There are currently no colorectal cancer (CRC) screening recommendations specifically outlined for people with HIV (PWH). Screening measures used for people without HIV (PWoH) have been previously discussed as sufficient for use among PWH, despite observations of higher CRC prevalence and CRC reportedly appearing at earlier ages among PWH in comparison to PWoH. Machine learning (ML) methods are regarded as robust approaches that may enhance predictive performance, particularly in the context of complex or high-dimensional data. This study aims to develop an ensemble ML model to predict CRC risk in PWH using comprehensive nationwide datasets. The model’s predictive performance will be evaluated and compared with a baseline Cox proportional regression model. The better-performing method will be implemented to develop a CRC risk prediction model with the aim of personalising screening recommendations for PWH.

The study population will include all PWH and PWoH born between 1940 and 2008, aged 18 or older and living in Sweden sometime between 1983 and 2024. The study population will be linked to six nationwide demographic and healthcare registers. Follow-up will continue until the first incident of CRC, emigration or death. The outcome of interest is CRC. PWH will be matched to negative controls 1:10. A Cox regression analysis will be completed first, and the results will be used as a baseline comparison to the ensemble ML results. A range of ML methods will be used to develop the ensemble model using stacking.

This study has ethical approval from the Regional Ethical Committee in Sweden (Dnr: 2024-04185-02, 2024-06783-02, 2023-00191-01, 2022-02897-02, 2022-05624-01, 2018/11-31/2). Given that the study is retrospective and register-based, using only pseudonymised data, there are minimal physical, psychological or privacy risks to included individuals. All results will be presented at the population level with no possibility of identification. The results of this study will be submitted for publication in a peer-reviewed journal.

Psychosocial interventions are essential to support people living with dementia and their carers. A consensus on what is most important for research on psychosocial intervention in dementia and how intervention studies should best be conducted is currently lacking. This protocol describes the research plan aimed at achieving consensus on (i) the relevance of core elements (CEs) for the development, feasibility testing/piloting, evaluation and/or implementation phases of psychosocial interventions in dementia and (ii) methodologies (eg, design) and methods most suitable to address CEs per phase.

This study was co-designed with a multi-stakeholder advisory group and a multi-disciplinary INTERDEM (psychosocial INTERventions in DEMentia) Methodology Taskforce steering committee. It will involve a multi-phase modified Delphi design, including surveys and group discussions with stakeholders, namely people living with dementia, (informal/unpaid/family) carers, health and social care professionals, policy makers, representatives from insurance companies and psychosocial researchers. A series of iterative ‘rounds’ will be conducted. In round 1 (Phase 1: ‘identification’), stakeholders will be asked to complete an online survey rating the importance of CEs from the UK Medical Research Council (MRC) Framework, namely (i) consider context; (ii) develop, refine and (retest) programme theory; (iii) engage stakeholders; (iv) identify key uncertainties; (v) refine interventions and (vi) economic considerations per phase; propose relevant additional CEs and list methodologies/methods that most suitably address CEs. These ratings will be further explored through online discussion rounds (Phase 2: ‘elaboration’). In round 2 (Phase 3: ‘consensus’), participants will be asked to rate the importance of CEs again (ie, new CEs and where no consensus was reached in Phase 1) and the usefulness of methodologies/methods to address CEs. Outcomes will be discussed with the advisory group and steering committee (Phase 4: ‘validation’). This process (Phases 3 and 4) will be repeated until a consensus on CEs and methodologies/methods is achieved.

Ethical approval was received at Maastricht University (FHML-REC/2025/078) and the University of West London (UWL/REC/SBS-01195). Participants will sign informed consent prior to study participation. Results will be disseminated through a peer-reviewed publication, seminars, webinars, conferences, postgraduate dementia programmes, blogs, commissioner briefings and social media.

Open Science Framework (https://doi.org/10.17605/OSF.IO/DQRFA).

To identify and appraise methods used to analyse patient flow across multiple care settings, and to describe how these methods have been applied to address health service research questions.

We searched MEDLINE, EMBASE, Web of Science databases and Google Scholar search engine between 1 January 2013 and 10 June 2026 using a systematic search strategy to identify the relevant literature for this review. Descriptive statistics and narrative synthesis were used to characterise the included papers.

Twenty-four studies met the inclusion criteria. Seven distinct methods and five health service research topics were identified. Most studies employed descriptive statistics and group comparison tests to provide a general description of the system. Discrete event simulation was more frequently used to simulate patient movement between settings. Furthermore, patient transfer volume and outcome, as well as capacity planning, were the most commonly studied health service research topics. This review highlights effective approaches—statistical analysis, mathematical modelling and computer simulation—for studying patient flow across care settings.

Statistical analysis, mathematical modelling and computer simulation offer complementary approaches for analysing patient flow between care settings. Each method has distinct strengths and limitations. Applying more than one method may provide a richer understanding of patient flow. Future research may focus on comprehensive patient flow analysis, particularly in managing chronic conditions and non-communicable diseases in interconnected care settings and organisations.

Dose can meaningfully affect the comparative effectiveness of depression treatments, yet how network meta-analyses (NMAs) in this field handle dose is not well characterised. We conducted a meta-research study to examine how current depression NMAs incorporate dosing information and identify methodological gaps in current practice.

Meta-research study following guidance for meta-epidemiological research and incorporating relevant elements of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020.

We searched PubMed, Embase, the Cochrane Library, PsycINFO, Web of Science and Scopus for NMAs published between January 2020 and May 2025.

NMAs comparing interventions, or different doses of a single intervention, in the context of depression—where an antidepressant was evaluated for depression-related indications and/or depressive symptoms were the primary clinical focus—and in which dose variation was incorporated into the evidence synthesis.

We extracted data on dose-handling strategies, analysis methods, statistical frameworks and reporting quality, and synthesised these narratively to characterise methodological practice across studies.

Twenty studies met inclusion criteria, evaluating pharmacologic interventions (n=11), non-pharmacologic interventions (n=7) or both (n=2). Dose handling varied substantially: in primary analyses, 50% treated dosages as separate nodes (split approach), 32% lumped doses together and only 15% used model-based methods incorporating dose-response relationships. Nine studies employed the R package MBNMAdose to conduct a model-based NMA for secondary analyses, primarily examining exercise interventions with varied dose-response functions. Reporting of priors, consistency assessments and justifications for dose categorisation or operationalisation was inconsistent.

Current depression NMAs demonstrate broad variability in handling dose-related heterogeneity, with dose-response modelling often absent or inconsistently applied—particularly for behavioural interventions lacking standardised dose metrics. Greater methodological clarity, practical guidance and reporting standards are needed to integrate dose-response modelling into NMAs of depression treatments, where both pharmacologic and behavioural interventions pose distinct dosing challenges.

Existing frameworks on Commercial Determinants of Health (CDoH) largely focus on macro-level corporate practices and policy environments. Individual-level exposure—mediated through targeted marketing, pricing strategies, product availability and placement—remains underexplored, particularly in low- and middle-income countries. The absence of standardised tools to capture these exposures limits the ability to quantify commercial influences on health and weakens evidence-informed public health responses. There is a critical need for a robust, contextually grounded instrument to measure individual-level exposure to CDoH. Developing and validating an individual-level CDoH measurement tool is therefore essential to strengthen research, surveillance and policy action aimed at mitigating health-harming commercial influences. The availability of this tool will allow policymakers and public health practitioners to identify high-risk populations and monitor the effectiveness of regulatory actions addressing harmful commercial practices.

This study will follow standard guidelines for tool (questionnaire) development. The process will include four sequential phases: item generation, refinement, validity testing and construct validation. A literature review with a systematic search strategy and in-depth interviews with purposively sampled adults will inform domain identification and item generation. An e-Delphi process involving experts in CDoH and public health will refine and confirm items followed by content validity. This will be followed by assessment of face validity for clarity and relevance. Construct validity will be assessed through exploratory and confirmatory factor analyses, using fit indices such as Minimum ²/df, Goodness of Fit Index, Tucker-Lewis Index, Comparative Fit Index, Root Mean Square Error of Approximation and Standardised Root Mean Square Residual. Reliability will be estimated using Cronbach’s alpha, and convergent and discriminant validity will be examined through correlation analyses.

Ethical approval has been obtained from the Institutional Ethics Committee, Amrita Institute of Medical Sciences, Kochi (ECASM-AIMS-2025-267). Results will be disseminated through peer-reviewed publications, conferences and policy briefs, and the validated tool will be made accessible for research and public health applications.

It is crucial that the outcomes used in clinical effectiveness studies are relevant to patients. This relevance can be assured by patients participating with other key stakeholders in core outcome set (COS) studies, yet recruiting patients to such studies can be challenging.

As no guidance currently exists to help COS developers create good COS invitations for patients, which are usually the first documents patients see when invited to participate in COS studies, the Good Research Invitation Study aimed to produce such guidance.

Consensus meeting to agree on guidance for COS developers designing research invitations.

Informed by findings from our previous qualitative study of patient and public opinions on COS study invitations, our team, which included a patient research partner, produced an initial set of candidate recommendations. An online consensus meeting was organised in the UK with 13 participants including patient research partners with and without COS study experience, COS developers, a representative from an ethics committee and experts in diversity, marketing and science communication. Through a process of discussion and voting, the initial set of recommendations was refined.

From the initial 35 recommendations, consensus meeting participants agreed a final set of 22 recommendations. Some initial recommendations were removed as they were beyond the scope, while others were merged. The finalised recommendations focused on producing and user testing invitations, reaching the audience, engaging potential COS participants and considering what they might find appealing or off-putting, explaining and creating interest in the study, keeping the invitation simple and understandable, considering the amount of information to include and how to present it, alongside ensuring accessibility. Discussion during the meeting highlighted the importance of improving the accessibility of all participant-facing resources in COS studies, not just the invitations.

Through consensus, a set of recommendations has been agreed on for use by COS developers to enhance study invitations for patients. Further testing and refinement of the recommendations will improve their utility.

The use of core outcome sets (COSs) in health research is widely recommended. COSs are developed with input from key decision makers, patients being a vital group to ensure COS relevance. However, recruitment to COS studies can be challenging.

The study aimed to explore what patients and the public think of COS study invitations, which are usually the first document a patient reads about a COS study.

Qualitative study involving focus groups and interviews. Analysis of transcribed data drew on reflexive thematic analysis.

Focus groups and interviews were conducted with a diverse range of patients and the public (n=31) from community and patient groups in North West England, exploring their perceptions of a sample of COS study invitations. Participants were eligible if aged over 18 years, they could speak English and had never previously participated in a COS study.

Themes identified included understanding, engagement, safety and accessibility. Participants were concerned about excessive information in the invitations which made them confused. Fear of cybercrime caused numerous concerns and participants were reluctant to click on links or attachments. Trust in the people sending the invitations was key. Participants wanted to see messages that COS studies had a meaningful purpose to feel their contributions were valuable. They were keen to contribute to improving future ‘treatment’ but less motivated to improve ‘research’. Messages that evoked a feeling of connection with others who they could relate to were positively regarded. Participants also highlighted ways that invitations could be made more accessible.

COS invitations can present numerous challenges for potential participants, but our study indicates ways that COS developers can address these challenges and make their invitations more appealing to potential participants. As part of the wider Good Research Invitation Study the findings have been used to inform guidance on designing a good COS invitation

To conduct a Delphi study to develop a consensus-based definition of complex case management within the UK context.

This study was conducted with members of the British Association of Brain Injury and Complex Case Management (BABICM).

A methodological approach informed by a modified Delphi design was employed, incorporating expert focus groups and two rounds of questionnaires distributed to members of the BABICM.

Initial focus groups (n=2) with eight expert case managers generated themes which were used to create a draft definition. Five definitions—four existing and one newly developed definition—were reviewed and refined through two rounds of online questionnaires. The top two definitions in round 1 were retained for round 2 (with no refinement required based on qualitative responses). The final definition was agreed-on when consensus was reached ≥80% agreement.

In round 1, 130 (10.8% of the 1200-member population) BABICM members ranked five definitions and provided qualitative feedback. Based on round 1 rankings, two definitions were retained for round 2. Definition 4, developed through expert focus groups, was ranked as the most preferred in round 1 (60%) and round 2 (85%), thus meeting the consensus threshold. The final definition emphasised collaborative, tailored support across systems, advocacy and person-centred care for clients and their families.

This study provides a consensus-based definition of complex case management in the UK, reflecting the complexity and interdisciplinary nature of the role. The definition offers a foundation for standardising practice, informing training and guiding future research and policy development.

To compare the diagnostic accuracy of four available automated electronic medical record (EMR) retrieval methods, including a large language model (LLM)-assisted workflow, against manual chart adjudication for identifying cardiovascular events.

Retrospective diagnostic accuracy study.

Three sites within a single US tertiary health system.

Two adult cohorts with previously adjudicated cardiovascular outcomes were included. Cohort 1 included 2258 patients treated with immune checkpoint inhibitors, and Cohort 2 included 1426 patients who underwent transcatheter aortic valve replacement.

The reference standard was clinician manual chart adjudication. Outcomes included ischaemic stroke or transient ischaemic attack, myocardial infarction (MI), heart failure (HF) exacerbation or hospitalisation and a composite major adverse cardiovascular events (MACE) outcome. Automated retrieval methods included International Classification of Diseases (ICD) codes, primary diagnosis, problem list and a zero-shot LLM workflow. Area under the (receiver operating characteristic) curve (AUC), sensitivity, specificity and net reclassification improvement were assessed.

In Cohort 1, the LLM achieved the highest AUC for stroke (0.920; 95% CI 0.881 to 0.958), MI (0.938; 95% CI 0.905 to 0.971) and composite MACE (0.880; 95% CI 0.854 to 0.907), whereas ICD-based retrieval had a higher AUC for HF (0.882; 95% CI 0.845 to 0.918 vs 0.873; 95% CI 0.831 to 0.914). In Cohort 2, the LLM achieved the highest AUC for all evaluated outcomes: stroke (0.915; 95% CI 0.862 to 0.968), MI (0.928; 95% CI 0.839 to 1.000), HF (0.844; 95% CI 0.803 to 0.884) and composite MACE (0.862; 95% CI 0.829 to 0.895). In Cohort 1, differences in AUC between the LLM and ICD methods were not statistically significant across outcomes, whereas in Cohort 2 the LLM showed significantly higher AUC for stroke and composite MACE.

In this multisite retrospective validation study, the LLM-assisted workflow showed strong but context-dependent performance for identifying cardiovascular events from the EMR. Performance varied by outcome and cohort, and ICD-based retrieval remained competitive for some use cases. These findings support a complementary role for LLM-assisted extraction in retrospective cardiovascular outcomes research.

Healthcare contributes substantially to global greenhouse gas emissions; however, the environmental impact of clinical research activities remains poorly understood. Quantifying emissions is a necessary first step toward reducing the carbon footprint of research.

To map and synthesise literature measuring carbon emissions associated with clinical research activities, with a focus on research domains assessed, tools and methods used and units of measurement reported.

A scoping review was conducted following the Arksey and O’Malley methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guidance. PubMed, Web of Science, CINAHL, Scopus, EconBiz, GreenFile and ProQuest were searched from database inception to June 2026. Eligible studies reported measurement of carbon emissions related to clinical research activities. Data were charted and synthesised narratively.

Twenty-five studies met the inclusion criteria, most published between 2019 and 2025 and primarily from Europe and the UK. Studies used a wide range of tools and resources, including life cycle assessment databases, online calculators, international standards, government emission factor datasets and healthcare-specific sustainability frameworks. A clear trade-off emerged between methodological rigour and accessibility: comprehensive life cycle assessment tools required expertise and licensing, while simpler calculators enabled rapid but less precise estimates. Carbon dioxide equivalent and global warming potential over a 100-year time horizon were the dominant reporting metrics, although variation in functional units limited comparability across studies.

The methodological landscape for measuring emissions in clinical research is fragmented and lacks standardisation. Development of consensus guidance and reporting standards is needed to support consistent measurement and reduction of research-related emissions.

Oral capsules for gastric submucosal delivery represent a fundamentally new route of administration for biologics, which are currently limited to injection. Involving patients and members of the public to understand their perspectives on this novel pharmaceutical form, distinct from both injections and traditional oral tablets, is essential for the clinical development, regulatory approval, adoption and acceptability. This study aims to identify perceived benefits, concerns and communication preferences regarding oral capsules for gastric submucosal delivery, using BIONDD as a case study, to initially document the elements of the perceived value proposition and potential reservations about the oral delivery system from the patient and public perspectives.

This two-country exploratory sequential mixed-methods study will be conducted in Denmark and the USA. First, focus group interviews with purposively sampled patients and members of the public will explore attitudes towards oral capsules for gastric submucosal delivery. Qualitative data will be analysed using thematic analysis, combining manual and artificial intelligence-assisted coding. Insights from the focus groups will inform the development of a structured questionnaire, which will subsequently be distributed to a broader sample in both countries. Survey data will be analysed descriptively, and where possible, exploratory comparisons between country samples will be made. Main outcomes will include perceived benefits, concerns, acceptability and preferred terminology for discussing this novel pharmaceutical form.

The study has been approved by the relevant ethics committees at the University of Copenhagen and Nova Southeastern University. All data will be managed confidentially in line with General Data Protection Regulation and local regulations. Informed consent will be obtained in accordance with site-specific ethical procedures, and withdrawal will be possible up to a defined stage of data processing, after which data cannot be linked to individual participants. Results will be disseminated in peer-reviewed journals, at conferences and on institutional websites, in accordance with established ethical research and authorship guidelines.

Upper-limb (UL) impairment following stroke significantly limits independence in activities of daily living (ADLs). Although tabletop functional task-oriented training (FTOT) is a cornerstone of neurorehabilitation, both conventional therapist-led and technology-supported FTOT face limitations in consistency, supervision, progression and continuity across settings. The objectives are to characterise current clinical practices in UL tabletop FTOT and identify stroke survivor–caregiver dyads’ needs, constraints and support requirements across clinical and home contexts to inform user-centred technology development.

A multi-phase mixed-methods design will be employed. Phase-A will be an explanatory sequential design including a quantitative online survey of rehabilitation therapists (target minimum n=100) to characterise UL tabletop training delivery (eg, task selection, dose, progression). Survey findings will inform subsequent data collection through virtual qualitative interviews with a purposive subsample of therapists (anticipated n10–20) to examine task orchestration, adaptation and clinical decision-making in depth. Phase-B will use a descriptive qualitative design involving semi-structured interviews of stroke survivor–caregiver dyads (target n=15 dyads) to explore FTOT experiences across clinical and non-clinical contexts. Quantitative data will be analysed descriptively, and qualitative data will be analysed using inductive content analysis. Mixed-methods integration, within Phase-A and between the two phases, will examine convergence, complementarity, expansion and divergence. Integration will be illustrated using joint displays, visual tools that present the findings from both strands side-by-side using a table or figure. Patient and public involvement activities (n=5) and a pilot dyadic interview (two dyads) were completed to refine study materials and procedures.

Ethical approval was obtained from the Institutional Review Board of Christian Medical College, Vellore (IRB Min No. 2511113). Electronic informed consent will be obtained from therapists for the survey and qualitative interviews. Written informed consent will be obtained from the dyadic participants before the interviews. All study procedures will adhere to ethical principles for human research. Study findings will be disseminated through conference presentations and publication in peer-reviewed journals, with stakeholder-oriented dissemination to support clinical and technology development.