The objective of this study was to understand primary care clinician perspectives on a novel linked health data system to facilitate diabetes prevention for individuals with a history of gestational diabetes mellitus (GDM). We used the conceptual example of linking the National Gestational Diabetes Register with primary care electronic health records to understand clinicians’ views on potential implementation.

A qualitative study of semistructured interviews with primary care clinicians.

Australian primary care.

Primary care clinicians (n=14). Inclusion criteria were: general practitioners (GPs), practice nurses and/or diabetes educators working in primary care in Australia, and seeing individuals with a history of GDM; aged 18 years and over; and willing to voluntarily contribute to the project. There were no exclusion criteria.

Clinicians’ views on acceptability, feasibility and utility were characterised by realistic optimism for a linked data system to improve GP workflow and patient outcomes. Clinicians noted existing pressures on primary care and patient concerns regarding confidentiality and privacy, and that these factors should be considered in the development process. Clinicians envisaged three functions for their clinical management systems: (1) automatically updating a patient’s past history; (2) generating actionable alerts and (3) generating recall lists.

Primary care clinicians were unanimously supportive of a linked health data system to facilitate diabetes prevention. Consistent with previous studies, we identified the key clinician-related enabler as the integration into existing GP workflows to facilitate pro-active clinical care. Point-of-care tools and preventative care consultations could increase the uptake of screening and provide opportunities for patient education post partum.

In combination with effective prevention programmes, and health policy and system supports, linked health data systems could be part of the equation for type 2 diabetes prevention for individuals with a history of GDM. Larger acceptability, feasibility, co-design and implementation studies are recommended.

To systematically review the evidence on the association between non-standard working time arrangements (such as night work or shift work) and the occurrence of safety incidents.

Systematic review conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and using a structured narrative approach and the Synthesis Without Meta-analysis framework to evaluate and summarise findings.

MEDLINE, Embase, PsycINFO, Web of Science and ProQuest Health and Safety Science Abstracts were searched through February 2024.

We included peer-reviewed English-language studies of paid workers (18–70 years) that examined the association between non-standard working time arrangements and safety incidents (accidents, near-accidents, safety incidents or injuries), excluding cross-sectional designs and studies on unpaid workers, athletes or military personnel.

Two reviewers independently extracted data and assessed risk of bias using standardised forms, extracting study characteristics (author, year, country, sector and population), working time arrangements and exposure assessment, outcomes and their assessment, and reported risk estimates. We conducted a narrative synthesis, classifying studies into three exposure contrasts (shift worker versus non-shift worker, time-of-day and shift intensity), and summarised risk estimates using forest plots without calculating pooled effects.

A total of 13 569 records were screened, and 24 studies met the inclusion criteria. The results indicated that shift workers generally had an elevated safety incident risk compared with non-shift workers (risk estimates ranged from 1.11 to 5.33). Most of the included studies found an increased risk of safety incidents during or after night shifts. Accumulated exposure to evening or night shifts increased the risk of safety incidents during the following 7 days. However, bias and heterogeneity across studies in design, populations and outcome measures resulted in an overall low to very low certainty of the evidence.

Non-standard working time arrangements, including night and evening shifts, appear to increase the risk of occupational safety incidents. Despite the low certainty of evidence, the findings highlight a potential area for preventive measures in work scheduling. Future longitudinal studies using individual data on daily working hours are needed.

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.

Chronic inflammatory skin diseases, despite low mortality, significantly impair quality of life (QoL). Up to 80% of patients with dermatological conditions experience severe itch and poor sleep, as well as related mental health challenges such as anxiety and depression. The relationship between skin diseases and mental health highlights the challenges that doctors face in treating these conditions. Existing psychotherapeutics, such as mindfulness training, cognitive behavioural therapy and acceptance and commitment therapy, are widely used and effective in the treatment of mental health illnesses. However, there is limited evidence on the application of such interventions in dermatology, and most mental health apps lack robust clinical evaluation. We report the design of a randomised controlled trial to evaluate the efficacy and implementation of a mobile app containing dermatology-specified psychotherapeutic strategies in reducing QoL burden.

English-speaking patients aged 16 years and older with psoriasis, eczema or chronic urticaria will be recruited and randomised into the intervention arm (psychotherapeutic application) or active control group (Healthy365 app, a general wellness application managed by the Singapore Health Promotion Board). This allows a comparative assessment of app-usage-specific outcomes while preserving the blinding of all participants. The primary outcome is the change in the Dermatology Life Quality Index (DLQI) score from baseline to week 8. Secondary outcomes include physician-assessed disease severity at weeks 8 and 16 relative to baseline, differences in other patient-reported measures at weeks 8, 16 and 32, self-reported treatment adherence and initiation/escalation of systemic medications. To understand how patients engage with the app, we will evaluate the implementation process, focusing on key measures such as engagement, satisfaction and willingness to pay. Statistical analysis will be carried out on an intention-to-treat basis, and missing data will be analysed using last observation carried forward.

All participants will receive both verbal and written study information that aligns with Good Clinical Practice guidelines. Ethical approval has been obtained from the National Healthcare Group’s Domain Specific Review Board (reference number: 2022/00751). Results will be disseminated via publication in a relevant journal. Data will be available from the corresponding author on reasonable request.

NCT06702293.

Emerging adulthood is a new life stage characterised by identity exploration, instability, self-focus, a feeling of ‘being in-between’ and the perception of a range of possibilities. Emerging adults may experience difficulties in their well-being during this complex stage. Adaptive emotion regulation can improve levels of well-being. Previous studies have shown that new technologies can enhance social-emotional competencies in this population. The purpose of the study is to design and implement a serious game, emoWELL, which improves knowledge and the use of adaptive skills of emotion regulation to improve well-being during emerging adulthood.

The participants will be 385 emerging adults aged 18–29 years. They will be randomly assigned to either the control or experimental group. The experimental group will complete the emoWELL serious game. The game takes place on a train ride with several stops where the player will learn about emotion regulation. To assess the effectiveness of emoWELL, psychological assessment instruments validated in the Spanish population will be used. The primary expected outcomes include characteristics of emerging adulthood, emotion regulation (emotion dysregulation, emotion regulation strategies and cognitive reappraisal and expressive suppression) and psychological well-being. The secondary expected outcomes are self-esteem, psychological distress, loneliness and optimism. The assessment will occur at two different time points: pretest (T1) and post-test (T2) to observe improvements in the variables of interest.

The study has been approved by the Ethics Committee of the Universitat de València (2013883) and will follow the standards of the Declaration of Helsinki for data collection. The findings will be shared with the scientific community. The intellectual property registration number is as follows: UV-SW-202460R.

NCT06049407.

There is a need for early, non-invasive and inexpensive biomarkers for Alzheimer’s disease (AD), which could serve as a proxy measure in prevention and intervention trials that might eventually be suitable for mass screening. People with Down syndrome (DS) are the largest patient group whose condition is associated with a genetically determined increased risk of AD. The REVEAL study aims to examine changes in the structure and function of the eye in individuals with DS compared with those with mild cognitive impairment (MCI) and cognitively healthy control (HC) individuals. REVEAL will also explore whether these changes are connected to inflammatory markers previously associated with AD.

The protocol describes a cross-sectional, non-interventional, single-centre study recruiting three cohorts, including (1) participants with DS (target n=50; age range, 6–60 years), (2) participants with MCI (target n=50; age range, 50–80 years) and (3) HC participants (target n=50; age range, 50–80 years). The primary research objective is to profile retinal, choroidal and lenticular status using a variety of eye imaging modalities and retinal functional testing to determine potential associations with cognitive status. The REVEAL study will also measure and compare established blood markers for AD and proteomic and transcriptomic marker profiles between DS, MCI and HC groups. Between-group differences will be assessed with an independent sample t-test and ² tests for normally distributed or binary measures, respectively. Multivariate regression analysis will be used to analyse parameters across all three cohorts. Data collection began in October 2023 and is expected to end in October 2025.

The study gained a favourable opinion from Health and Social Care Research Ethics Committee A (REC reference 22/NI/0158; approved on 2 December 2022; Amendment 22/0064 Amend 1, 5 April 2023; Amendment 22/0064 Amend 2; 23 May 2024; Amendment 22/0064 Amend 3; 25 June 2024; Amendment 22/0064 Amend 4; 16 January 2025; Amendment 22.0064 Amend 5; 9 May 2025; Amendment 22.0064 Amend 6; 9 June 2025). The study has also been reviewed and approved by the School of Biomedical Sciences Research Ethics Filter Committee within Ulster University. Findings from the REVEAL study will be presented to academic audiences at international conferences and peer-reviewed publications in targeted high-impact journals after data collection and analysis are complete. Dissemination activities will also include presentations at public events.

This study aimed to investigate the opportunities and challenges associated with integrating artificial intelligence (AI) in healthcare by exploring the perspectives of various stakeholders. The objective was to provide a nuanced understanding of stakeholder views to address concerns and promote the acceptance and successful integration of AI technologies in medical practice.

This exploratory qualitative study used semi-structured interviews. Data were analysed using a combination of deductive and inductive coding, followed by content analysis to identify and develop categories.

This study was conducted in Tübingen, Germany, within the framework of the TüKITZMed project (Tübingen AI Training Center for Medicine), between August 2022 and March 2023.

A total of 38 stakeholders participated, including 6 lecturers, 9 clinicians, 10 healthcare students, 6 AI experts and 7 institutional stakeholders. Inclusion criteria included professionals involved in or affected by AI in healthcare, while exclusion criteria comprised individuals without relevant experience.

Not applicable.

The main outcome was the identification of thematic categories capturing stakeholders’ perceptions, expectations and concerns regarding the integration of AI in healthcare.

The analysis identified two main thematic categories: two main categories encompassing a total of 14 subcategories: (1) perceived opportunities of AI in medicine, including aspects of increased efficiency, reduced workload and improved patient safety and (2) perceived challenges of AI in medicine, such as its impact on medical decision-making and concerns about dependence on technology. These themes reflect diverse perspectives and insights across stakeholder groups.

Diverse stakeholder perspectives offer valuable insights into the anticipated effects of AI in healthcare. Understanding these perspectives can support decision-makers in designing context-sensitive AI strategies and identifying areas for further professional and institutional development. Future research should monitor how these attitudes evolve in response to technological progress and real-world implementation.