Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/26800
Appears in Collections:Faculty of Social Sciences Journal Articles
Peer Review Status: Refereed
Title: 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
Author(s): Hildon, Zoe J-L
Tan, Chuen Seng
Shiraz, Farah
Ng, Wai Chong
Deng, Xiaodong
Koh, Gerald Choon Huat
Tan, Kelvin Bryan
Philp, Ian
Wiggans, Dick
Aw, Su
Wu, Treena
Vrijhoef, Hubertus J M
Keywords: Interdisciplinary theory
Successful ageing
Risk stratification
Measurement study
Implementation science
Integrated care delivery in the community
Issue Date: 17-Feb-2018
Citation: Hildon 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.
Abstract: Background 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.
DOI Link: http://dx.doi.org/10.1186/s12877-018-0739-x
Rights: © The Author(s). 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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 (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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