Evidence map›Paper›PMID 35231093›Full record

ArticleAge and ageing2022

Factors associated with accessing long-term adult social care in people aged 75 and over: a retrospective cohort study.

Mable Nakubulwa, Cornelia Junghans, Vesselin Novov, Clare Lyons-Amos, Derryn Lovett, Azeem Majeed, Paul Aylin, Thomas Woodcock

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Age and ageing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Mable NakubulwaNIHR Applied Research Collaboration Northwest London, Imperial College London, London, UK.
Cornelia JunghansDepartment of Primary Care and Public Health, School of Public Health, Imperial College London, London W6 8RP, UK.
Vesselin NovovNIHR Applied Research Collaboration Northwest London, Imperial College London, London, UK.
Clare Lyons-AmosDepartment of Adult Social Care and Public Health, Westminster City Council, London SW1E 6QP, UK.
Derryn LovettNIHR Applied Research Collaboration Northwest London, Imperial College London, London, UK.
Azeem MajeedNIHR Applied Research Collaboration Northwest London, Imperial College London, London, UK.
Paul AylinNIHR Applied Research Collaboration Northwest London, Imperial College London, London, UK.
Thomas WoodcockNIHR Applied Research Collaboration Northwest London, Imperial College London, London, UK.
NIHR Imperial Biomedical Research Centre · GBImperial College London · GBWestminster City Council · GB

Funding

Department of Health NIHR200180
6 · The paper itself

Abstract

backgroundAn ageing population and limited resources have put strain on state provision of adult social care (ASC) in England. With social care needs predicted to double over the next 20 years, there is a need for new approaches to inform service planning and development, including through predictive models of demand.

objectiveDescribe risk factors for long-term ASC in two inner London boroughs and develop a risk prediction model for long-term ASC.

methodsPseudonymised person-level data from an integrated care dataset were analysed. We used multivariable logistic regression to model associations of demographic factors, and baseline aspects of health status and health service use, with accessing long-term ASC over 12 months.

resultsThe cohort comprised 13,394 residents, aged ≥75 years with no prior history of ASC at baseline. Of these, 1.7% became ASC clients over 12 months. Residents were more likely to access ASC if they were older or living in areas with high socioeconomic deprivation. Those with preexisting mental health or neurological conditions, or more intense prior health service use during the baseline period, were also more likely to access ASC. A prognostic model derived from risk factors had limited predictive power.

conclusionsOur findings reinforce evidence on known risk factors for residents aged 75 or over, yet even with linked routinely collected health and social care data, it was not possible to make accurate predictions of long-term ASC use for individuals. We propose that a paradigm shift towards more relational, personalised approaches, is needed.

Indexed as

Long-Term CareMental HealthCohort StudiesHumansRetrospective StudiesSocial Supportadult social carefrailtyOlder adultsrisk prediction modellingroutinely collected data

Identifiers

PMID35231093
PMCPMC8887841
OpenAlexW4213182263

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.