Developing attributes for a generic quality of life measure for older people: Preferences or capabilities?

Grewal, Ini; Lewis, Jane; Flynn, Terry N.; Brown, Joshua R.; Bond, John; Coast, Joanna

doi:10.1016/j.socscimed.2005.08.023

Cited by 312 publications

(340 citation statements)

References 25 publications

Supporting

Mentioning

328

Contrasting

Unclassified

Order By: Relevance

“…Cleaning the house, social participation and being active/occupied was seen as at a less fundamental level in terms such as Maslov's hierarchy of needs (Grewal, Lewis, Flynn, Brown, Bond, & Coast, 2006), so an additional argument existed for grouping these together.…”

Section: Discrete Choice Experimentsmentioning

confidence: 99%

Best–worst scaling vs. discrete choice experiments: An empirical comparison using social care data

Potoglou

Burge

Flynn

et al. 2011

Social Science & Medicine

Self Cite

131

111

View full text Add to dashboard Cite

Key messages• This study illustrates key issues that are important in choosing between profile-case best-worst scaling and discrete choice experiment studies • Empirical research on the value of outcomes of social care reveals similar patterns in the preference weights obtained from the two approaches • In the majority of cases examined, preference weights are not significantly different once the weights have been appropriately normalised/rescaled 3 Abstract This paper presents empirical findings from the comparison between two principal preference elicitation techniques: discrete choice experiments and profile-based best-worst scaling. Best-worst scaling involves less cognitive burden for respondents and provides more information than traditional "pick-one" tasks asked in discrete choice experiments. However, there is lack of empirical evidence on how best-worst scaling compares to discrete choice experiments. This empirical comparison between discrete choice experiments and best-worst scaling was undertaken as part of the Outcomes of Social Care for Adults project, which aims to develop a weighted measure of social care outcomes. The findings show that preference weights from best-worst scaling and discrete choice experiments do reveal similar patterns in preferences and in the majority of cases preference weights -when normalised/rescaled -are not significantly different.

show abstract

Section: Discrete Choice Experimentsmentioning

confidence: 99%

Best–worst scaling vs. discrete choice experiments: An empirical comparison using social care data

Potoglou

Burge

Flynn

et al. 2011

Social Science & Medicine

Self Cite

131

111

View full text Add to dashboard Cite

show abstract

“…In the health sector, there is a growing sense that narrow measures of health gain may not be sufficient for evaluating the benefits of social care (Ryan, Netten, Skatun, & Smith, 2006), care for older people (Grewal et al, 2006), and mental health care (Simon et al, 2013). This has led to interest in operationalising Sen's capability approach.…”

Section: Introductionmentioning

confidence: 99%

Do capability and functioning differ? A study of U.K. survey responses

Al‐Janabi

2017

Health Economics

View full text Add to dashboard Cite

SummaryA core feature of the capability approach is that a person's capabilities (what they are able to do and be in their life) can differ from their functionings (what they actually do and are in their life). However, the degree to which capability and functioning differ in practice is unclear. This paper investigates this issue, focusing on capability and functioning differences (CFD) across different aspects of life and different individuals. In the study, the ICECAP‐A capability questionnaire was modified to measure both functionings and capabilities and was completed by U.K.‐based convenience sample of 943 people. Around one third of people reported CFD in at least one area of their life, most commonly in terms of their “achievement.” People were more likely to report CFD when they had a degree‐level education and when they had impaired health. An additional finding was that capability varied more with education whereas functioning varied more with health status. This finding needs further examination, but it suggests that the choice of evaluative space may influence how priorities are set for public spending.

show abstract

Section: Discussionmentioning

confidence: 99%

“…[45,46] Whilst these measures cannot be used to calculate QALYs, they still provide valuable information in assessing the benefits of interventions. The ICECAP A and ICECAP O are measures of capability for use in adults and older people respectively [45,46]. The descriptive systems of both these measures were developed using qualitative methods, involving in depth interviews with relevant populations (adults and older people) to identify and refine the attributes that should be included.…”

Section: Discussionmentioning

confidence: 99%

How Well Do the Generic Multi-attribute Utility Instruments Incorporate Patient and Public Views Into Their Descriptive Systems?

Stevens

2015

Patient

View full text Add to dashboard Cite

Short running title: Incorporating patient and public views in multi attribute utility instrumentsAbstract 2 Multi attribute utility instruments (MAUI) are being increasingly used to generate utility data which can be used to calculate quality adjusted life years (QALYs). This QALY data can then be incorporated into a cost utility analysis as part of an economic evaluation, to inform health care resource allocation decisions. Many health care decision making bodies around the world such as The National Institute for Health and Care Excellence require the use of generic MAUIs. Recently there has been a call for greater input of patients in the development of patient reported outcome measures and this is now actively encouraged. By incorporating the views of patients, greater validity of an instrument is expected and it is more likely that patients will be able to self-complete an instrument, which is the ideal when obtaining information about a patient's health related quality of life. This paper examines the stages of MAUI development and the scope for patient and/or public involvement at each stage. The paper then reviews how much the main generic MAUIs have incorporated the views of patients/the public into the development of their descriptive systems at each of these stages and the implications of this. The review finds that the majority of MAUIs had very little input from patients/the public. Instead, existing literature and/or the views of experts was used. If we wish to incorporate patient/public views in future development of MAUIs, then qualitative methods are recommended. Key Points for Decision Makers The majority of multi attribute utility instruments had very little involvement of patients in the development of their descriptive systems  The descriptive systems of multi attribute utility instruments were mostly developed using top down methods, which made use of existing literature and/or views of experts in determining what should be included  If patient or public views are to be incorporated in the development of descriptive systems in the future, qualitative methods are recommended.3

show abstract

Developing attributes for a generic quality of life measure for older people: Preferences or capabilities?

Cited by 312 publications

References 25 publications

Best–worst scaling vs. discrete choice experiments: An empirical comparison using social care data

Best–worst scaling vs. discrete choice experiments: An empirical comparison using social care data

Do capability and functioning differ? A study of U.K. survey responses

How Well Do the Generic Multi-attribute Utility Instruments Incorporate Patient and Public Views Into Their Descriptive Systems?

Contact Info

Product

Resources

About