OHS or WHP, particularly regarding OHS professionals' limited understanding of WHP and HP professionals' difficulties with OHS terminology; (2) reasons for inadequate integration implementation, including scarce WHP implementation, invisible WHP benefits, poor WHP evaluation, differing views of OHS professionals about WHP, debate about worker health and WHP quality and implementation issues; (3) trends and examples of integration, often motivated by factors like COVID-19 and occurring more successfully in large organisations, though often hindered by departmental siloing; and (4) roles, attitudes and knowledge of employers, with varying support for integration across management levels and organisational sizes.

Limited implementation of integrated OHS-WHP approaches in Australia stems from lack of policy emphases, professional knowledge gaps, and WHP implementation and evaluation concerns. SO WHAT?: Urgent educational opportunities for employers and OHS professionals are needed to foster a holistic consideration of worker health and wellbeing, encouraging meaningful collaboration with health professionals and applying systems thinking to contemporary WHP.

BACKGROUND Pneumocystis jirovecii pneumonia (PJP) is a life-threatening opportunistic infection in kidney transplant recipients (KTRs). Early identification of patients liable to progress to severe disease is critical for improving prognosis. This study aimed to construct and validate a machine learning-based nomogram for predicting the risk of severe PJP in KTRs using routine clinical indicators. MATERIAL AND METHODS A retrospective cohort of 169 KTRs diagnosed with PJP was analyzed. Severe PJP was defined as cases requiring intensive care unit (ICU) admission or death. The cohort was randomized into training (n=120) and testing (n=49) sets. Three machine learning algorithms (Boruta, RFE, and LASSO) were utilized for feature selection. A multivariate logistic regression model was established and visualized as a nomogram. Model performance was evaluated via area under the ROC curve (AUC), calibration plots, and decision curve analysis (DCA). Kaplan-Meier analysis was performed to assess risk stratification. RESULTS Four key predictors were identified: procalcitonin (PCT), (1→3)-ß-D-glucan (G_test), C-reactive protein (CRP), and the time from kidney transplantation to PJP onset (Time KT to PJP). Notably, shorter post-transplant time and elevated biomarkers were associated with greater severity. The nomogram demonstrated robust discrimination with AUCs of 0.935 (training) and 0.886 (testing), alongside excellent calibration. DCA confirmed a significant clinical net benefit. Furthermore, Kaplan-Meier analysis revealed that patients stratified as high-risk by the model had significantly lower survival rates compared to the low-risk group (P<0.0001). CONCLUSIONS We developed a practical nomogram incorporating 4 accessible indicators to accurately predict severe PJP in KTRs. This tool facilitates the early identification of high-risk patients, enabling timely, individualized interventions and the rational allocation of medical resources.

ObjectiveTo describe adherence to early discharge (<24 h) among patients with low-risk pulmonary embolism and to characterize barriers to its implementation.MethodsThis was a descriptive, retrospective cohort study conducted within an Anticoagulation Stewardship Program at a Colombian tertiary hospital. Low-risk pulmonary embolism was defined as simplified Pulmonary Embolism Severity Index of 0, absence of right ventricular dysfunction, and negative cardiac biomarkers. Outcomes at 30 days included mortality, major bleeding, and rehospitalization.ResultsAmong 765 patients with pulmonary embolism, 62 were classified as low risk. The median age was 45.5 years (interquartile range: 32-62) and 36/62 (58.1%) were women. Early discharge occurred in 13/62 patients (20.9%), whereas 49/62 (79.1%) experienced longer hospital stay (median, 3 days (interquartile range: 2-6)). Early discharge rates increased from 9.5% (2019-2022) to 45% (2022-2024). Thirty-day outcomes were favorable, with no deaths, major bleeding events, or rehospitalizations. Five patients revisited the emergency department for pain but did not require admission. Delayed discharge was more frequent in patients with anemia, thrombocytopenia, those receiving medications associated with increased bleeding risk, and in those managed outside the internal medicine service. Documented reasons for delayed discharge included awaiting echocardiography (12/49), international normalized ratio monitoring (11/49), other comorbidities (11/49), delayed direct oral anticoagulants dispensing or authorization (9/49), and uncontrolled pain (6/49).ConclusionsAdherence to early discharge for low-risk pulmonary embolism was limited despite excellent short-term safety outcomes. System- and process-level barriers, particularly echocardiography utilization, warfarin/international normalized ratio requirements, direct oral anticoagulants access, and pain management, may be addressed through standardized discharge pathways and diagnostic stewardship.

To assess whether a medical telephone helpline and the use of a computer-assisted structured triage tool led to a reduction in demand for acute and emergency care in hospital emergency departments (EDs) or other ambulatory out-of-hour (OOH) services.

We conducted an ecological study using secondary data on outpatient care.

The study was conducted in 10 out of 16 federal states of Germany.

The analysis was based on ambulatory claims data for the years 2016-2020 by 11 Associations of Statutory Health Insurance Physicians (ASHIPs) covering more than 64% of the total German population.

The evaluated intervention comprised two components. The first was the introduction of a 24/7 medical helpline (116117), established to assist individuals with medical concerns in accessing appropriate care. The second component was the introduction of the computer-assisted triage tool SmED (Strukturierte medizinische Ersteinschätzung in Deutschland, Structured medical initial assessment in Germany) to support call-takers by suggesting medically relevant questions to identify red flags and determine the urgency of treatment and a possible treatment facility. For the analysis, approximately 3 years before and 1 ½ years during the intervention were considered.

Main outcome was the effect on acute and emergency care which was measured as the number of personal doctor-patient contacts (1) in EDs (ED cases, data of 10 ASHIPs could be considered) and (2) in EDs or other OOH services (ED and OOH cases, data of 11 ASHIPs could be considered).

The analysis was limited by legal changes mandating intervention components across all study sites-leading to a loss of control groups and delayed implementation-and the onset of the COVID-19 pandemic. Across all ASHIPs and counties, the number of calls to 116117 and the number of SmED assessments showed a negative association with the number of ED cases (total change: 295.0 cases to 224.5 cases per 100 000 inhabitants, 116117 calls: r=-0.04; 95% CI -0.04 to -0.035; p≤0.001, SmED: r=-0.15; 95% CI -0.35 to 0.05; p=0.138) as well as with the combined number of ED and OOH cases (total change: 516.4 cases to 400.3 cases per 100 000 inhabitants, 116117 calls: r=-0.02; 95% CI -0.03 to -0.001; p≤0.01, SmED: r=-0.58; 95% CI -0.98 to -0.19; p≤0.01). However, the association between the number of SmED assessments and ED cases was not statistically significant. Moreover, the magnitude and direction of effects varied across ASHIPs. Sensitivity analyses restricted to time periods preceding the onset of the COVID-19 pandemic showed a non-significant negative association for 116117 calls and a significant positive association for SmED assessments with both ED cases and combined ED and OOH cases (ED cases: 116117 calls: r=-0.001; 95% CI -0.019 to -0.018; p=0.928; SmED: r=0.37; 95% CI 0.29 to 0.45; p≤0.001; ED and OOH services cases: 116117 calls: r=-0.03; 95% CI -0.06 to 0.003; p=0.077; SmED: r=0.34; 95% CI 0.20 to 0.48; p≤0.001).

Our findings indicate a trend suggesting that implementation of a 24/7 medical helpline may reduce the demand for acute and emergency care at EDs and OOH services, although clear evidence is lacking. The impact of SmED use remains inconclusive. Further research should ideally incorporate data linkage and controls and assess the effectiveness and efficiency of the triage process, as well as the quality of subsequent care at the individual level.

Factor analysis (FA) can be used to identify key biomarkers in biological processes by assuming that latent biological pathways (statistically, "latent factors") drive the activity of measurable biomarkers ("observed variables"). However, biological pathways often interact, meaning that the classical FA assumption of independence between factors is questionable. Motivated by sparsely and irregularly collected longitudinal measurements of metabolites in a COVID-19 study, we propose a dynamic factor analysis model that accounts for cross-correlations between pathways via a multi-output Gaussian processes (MOGP) prior on the factor trajectories. To mitigate against overfitting caused by sparsity of longitudinal measurements, we introduce a roughness penalty upon MOGP hyperparameters and allow for non-zero mean functions. We also propose a scalable stochastic expectation maximization (StEM) algorithm that, in simulations, is both 20 times faster and provides more accurate and stable MOGP hyperparameter estimates than a previously-proposed Monte Carlo Expectation Maximization algorithm. In the motivating COVID-19 study, our methodology identifies a kynurenine pathway that affects the clinical severity of patients with COVID-19 disease and uncovers the role of the biomarker taurine. Our R package DFA4SIL implements the proposed method.

Distal radius fractures (DRFs) are common upper-extremity fractures in older adults and are often considered sentinel events for frailty and future falls. COVID-19 lockdowns introduced major mobility restrictions that altered physical activity patterns and injury epidemiology.

To describe nationwide trends in DRF incidence before, during, and after COVID-19 lockdown phases in Israel, and to interpret these trends in the context of deconditioning and rehabilitation needs.

This retrospective population-based cohort study analyzed electronic health records from Clalit Health Services, covering > 4.5 million insured individuals. Adults aged ≥ 18 years with a documented DRF between June 2019 and December 2022 were included in the phase-based analysis. Seven pandemic phases were defined according to national restriction policies. DRF incidence was calculated as cases per 100,000 insured individuals per day, and demographic trends were described across phases.

Overall, 62,731 DRFs were identified (mean age 57.1 ± 19.0 years; 58.4% female). DRF incidence declined by 27% during the first national lockdown compared with the pre-pandemic period. Incidence increased across later phases and exceeded baseline in the post-pandemic period (+19.8%). Mean age rose over time, and the proportion of fractures among women was higher in later phases.

DRF incidence showed a marked short-term decline during strict lockdowns followed by a sustained rebound above baseline. These patterns likely reflect combined effects of restrictions, behavioral adaptations, and lockdown-related deconditioning. DRFs may indicate functional vulnerability, supporting timely rehabilitation and integrated fall-prevention strategies, including tele-rehabilitation, during and after periods of restricted mobility.

Vaccine hesitancy is relevant among nursing students, as they move across healthcare and university settings. Given the opportunity of social media to disseminate misleading information to users and the exposure of the digital natives, social media addiction (SMA) is considered a predictor of vaccine hesitancy, although to date no research within this specific population exists.

To investigate the role of SMA on vaccine hesitancy in nursing students.

Cross-sectional.

Structural Equation Modelling was adopted to test the study's aim. The VAX scale was used among 227 nursing students in the UK regarding COVID-19 and Influenza vaccines during the period from March to July 2023. The Bergen Social Media Addiction scale was adopted to measure SMA.

Statistically significant results were found between SMA and mistrust of vaccine benefits. No significant correlations were found between SMA and concerns about unforeseen future effects or a preference for natural immunity. Regarding concerns about commercial profiteering, there was a significant negative correlation for the COVID-19 vaccine.

Mistrust in institutions and scepticism towards vaccine benefits and commercial interests are recurring issues tied to social media. Targeting popular social media platforms for tailored vaccination campaigns is recommended to promote vaccine acceptance among nursing students.

Providing accurate and accessible vaccine information on social media platforms, promoting media literacy and engaging with individuals to address their concerns are key to promoting vaccination among nursing students.

This study provides new strategies for tailoring vaccination campaigns and policies. Public health efforts to combat vaccine hesitancy should consider the role of social media and work to provide accurate and balanced information to the public.

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were adopted.

No patient or public contribution.

Cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS) is caused by biallelic pathogenic repeat expansions in the RFC1 gene. Chronic cough can precede the neurological features of CANVAS by decades and, in some instances, may be the sole clinical manifestation. However, the prevalence of biallelic RFC1 repeat expansions among patients with unexplained chronic cough (UCC), as well as the diagnostic utility of targeted neurological screening in this setting, remains unclear.

In this 6-month pilot study, 13 consecutive patients with UCC underwent a standardized neurological evaluation and screening nerve conduction studies (NCS) during a single clinical visit. All patients were subsequently tested for RFC1 repeat expansions. Those carrying biallelic pathogenic expansions (RFC1+) were further assessed with extended NCS, electrochemical skin conductance (ESC), and thermal quantitative sensory testing (QST).

Three patients (23%) were RFC1+. Clinical and demographic features did not significantly differ between RFC1+ and RFC1- groups. All RFC1+ individuals exhibited marked bilateral reduction in radial and sural sensory nerve action potential (SNAP) amplitudes. In contrast, only two RFC1- patients showed reduced sural SNAPs. QST revealed impaired cold detection thresholds with preserved warm detection in all RFC1+ cases, while ESC results were normal.

These findings suggest that standardized neurological and electrophysiological assessment can detect subclinical sensory neuropathy in UCC patients lacking overt neurological symptoms, thereby identifying those more likely to carry RFC1 expansions. The observed 23% prevalence supports incorporating RFC1 testing into the diagnostic approach for selected UCC patients, particularly when radial SNAP amplitudes are reduced.

Dense population, rapid urbanization, and industrialization make India a highly vulnerable country to the consequences of global warming. This study examines spatiotemporal trends of diurnal land surface temperature (LST) over the past 25 years (2000-2024) and analyzes the surface urban heat island (SUHI) intensities across the country and for 50 major cities, respectively, including the influence of zonal biogeography. The significance of the LST trends is statistically confirmed by using the Mann-Kendall test and zonal heterogeneity is analyzed by using ANOVA test. The study covers total span of 25 years (2000-2024) which is classified in two periods, pre-COVID-19 years (2000-2019) and including the post-COVID-19 years (2000-2024). In the period from 2000 to 2019, the mean LST variability range (minimum to maximum) has substantially widened by 7.8 °C and 2.3 °C for daytime and nighttime, respectively. The LST change during the COVID-19 period was significantly hindered; the change in daytime and nighttime LST for May month was 0.18 °C and 0.04 °C, respectively, whereas during 2020-2024, it has become -1.24 °C and -0.2 °C, respectively. In general, the zones follow the country-level LST trends for 2000-2019 as well as for 2020-2024 periods, with variable LST change rates. The highest annual daytime LST growth (+ 0.15 year^-1) is observed for the Desert (DES) zone, whereas the highest nighttime LST rise (+ 0.07 year^-1) is observed for the Western Ghats (WG). Notably, the Himalaya and Trans-Himalaya (HTH) zones exhibit negative LST growth rate (-0.08 and -0.09 for daytime and nighttime, respectively). Further, SUHI analysis indicates that the cities within theIndo-Gangetic Plain (IGP), Semi-Arid Region (SAR), Deccan Plateau (DP), and Western Coastal Region (WCR) zones are found to be largely impacted by SUHI intensification, ranging between 1 and 5 °C for daytime as well as nighttime. Interestingly, even trivial SUHI values of DES cities (1-3 °C for daytime) could be consequential, as the zonal LST is extremely high. The study points out the requirement of urgent policy intervention and mitigation measures.

Post-COVID syndrome is widely recognised in children and young people (CYP), where one or more persistent physical symptoms are present 12 weeks after the initial infection that cannot be explained by an alternative cause. We aimed to assess whether an intervention based on narrative therapy and breathing pattern retraining, co-designed with CYP with PCS (12-18 years) was feasible and acceptable within an NHS service. Participants were randomised to standard clinical care or intervention plus standard clinical care. The primary aim was to assess acceptability and feasibility within the study cohort. Intervention effects were evaluated using the Strengths and Difficulties Questionnaire (SDQ) Impact Score,with additional secondary outcomes included the Nijmegen questionnaire, Chandler Fatigue, and EQ-5D-Y, wellness rating, pulmonary function, and exercise testing. Thirty-two CYP were randomised to standard treatment (n = 15) or intervention (n = 17), mean age of 15 years, and 11 (34%) male. Twenty-seven (84%) were diagnosed with breathing pattern disorders. Four intervention groups were offered over 6 months. 14/17 completed the session. Qualitative feedback was positive. There was no statistically significant improvement in the SDQ over time or between groups. Nearly all secondary outcome measures showed statistically significant improvement over time (< 0.001) but not between groups. Conclusions: The intervention was acceptable and feasible to run in an NHS clinic setting for CYP with post-COVID syndrome. Significant improvements seen with time in secondary outcome measures in both groups indicate that post-COVID symptoms improve with time independent of the intervention. What is known - What is new: • Post-COVID syndrome (PCS) affects up to 66.5% of children and young people (CYP) with common persistent or fluctuating symptoms of fatigue, headaches, anxiety, brain fog, breathlessness, and post-exertional malaise and symptom exacerbation. • Few interventions have sought to address both the physical and mental health impact of PCS in adults and the evidence remains limited for CYP. • This novel psychology/physiotherapy co-designed intervention is acceptable and feasible in an NHS clinic setting. • We identified that breathing pattern disorders are common and a predominant cause of breathlessness in teenagers with PCS.