Evidence map›Paper›PMID 29454316›Full record

ArticleBMC geriatrics2018

The theoretical and empirical basis of a BioPsychoSocial (BPS) risk screener for detection of older people's health related needs, planning of community programs, and targeted care interventions.

Zoe J-L Hildon, Chuen Seng Tan, Farah Shiraz, Wai Chong Ng, Xiaodong Deng, Gerald Choon Huat Koh, Kelvin Bryan Tan, Ian Philp, Dick Wiggins, Su Aw and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

16 citing papers in PubMed, 24 citations in OpenAlex.

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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

12 authors at 7 institutions in 5 countries.

Zoe J-L HildonJohns Hopkins University, Center for Communication Programs, 111 Market Place, Suite 310, Baltimore, MD, 21202, USA. Zhildon1@jhu.edu.
Chuen Seng TanSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Farah ShirazSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Wai Chong NgTsao Foundation, 298 Tiong Bahru Road, #15-01/06 Central Plaza, Singapore, 168730, Singapore.
Xiaodong DengSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Gerald Choon Huat KohSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Kelvin Bryan TanSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Ian PhilpUniversity of Stirling, Stirling, UK.
Dick WigginsUCL Institute of Education, IOE - Social Science, University College London, 20 Bedford Way, London, WC1H 0AL, England.
Su AwSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Treena WuTsao Foundation, 298 Tiong Bahru Road, #15-01/06 Central Plaza, Singapore, 168730, Singapore.
Hubertus J M VrijhoefDepartment of Patient & Care, Maastricht University Medical Center, Maastricht, the Netherlands.
National University Health System · SGNational University of Singapore · SGJohns Hopkins University · USMinistry of Health · SGUniversity College London · GBUniversity of Stirling · GBVrije Universiteit Brussel · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study introduces the conceptual basis and operational measure, of BioPyschoSocial (BPS) health and related risk to better understand how well older people are managing and to screen for risk status. The BPS Risk Screener is constructed to detect vulnerability at older ages, and seeks to measure dynamic processes that place equal emphasis on Psycho-emotional and Socio-interpersonal risks, as Bio-functional ones. We validate the proposed measure and describe its application to programming.

methodsWe undertook a quantitative cross-sectional, psychometric study with n = 1325 older Singaporeans, aged 60 and over. We adapted the EASYCare 2010 and Lubben Social Network Scale questionnaires to help determine the BPS domains using factor analysis from which we derive the BPS Risk Screener items. We then confirm its structure, and test the scoring system. The score is initially validated against self-reported general health then modelled against: number of falls; cognitive impairment; longstanding diseases; and further tested against service utilization (linked administrative data).

resultsThree B, P and S clusters are defined and identified and a BPS managing score ('doing' well, or 'some', 'many', and 'overwhelming problems') calculated such that the risk of problematic additive BPS effects, what we term health 'loads', are accounted for. Thirty-five items (factor loadings over 0.5) clustered into three distinct B, P, S domains and were found to be independently associated with self-reported health: B: 1.99 (1.64 to 2.41), P: 1.59 (1.28 to 1.98), S: 1.33 (1.10 to 1.60). The fit improved when combined into the managing score 2.33 (1.92 to 2.83, < 0.01). The score was associated with mounting risk for all outcomes.

conclusionsBPS domain structures, and the novel scoring system capturing dynamic BPS additive effects, which can combine to engender vulnerability, are validated through this analysis. The resulting tool helps render clients' risk status and related intervention needs transparent. Given its explicit and empirically supported attention to P and S risks, which have the potential to be more malleable than B ones, especially in the older old, this tool is designed to be change sensitive.

Indexed as

Health StatusSocial WelfareAgedAged, 80 and overCross-Sectional StudiesEarly Medical InterventionFactor Analysis, StatisticalFemaleHealth SurveysHumansMaleMiddle AgedPsychometricsRisk FactorsSingaporeSurveys and QuestionnairesImplementation scienceIntegrated care delivery in the communityInterdisciplinary theoryMeasurement studyRisk stratificationSuccessful ageing

Identifiers

PMID29454316
PMCPMC5816546
OpenAlexW2790640051

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.