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OFF Episodes occur in people with Parkinson's disease when their medication wears off, and motor and/or non-motor symptoms emerge. Existing measures used to assess OFF Episodes focus on the time spent in OFF Episodes through diaries or by identifying symptoms, but they are limited in their ability to capture the severity and functional impact of OFF episodes. The aim of this study was to develop and validate a new instrument, called "OFFELIA," that measures the impact of OFF episodes on the quality of life of individuals with Parkinson's disease. Participants completed a cross-sectional questionnaire, "Impact and Communication on OFF Periods," while enrolled in the online clinical study Fox Insights. The data collected was used to develop OFFELIA. Psychometric testing was performed on 18 candidate items using classical, exploratory factor analysis, and item response theory methods. 569 individuals with Parkinson's disease completed the questionnaire. All items were retained for the final measure, with 17 items aggregated into two multi-item scales (functioning and psychological well-being) and one item reported separately as it did not function well with the other items (employment). Known group comparisons based on average duration, frequency and unpredictability of OFF episodes indicated that OFFELIA subscales were more sensitive than existing generic and condition-specific measures. Initial evidence supports the validity of OFFELIA, a new instrument that assesses the impact of OFF periods on daily life. This instrument can be used in assessing clinical therapeutic strategies targeting OFF episodes in Parkinson's disease. • OFFELIA is a new patient-reported outcome measure for Parkinson's Disease. • OFFELIA assesses off episodes' impact on quality of life in people with Parkinson's. • Evidence supports validity and reliability of OFFELIA. • OFFELIA aids clinicians assessing treatment's effect on off episodes. • OFFELIA measures impact of interventions on off episodes in trials. [ABSTRACT FROM AUTHOR]

Objectives: Existing measures for estimating quality-adjusted life-years are mostly limited to health-related quality of life. This article presents an overview of the development the EQ-HWB (EQ Health and Wellbeing), which is a measure that encompasses health and wellbeing.Methods: Stages: (1) Establishing domains through reviews of the qualitative literature informed by a conceptual framework. (2) Generation and selection of items to cover the domains. (3) Face validation of these items through qualitative interviews with 168 patients, social care users, general population, and carers across 6 countries (Argentina, Australia, China, Germany, United Kingdom, United States). (4) Extensive psychometric testing of candidate items (using classical, factor analysis, and item response theory methods) on > 4000 respondents in the 6 countries. Stakeholders were consulted throughout.Results: A total of 32 subdomains grouped into 7 high-level domains were identified from the qualitative literature and 97 items generated to cover them. Face validation eliminated 36 items, modified 14, and added 3. Psychometric testing of 64 items found little difference in missing data or problems with response distribution, the conceptual model was confirmed except in China, and most items performed well in the item response theory in all countries. Evidence was presented to stakeholders in 2 rounds of consultation to inform the final selection of items for the EQ-HWB (25-item) and the short version of EQ-HWB (9-items).Conclusions: EQ-HWB measures have been developed internationally for evaluating interventions in health, public health, and social care including the impact on patients, social care users, and carers. [ABSTRACT FROM AUTHOR]

Objectives: The development of measures such as the EQ-HWB (EQ Health and Wellbeing) requires selection of items. This study explored the psychometric performance of candidate items, testing their validity in patients, social carer users, and carers.Methods: Article and online surveys that included candidate items (N = 64) were conducted in Argentina, Australia, China, Germany, United Kingdom, and the United States. Psychometric assessment on missing data, response distributions, and known group differences was undertaken. Dimensionality was explored using exploratory and confirmatory factor analysis. Poorly fitting items were identified using information functions, and the function of each response category was assessed using category characteristic curves from item response theory (IRT) models. Differential item functioning was tested across key subgroups.Results: There were 4879 respondents (Argentina = 508, Australia = 514, China = 497, Germany = 502, United Kingdom = 1955, United States = 903). Where missing data were allowed, it was low (UK article survey 2.3%; US survey 0.6%). Most items had responses distributed across all levels. Most items could discriminate between groups with known health conditions with moderate to large effect sizes. Items were less able to discriminate across carers. Factor analysis found positive and negative measurement factors alongside the constructs of interest. For most of the countries apart from China, the confirmatory factor analysis model had good fit with some minor modifications. IRT indicated that most items had well-functioning response categories but there was some evidence of differential item functioning in many items.Conclusions: Items performed well in classical psychometric testing and IRT. This large 6-country collaboration provided evidence to inform item selection for the EQ-HWB measure. [ABSTRACT FROM AUTHOR]