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Abstract Introduction To make efficient use of available resources, decision-makers in healthcare may assess the costs and (health) benefits of health interventions. For interventions aimed at improving mental health capturing the full health benefits is an important challenge. The Mental Health Quality of Life (MHQoL) instrument was recently developed to meet this challenge. Evaluating the pyschometric properties of this instrument in different contexts remains important. Methods A psychometric evaluation of the MHQoL was performed using existing international, cross-sectional data with 7155 respondents from seven European countries (Denmark, France, Germany, Italy, Portugal, The Netherlands, Portugal and the United Kingdom). Reliability was examined by calculating Cronbach’s alpha, a measure of internal consistency of the seven MHQoL dimensions, and by examining the association of the MHQoL sum scores with the MHQoL-VAS scores. Construct validity was examined by calculating Spearman’s rank correlation coefficients between the MHQoL sum scores and EQ-5D index scores, EQ-VAS scores, EQ-5D anxiety/depression dimension scores, ICECAP-A index scores and PHQ-4 sum scores. Results The MHQoL was found to have good internal consistency for all seven countries. The MHQoL sum score and the MHQoL-VAS had a high correlation. Spearman’s rank correlation coefficients were moderate to very high for all outcomes. Conclusion Our results, based on data gathered in seven European countries, suggest that the MHQoL shows favourable psychometrical characteristics. While further validation remains important, the MHQoL may be a useful instrument in measuring mental health-related quality of life in the Western European context.

Introduction: To make efficient use of available resources, decision-makers in healthcare may assess the costs and (health) benefits of health interventions. For interventions aimed at improving mental health capturing the full health benefits is an important challenge. The Mental Health Quality of Life (MHQoL) instrument was recently developed to meet this challenge. Evaluating the pyschometric properties of this instrument in different contexts remains important.Methods: A psychometric evaluation of the MHQoL was performed using existing international, cross-sectional data with 7155 respondents from seven European countries (Denmark, France, Germany, Italy, Portugal, The Netherlands, Portugal and the United Kingdom). Reliability was examined by calculating Cronbach's alpha, a measure of internal consistency of the seven MHQoL dimensions, and by examining the association of the MHQoL sum scores with the MHQoL-VAS scores. Construct validity was examined by calculating Spearman's rank correlation coefficients between the MHQoL sum scores and EQ-5D index scores, EQ-VAS scores, EQ-5D anxiety/depression dimension scores, ICECAP-A index scores and PHQ-4 sum scores.Results: The MHQoL was found to have good internal consistency for all seven countries. The MHQoL sum score and the MHQoL-VAS had a high correlation. Spearman's rank correlation coefficients were moderate to very high for all outcomes.Conclusion: Our results, based on data gathered in seven European countries, suggest that the MHQoL shows favourable psychometrical characteristics. While further validation remains important, the MHQoL may be a useful instrument in measuring mental health-related quality of life in the Western European context. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to develop and psychometrically evaluate a new quality of life measure for use in people with mental health problems—the Mental Health Quality of Life questionnaire (MHQoL). Methods: The MHQoL dimensions were based on prior research by Connell and colleagues, highlighting the seven most important quality of life dimensions in the context of mental health. Items were generated following a systematic review we performed and through inviting expert opinion. A focus group and an online qualitative study (N = 120) were carried out to assess the face and content validity of the MHQoL. The MHQoL was further tested for its internal consistency, convergent validity, known-group validity and test–retest reliability among mental healthcare service users (N = 479) and members of the general population (N = 110). Results: The MHQoL consists of a descriptive system (MHQoL-7D), including s items covering seven dimensions (self-image, independence, mood, relationships, daily activities, physical health, future) and a visual analogue scale of general psychological well-being (MHQoL-VAS). Internal consistency was high (Cronbach's ∝ = 0.85) and correlations between MHQoL-7D scores and related measures (EQ-5D-5L, MANSA, ICECAP-A, and BSI) supported convergent validity. The intraclass correlation coefficient of the MHQoL-7D sum score for test–retest reliability was 0.85. Known-group validity was supported by the ability to detect significant differences in MHQoL-7D levels between service users and the general population, and between groups with different levels of psychological distress. Conclusion: The MHQoL demonstrated favourable psychometric properties and showed promise as a simple and effective measure to assess quality of life in people with mental health problems. [ABSTRACT FROM AUTHOR]

BackgroundProfile instruments are frequently used to assess health-related quality of life and other patient-reported outcomes. However, preference-based measures are required for health-economic cost-utility evaluations.ResultsAlthough regression-based approaches are commonly used to map from profile measures to preference measures, we show that this results in biased estimates because of regression to the mean.ConclusionsLinking (scale-aligning) is proposed as an alternative.

Objective: To assess the evidence on the validity and responsiveness of five commonly used preference-based instruments, the EQ-5D, SF-6D, HUI3, 15D and AQoL, by undertaking a review of reviews.Methods: Four databases were investigated using a strategy refined through a highly sensitive filter for systematic reviews. References were screened and a search for grey literature was performed. Identified citations were scrutinized against pre-defined eligibility criteria and data were extracted using a customized extraction template. Evidence on known group validity, convergent validity and responsiveness was extracted and reviewed by narrative synthesis. Quality of the included reviews was assessed using a modified version of the AMSTAR checklist.Results: Thirty reviews were included, sixteen of which were of excellent or good quality. The body of evidence, covering more than 180 studies, was heavily skewed towards EQ-5D, with significantly fewer studies investigating HUI3 and SF-6D, and very few the 15D and AQoL. There was also lack of head-to-head comparisons between GPBMs and the tests reported by the reviews were often weak. Where there was evidence, EQ-5D, SF-6D, HUI3, 15D and AQoL seemed generally valid and responsive instruments, although not for all conditions. Evidence was not consistently reported across reviews.Conclusions: Although generally valid, EQ-5D, SF-6D and HUI3 suffer from some problems and perform inconsistently in some populations. The lack of head-to-head comparisons and the poor reporting impedes the comparative assessment of the performance of GPBMs. This highlights the need for large comparative studies designed to test instruments' performance. [ABSTRACT FROM AUTHOR]

Measuring quality-adjusted-life years using generic preference-based quality of life measures is common practice when evaluating health interventions. However, there are concerns that measures in common use, such as the EQ-5D and SF-6D, focus overly on physical health and therefore may not be appropriate for measuring quality of life for people with mental health problems. The aim of this research was to identify the domains of quality of life that are important to people with mental health problems in order to assess the content validity of these generic measures. Qualitative semi-structured interviews were conducted with 19 people, recruited from UK mental health services, with a broad range of mental health problems at varying levels of severity. This complemented a previous systematic review and thematic synthesis of qualitative studies on the same topic. Seven domains important to quality of life for people with mental health problems were identified: well-being and ill-being; relationships and a sense of belonging; activity; self-perception; autonomy, hope and hopelessness; and physical health. These were consistent with the systematic review, with the addition of physical health as a domain, and revealed a differing emphasis on the positive and negative aspects of quality of life according to the severity of the mental health problems. We conclude that the content of existing generic preference-based measures of health do not cover this domain space well. Additionally, because people may experience substantial improvements in their quality of life without registering on the positive end of a quality of life scale, it is important that the full spectrum of negative through to positive aspects of each domain are included in any quality of life measure. [ABSTRACT FROM AUTHOR]

Abstract: There are few clearly described utility studies in advanced ovarian cancer, despite the public health importance of condition and the need for preference based measures of quality of life in economic evaluation of the new treatments. We used data clustering techniques to develop health state descriptions based on data from 66 women who completed the EORTC QLQ-C30 over a six month period while receiving chemotherapy for ovarian cancer. The health state descriptions were presented to a group of members of the general public (n =38), via the internet, and preferences elicited using the standard gamble technique. Mean utility values ranged from 0.685 to 0.977, although the range of individual preferences was wider, including values as low as 0.125. This is the first study to use data clustering methods combined with internet preference elicitation in oncology. The resulting health state model is parsimonious, data driven, and incorporates quality of life items tailored to cancer. The estimates therefore meet the needs of policy makers while reflecting more accurately the experience of disease than those based on generic preference measures. [Copyright &y& Elsevier]

Purpose: The Quality of Life Alzheimer's Disease Scale (QoL-AD) is commonly used to assess disease specific health-related quality of life (HRQoL) as rated by patients and their carers. For cost-effectiveness analyses, utilities based on the EQ-5D are often required. We report a new mapping algorithm to obtain EQ-5D indices when only QoL-AD data are available.Methods: Different statistical models to estimate utility directly, or responses to individual EQ-5D questions (response mapping) from QoL-AD, were trialled for patient-rated and proxy-rated questionnaires. Model performance was assessed by root mean square error and mean absolute error.Results: The response model using multinomial regression including age and sex, performed best in both the estimation dataset and an independent dataset.Conclusions: The recommended mapping algorithm allows researchers for the first time to estimate EQ-5D values from QoL-AD data, enabling cost-utility analyses using datasets where the QoL-AD but no utility measures were collected. [ABSTRACT FROM AUTHOR]

Purpose: The Quality of Life Alzheimer's Disease Scale (QoL-AD) is commonly used to assess disease specific health-related quality of life (HRQoL) as rated by patients and their carers. For cost-effectiveness analyses, utilities based on the EQ-5D are often required. We report a new mapping algorithm to obtain EQ-5D indices when only QoL-AD data are available., Methods: Different statistical models to estimate utility directly, or responses to individual EQ-5D questions (response mapping) from QoL-AD, were trialled for patient-rated and proxy-rated questionnaires. Model performance was assessed by root mean square error and mean absolute error., Results: The response model using multinomial regression including age and sex, performed best in both the estimation dataset and an independent dataset., Conclusions: The recommended mapping algorithm allows researchers for the first time to estimate EQ-5D values from QoL-AD data, enabling cost-utility analyses using datasets where the QoL-AD but no utility measures were collected.