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

Autor: Su Aw, Chuen Seng Tan, Farah Shiraz, Wai Chong Ng, Xiaodong Deng, Zoe Hildon, Gerald Choon-Huat Koh, Dick Wiggins, Hubertus J. M. Vrijhoef, Treena Wu, Ian Philp, Kelvin Bryan Tan
Přispěvatelé: Family Medicine and Chronic Care, RS: CAPHRI - R2 - Creating Value-Based Health Care, MUMC+: KIO Kemta (9), Health Services Research
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Gerontology
Biopsychosocial model
Male
Psychometrics
Singapore/epidemiology
Psychological intervention
Vulnerability
Poison control
health status
lcsh:Geriatrics
Health Surveys/methods
Suicide prevention
Occupational safety and health
0302 clinical medicine
QUALITY-OF-LIFE
Surveys and Questionnaires
80 and over
Medicine
risk factors
030212 general & internal medicine
PREDICTORS
Singapore
Statistical
Middle Aged
Successful ageing
Implementation science
Female
0305 other medical science
Factor Analysis
social welfare
Research Article
Integrated care delivery in the community
Early Medical Intervention/methods
Interdisciplinary theory
03 medical and health sciences
Quality of life (healthcare)
Measurement study
030502 gerontology
Early Medical Intervention
ADVERSITY
Humans
FRAILTY
Risk stratification
Aged
business.industry
ADULTS
RESILIENCE
INSTRUMENTS
Health Surveys
lcsh:RC952-954.6
PROMOTION
Cross-Sectional Studies
PARALLEL ANALYSIS
SCALES
Geriatrics and Gerontology
business
aged
80 and over
Factor Analysis
Statistical
Zdroj: BMC Geriatrics, 18:49. BioMed Central Ltd
BMC Geriatrics
BMC Geriatrics, Vol 18, Iss 1, Pp 1-15 (2018)
BASE-Bielefeld Academic Search Engine
ISSN: 1471-2318
DOI: 10.1186/s12877-018-0739-x
Popis: Background This 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. Methods We 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). Results Three 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
Databáze: OpenAIRE
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