Literature DB >> 31875309

Capability instruments in economic evaluations of health-related interventions: a comparative review of the literature.

Timea Mariann Helter1, Joanna Coast2, Agata Łaszewska3, Tanja Stamm4, Judit Simon3,5.   

Abstract

PURPOSE: Given increasing interest in using the capability approach for health economic evaluations and a growing literature, this paper aims to synthesise current information about the characteristics of capability instruments and their application in health economic evaluations.
METHODS: A systematic literature review was conducted to assess studies that contained information on the development, psychometric properties and valuation of capability instruments, or their application in economic evaluations.
RESULTS: The review identified 98 studies and 14 instruments for inclusion. There is some evidence on the psychometric properties of most instruments. Most papers found moderate-to-high correlation between health and capability measures, ranging between 0.41 and 0.64. ASCOT, ICECAP-A, -O and -SCM instruments have published valuation sets, most frequently developed using best-worst scaling. Thirteen instruments were originally developed in English and one in Portuguese; however, some translations to other languages are available. Ten economic evaluations using capability instruments were identified. The presentation of results show a lack of consensus regarding the most appropriate way to use capability instruments in economic evaluations with discussion about capability-adjusted life years (CALYs), years of capability equivalence and the trade-off between maximisation of capability versus sufficient capability.
CONCLUSION: There has been increasing interest in applying the capability-based approach in health economic evaluations, but methodological and conceptual issues remain. There is still a need for direct comparison of the different capability instruments and for clear guidance on when and how they should be used in economic evaluations.

Entities:  

Keywords:  Capability approach; Economic evaluation; Outcome; Patient reported outcome measures; Preference weighting; Validation

Mesh:

Year:  2019        PMID: 31875309      PMCID: PMC7253529          DOI: 10.1007/s11136-019-02393-5

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


Background

Economic evaluations assess whether an intervention provides value for money through the comparative analysis of alternative courses of action in terms of both costs and consequences [1]. The assessment of consequences in economic evaluation requires information about their identification (what), measurement (how much) and valuation (how valuable) [2]. Standard methods of health economic evaluations identify outcomes based on a rather narrow definition of health that aims to express outcomes in Quality-Adjusted Life Years (QALYs). However, there are many interventions, particularly in the areas of mental health, end-of-life care, public health and social care, where the impacts of interventions go beyond this narrow view of health. The contemporary literature (e.g. [3-6]) recognises the need to move away from the standard methods for assessing effects of interventions and toward incorporating outcomes beyond the QALY framework, when producing an economic evaluation which feeds into decision making about resource allocation in health-related interventions. The most promising approach to address this issue is the application of Sen’s capability framework, which was introduced by Sen [7] in the early 1980s as an alternative to standard utilitarian welfare economics. The core focus of the capability approach is on what individuals are able to be and do in their lives (i.e. capable of). The application of the capability approach in health economics has gained popularity because it potentially provides a richer evaluative space for the evaluation of interventions [8]. There has been increasing interest in developing instruments for using the capability approach in the measurement and valuation of outcomes for health economic evaluations. Capability instruments have been in the public domain for over a decade and publications have started to shift from methodological issues towards use of the measures within economic evaluations. Some decision-making institutions currently recommend the inclusion of capability measures in economic evaluations in certain contexts. The Zorginstituut in the Netherlands [9] recommends the inclusion of ICEpop CAPability measure for Older people (ICECAP-O) alongside the EuroQol instrument (EQ-5D) for the evaluation of interventions in long-term care, where the relevant outcomes extend beyond health. The most recent methods guideline [10] of the National Institute for Health and Care Excellence (NICE) acknowledges that the intended outcomes of interventions go beyond changes in health status for some decision problems; hence, ‘broader, preference weighted measures of outcomes, based on specific instruments, may be more appropriate…’ and ‘the economic analysis may also consider effects in terms of capability and well-being’ (p. 137). The manual specifically recommends the Adult Social Care Outcomes Toolkit (ASCOT) and ICECAP-O instruments. However, the choice between instruments and their practical application in particular contexts lack a systematic approach. For instance, the ICECAP-O recommended by NICE is targeted at a subgroup of the population (older adults), whilst the ASCOT was specifically developed for the assessment of social care interventions. A recent review of the literature examined current trends in the application of ICECAP-O [11]. The authors found that the ICECAP-O has mainly been included as a secondary economic measure and the reporting of results is brief with minimal detail and often no discussion or interpretation. An overview of the psychometric properties of all potential capabilities instruments and their usefulness for economic evaluations would contribute to providing a clear guidance. This could later be used as a reference point for future comparative analysis of policies or interventions. Hence, the main aim of this paper is to synthesise the current evidence about the application of capability instruments in health economic evaluations. This translates into the following objectives: (i) to summarise information about the development, psychometric properties and preference valuation of relevant capability instruments; (ii) to compare the identified capability instruments in terms of their psychometric properties and up-to-date application in health economic evaluations; (iii) to identify applied evaluations that have used the capability-based approach in health economic evaluations and (iv) to pinpoint the challenges and considerations in the application of the capability approach in economic evaluations of health-related interventions.

Methods

Identification of relevant studies

The identification of papers was based on two main approaches: a traditional systematic literature search and a comprehensive pearl growing method [12]. The grey literature search in Google Advance either generated an unmanageable number of hits due to the term “capability” being used across a number of disciplines with varying meanings, as well as having generic lay use and interpretation of the term; or there was no addition to the search of other databases when more precise terms were used. As the development and validation of the capability approach in health economics currently appears to be concentrated among a limited group of researchers, as an additional step, websites dedicated to the instruments identified through the systematic search were specifically targeted and reviewed for relevant information.

Systematic literature search

Firstly, we conducted a systematic literature search. Search terms combined expressions for economic evaluation and frequently used terms for the capability approach, including synonyms and names of instruments most well-known in the area of health economics. Search terms are presented in Appendix 1. The selection of databases was based on similar reviews of health measures (PROMs) [6, 13] in the area and included Embase, Medline, Web of Science, Psychinfo and Scopus. The literature search was conducted on 1 February 2019 and the review was limited to the last 20 years when the first publications in this topic area appeared [14]. Relevant systematic literature reviews were searched for further references and their findings were kept for comparison and discussion.

Comprehensive pearl growing method

The term ‘capability’ produces very broad ranging results when used as a search term due to its wide range of meanings, including lay meanings. The so-called comprehensive pearl growing method [12] is a technique used to ensure all relevant articles are included, particularly in case of issues with vocabulary in a search strategy. This method is particularly useful in interdisciplinary research and where recent developments are expected in the literature. The process of pearl growing commences with the identification of ‘key pearls’ (i.e. key studies), that can be identified from within the literature as being compatible with the aim of the review [12]. Once the key pearls have been identified, these are used to generate the ‘first wave of pearls’, that is, papers that have cited the key pearls within their reference list. It has been used successfully in a different type of review in the context of capabilities [13]. This second approach was implemented to validate the strategy applied during the systematic search and to identify potential further papers. Two waves of the pearl growing method were conducted: one focusing on the development of instruments and a second wave related to the application of the instruments. A third wave was deemed unnecessary because the identified last generation of seminal papers were published only recently and have not been cited yet. The results are presented in Table 1. The first wave used for citation searching were the developmental studies of the four most commonly used and reported capability instruments: ASCOT, ICECAP-O, its version for adults (ICECAP-A) and the Oxford CAPabilities questionnaire-Mental Health (OxCAP-MH). The second wave relied on the three main papers from the last 5 years (but already with some relevant citations) that aimed to identify recent developments and up-to-date knowledge in the application of the capability approach in health economic evaluations. The number of citations was retrieved from Scopus on 14 March 2019.
Table 1

Key pearls for the two waves of the comprehensive pearl growing method

WaveStudyNumber of citationsShort description
Wave 1[52]92Development of the ASCOT
[53]146Development of the ICECAP-A
[54]158Development of the ICECAP-O
[39]66Development of the OxCAP-MH
Wave 2[48]27Description of new methods to conduct economic evaluations using the capability approach
[55]13Presents the opportunities and challenges of the capability approach in health economics
[49]4Critical review of relevant questionnaires to measure and value capability
Key pearls for the two waves of the comprehensive pearl growing method

Study selection

Titles and abstracts were sifted by two researchers (TL and AL) and studies were included for further assessment if they met the following inclusion criteria: (1) Full paper available in English or German languages. (2) Scope of study is the area of health or health-related interventions, including any interventions specifically targeting the promotion of health and prevention and treatment of ill-health irrespective of the sector where these were implemented. Hence, our study also included potentially relevant studies from the social care and public health sectors. (3) Focus of research is the evaluation or assessment of the outcomes of interventions using the capability approach. (4) Paper includes information on the use (or recommended use) of the capability approach in economic evaluations. (5) Paper is an applied evaluation OR focuses on the development, psychometric validation (or comparison to other tools) or preference valuation of instruments. The full paper was retrieved if a study met the inclusion criteria based on its title and abstract. Consequently, full papers were assessed by two researchers (TH and AL) for inclusion based on their contribution to at least one of the aims of this literature review and subsequently allocated to the categories of either (i) applied evaluations (using a capability instrument in a completed economic evaluation) or (ii, iii, iv, v) methods papers. Methods papers were further categorised based on their relevance to the identification, measurement and valuation of outcomes, as well as the practical application of tools and theoretical contributions. Papers were grouped into categories of (ii) instrument development, (iii) psychometric validation or quantitative comparison of instruments, (iv) preference valuation of instruments and (v) methods for incorporation of the capability approach in economic evaluations. The latter one includes potential fields of application, approaches to use the results, incorporation of the results into a potential framework, for instance, Capability-Adjusted Life Years (CALYs), years of full capability or years of sufficient capability equivalence, etc. Some of the studies with significant theoretical contributions to the application of the capability approach in health economic evaluations which did not fit the above criteria were noted for discussion. No specific quality assessment was applied, all studies which provided information on either the psychometric properties or use of capabilities instruments in economic evaluations were included. The instruments were assessed based on their psychometric properties according to the COSMIN checklist [15], feasibility [16], potential for transferability and evidence regarding valuation.

Data extraction and analysis

Separate data extraction forms were created for empirical and psychometric evaluation (and other methods) studies. The search for information on valuation included any kind of preference-based valuation of instruments (or their dimensions/domains) and the existence of value sets. Further information on data extraction is presented in Appendix 2. Trends in the literature were analysed based on the number of different types of studies published each year. The information elicited from the studies was structured according to the capability instrument in question. Information about economic evaluations, and the psychometric properties and correlation coefficients from studies comparing instruments are presented in review tables. Due to the variability of methods used in the validation and comparison studies, only narrative synthesis, including tabulation and frequency analyses, was conducted as no statistical pooling was possible. The information gathered was synthesised in a qualitative rather than quantitative manner by TH.

Results

Search results

The literature search identified 98 studies for inclusion (Appendix 4 provides a complete list). The pearl growing method identified 29 citations beyond those captured by the systematic search strategy. However, none of the additional references met the inclusion criteria, and the papers included in this review were actually all picked up by the systematic search. An overview of the literature search based on the PRISMA statement is presented in Fig. 1.
Fig. 1

PRISMA chart

PRISMA chart The increasing number of relevant publications in recent years is a clear trend (shown in Fig. 2). A further trend also appears to be a shift from developmental studies towards the validation of capability instruments and their use in empirical studies.
Fig. 2

Annual changes in the number and type of publications related to using the capability approach in the economic evaluation of health-related interventions. Year 2019 not included in this figure because data were not available for the full year. Instruments to assess capability

Annual changes in the number and type of publications related to using the capability approach in the economic evaluation of health-related interventions. Year 2019 not included in this figure because data were not available for the full year. Instruments to assess capability

Instruments to assess capability

Development of instruments

The literature review identified 14 capability instruments. Table 2 shows the heterogeneity of the capability instruments in terms of development methods, disease areas, types of interventions, population groups and the questionnaire structure.
Table 2

Overview of the main characteristics and development methods of instruments that measure and value capability for economic evaluations in health

InstrumentInstrument full nameFieldPopulationNumber ofDevelopment methodInformantsNumber of informantsReferences
DimensionsLevels
ACQ‐CMH‐104Achieved Capabilities Questionnaire for Community Mental HealthMental healthPatients104UnknownFocus groupsParticipants of Portuguese community mental health services50[56]
ASCOTAdult Social Care Outcomes ToolkitSocial carePatients84Delphi exercise, Literature review and expert opinion, Further improvement of the Older People’s Utility Scale (OPUS)Experts and service users330[52]
ASCOT Easy Read versionEasy Read Version of the Adult Social Care Outcomes ToolkitSocial carePeople w. intellectual disabilities84Focus groups and in-depth interviewsIntellectual disability or autism54[57]
ASCOT – proxy versionProxy-report version of the Adult Social Care Outcomes ToolkitSocial carePatients84In-depth qualitative interviewsAdult care workers or unpaid family carers of patients with cognitive and/or communication impairments25[58]
ASCOT-CarerCarer Version of Adult Social Care Outcomes ToolkitSocial careCarers74Literature review and feedback from service users, carers, practitioners and policy-makersService users, carers, practitioners and policy-makers31[59]
CAFCurrently Achieved FunctioningGeneralOlder people55In-depth qualitative interviewsOlder people living in 3 Dutch urban areas99[60]
ICECAP-AICEpop CAPability measure for AdultsGeneralGeneral public54In-depth, informant-led, interviewsGeneral public (purposively selected through a random electoral sample)36[53]
ICECAP-CPMICEpop CAPability Close Person MeasureEnd of lifeClose persons65In-depth qualitative interviewsBereaved within the last 2 years or with a close person currently receiving end-of-life care27[61]
ICECAP-OICEpop CAPability measure for Older peopleGeneralOlder people54In-depth qualitative interviewsPurposively selected informants aged 65 and over in private households40[54]
ICECAP-SCMICEpop CAPability Supportive Care MeasureEnd of lifePatients74In-depth qualitative interviewsOlder people from different groups across the dying trajectory23[62]
OCAP-18OCAP-18Public healthGeneral public18Unknown

Theoretical framework,

Focus groups and in-depth interviews

Purposively sampled from various community groups in Glasgow, United Kingdom40[63]
OxCAP-MHOxford Capabilities Questionnaire for Mental HealthMental healthPatients165

Theoretical framework,

Focus group discussions

Psychiatrists, Psychologists, Social scientists, Health economists336[39]
(Low-income questionnaire)(Low-income questionnaire)Low-income settingsGeneral public6UnknownFocus groupsWomen in rural Malawi129[64]
(Chronic pain questionnaire)(Chronic pain questionnaire)Chronic painPatients8UnknownFocus groups and in-depth interviewsRespondents were recruited through a Pain Management Clinic in the East of England16[65]
Overview of the main characteristics and development methods of instruments that measure and value capability for economic evaluations in health Theoretical framework, Focus groups and in-depth interviews Theoretical framework, Focus group discussions

Availability of evidence on the characteristics of capability instruments

As Table 3 demonstrates, there is at least some evidence about the psychometric properties of most instruments.
Table 3

Availability of evidence on the characteristics of capability instruments for health economic evaluations

InstrumentReliabilityValidityResponsivenessInterpretability/FeasibilityValuation
ACQ‐CMH‐104[66][66]UnknownUnknownUnknown
ASCOT[67][21, 68, 69, 70, 71, 72, 73, 74][71][75][52]
ASCOT easy readUnknownUnknownUnknown[57]Unknown
ASCOT-proxyUnknownUnknownUnknown[58]Unknown
ASCOT-carer[76][76]UnknownUnknownUnknown
CAFUnknownUnknownUnknown[60]Unknown
ICECAP-A[77][20, 23, 24, 27, 33, 34, 38, 78, 79, 80][23, 32, 33, 34, 37, 81][82, 83, 84][85]
ICECAP-CPMUnknownUnknownUnknownUnknownUnknown
ICECAP-O[30, 86, 87][18, 21, 22, 25, 26, 40, 74, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96][26, 31, 35, 36, 95, 97][25, 26, 30, 40, 89, 91, 98, 99][88]
ICECAP-SCMUnknownUnknownUnknown[29, 83][100, 101]
low-income QUnknown[102]UnknownUnknownUnknown
pain QUnknownUnknownUnknownUnknownUnknown
OCAP-18UnknownUnknownUnknownUnknownUnknown
OxCAP-MH[17, 19, 103][17, 19, 103][17][39]Unknown
Availability of evidence on the characteristics of capability instruments for health economic evaluations The most recently developed instruments, unsurprisingly, have less information available about their reliability, validity and responsiveness; an exception is OCAP-18 which was among the first capability instruments to be developed, but for which there is no further psychometric evidence available. The main difference across different groups of capability instruments is whether valuations that reflect the preferences of patients or the general public are available. The ASCOT and most ICECAP instruments have reported valuation studies and are therefore considered to possess evidence regarding their ability to reflect values of informants, whilst this is currently missing, for instance, for OxCAP-MH.

Different language versions of instruments

Apart from ACQ‐CMH‐104, all instruments were originally developed in English. The ASCOT, ICECAP-A, ICECAP-O and OxCAP-MH instruments have been translated to further languages, and these new versions have been validated (Table 4).
Table 4

Availability of different language versions of capability instruments

InstrumentAvailability of language versions beside Englisha
ACQ‐CMH‐104Only available in Portuguese language
ASCOTJapanese [105]; Dutch [106]
ASCOT easy readNone identified
ASCOT-proxyNone identified
ASCOT-carerNone identified
CAFNone identified
ICECAP-AChinese [107], Danish (unpublished), Dutch (unpublished), German [107], Italian (unpublished), Persian (unpublished), Welsh (unpublished)
ICECAP-CPMnone identified
ICECAP-OChinese (unpublished), Dutch [92], French (unpublished), German [18], Spanish [87], Swedish [86], Welsh (unpublished); Italian, Norwegian and Portuguese [109]
ICECAP-SCMNone identified
low-income QNone identified
pain QNone identified
OCAP-18None identified
OxCAP-MHGerman [103]

aInformation on unpublished translations of instruments stem from the dedicated websites of the instruments

Availability of different language versions of capability instruments aInformation on unpublished translations of instruments stem from the dedicated websites of the instruments

Validation of capability instruments

Reliability

The test–retest reliability of most instruments have been successfully assessed in some groups of population, e.g. ACQ‐CMH‐104 [56]; ASCOT [72]; ICECAP-A [77]; ICECAP-O [86]; OxCAP-MH [19].

Validity

There were 25 studies among the included papers that used Pearson’s or Spearman rank correlation coefficients to quantitatively assess the validity of all language versions of the capability instruments and/or compare it to other instruments. Quantitative evidence was provided on the validity of six capability instruments, including ACQ‐CMH‐104, ASCOT, ICECAP-A, ICECAP-O, OxCAP-MH and Women’s Capabilities Index. Table 5 (and Appendix 5) summarise the correlations.
Table 5

Construct validity of capability instruments for health economic evaluations

Capabilities instrumentCompared with… (full names in Appendix 5)Value of correlation*Population (country in Appendix 5)Number of informantsReferences
ACQ‐CMH‐104RAS0.46*Psychiatric patients92[66]
WHOQOL‐Bref0.60*Psychiatric patients129[66]
ASCOTBarthel Index0.45Older social care users205[21]
Cantril’s Ladder0.66Older social care users205[21]
CASP-120.58Older home care residents301[52]
EQ-5D-3L0.41Older home care residents301[52]
EQ-5D-3L0.40Older home care residents301[70]
EQ-5D-3L0.47Older home care residents224[68]
EQ-5D-3L0.41*Frail older adults living at home190[74]
EQ-5D-3L0.37Older social care users748[72]
EQ-5D-5L0.63Older social care users205[21]
EQ-5D-5L0.24Older adults in a day rehabilitation facility22[71]
EQ-5D-VAS0.64Older social care users205[21]
GDS-15− 0.69Older social care users205[21]
GHQ-12− 0.58Older home care residents301[52]
ICECAP-A0.62Older social care users748[72]
ICECAP-O0.81Older social care users205[21]
ICECAP-O0.41*Frail older adults living at home190[74]
ICECAP-O0.67Older social care users748[72]
OPQOL-130.76Older social care users205[21]
OPQOL-brief0.38Older adults in a day rehabilitation facility22[71]
OPQoL-Brief0.58Older social care users87[69]
SWLS0.74Older social care users205[21]
ASCOT-CarerCES0.58Social care recipients376[76]
CSI− 0.59Social care recipients384[76]
EQ-5D-3L0.34Social care recipients382[76]
QoL0.62Social care recipients384[76]
ICECAP-A15D0.50*Healthy general public and patients from 8 disease areas6756[24]
AQoL-8D0.31*Healthy general public and patients from 8 disease areas6756[24]
AQoL-8D0.80Healthy general public and patients with 7 chronic conditions8022[20]
EQ-5D-3L0.53Women with lower urinary tract infection478[23]
EQ-5D-3L0.49Knee pain patients in primary care500[27]
EQ-5D-5L0.62*Healthy general public and patients with 7 chronic conditions1212[108]
EQ-5D-5L0.49*Healthy general public and patients from 8 disease areas6756[24]
EQ-5D-5L0.60Healthy general public and patients with 7 chronic conditions8022[20]
HUI-30.32*Healthy general public and patients from 8 disease areas6756[24]
LDQ− 0.48Opiate substitution recipients83[34]
SF-6D0.64*Healthy general public and patients with 7 chronic conditions1212[108]
SF-6D0.47*Healthy general public and patients from 8 disease areas6756[24]
SSQ0.43Opiate substitution recipients83[34]
SWLS0.66*Healthy general public and patients with 7 chronic conditions1212[108]
ICECAP-OADRQL0.53*Nursing home residents with dementia95[18]
Barthel Index0.49Older social care users209[21]
Barthel Index0.72*Nursing home residents with dementia95[18]
Cantril’s Ladder0.74Older social care users213[21]
CTM-30.23Patients from outpatient day rehabilitation unit82[22]
EQ-5D-3L0.34Older people with hip fracture113[95]
EQ-5D-3L0.69*Nursing home residents with dementia95[18]
EQ-5D-3L0.53Older people after hip fracture surgery87[93]
EQ-5D-3L0.44Patients from outpatient day rehabilitation unit80[22]
EQ-5D-3L0.47Patients visiting the clinic215[25]
EQ-5D-3L0.63Frail older adults living at home190[74]
EQ-5D-5L0.68Older social care users207[21]
EQ-5D-5L0.63General population aged 70 or older516[90]
EQ-5D-VAS0.66Older social care users208[21]
GDS-15− 0.73Older social care users210[21]
OHS0.38Older people with hip fracture113[95]
OPQOL-130.80Older social care users211[21]
SWLS0.82Older social care users212[21]
ICECAP-O family versionEQ-5D family version0.57*Nursing professionals of psycho-geriatric elderly96[92]
EQ-VAS family version0.43*Family members of psycho-geriatric elderly68[92]
ICECAP-O nursing versionEQ-5D nursing version0.48*Nursing professionals of psycho-geriatric elderly96[92]
EQ-VAS nursing version0.55*Family members of psycho-geriatric elderly68[92]
OxCAP-MHBPRS− 0.41Patients with psychosis172[19]
BSI-18− 0.67*Patients in socio-psychiatric services162[17]
EQ-5D VAS0.58*Patients in socio-psychiatric services161[17]
EQ-5D-3L0.45Patients with psychosis172[19]
EQ-5D-5L0.66*Patients in socio-psychiatric services160[17]
EQ-5D-VAS0.52Patients with psychosis172[19]
GAF0.24Patients with psychosis172[19]
GAF0.35*Patients in socio-psychiatric services168[17]
Mini-ICF-APP− 0.47*Patients in socio-psychiatric services167[17]
SIX0.12Patients with psychosis172[19]
WHOQOL-Bref Environment0.69*Patients in socio-psychiatric services166[17]
WHOQOL-BREF Physical health0.69*Patients in socio-psychiatric services163[17]
WHOQOL-Bref Psychological0.75*Patients in socio-psychiatric services164[17]
WHOQOL-Bref Social relationships0.50Patients in socio-psychiatric services165[17]
Women’s Capabilities IndexWHOQOL-Bref0.62*Women from Malawi20[64]

Values in italic are Pearson’s coefficients, values in standard writing are Spearman rank correlations. A * behind the value means that the study used a non-English version of the capability instrument

Construct validity of capability instruments for health economic evaluations Values in italic are Pearson’s coefficients, values in standard writing are Spearman rank correlations. A * behind the value means that the study used a non-English version of the capability instrument There is variation between studies in the correlation measures used, the instruments compared, the characteristics of the population, number of informants, testing of hypotheses generated regarding likely associations between the data and testing across known groups for discriminant and convergent validity. Hence, it is difficult to provide general statements about the comparison of capability instruments with other PROMs, or to conduct statistical pooling of the results. High correlation estimates (above 0.8) were found between capability instruments: ASCOT/ICECAP-O [49] and ICECAP-A/AQoL-8D [20]. The examined studies provided very diverse estimates for the correlations between Health-related Quality of Life (HRQoL) and the different capability instruments. Most studies compared the ASCOT, ICECAP-A and ICECAP-O instruments with either disease-specific or generic HRQoL instruments. A wide range of disease-specific instruments were applied across studies, mainly being used when informants consisted of patients and social care recipients. EQ-5D-3L/-5L was used in 92% (n = 23) of the included validation and comparison studies as a HRQoL measure. In most cases, the 5L version of the EQ-5D instruments provided higher correlation coefficients compared to the 3L version. The higher correlation with capability instruments could be explained by lower ceiling effects and higher sensitivity to minor changes in the 5L version compared to the 3L version. There seem to be a consensus in the literature that the capability approach provides complementary information to HRQoL measures. However, capability instruments could also be perceived as enhanced rather than complementary to the narrow interpretation of well-being/quality of life when focusing only on HRQoL. Most studies [25-27] found that the ICECAP and EQ-5D instruments provide complementary information, and a mapping is not recommended between them. Engel et al. [24] found that the ICECAP-A provides evidence above that gathered from most commonly used preference-based HRQoL instruments. Similar findings were reported for other capability instruments. Forder and Caiels [68] found that ASCOT has greater validity in measuring the effects of social care services than EQ-5D. Van Leeuwen et al. [28] investigated the validity of ICECAP-O and ASCOT among Dutch older adults. Although it could be attributable to cultural transferability issues, they found that respondents did not feel that these instruments give a comprehensive picture of their HRQoL because they did not find all domains of the instruments relevant, whilst other important domains were not covered, particularly concerns or delight about the well-being of family members. HRQoL instruments capture an important part of broader well-being, and some studies [22, 23] established strong and positive association between capability and HRQoL instruments, which questions whether they focus on complementary constructs. Evidence suggests that some capability instruments could rather be interpreted as an enhancement of the HRQoL concept, for instance, an exploratory factor analysis [17] found that all EQ-5D-5L items and seven OxCAP-MH items loaded on one factor and nine remaining OxCAP-MH items loaded on a separate factor. It is questionable whether the issues discussed above relate to all HRQoL measures or only the EQ-5D Utility instrument. Lower correlation between the OxCAP-MH and EQ-5D Utility scores was observed in the Vergunst et al. [19] study than between OxCAP-MH and EQ-5D-VAS. This could be explained by the fact that the latter reflects the patient’s overall judgement about their health status rather than focusing only five dimensions of their health, which is arguably more in line with the underlying broader well-being concept and the used non-preference-based index score of the OxCAP-MH instrument.

Interpretability

In terms of ease of understanding, Bailey et al. [29] investigated the appropriateness of ICECAP-SCM to measure QoL and found that the capability instrument appeared more meaningful, easier to complete and had fewer errors among patients and close persons, compared to EQ-5D-5L. However, these results did not apply to healthcare professionals who preferred the EQ-5D-5L over ICECAP-SCM when measuring clinician-rated health states because it focused on observable attributes. Similar studies have also demonstrated the feasibility of use of other ICECAP measures [81, 90]. Malley et al. [70] and Towers et al. [67] demonstrated the feasibility of using ASCOT among older people and care home residents; however, the study also highlighted the need for proxy respondents in some situations. This later led to the development of a proxy version of the ASCOT, which demonstrated good feasibility [58]. Davis et al. [30] reported that the level of agreement between patient and proxy for the EQ-5D-3L was significantly better than the level of agreement observed for the ICECAP-O in case of patients with vascular cognitive impairment. The authors conclude that due to its complexity, the ICECAP-O may have limited clinical, research and policy-related utility among individuals with mild cognitive impairment. However, these results need to be interpreted carefully due to the differing number of levels and the greater ability of proxies to observe the dimensions in EQ-5D. Although it could be explained by translational issues, van Leeuwen [28] who also reported difficulties with understanding the ASCOT and ICECAP-O in a study assessing a small number (n = 10) of Dutch, community-dwelling frail older adults. Simon et al. [39] explored the feasibility of OxCAP-MH among severely ill mental health service users. Patients provided positive feedback and felt that the questions allowed them to express their views and experience on topics they considered important but which were often left out of clinical or research interviews [39].

Responsiveness

The sensitivity of the capability instruments to measure changes is generally reported to be higher than in case of HRQoL measures [6, 17, 31–34]. However, some authors found capability instruments to be less responsive than HRQoL measures. Davis et al. [35] and Couzner et al. [36] reported that the difference in values between the patient and general population groups was found to be far more pronounced for the EQ-5D-3L than for the ICECAP-O. There is a consensus in the literature that changes related to the broader meaning of health are better captured by the capability instruments than by EQ-5D [37-39]. Coast et al. [40] found strong evidence of association of general health with all capability attributes except for the attachment domain of ICECAP-A. Laszewska et al. [17] found that the OxCAP-MH may be seen as enhanced rather than complementary in its concept, when compared to EQ-5D-5L.

Valuation of instruments

From the reviewed 14 capability instruments, only four have a published valuation set. These used the best–worst scaling method, most often relying on the MaxDiff model. Informants mainly came from the general public. There is no published evidence available for the valuation of the remaining ten capability questionnaires (Table 6).
Table 6

Valuation of capability instruments for health economic evaluations

InstrumentMethods of valuationNumber of choices per BWS taskNumber of BWS tasks per respondentsPopulationNumber of informantsReferences
ASCOTBWS, TTO48General public958 (BWS) + 126 (TTO)[52]
ICECAP-ABWS516General public413[85]
ICECAP-OVariants of DCEs and BWS tasks (online)516General public aged 65 or over255[88]
ICECAP-SCMBWS716General public6020[101, 110]
Valuation of capability instruments for health economic evaluations

Applied economic evaluations and potential methods to incorporate the capability approach

Ten applied evaluations were identified in this review that have used a capability-based instrument as secondary outcome measure in health economic evaluations. No economic evaluation was found where a capability instrument was used as a primary measure of health outcomes. The information extracted from the applied evaluations is presented in Table 7 and in Appendix 6.
Table 7

Applied evaluations using the capability approach in their economic evaluations

Capability measureDiseaseTime pointsOther HE measuresChanges in QALYs vs. capability valuesPresentation of resultsReference
ICECAP-AVisual impairmentBaseline; 2–4 monthsEQ-5D-5LNearly identicalaCost per Year of Full Capability (YFC)[111]
Diabetic plantar ulcerationBaseline; 6 monthsEQ-5D-5LQALYs negative; Capability positiveCost and outcome data presented separately[43]
Drug addictionBaseline; 12 monthsEQ-5D-5LFull capability higher than Sufficient capability, and both higher than QALYsYears of full capability (YFC), years of sufficient capability equivalent (YSC)[112]
SchizophreniaBaseline; 12–36–48 weeksEQ-5D-3LNearly identicalaCost and outcome data presented separately[44]
ICECAP-OHealth decline in the older peopleBaseline; 3 monthsEQ-5D-3LQALYs positive; Capability negativeIncremental net monetary benefit (INMB) regressions based on capability QALYs[31]
Heart failure, chronic obstructive pulmonary disease, or diabetesBaseline; 12 monthsEQ-5D-3LNearly identicalaWillingness to pay for 100% improvement in capability[113]
Visual impairment3 months; post-intervention; pre-studyEQ-5D-5LCapability higher than QALYsCosts per years of well-being[46]
Hip fractureBaseline; 3 monthsEQ-5D-3LCapability lower than QALYsCost and outcome data presented separately[42]
OxCAP-MHPsychosisBaseline; 6–12 monthsEQ-5D-3LNearly identicalaCost and outcome data presented separately[45]
ICECAP-A and OxCAP-MHSchizophrenia or schizoaffective disorder and depressionBaseline, 3–6–9 monthsEQ-5D-5LQALYs positive; Capability: no significant changeCost and outcome data presented separately[114]

aNearly identical means that the difference between baseline and follow-up are within a 10% range when comparing the QALYs and capability estimates

Applied evaluations using the capability approach in their economic evaluations aNearly identical means that the difference between baseline and follow-up are within a 10% range when comparing the QALYs and capability estimates The number of economic evaluations reporting the use of a capability instrument has increased in recent years and further increases can be expected given that this search identified a number of recent study protocols (e.g. [41, 42, 114]). Four further studies were identified that specifically addressed the issues and discussed considerations when incorporating the capability approach into health-related economic evaluations. A recent review [13] focused on using the capability approach in health research, not limited to economic evaluations. It identified four distinct common areas of application including: (1) physical activity and diet; (2) patient empowerment; (3) multidimensional poverty and (4) assessments of health and social care interventions. The authors also noted that there is a noticeable non-reliance on health status as a sole indicator of capability in health, and differences were found across studies in approaches to applying mixed methods, selecting capability dimensions and weighting capabilities. The current review identified applied economic evaluations from areas with widely accepted issues related to outcomes beyond the QALYs framework, e.g. mental health, visual impairment, chronic diseases and health decline in older people. The presentation of results in the included economic evaluations demonstrate that there is a lack of consensus regarding the most appropriate way to use capability instruments in economic evaluations. Some authors present cost and outcome data separately and conduct a cost-consequence analysis [42-45], whilst others reported the results following the idea behind the incremental cost-effectiveness ratio (ICER) [31, 46]. This lack of consensus about the use of capability instruments in decision making relates to the different approaches taken by different research groups to valuation, which means that in practice these measures are not comparable along the lines of a QALY. The idea of CALYs has been proposed by Mansdotter et al. [47] who highlights the following issues. First, it is questionable which capabilities are able to explain differences in well-being and are sensitive to public policies in high-income countries. Second, questions of the relevant instruments should capture voluntary and involuntary positions because an applied conceptualization of the capability approach includes opportunity as well as achievement. Third, methods for weighting capability and threshold values should be established, similar to QALYs. Finally, a trade-off should be made between the maximisation of capability and equity. Mitchell et al. [48] proposed the concept of years of sufficient capability which is more closely aligned to the theory underpinning the capability approach because it has a greater focus on those in capability poverty. The process of defining a threshold for sufficient capability should be based on generating a sufficient capability score and using these scores to produce a capability outcome over time [48]. The use of ICECAP-A in the economic evaluations included in this literature review seem to focus on the choice between the options of years of full capability vs. years of sufficient capability equivalent [48]. The current state of the art identified in the reported economic evaluations applying the capability approach to their assessment are in line with the previously identified main challenges [50], including the need to research what the value of a capability improvement is, how to use the instruments globally, and compare the sensitivity of each measure to different patient groups and conditions. Only one study [49] was identified that posed a critique to using the capability approach in health economic evaluations. The authors claim that the method used in the questionnaires to measure capability will result in a capability set that is an inaccurate description of the individual’s true capability set. The measured capability set will either represent only one combination and ignore the value of choice in the capability set, or represent one combination that is not actually achievable by the individual. In addition, existing methods of valuing capability may be inadequate because they do not consider that capability is a set. (Although the Oxford instruments were developed based on Nussbaum’s 10 basic human capabilities.) Hence, it may be practically more feasible to measure and value capability approximately rather than directly. Nevertheless, the argument is based on the questionable assumption that all capabilities have to be traded against other capabilities.

Discussion

This systematic literature review about capability instruments in economic evaluations of health-related interventions included 98 articles and identified 14 capability-based instruments. It provides a unique, comprehensive synthesis of the relevant evidence by focusing on the full spectrum of potentially available capability measures and summarising the practical and theoretical aspects of use of these instruments in economic evaluations. Most identified information related to the ASCOT, ICECAP-A, ICECAP-O and OxCAP-MH instruments. The development of capability instruments relies on methods similar to those applied in the case of HRQoL measures. Capability instruments were often compared to EQ-5D, but less often to each other. Possible reasons for this are that some instruments are population or disease-specific, and that the inclusion of two instruments measuring the same concept in an applied evaluation study is assumed to unnecessarily increase participants’ completion burden. In general, the information identified in the literature regarding the comparison of capability measures with other instruments could not be used for a pooled analysis. This is mainly due to the vast variation in the correlation measures used, the instruments compared, the characteristics of the populations and the number of informants. Despite the diverse quantitative estimates for the correlations with EQ-5D, the different capability instruments and the limited available data, this review confirms that capability measures capture a wider range of outcomes than the EQ-5D and may be more responsive when an intervention is likely to have broad impacts on HRQoL. Following the guidelines [51] to evaluate the strength of correlations, this generally observed moderate-to-high correlation suggests that EQ-5D and capability instruments measure somewhat similar, yet complementary concepts. However, there are competing statements in the literature regarding the association between capability and HRQoL instruments. Most authors argue that these measures complement each other; however, some studies suggest that capability instruments could be perceived as enhancements of the HRQoL concept. It is possible that this relationship depends on the choice of both capability and health instruments used in these comparisons. For instance, the OxCAP-MH has a relatively high number of items, which potentially capture a broader range of capability concepts than measures such as the ICECAP measures. Similarly, the EQ-5D measure of health has a narrower focus than other health measures such as measures based on SF-36 or the AQoL. The higher correlations between capability instruments and the EQ-5D-VAS scores than those observed between capability instruments and the EQ-5D utility scores suggest that respondents’ overall judgement of their health status on a VAS seems to reflect better broader quality-of-life concepts present in the capability approach than specific scores for a certain limited number of HRQoL dimensions. Moreover, the differences in correlations found between measures may be due to differences in the populations studied. Hence, further research could explore which population subgroups and disease areas could benefit from the inclusion of certain capability instruments in economic evaluations. Three of the identified 14 capability instruments were used in applied economic evaluation of interventions in the health and social care field; however, only as secondary outcome measures. Eight of the identified ten applied economic evaluations were conducted in the United Kingdom. This may be the result of the fact that the measures were developed in the UK and only available in English for some years. From the perspective of (health) economists concerned with economic evaluations, a good outcome measure should possess three main characteristics [2]. First, it should be comparable among diseases and interventions to allow for interpretation in a comparative way for resource allocation purposes. The capability instruments identified in this literature review were developed for specific population groups; hence, a comparison is currently challenging without a standard application of, for instance, the CALYs framework. Second, the instruments should have a scale with interval properties. All instruments provide a summary score; however, only a few are anchored and therefore have interval properties. The ICECAP scores are anchored on no capability and full capability, and the ASCOT scales are anchored on death and full capability. Finally, most economists are looking for an outcome measure for economic evaluation that reflects preferences, either of individual patients or the general public. Instruments with tariffs derived from the general population (ASCOT, ICECAP-A and ICECAP-SCM) or the relevant subpopulation (ICECAP-O) possess this characteristic. On the other hand, reducing capabilities information only to a single, preference-based index value on a scale of 0–1 may limit the actionable policy relevance of the information [39]. The two approaches, however, are not mutually exclusive and more research is needed about the relative values of different capabilities and their variance according to population specifics (e.g. age, disease experience, culture). More information about the weights people allocate to the attributes and levels of capability instruments would be needed to improve our understanding of the relative value of individual capability domains and dimensions. Major limitations of this study design include that the search was limited to English and German. Next, this review only assessed instruments and studies reported in the literature, and a thorough grey literature search could not be conducted due to difficulties with the search term capability. In terms of grey literature, only dedicated websites of capability instruments were reviewed for relevant information. This resulted in some limitations, for instance, some cost-effectiveness components of studies that have used ASCOT have not been written up as journal articles and fell therefore outside the findings of this review [118, 119]. Furthermore, ongoing research and developments could not be included which could be important in such a dynamically moving area. For example, we found information about ongoing economic evaluations [41, 42, 114] with the identified instruments where results expected to be published soon, additional capability instruments might have been used in unpublished economic evaluations, or some are currently under development. There is a potential need to update this literature review in the future to gather information from this rapidly growing body of literature about the potential development of additional capability measures, the further validation of existing ones, the empirical use of capability measures in economic evaluations, and the lessons learned from these applications.

Conclusion

There has been an increasing interest in the application of the capability-based approach in economic evaluations of health-related interventions. Different instruments are available and the choice between them should be based on both the research question and the characteristics of the instruments. Further research should focus on the comparison of the existing capability instruments and examining the correlation across capability measures. This would help future researchers in choosing the most suitable capability instrument for their study and provide further information for instrument developers.
Table 8

List of included papers

AuthorYearReferencesCategoryInstrument(s)
Al-Janabi2012[53]DevelopmentICECAP-A
Al-Janabi2015[77]ValidationICECAP-A
Al-Janabi2013[33]ValidationICECAP-A
Al-Janabi2013[82]ValidationICECAP-A
Bailey2016[29]ValidationICECAP-SCM
Barnes2016[44]EmpiricalICECAP-A
Baumgardt2018[103]ValidationOxCAP-MH
Botes2018[60]DevelopmentCAF
Botes2018[115]ValidationCAF
Bray2017[111]EmpiricalICECAP-A
Burns2016[45]EmpiricalOxCAP-MH
Chen2018[20]ValidationICECAP-A
Coast2008[88]ValuationICECAP-O
Coast2016[100]ValuationICECAP-SCM
Coast2008[40]ValidationICECAP-O
Coast2018[83]ValidationICECAP-A, ICECAP-SCM
Comans2012[97]ValidationICECAP-O
Couzner2012[22]ComparisonICECAP-O
Couzner2013[36]ValidationICECAP-O
Davis2013[25]ComparisonICECAP-O
Davis2016[30]ValidationICECAP-O
Davis2017[35]ValidationICECAP-O
Engel2018[78]ValidationICECAP-A
Engel2018[79]ValidationICECAP-A
Engel2016[89]ValidationICECAP-O
Engel2017[24]ComparisonICECAP-A
Flynn2015[85]ValuationICECAP-A
Forder2011[68]ValidationASCOT
Franklin2018[26]ComparisonICECAP-O
Goranitis2016[34]ComparisonICECAP-A
Goranitis2017[112]EmpiricalICECAP-A
Goranitis2016[23]ValidationICECAP-A
Greco2018[102]Validationlow-income Q
Greco2015[64]Developmentlow-income Q
Grewal2006[54]DevelopmentICECAP-O
Hackert2017[21]ComparisonASCOT, ICECAP-O
Hackert2019[90]ValidationICECAP-O
Handels2018[109]TranslationICECAP-O
Henderson2013[113]EmpiricalICECAP-O
Horder2016[86]ValidationICECAP-O
Horwood2014[91]ValidationICECAP-O
Huynh2017[101]ValuationICECAP-SCM
Jones2017[32]ValidationICECAP-A
Kaambwa2019[69]ValidationASCOT
Karimi2016[49]IncorporationGeneral
Keeley2013[80]ValidationICECAP-A
Keeley2015[81]ValidationICECAP-A
Keeley2016[27]ComparisonICECAP-A
Khan2018[116]ValidationICECAP-A
Kinghorn2015[65]DevelopmentPain Q
Łaszewska2019[17]ComparisonOxCAP-MH
Linton2018[108]ValidationICECAP-A
Looman2014[98]ValidationICECAP-O
Lorgelly2015[63]DevelopmentOCAP-18
Makai2014[6]ValidationASCOT, ICECAP-O
Makai2015[31]EmpiricalICECAP-O
Makai2012[92]ValidationICECAP-O
Makai2014[18]ValidationICECAP-O
Malley2012[70]ValidationASCOT
Mansdotter2017[47]IncorporationGeneral
Milte2014[71]ComparisonASCOT
Milte2018[93]ValidationICECAP-O
Mitchell2017[13]IncorporationGeneral
Mitchell2015[37]ValidationICECAP-A
Mitchell2013[94]ComparisonICECAP-O
Mitchell2015[48]IncorporationGeneral
Mitchell2017[38]ComparisonICECAP-A
Netten2012[52]DevelopmentASCOT
Parker2019[43]EmpiricalICECAP-A
Parsons2014[95]ValidationICECAP-O
Patty2018[46]EmpiricalICECAP-O
Peak2018[84]ValidationICECAP-A
Rand2017[72]ComparisonASCOT
Rand2012[58]DevelopmentASCOT-proxy
Ratcliffe2013[99]ValidationICECAP-O
Sacchetto2016[56]DevelopmentACQ‐CMH‐104
Sacchetto2018[66]ValidationACQ‐CMH‐104
Sarabia-Cobo2017[87]ComparisonICECAP-O
Shiroiwa2018[105]ValidationASCOT
SimonUnpublished[114]EmpiricalOxCAP-MH
Simon2018[117]TranslationOxCAP-MH
Simon2013[39]DevelopmentOxCAP-MH
Stevens2018[73]ComparisonASCOT
Sutton2014[62]DevelopmentICECAP-SCM
Tang2018[107]ComparisonICECAP-A
Towers2015[75]ValidationASCOT
Towers2016[67]ValidationASCOT
Turnpenny2018[57]DevelopmentASCOT Easy Read
Van Leeuwen2015[74]ComparisonASCOT, ICECAP-O
Van Leeuwen2015[106]ValidationASCOT
Van Leeuwen2014[104]ValidationASCOT
Van Leeuwen2015[28]ValidationASCOT, ICECAP-O
Vergunst2017[19]ComparisonOxCAP-MH
Williams2016[42]EmpiricalICECAP-O
Xin2017[96]ComparisonICECAP-O
Table 9

Correlations reported in the included studies

Capabilities instrumentCompared with (long name)Compared with (short name)CountryPopulationNumber of informantsMeasurement of correlationValue of correlationReference
ACQ‐CMH‐104WHOQOL‐BrefWHOQOL‐BrefPortugalPsychiatric patients participating in community mental health organisations129Pearson coefficient0.60[66]
ACQ‐CMH‐104RAS-PRecovery assessment scalePortugalPsychiatric patients participating in community mental health organisations92Pearson coefficient0.46[66]
ASCOTEQ-5D-3LEQ-5D-3LUKDay care for older people224Spearman Rank0.47[68]
ASCOTICECAP-OICECAP-OUKOlder social care users205Spearman Rank0.81[21]
ASCOTEQ-5D-5LEQ-5D-5LUKOlder social care users205Spearman Rank0.63[21]
ASCOTEQ-5D-VASEQ-5D-VASUKOlder social care users205Spearman Rank0.64[21]
ASCOTBarthel IndexBarthel IndexUKOlder social care users205Spearman Rank0.45[21]
ASCOTGDS-15 (negative correlation)GDS-15*UKOlder social care users205Spearman Rank0.69[21]
ASCOTOPQOL-13OPQOL-13UKOlder social care users205Spearman Rank0.76[21]
ASCOTSWLSSWLSUKOlder social care users205Spearman Rank0.74[21]
ASCOTCantril’s LadderCantril’s LadderUKOlder social care users205Spearman Rank0.66[21]
ASCOTOlder People’s Quality-of-Life brief questionnaireOPQoL-BriefAustraliaCommunity-dwelling older people receiving aged care services87Spearman Rank0.58[69]
ASCOTEQ-5D-3LEQ-5D-3LUKOlder people receiving publicly funded home care services301Pearson correlation0.40[70]
ASCOTEQ-5D-5LEQ-5D-5LAustraliaOlder adults in a day rehabilitation facility22Spearman Rank0.24[71]
ASCOTBrief Older People’s Quality of LifeOPQOL-briefAustraliaOlder adults in a day rehabilitation facility22Spearman Rank0.38[71]
ASCOTEQ-5D-3LEQ-5D-3LUKOlder home care residents301Pearson coefficient0.41[52]
ASCOTGHQ-12 (negative correlation)GHQ-12*UKOlder home care residents301Pearson coefficient0.58[52]
ASCOTControl and autonomy subscale of CASP-12CASP-12UKOlder home care residents301Pearson coefficient0.58[52]
ASCOTEQ-5D-3LEQ-5D-3LUKGeneral population200Gradient0.98[73]
ASCOTEQ-5D-3LEQ-5D-3LNetherlandsFrail older adults living at home190Spearman Rank0.41[74]
ASCOTICECAP-OICECAP-ONetherlandsFrail older adults living at home190Spearman Rank0.41[74]
ASCOTEQ-5D-3LEQ-5D-3LUKCommunity-based adult social care service users748Spearman Rank0.37[72]
ASCOTICECAP-OICECAP-OUKCommunity-based adult social care service users748Spearman Rank0.67[72]
ASCOTICECAP-AICECAP-AUKCommunity-based adult social care service users748Spearman Rank0.62[72]
ASCOT-CarerCarer Experience Scale (CES)CESUKSocial care recipients376Spearman Rank0.58[76]
ASCOT-CarerCarer Strain Index (negative correlation)CSIUKSocial care recipients384Spearman Rank− 59[76]
ASCOT-CarerEQ-5D-3LEQ-5D-3LUKSocial care recipients382Spearman Rank0.34[76]
ASCOT-CarerQoL (single item using a 7-point Likert scale)QoLUKSocial care recipients384Spearman Rank0.62[76]
ICECAP-AAssessment of Quality of LifeAQoL-8DAustralia, Canada, Germany, Norway, UK, USAPatients with seven chronic conditions and a sample of the ‘healthy’ public8022Spearman Rank0.80[20]
ICECAP-AEQ-5D-5LEQ-5D-5LAustralia, Canada, Germany, Norway, UK, USAPatients with seven chronic conditions and a sample of the ‘healthy’ public8022Spearman Rank0.60[20]
ICECAP-A15D15D6 countries (MIC)Representative healthy cohort and from patients in eight clinical areas6756Pearson coefficient (average of correlations among factors)0.50[24]
ICECAP-AAQoL-8DAQoL-8D6 countries (MIC)Representative healthy cohort and from patients in eight clinical areas6756Pearson coefficient (average of correlations among factors)0.31[24]
ICECAP-AEQ-5D-5LEQ-5D-5L6 countries (MIC)Representative healthy cohort and from patients in eight clinical areas6756Pearson coefficient (average of correlations among factors)0.49[24]
ICECAP-AHUI-3HUI-36 countries (MIC)Representative healthy cohort and from patients in eight clinical areas6756Pearson coefficient (average of correlations among factors)0.32[24]
ICECAP-ASF-6DSF-6D6 countries (MIC)Representative healthy cohort and from patients in eight clinical areas6756Pearson coefficient (average of correlations among factors)0.47[24]
ICECAP-AHUI-3HUI-3Australia, Canada, Germany, Norway, UK, and USAIndividuals with self-reported depression917R20.46[79]
ICECAP-ASF-6DSF-6DAustralia, Canada, Germany, Norway, UK, and USAIndividuals with self-reported depression917R20.36[79]
ICECAP-A15D15DAustralia, Canada, Germany, Norway, UK, and USAIndividuals with self-reported depression917R20.42[79]
ICECAP-AAssessment of Quality-of-Life Multi-Attribute Utility InstrumentAQoL-8DAustralia, Canada, Germany, Norway, UK, and USAIndividuals with self-reported depression917R20.58[79]
ICECAP-AEQ-5D-5LEQ-5D-5LAustralia, Canada, Germany, Norway, UK, and USAIndividuals with self-reported depression917R20.34[79]
ICECAP-AEQ-5D-5LEQ-5D-5LCanadaPatients with Spinal Cord Injury364Path analysis0.37[78]
ICECAP-AAssessment of Quality-of-Life Multi-Attribute Utility InstrumentAQoL-8DCanadaPatients with Spinal Cord Injury364Path analysis0.54[78]
ICECAP-ALeeds Dependence Questionnaire (negative correlation)LDQ*UKIndividuals receiving opiate substitution treatment for more than 12 months83Pearson coefficient0.48[34]
ICECAP-ASocial Satisfaction QuestionnaireSSQUKIndividuals receiving opiate substitution treatment for more than 12 months83Pearson coefficient0.43[34]
ICECAP-AEQ-5D-3LEQ-5D-3LUKWomen with lower urinary tract symptoms478Pearson coefficient0.53[23]
ICECAP-AEQ-5D-3LEQ-5D-3LUKKnee pain patients in primary care500Spearman Rank0.49[27]
ICECAP-A36-Item Short Form Health SurveySF-36Australia, Canada, Germany, Norway, UK, USAPatients with seven chronic conditions and a sample of the ‘healthy’ public8022R20.57[116]
ICECAP-A36-Item Short Form Health SurveyAQoL-8DAustralia, Canada, Germany, Norway, UK, USAPatients with seven chronic conditions and a sample of the ‘healthy’ public8022R20.71[116]
ICECAP-AEQ-5D-5LEQ-5D-5LGermanyHealthy Samples and Seven Health Condition Groups1212Pearson coefficient0.62[108]
ICECAP-ASWLSSWLSGermanyHealthy Samples and Seven Health Condition Groups1212Pearson coefficient0.66[108]
ICECAP-ASF-6DSF-6DGermanyHealthy Samples and Seven Health Condition Groups1212Pearson coefficient0.64[108]
ICECAP-ADepression, Anxiety and Stress ScaleDASS-D4 English speaking countries of MICIndividuals with depression617R2?[38]
ICECAP-AKessler Psychological Distress ScaleK104 English speaking countries of MICIndividuals with depression617R2?[38]
ICECAP-AEQ-5D-3LEQ-5D-3LChinaGeneral population975Polychoric correlation coefficient0.45[107]
ICECAP-OEQ-5D-3LEQ-5D-3LUKGeneral population aged 65 and over315Chi-squared tests0.42 (Attachment), 0.008** (Security), < 0.001** (Role), < 0.001** (Enjoyment), < 0.001** (Control)[40]
ICECAP-OEQ-5DEQ-5D-3LAustraliaPatients from an outpatient day rehabilitation unit80Spearman Rank0.44[22]
ICECAP-OCTM-3CTM-3AustraliaPatients from an outpatient day rehabilitation unit82Spearman Rank0.23[22]
ICECAP-OEQ-5DEQ-5D-3LCanadaParticipants visiting the Vancouver Falls Prevention Clinic215Spearman Rank0.47[25]
ICECAP-OEQ-5D-3LEQ-5D-3LUKAged over 65 years, requiring a hospital visit and/or care home resident, and recruited to one of 3 studies forming the Medical Crisis in Older People (MCOP) programme584R20.35[26]
ICECAP-OEQ-5D-5LEQ-5D-5LUKOlder social care users207Spearman Rank0.68[21]
ICECAP-OEQ-5D-VASEQ-5D-VASUKOlder social care users208Spearman Rank0.66[21]
ICECAP-OBarthel IndexBarthel IndexUKOlder social care users209Spearman Rank0.49[21]
ICECAP-OGDS-15 (negative correlation)GDS-15*UKOlder social care users210Spearman Rank0.73[21]
ICECAP-OOPQOL-13OPQOL-13UKOlder social care users211Spearman Rank0.80[21]
ICECAP-OSWLSSWLSUKOlder social care users212Spearman Rank0.82[21]
ICECAP-OCantril’s LadderCantril’s LadderUKOlder social care users213Spearman Rank0.74[21]
ICECAP-OEQ-5D-5LEQ-5D-5LUKPeople aged 70 and older516Spearman Rank0.63[90]
ICECAP-OBarthel IndexBarthel IndexGermanyNursing Home Residents with Dementia95Pearson coefficient0.72[18]
ICECAP-OEQ-5D-3LEQ-5D-3LGermanyNursing Home Residents with Dementia95Pearson coefficient0.69[18]
ICECAP-OADRQLADRQLGermanyNursing Home Residents with Dementia95Pearson coefficient0.53[18]
ICECAP-OEQ-5D-3LEQ-5D-3LAustraliaOlder people following surgery for hip fracture87Spearman Rank0.53[93]
ICECAP-OWestern Ontario and McMaster UniversitiesWOMACUKOsteoarthritis patients requiring joint replacement105R20.40[94]
ICECAP-OEQ-5D-3LEQ-5D-3LUKParticipants aged 65 years and over with an intracapsular fracture of the hip113Pearson coefficient0.34[95]
ICECAP-OOxford Hip ScoreOHSUKParticipants aged 65 years and over with an intracapsular fracture of the hip113Pearson coefficient0.38[95]
ICECAP-OBarthel Index measure of activities of daily livingBarthel IndexSpainNursing professionals serving as proxy respondents for dementia patients217Not reported0.68[87]
ICECAP-OAlzheimer’s Disease-Related Quality of LifeADRQLSpainNursing professionals serving as proxy respondents for dementia patients217Not reported0.61[87]
ICECAP-OEQ-5D extended with a cognitive dimensionEQ-5D + CSpainNursing professionals serving as proxy respondents for dementia patients217Not reported0.62[87]
ICECAP-OEQ-5D-3LEQ-5D-3LNetherlandsFrail older adults living at home190Spearman Rank0.63[74]
ICECAP-OParkinson’s specific QoLPDQ-39?People with Parkinson’s1023Not reported0.53[96]
ICECAP-O family versionEQ-5D family versionEQ-5D family versionNetherlandsNursing professionals of psycho-geriatric elderly96Pearson coefficient0.57[92]
ICECAP-O family versionEQ-VAS family versionEQ-VAS family versionNetherlandsFamily members of psycho-geriatric elderly68Pearson coefficient0.43[92]
ICECAP-O nursing versionEQ-5D nursing versionEQ-5D nursing versionNetherlandsNursing professionals of psycho-geriatric elderly96Pearson coefficient0.48[92]
ICECAP-O nursing versionEQ-VAS nursing versionEQ-VAS nursing versionNetherlandsFamily members of psycho-geriatric elderly68Pearson coefficient0.55[92]
OxCAP-MHEQ-5D-index UKEQ-5D-index UKAustriaPatients in socio-psychiatric services159Spearman Rank0.67[17]
OxCAP-MHEQ-5D-index DEEQ-5D-index DEAustriaPatients in socio-psychiatric services160Spearman Rank0.66[17]
OxCAP-MHEQ-5D VASEQ-5D VASAustriaPatients in socio-psychiatric services161Spearman Rank0.58[17]
OxCAP-MHBSI-18BSI-18AustriaPatients in socio-psychiatric services162Spearman Rank− 67[17]
OxCAP-MHWHOQOL-BREF Physical healthWHOQOL-BREF Physical healthAustriaPatients in socio-psychiatric services163Spearman Rank0.69[17]
OxCAP-MHWHOQOL-BREF PsychologicalWHOQOL-BREF PsychologicalAustriaPatients in socio-psychiatric services164Spearman Rank0.75[17]
OxCAP-MHWHOQOL-BREF Social relationshipsWHOQOL-BREF Social relationshipsAustriaPatients in socio-psychiatric services165Spearman Rank0.50[17]
OxCAP-MHWHOQOL-BREF EnvironmentWHOQOL-BREF EnvironmentAustriaPatients in socio-psychiatric services166Spearman Rank0.69[17]
OxCAP-MHMini-ICF-APPMini-ICF-APPAustriaPatients in socio-psychiatric services167Spearman Rank− 0.47[17]
OxCAP-MHGlobal Assessment of FunctioningGAFAustriaPatients in socio-psychiatric services168Spearman Rank0.35[17]
OxCAP-MHEQ-5D-3L UtilityEQ-5D-3LUKPatients with psychosis172Pearson coefficient0.45[19]
OxCAP-MHEuroQol Visual Analogue ScaleEQ-5D-VASUKPatients with psychosis172Pearson coefficient0.52[19]
OxCAP-MHBrief Psychiatric Rating Scale (negative correlation)BPRS*UKPatients with psychosis172Pearson coefficient0.41[19]
OxCAP-MHGlobal Assessment of FunctioningGAFUKPatients with psychosis172Pearson coefficient0.24[19]
OxCAP-MHObjective Social Outcomes IndexSIXUKPatients with psychosis172Pearson coefficient0.12[19]
Women’s Capabilities IndexWHOQOL-BrefWHOQOL-BrefMalawiWomen from Mchinji, Malawi20Pearson correlation0.62[64]
Table 10

Abbreviations of health-related instruments

Short formFull name of instrument
15D15D
SF-3636-Item Short Form Health Survey
ADRQLAlzheimer’s Disease-Related Quality of Life
AQoL-8DAssessment of Quality-of-Life Multi-Attribute Utility Instrument
Barthel IndexBarthel Index measure of activities of daily living (ADL)
OPQOL-briefbrief Older People’s Quality of Life
BPRSBrief Psychiatric Rating Scale
BSI-18brief symptom inventory 18
Cantril’s LadderCantril’s Ladder
CESCarer Experience Scale
CSICarer Strain Index
CASP-12Control and autonomy subscale of CASP-12
CTM-3Care Transitions Measure
DASS-DDepression, Anxiety and Stress Scale (DASS-D of DASS-21)
EQ-5D + CEQ-5D extended with a cognitive dimension
EQ-5D-VASEuroQol Visual Analogue Scale
GDS-1515-item Geriatric Depression Scale
GHQ-1212-item General Health Questionnaire
GAFGlobal Assessment of Functioning
HUI-3Health Utilities Index Mark 3
K10Kessler Psychological Distress Scale
LDQLeeds Dependence Questionnaire
Mini-ICF-APPMini-ICF-APP Social Functioning Scale
SIXObjective Social Outcomes Index
OPQoL-BriefOlder People’s Quality-of-Life brief questionnaire (13 items)
OHSOxford Hip Score
PDQ-39Parkinson’s specific Quality of Life
RAS-PRecovery Assessment Scale
SF-6DShort Form Six Dimension
SSQSocial Satisfaction Questionnaire
SWLSSatisfaction with Life Scale
WOMACWestern Ontario and McMaster Universities
WHOQOL-BrefWorld Health Organization Quality-of-Life Instruments - abbreviated version
Table 11

Details of applied evaluations

Author, YearCountryDiseaseInterventionPopulationPerspectiveCapability measureTime pointsMissing data
Barnes, 2016UKSchizophreniaCitalopram (ACTIONS trial)Adult patientsSocietalICECAP-ABaseline; 12–36–48 weeksMultiple imputation
Bray, 2017UKVisual impairmentPortable electronic vision enhancement system (compared with optical low vision aids)Adult patientsSocietalICECAP-ABaseline; 2 months; 4 monthsNot reported
Burns, 2016UKPsychosisCommunity treatment ordersAdult patientsHealth and social careOxCAP-MHBaseline; 6 months; 12 monthsMultiple imputation
Goranitis, 2017UKDrug addiction2 Psychological interventions relative to usual careTreatment resistant adult addictsHealth and social careICECAP-ABaseline; 12 monthsChained equations with predictive mean matching
Henderson, 2013UKHeart failure, chronic obstructive pulmonary disease, or diabetesCommunity-based telehealth (Whole Systems Demonstrator)People with a long-term conditionSocietalICECAP-OBaseline; 12 monthsMultiple imputation
Makai, 2014NetherlandsHealth decline in the elderlyWalcheren integrated care modelFrail elderlySocietalICECAP-OBaseline, 3 monthsNot reported
Parker, 2019UKDiabetic plantar ulcerationTraditional vs. digital foot orthosesAdult patientsHealthcare providerICECAP-ABaseline; 6 monthsNot reported
Patty, 2018NetherlandsVisual impairmentICT trainingAdult patientsSocietalICECAP-O3 months; post-intervention; pre-studyNot reported
Simon, unpublishedUKSchizophrenia or schizoaffective disorder and depressionPositive Memory Training (PoMeT)Adult patients(1) Healthcare, (2) Health and social care, (3) Broader societalICECAP-A and OxCAP-MHBaseline, 3, 6 and 9 monthsStepwise approach
Williams, 2016UKHip fractureMultidisciplinary rehabilitation package following hip fractureOlder adults (aged ≥ 65)Healthcare providerICECAP-OBaseline, 3 monthsNot reported
  92 in total

Review 1.  Systematic review of the psychometric properties, interpretability and feasibility of self-report pain intensity measures for use in clinical trials in children and adolescents.

Authors:  Jennifer N Stinson; Tricia Kavanagh; Janet Yamada; Navreet Gill; Bonnie Stevens
Journal:  Pain       Date:  2006-06-13       Impact factor: 6.961

Review 2.  Quality of life instruments for economic evaluations in health and social care for older people: a systematic review.

Authors:  Peter Makai; Werner B F Brouwer; Marc A Koopmanschap; Elly A Stolk; Anna P Nieboer
Journal:  Soc Sci Med       Date:  2013-12-04       Impact factor: 4.634

3.  Beyond QALYs: Multi-criteria based estimation of maximum willingness to pay for health technologies.

Authors:  Erik Nord
Journal:  Eur J Health Econ       Date:  2017-03-03

4.  Facilitation of noradrenaline release from sympathetic nerves in rat anococcygeus muscle by activation of prejunctional beta-adrenoceptors and angiotensin receptors.

Authors:  C G Li; H Majewski; M J Rand
Journal:  Br J Pharmacol       Date:  1988-10       Impact factor: 8.739

5.  Investigating Choice Experiments for Preferences of Older People (ICEPOP): evaluative spaces in health economics.

Authors:  Joanna Coast; Terry Flynn; Eileen Sutton; Hareth Al-Janabi; Jane Vosper; Sarita Lavender; Jordan Louviere; Tim Peters
Journal:  J Health Serv Res Policy       Date:  2008-10

6.  QALYs and carers.

Authors:  Hareth Al-Janabi; Terry N Flynn; Joanna Coast
Journal:  Pharmacoeconomics       Date:  2011-12       Impact factor: 4.981

7.  Applications of the Capability Approach in the Health Field: A Literature Review.

Authors:  Paul Mark Mitchell; Tracy E Roberts; Pelham M Barton; Joanna Coast
Journal:  Soc Indic Res       Date:  2016-05-10

8.  Measuring broader wellbeing in mental health services: validity of the German language OxCAP-MH capability instrument.

Authors:  Agata Łaszewska; Markus Schwab; Eva Leutner; Marold Oberrauter; Georg Spiel; Judit Simon
Journal:  Qual Life Res       Date:  2019-04-27       Impact factor: 4.147

9.  Outcomes in Economic Evaluations of Public Health Interventions in Low- and Middle-Income Countries: Health, Capabilities and Subjective Wellbeing.

Authors:  Giulia Greco; Paula Lorgelly; Inthira Yamabhai
Journal:  Health Econ       Date:  2016-02       Impact factor: 3.046

10.  ICECAP-O, the current state of play: a systematic review of studies reporting the psychometric properties and use of the instrument over the decade since its publication.

Authors:  Louise Proud; Carol McLoughlin; Philip Kinghorn
Journal:  Qual Life Res       Date:  2019-01-21       Impact factor: 4.147

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  20 in total

1.  Validation and comparison of five preference-based measures among age-related macular degeneration patients: evidence from mainland China.

Authors:  Yanhui Si; Shunping Li; Yanjiao Xu; Gang Chen
Journal:  Qual Life Res       Date:  2021-12-02       Impact factor: 4.147

2.  Out of Date or Best Before? A Commentary on the Relevance of Economic Evaluations Over Time.

Authors:  Gemma E Shields; Becky Pennington; Ash Bullement; Stuart Wright; Jamie Elvidge
Journal:  Pharmacoeconomics       Date:  2021-12-06       Impact factor: 4.981

3.  Does the relative importance of the OxCAP-MH's capability items differ according to mental ill-health experience?

Authors:  Timea Mariann Helter; Alexander Kaltenboeck; Josef Baumgartner; Franz Mayrhofer; Georg Heinze; Andreas Sönnichsen; Johannes Wancata; Judit Simon
Journal:  Health Qual Life Outcomes       Date:  2022-06-24       Impact factor: 3.077

Review 4.  Ethics of vaccination: Should capability measures be used to inform SARS-CoV-2 vaccination strategies?

Authors:  Michael R Millar; Yannis Gourtsoyannis; Angelina Jayakumar
Journal:  Br J Clin Pharmacol       Date:  2021-05-07       Impact factor: 3.716

5.  Assessing the reliability and validity of the ICECAP-A instrument in Chinese type 2 diabetes patients.

Authors:  Yao Xiong; Hongyan Wu; Judy Xu
Journal:  Health Qual Life Outcomes       Date:  2021-01-06       Impact factor: 3.186

6.  A randomised controlled feasibility study of interpersonal art psychotherapy for the treatment of aggression in people with intellectual disabilities in secure care.

Authors:  Simon S Hackett; Ania Zubala; Katie Aafjes-van Doorn; Thomas Chadwick; Toni Leigh Harrison; Jane Bourne; Mark Freeston; Andrew Jahoda; John L Taylor; Cono Ariti; Rachel McNamara; Lindsay Pennington; Elaine McColl; Eileen Kaner
Journal:  Pilot Feasibility Stud       Date:  2020-11-19

7.  Measuring capabilities in health and physical activity promotion: a systematic review.

Authors:  M Till; K Abu-Omar; S Ferschl; A K Reimers; P Gelius
Journal:  BMC Public Health       Date:  2021-02-15       Impact factor: 3.295

8.  EQ-5D-5L reference values for the German general elderly population.

Authors:  Ole Marten; Wolfgang Greiner
Journal:  Health Qual Life Outcomes       Date:  2021-03-06       Impact factor: 3.186

9.  Capability of well-being: validation of the Hungarian version of the ICECAP-A and ICECAP-O questionnaires and population normative data.

Authors:  Petra Baji; Miklós Farkas; Ágota Dobos; Zsombor Zrubka; László Gulácsi; Valentin Brodszky; Fanni Rencz; Márta Péntek
Journal:  Qual Life Res       Date:  2020-05-28       Impact factor: 4.147

10.  Estimating the monetary value of health and capability well-being applying the well-being valuation approach.

Authors:  Sebastian Himmler; Job van Exel; Werner Brouwer
Journal:  Eur J Health Econ       Date:  2020-09-16
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