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dc.contributor.authorHildon, Zoe J-Len_UK
dc.contributor.authorTan, Chuen Sengen_UK
dc.contributor.authorShiraz, Farahen_UK
dc.contributor.authorNg, Wai Chongen_UK
dc.contributor.authorDeng, Xiaodongen_UK
dc.contributor.authorKoh, Gerald Choon Huaten_UK
dc.contributor.authorTan, Kelvin Bryanen_UK
dc.contributor.authorPhilp, Ianen_UK
dc.contributor.authorWiggans, Dicken_UK
dc.contributor.authorAw, Suen_UK
dc.contributor.authorWu, Treenaen_UK
dc.contributor.authorVrijhoef, Hubertus J Men_UK
dc.description.abstractBackground This study introduces the conceptual basis and operational measure, ofBioPyschoSocial (BPS) healthand related risk to better understand how well older people are managing and to screen for risk status. The BPS Risk Screener is constructed to detectvulnerabilityat 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. Methods We undertook a quantitative cross-sectional, psychometric study withn = 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). Results Three B, P and S clusters are defined and identified and a BPSmanaging 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. Conclusions BPS 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.en_UK
dc.publisherBioMed Centralen_UK
dc.relationHildon ZJ, Tan CS, Shiraz F, Ng WC, Deng X, Koh GCH, Tan KB, Philp I, Wiggans D, Aw S, Wu T & Vrijhoef HJM (2018) 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. BMC Geriatrics, 18 (1), Art. No.: 49.
dc.rights© The Author(s). 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.en_UK
dc.subjectInterdisciplinary theoryen_UK
dc.subjectSuccessful ageingen_UK
dc.subjectRisk stratificationen_UK
dc.subjectMeasurement studyen_UK
dc.subjectImplementation scienceen_UK
dc.subjectIntegrated care delivery in the communityen_UK
dc.titleThe 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 interventionsen_UK
dc.typeJournal Articleen_UK
dc.citation.jtitleBMC Geriatricsen_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.affiliationJohns Hopkins Universityen_UK
dc.contributor.affiliationNational University of Singaporeen_UK
dc.contributor.affiliationNational University of Singaporeen_UK
dc.contributor.affiliationTsao Foundationen_UK
dc.contributor.affiliationNational University of Singaporeen_UK
dc.contributor.affiliationNational University of Singaporeen_UK
dc.contributor.affiliationNational University of Singaporeen_UK
dc.contributor.affiliationFaculty of Social Sciencesen_UK
dc.contributor.affiliationUniversity College Londonen_UK
dc.contributor.affiliationNational University of Singaporeen_UK
dc.contributor.affiliationTsao Foundationen_UK
dc.contributor.affiliationUniversity of Maastrichten_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
local.rioxx.authorHildon, Zoe J-L|en_UK
local.rioxx.authorTan, Chuen Seng|en_UK
local.rioxx.authorShiraz, Farah|en_UK
local.rioxx.authorNg, Wai Chong|en_UK
local.rioxx.authorDeng, Xiaodong|en_UK
local.rioxx.authorKoh, Gerald Choon Huat|en_UK
local.rioxx.authorTan, Kelvin Bryan|en_UK
local.rioxx.authorPhilp, Ian|0000-0002-3972-6496en_UK
local.rioxx.authorWiggans, Dick|en_UK
local.rioxx.authorAw, Su|en_UK
local.rioxx.authorWu, Treena|en_UK
local.rioxx.authorVrijhoef, Hubertus J M|en_UK
local.rioxx.projectInternal Project|University of Stirling|
local.rioxx.filenameThe theoretical and empirical basis of a BioPsychoSocial risk screener.pdfen_UK
Appears in Collections:Faculty of Social Sciences Journal Articles

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