Evidence map›Paper›PMID 42626557›Full record

ArticleInternational journal of population data science2026

Understanding Inequalities in Adult Social Care in Wales: Protocol for the CARE Lab Linked Administrative Data Study.

Fiona Victoria Lugg-Widger, Ashley Akbari, Rebecca Cannings-John, Oliver S Cumming, Matthew Curds, Miranda Evans, José-Luis Fernandez, Henrietta Graham, Mala Mann, Melissa Meindl and 7 more

Abstract read
In one paragraph

Article in International journal of population data science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Fiona Victoria Lugg-WidgerCentre for Trials Research, Cardiff University, Wales.
Ashley AkbariPopulation Data Science, Faculty of Medicine, Health & Life Science, Swansea University, Wales.
Rebecca Cannings-JohnCentre for Trials Research, Cardiff University, Wales.
Oliver S CummingCentre for Trials Research, Cardiff University, Wales.
Matthew CurdsKnowledge and Analytical Services, Welsh Government, Wales.
Miranda EvansDisability Wales, Maindy Road, Cardiff, Wales.
José-Luis FernandezCare Policy and Evaluation Centre, London School of Economics and Political Science, London, UK.
Henrietta GrahamSpecialist Unit for Review Evidence, Cardiff University, Wales.
Mala MannDivision of Population Medicine, School of Medicine, Cardiff University, Wales.
Melissa MeindlDivision of Population Medicine, School of Medicine, Cardiff University, Wales.
Abigail PalmerCentre for Adult Social Care Research (CARE), School of Social Sciences, Cardiff University, Wales.
Lisa TriggSocial Care Wales, Wood Street, Cardiff, Wales.
Nell WarnerChildren's Social Care Research and Development Centre (CASCADE), School of Social Sciences, Cardiff University, Wales.
Paul WillisCentre for Adult Social Care Research (CARE), School of Social Sciences, Cardiff University, Wales.
Julie WychCentre for Trials Research, Cardiff University, Wales.
Simone WillisSpecialist Unit for Review Evidence, Cardiff University, Wales.
Jonathan ScourfieldCentre for Adult Social Care Research (CARE), School of Social Sciences, Cardiff University, Wales.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Adult social care in the UK faces increasing demand and persistent inequalities in terms of access and care quality, yet national-level understanding remains limited. The CARE Lab study aims to address these gaps using newly available individual-level routine administrative data for the whole of Wales from the Adults Receiving Care and Support (ARCS) census. This study will explore patterns of care provision, transitions from children's to adult services, and socio-demographic disparities, using linked data to inform service planning and policy. Methods: and analysis This quantitatively-led mixed-methods study comprises five research questions. Quantitative analysis will use ARCS census data, both standalone and linked to health, education, and social care datasets within the Secure Anonymised Information Linkage (SAIL) Databank. Qualitative interviews with people receiving care and support, carers, and professionals will contextualise findings. Key research questions address care patterns, demographic comparisons, regional variation, transitions from child to adult care, and the feasibility of evaluating care models using linked data. Statistical analyses will include descriptive and inferential statistics, propensity score matching, and there will be thematic analysis of qualitative data. Ethics: Ethical approval has been obtained from Cardiff University. Data access approvals will be sought from Welsh Government, SAIL, and the Office for National Statistics. Dissemination will occur through peer-reviewed publications, policy briefings, accessible multimedia outputs, and stakeholder engagement via an action group. The study will also produce a research-ready data asset and recommendations for future data infrastructure development across the UK.

Indexed as

Healthcare DisparitiesSocial WorkAdultHumansSecondary Data AnalysisSocioeconomic Disparities in HealthSocioeconomic FactorsWalesadult social careinequalitieslinked datanational levelTRE (Trusted Research Environment)wales

Identifiers

PMID42626557
PMCPMC13492271

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.