BACKGROUND: The Investigating Choice Experiments for the Preferences of Older People (ICEPOP) programme developed a capability-based measure of general quality of life (QOL): the ICEPOP CAPability (ICECAP-O) instrument. ICECAP-O was originally intended for use in the economic evaluation of health and social care interventions, but there is increasing interest in using it to quantify differences in QOL in cross-sectional data. OBJECTIVE: The objective of this study was to assess the construct validity of the overall ICECAP-O scores and quantify differences in QOL associated with various factors in a multivariable regression model among residents of a British city. METHODS: ICECAP-O was administered as part of a survey of 4304 citizens of a British city. QOL values in only those respondents aged ≥65 years (n = 809) were compared across subgroups using univariable analyses and multivariable regression models. RESULTS: QOL values were associated with differences in responses to a variety of questions about respondents' socioeconomic status, locality, contact with others, participation, health and social support. Multivariable regression results showed that poor physical and psychological health were associated with 4-7% lower QOL. Living alone and infrequent socializing were each associated with an approximately 2.5% impairment in QOL. Feeling unsafe after dark was associated with an 8% impairment, whilst those without a faith experienced 5% lower QOL on average. Distribution of ICECAP-O values by electoral ward enabled the identification of areas of deprivation, although the associations were strong only for enjoyment and control. CONCLUSION: ICECAP-O provides policy makers with robust quantitative evidence of differences in QOL. It offers local government an opportunity to evaluate the effects of health and other interventions, and to make comparisons across sectors for which it is responsible. It also demonstrates good ability to compare impairments in QOL associated with sociodemographic, health and attitudinal variables.
BACKGROUND: The Investigating Choice Experiments for the Preferences of Older People (ICEPOP) programme developed a capability-based measure of general quality of life (QOL): the ICEPOP CAPability (ICECAP-O) instrument. ICECAP-O was originally intended for use in the economic evaluation of health and social care interventions, but there is increasing interest in using it to quantify differences in QOL in cross-sectional data. OBJECTIVE: The objective of this study was to assess the construct validity of the overall ICECAP-O scores and quantify differences in QOL associated with various factors in a multivariable regression model among residents of a British city. METHODS: ICECAP-O was administered as part of a survey of 4304 citizens of a British city. QOL values in only those respondents aged ≥65 years (n = 809) were compared across subgroups using univariable analyses and multivariable regression models. RESULTS: QOL values were associated with differences in responses to a variety of questions about respondents' socioeconomic status, locality, contact with others, participation, health and social support. Multivariable regression results showed that poor physical and psychological health were associated with 4-7% lower QOL. Living alone and infrequent socializing were each associated with an approximately 2.5% impairment in QOL. Feeling unsafe after dark was associated with an 8% impairment, whilst those without a faith experienced 5% lower QOL on average. Distribution of ICECAP-O values by electoral ward enabled the identification of areas of deprivation, although the associations were strong only for enjoyment and control. CONCLUSION: ICECAP-O provides policy makers with robust quantitative evidence of differences in QOL. It offers local government an opportunity to evaluate the effects of health and other interventions, and to make comparisons across sectors for which it is responsible. It also demonstrates good ability to compare impairments in QOL associated with sociodemographic, health and attitudinal variables.
Authors: Vadim Dukhanin; Alexandra Searle; Alice Zwerling; David W Dowdy; Holly A Taylor; Maria W Merritt Journal: Soc Sci Med Date: 2017-12-14 Impact factor: 4.634
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Authors: Jennifer C Davis; John R Best; Stirling Bryan; Linda C Li; Chun Liang Hsu; Caitlin Gomez; Kelly Vertes; Teresa Liu-Ambrose Journal: Arch Phys Med Rehabil Date: 2015-04-08 Impact factor: 3.966
Authors: Joyce Siette; Mikaela L Jorgensen; Andrew Georgiou; Laura Dodds; Tom McClean; Johanna I Westbrook Journal: BMC Geriatr Date: 2021-06-28 Impact factor: 3.921