Atherosclerotic cardiovascular disease (ASCVD) continues to be a leading cause of preventable death globally. Polygenic risk scores (PRS) offer a way to detect individuals at higher relative risk of developing ASCVD, but they have not yet been incorporated into routine clinical practice. Pragmatic trials offer a way to evaluate the integration of PRS into cardiovascular disease prevention in primary care, allowing for a more accurate assessment of their effectiveness in everyday clinical practice.

This trial evaluates the effectiveness of preventive statin treatment on reducing the incidence of cardiovascular events and death over 5 years in women (aged 55–80) and men (aged 45–80) with a high coronary artery disease PRS. This is a pragmatic, multicentre, open-label, parallel group, randomised clinical trial with a 1:1 allocation ratio to intervention (n=1350), receiving preventive rosuvastatin 20 mg treatment or control (n=1350), receiving current standard of care. Following the intention-to-treat principle, all randomised participants are analysed according to their allocated group, with the primary outcome defined as time to first major adverse cardiovascular event, comprising ischaemic heart disease, stroke or transient ischaemia, peripheral vascular occlusion and stenosis, revascularisation or cardiovascular death.

This trial has received ethical approval from the Estonian Committee on Bioethics and Human Research (13.06.2024 nr 1.1-12/1531) and the Estonian Ethics Committee for Medicinal Products (19.12.2024 nr RKU-4/92).

NCT06820086.

This study aimed to co-design a tailored model of care for older people with long COVID.

Using a human-centred design approach, semistructured interviews were conducted with patients and health professionals from a long COVID service to explore their experiences. Insights were further developed during a co-design workshop involving patients, health professionals and community members who identified as older people and who had experience with chronic illness. Key themes were identified and used to map an ideal patient journey and inform the final model of care.

Long COVID outpatient service in a tertiary hospital in Adelaide, South Australia.

Four patients and four health professionals participated in the interviews. The workshop included four patients, five health professionals and seven community members.

The co-design process identified challenges experienced by people with long COVID, including lack of validation, delayed multidisciplinary care, mental health deterioration and difficulties navigating the healthcare system. These challenges were described as having particular relevance for older adults. In response, a model of care was developed focused on comprehensive assessment, coordinated multidisciplinary care, education for self-management, mental health support and opportunities for research participation.

A comprehensive and adaptable model of care is needed to address the complex and multifaceted nature of long COVID. This human-centred design approach ensured the model was grounded in lived experience, clinically informed and aligned with patient priorities. While not unique to older adults, the findings highlight areas that may require particular attention in this population, including care coordination, validation and support for comorbidities and social vulnerabilities. While developed in a single tertiary service, these principles may inform the design of services for similar populations in other healthcare settings.

People with chronic pain are a high health service using population, representing a significant proportion of primary care visits, but their health service use and needs have been largely understudied. This mixed-methods study investigates experiences of accessing primary care services for people with chronic pain in British Columbia (BC), Canada.

This research programme includes a retrospective cohort study using administrative data, semistructured interviews with people with chronic pain, and triangulation of data. The aim is to support a more robust understanding of how people with chronic pain access primary care services and how this impacts other health services use. These studies emphasise the importance of lived/living experience of chronic pain through the inclusion of individuals with lived experience on the research team and study council, qualitative interviews with people with chronic pain and application of a critical disability theory lens.

We have obtained ethics approvals from the Simon Fraser University research ethics board. Population Data BC has granted access to de-identified administrative data. Study findings will be disseminated through academic outputs and through knowledge mobilisation with relevant community partners.

Risk reduction training for UK care home staff is limited, not standardised and challenging to implement. Virtual reality (VR) is an immersive, engaging method of education delivery that is being adopted in health and social care. VR may be an effective education tool in care homes, but this research has yet to be conducted.

The VR-CARE project aims to create a new VR risk reduction training programme for care homes that combines hand hygiene and falls prevention modules, and to evaluate this through a pilot trial to inform a future randomised controlled trial (RCT).

There are two research phases with patient and public involvement and engagement (PPIE) activities embedded throughout. Care home stakeholders are collaborating to design the training and toolkit, oversee methods, review resources for accessibility, support recruitment and ensure the project meets the needs of the workforce and positively impacts resident care.

In phase 1, we will use a mixed-methods and user-centred design approach to develop the VR training and an accompanying implementation toolkit needed to deliver it. The training will be developed and tested by 15 care home staff across three rounds to identify and inform changes that maximise usability and acceptability. We will conduct up to 20 interviews with staff from VR companies and care homes to support toolkit development.

Phase 2 is a mixed-methods pilot cluster RCT, with a waitlist control and process evaluation with up to 80 unregistered staff members from six North England care homes, to develop the measures and methods to inform a future trial. The process evaluation will generate knowledge about VR as a training mechanism in care homes. This phase will focus on the practicality of using VR, broader impacts (eg, on residents), contextual considerations and how it might be scaled up.

The University of Manchester Proportionate University Research Ethics Committee has approved phase 1 (Reference: 2025-24416-44642). We will obtain further approval before commencing phase 2.

Outputs will include user-friendly and acceptable VR risk reduction training for care homes, accompanied by an implementation toolkit adaptable for other VR training in social care settings. Materials (eg, training overviews, infographics and videos) will be developed to support uptake. Findings will be presented at conferences and published in journals. Lay summaries will be co-created with our PPIE group, and additional dissemination methods will be co-developed to broaden reach.

Persistent postsurgical pain (PPSP) affects up to 15% of patients after major surgery, impairing physical function, quality of life and increasing risk for long-term opioid use. Current PPSP prediction models rely on static or retrospective data and fail to incorporate dynamic perioperative factors. The Personalised Prediction of Persistent Postsurgical Pain (P5) study aims to develop individualised, multimodal prediction models by integrating preoperative behavioural, psychophysical and neurocognitive assessments and high-frequency symptom monitoring.

P5 is a prospective, single-centre cohort study enrolling 2500 adults aged 18–75 undergoing major surgery at a tertiary academic hospital. Participants complete baseline surveys, cognitive testing and quantitative sensory testing preoperatively. Ecological momentary assessments (EMAs) are collected via smartphone three times per day through 30 days postoperatively, capturing pain, mood, catastrophising and medication use. Participants are assessed on postoperative day 1 and complete online surveys at 3 and 6 months, evaluating pain persistence, interference, neuropathic symptoms and related outcomes. Clinical and perioperative data are extracted from the electronic health record. The primary outcome is PPSP at 3 months. Predictive models will be developed using supervised machine learning and dynamic structural equation modelling to extract latent features from EMA data. Model performance will be assessed using area under the receiver operating characteristic curve, area under the precision-recall curve and SHapley Additive exPlanations for interpretability.

This study has received ethics approval from the Washington University School of Medicine Institutional Review Board #202101123. Informed consent is required. Results will be submitted for publication in peer-reviewed journals and presented at research conferences.

NCT04864275.

There is interest in using predictive models to address non-attendance of healthcare appointments without prior notification. Although several National Health Service (NHS) hospital trusts have piloted predictive models for non-attendance, there is a lack of published evidence in clinical settings.

This mixed-methods evaluation of the pilot of a predictive model intervention in outpatient services aimed to examine (1) the effect of the intervention on patient non-attendance and (2) staff engagement in the delivery of the intervention.

A mixed-methods study across two pilot phases. Quantitative data explored the use and impact of the predictive model on non-attendance. Z-tests were conducted to assess changes to non-attendance rates prepilot and in the two phases. Qualitative ethnographic work included 30 periods of observation and interviews with staff.

Nine outpatient services in an NHS Foundation Trust that volunteered to pilot the predictive model intervention. Qualitative participants were NHS clerical and administrative staff delivering the intervention and service managers.

An off-the-shelf predictive model, consisting of a cloud-based, random forest algorithm, produced a risk score of non-attendance by drawing on information from patients’ electronic health records. Staff in the pilot sites attempted to phone patients with a risk score to remind them of upcoming appointments.

Quantitative analysis showed that in phase 1, there were low volumes of intervention calls made across services, but three of nine outpatient services significantly reduced their non-attendance rate. There was a lower overall call rate in phase 2 among the four remaining participating services. One significantly reduced its non-attendance rate from 20.4% to 19.1% (p

The predictive model intervention was positioned as a simple solution to address a complex problem; however, there were challenges inherent in deployment within a dynamic healthcare setting. The sustainability of the intervention and its impact on patient experience warrants further exploration.

Addressing physical inactivity is a promising dementia risk reduction strategy due to its direct benefits for brain health, and indirect benefits for other modifiable dementia risk factors. A potential limitation of previous interventions is that they often overlook how increasing physical activity affects other behaviours throughout the 24-hour day, such as sleep and sedentary behaviour, which are also important for brain health. Further, interventions are rarely tailored to the individual, considering their needs, preferences and constraints that may serve as barriers or facilitators to behaviour change. The current phase I randomised controlled trial, Small Steps, aims to investigate feasibility, acceptability and preliminary effectiveness of a personalised 24-hour time-use intervention to improve lifestyle and cognitive health in older adults.

Participants aged ≥65 years from Adelaide, South Australia will be recruited and randomised to either the Extended or Condensed programme. During the first 12 weeks, participants in the Extended programme will use a tailored website to set personalised weekly goals to move towards their ‘optimal’ 24-hour day for brain health, facilitated by weekly website ‘check-ins’ and weekly phone calls with a research staff member. Participants randomised to the Condensed programme will have access to the website educational resources only but will not undergo personalised goal setting or telephone calls. Following the introductory phase (first 12 weeks), phone calls will be gradually withdrawn for the Extended programme. Primary (feasibility and acceptability) and secondary outcomes (changes in time use, cognitive function and behaviour change metrics) will be assessed 12, 24 and 36 weeks after the beginning of the intervention.

Ethics approval has been obtained from the University of South Australia’s Human Research Ethics Committee (205989). Study findings will be disseminated through peer-reviewed journal articles, conference presentations, media releases and community engagement.

NCT06291909).

Advancements in technology for treating diabetes mellitus (DM) are progressing rapidly. With the growing availability and use of continuous glucose monitoring (CGM) systems and continuous subcutaneous insulin infusion (CSII), glucose regulation is improved in individuals with DM, which will lead to less long-term complications and reduce the overall disease burden on patients with DM. Collecting vast amount of biomedical data, these devices combined with clinical outcome data provide more insight into the development and treatment of the disease. The objective of the DIABASE initiative is to collect and examine real-world data from medical devices and clinical practice in a registry.

The ongoing study is structured as an observational study registry. Clinical data and real-world data from diabetes wearable devices, such as CGM and CSII, are aggregated in the database. Clinical data is automatically extracted from the hospital’s electronic health record. Data from wearables is periodically collected manually from the various online data platforms for sharing and automatically added to the database.

This study is exempted from ethics approval by the Medical Research Ethics Committees United (MEC-U) since participants are not subject to procedures and are not required to follow rules of behaviour (approval ID: AW23.009/W20.197). The execution of this study has been approved by the board of the study site Hospital Group Twente (ZGT) (ZGT20-40). Results will be shared through scientific meetings and publications and through articles for the general public.

NCT05584293; Pre-results.

The COVID-19 pandemic led to major disruptions in society across many spheres, including healthcare, the economy and social behaviours. While early predictions warned of an increased risk of suicide during and after the COVID-19 pandemic, rates of suicide deaths remained stable or decreased over that period for most countries. In contrast, the prevalence of suicidal ideation doubled and suicide attempts slightly increased during the COVID-19 pandemic in the adult general population worldwide, accompanied by a higher prevalence of major depressive disorder and anxiety disorders. While these data can tell us what happened, they cannot tell us why. Qualitative suicide research seeks to understand experiences of individuals with suicide-related thoughts and behaviours, provides an in-depth exploration of their lives and interactions with others and centres their views and unique context. There is little qualitative research focusing on suicidality during the pandemic. This study will use a qualitative approach to explore the extent and impact of the COVID-19 pandemic on Canadians who experienced suicidality and review their experiences of accessing mental healthcare to identify key components in supporting safety and recovery.

This study will involve approximately 100 semistructured interviews with participants across four Canadian provinces and will explore experiences with suicide-related thoughts and behaviours during the COVID-19 pandemic. Transcripts will be analysed through qualitative analysis informed by constructivist grounded theory.

The study was approved by the Research Ethics Board of the Centre for Addiction and Mental Health, Toronto Academic Health Sciences Network (for JZ: CAMH REB No 104-2022). In addition to traditional peer-reviewed presentations and publications, a report will make study findings accessible to policy makers, media and the public.