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Underlying dimensions of the five health-related quality-of-life measures used in utility assessment: evidence from the National Health Measurement Study.

ABSTRACT: Preference-weighted health-related quality-of-life (HRQoL) indexes produce a summary score from discrete health states determined by questions falling into several attributes, such as pain and mobility. Values of HRQoL are used alongside other health outcomes to monitor the health of populations.The purpose of this study was to examine among US adults, the underlying factor structure of HRQoL attribute scores across 5 indexes of HRQoL: EuroQol-5 Dimension, Health Utilities Index Mark 2, Health Utilities Index Mark 3, Short Form-6 Dimension, and Quality of Well-Being Scale Self-Administered form.The National Health Measurement Study surveyed a nationally representative sample of 3844 noninstitutionalized adults aged 35 to 89 years residing in the continental US. Simultaneous data on all 5 indexes were collected cross-sectionally from June 2005 to August 2006. Exploration of underlying dimensions of HRQoL was done by categorical exploratory factor analysis of HRQoL indexes' attribute scores. Item response theory was applied to explore the amount of information HRQoL attributes contribute to the underlying latent dimensions.Three main dimensions of HRQoL emerged: physical, psychosocial, and pain. Most HRQoL index attributes contributed to the physical or psychosocial dimension. The 3 dimensions were correlated: 0.47 (physical and psychosocial), 0.57 (physical and pain), 0.46 (psychosocial and pain). Some HRQoL index attributes displayed relatively more unique variance: HUI3 hearing, speech, and vision, and some contributed to more than 1 dimension The identified factor structure fit the HRQoL data well (Comparative Fit Index = 0.98, Tucker-Lewis Index = 0.98, and Root Mean Square Error of Approximation = 0.042).The attributes of 5 commonly used HRQoL indexes share 3 underlying latent dimensions of HRQoL, physical, psychosocial, and pain.

SUBMITTER: Cherepanov D

PROVIDER: S-EPMC3635481 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Underlying dimensions of the five health-related quality-of-life measures used in utility assessment: evidence from the National Health Measurement Study.

Cherepanov Dasha D Palta Mari M Fryback Dennis G DG

Medical care 20100801 8

<h4>Background</h4>Preference-weighted health-related quality-of-life (HRQoL) indexes produce a summary score from discrete health states determined by questions falling into several attributes, such as pain and mobility. Values of HRQoL are used alongside other health outcomes to monitor the health of populations.<h4>Objective</h4>The purpose of this study was to examine among US adults, the underlying factor structure of HRQoL attribute scores across 5 indexes of HRQoL: EuroQol-5 Dimension, He ...[more]

PMID: 20613664

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Project description:National Social Life, Health, and Aging Project (NSHAP) included five unique mental health measures in Waves 1 and 2 that researchers can use to measure the overall emotional health of participants: depressive symptoms, happiness-unhappiness, anxiety symptoms, perceived stress, and felt loneliness. For each, we detail the rationale for its development and explain how to score, analyze, and interpret results.NSHAP developed its measures by modifying traditional short-form scales to improve response efficiency and reduce respondent burden. Scoring protocols and interpretations were developed for each measure. U.S. population estimates for older adults born between 1920 and 1947 were generated using age-eligible samples from Waves 1 and 2.NSHAP's protocols yielded U.S. prevalence rates similar to other nationally representative studies of older adults and comparable between waves. Higher estimates of anxiety symptoms and perceived stress in Wave 2 compared with Wave 1 were explained by age, administration mode, and time period. Analytic strategies for longitudinal analyses are provided. In Wave 2, mental health generally was worse at older ages, with women having more symptoms at younger ages than men. Women had fewer anxiety symptoms at the oldest ages.NSHAP's mental health measures were successfully integrated into the project's survey and showed acceptable external reliability as well as moderately stable individual characteristics across the 5 years between Waves 1 and 2. Depressive symptoms and unhappiness may form a mental health cluster in the elderly, distinct from anxiety symptoms, perceived stress, and felt loneliness. Gender differences in age-specific patterns of mental health were evident using the exact age of participants rather than the traditional decade groupings. Administration mode and time period (between 2005-2006 and 2010-2011) were determined to be potential confounds that need to be accommodated in longitudinal analyses of aging, whereas sample composition was not an issue for interpreting mental health measures.

Project description:The purpose of the study was to examine whether gender differences in summary health-related quality of life (HRQoL) are due to differences in specific dimensions of health, and whether they are explained by sociodemographic and socioeconomic (SES) variation.The National Health Measurement Study collected cross-sectional data on a national sample of 3648 black and white noninstitutionalized adults ages 35 to 89 years. Data included the Short Form 36-Item survey, which yielded separate Mental and Physical Component Summary scores (MCS and PCS, respectively), and five HRQoL indexes: Short Form 6 dimension, EuroQol 5 dimension, the Health Utilities Indexes Mark 2 and 3, and the Quality of Well-Being Scale Self-Administered form. Structural equation models were used to explore gender differences in physical, psychosocial, and pain latent dimensions of the 5 indexes, adjusting for sociodemographic and SES indicators. Observed MCS and PCS scores were examined in regression models to judge robustness of latent results.Men had better estimated physical and psychosocial health and less pain than women with similar trends on the MCS and PCS scores. Adjustments for marital status or income reduced gender differences more than did other indicators. Adjusting results for partial factorial invariance of HRQoL attributes supported the presence of gender differentials, but also indicated that these differences are impacted by dimensions being related to some HRQoL attributes differently by gender.Men have better estimated health on 3 latent dimensions of HRQoL-physical, psychosocial, and pain-comparable to gender differences on the observed MCS and PCS scores. Gender differences are partly explained by sociodemographic and SES factors, highlighting the role of socioeconomic inequalities in perpetuating gender differences in health outcomes across multiple domains. These results also emphasize the importance of accounting for measurement invariance for meaningful comparison of group differences in estimated means of self-reported measures of health.

Project description:BACKGROUND:Patients are at risk for harm when treated simultaneously by healthcare providers from different healthcare organisations. To assess current practice and improvements of transitional patient safety, valid measurement tools are needed. AIM AND METHODS:To identify and appraise all measurement tools and outcomes that measure aspects of transitional patient safety, PubMed, Cinahl, Embase and Psychinfo were systematically searched. Two researchers performed the title and abstract and full-text selection. First, publications about validation of measurement tools were appraised for quality following COSMIN criteria. Second, we inventoried all measurement tools and outcome measures found in our search that assessed current transitional patient safety or the effect of interventions targeting transitional patient safety. RESULTS:The initial search yielded 8288 studies, of which 18 assessed validity of measurement tools of different aspects of transitional safety, and 191 assessed current transitional patient safety or effect of interventions. In the validated measurement tools, the overall quality of content and structural validity was acceptable; other COSMIN criteria, such as reliability, measurement error and responsiveness, were mostly poor or not reported. In our outcome inventory, the most frequently used validated outcome measure was the Care Transition Measure (n = 9). The most frequently used non-validated outcome measures were: medication discrepancies (n = 98), hospital readmissions (n = 55), adverse events (n = 34), emergency department visits (n = 33), (mental or physical) health status (n = 28), quality and timeliness of discharge summary, and patient satisfaction (n = 23). CONCLUSIONS:Although no validated measures exist that assess all aspects of transitional patient safety, we found validated measurement tools on specific aspects. Reporting of validity of transitional measurement tools was incomplete. Numerous outcome measures with unknown measurement properties are used in current studies on safety of care transitions, which makes interpretation or comparison of their results uncertain.

Project description:Several measurement tools commonly used in face-to-face neurological rehabilitation have been used in telerehabilitation. However, it is not known whether these tools have adequate measurement properties and clinical utility. This systematic review aims to investigate the measurement properties and the clinical utility of measurement tools used in telerehabilitation in individuals with neurological diseases. A systematic review to investigate the measurement properties and clinical utility of measurement tools used in telerehabilitation in individuals with neurological conditions will be conducted. This systematic review will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. this systematic review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) on 28 May 2021 (registration number: CRD42021257662). Electronic searches will be performed in following databases: Medical Literature Analysis and Retrieval System Online (MEDLINE Ovid), Excerpta Medica Database (Embase Classic + Embase Ovid), Physiotherapy Evidence Database (PEDro), Scientific Electronic Library Online (Scielo), and Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS). Two trained independent reviewers will select the studies according to the inclusion criteria, and will also extract the data, evaluate the clinical utility and methodological quality. The relevant data such as design, participants, settings, and mode of administration, measurement properties, and clinical utility will be summarized. Disagreements between reviewers will be resolved by consensus or by the decision of a third independent reviewer. Hand searches of other relevant studies will be employed. The COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) checklist and the clinical utility scale will be used to assess the methodological quality and clinical utility of these tools, respectively. This systematic review will provide information regarding the measurement properties and the clinical utility of the measurement tools used in neurological telerehabilitation. This information will be useful to assist health professionals in choosing adequate measurement tools and planning new research studies.

Project description:Background Synthetic tabular data generation is a potentially valuable technology with great promise for data augmentation and privacy preservation. However, prior to adoption, an empirical assessment of generated synthetic tabular data is required across dimensions relevant to the target application to determine its efficacy. A lack of standardized and objective evaluation and benchmarking strategy for synthetic tabular data in the health domain has been found in the literature.Objective The aim of this paper is to identify key dimensions, per dimension metrics, and methods for evaluating synthetic tabular data generated with different techniques and configurations for health domain application development and to provide a strategy to orchestrate them.Methods Based on the literature, the resemblance, utility, and privacy dimensions have been prioritized, and a collection of metrics and methods for their evaluation are orchestrated into a complete evaluation pipeline. This way, a guided and comparative assessment of generated synthetic tabular data can be done, categorizing its quality into three categories ("Excellent," "Good," and "Poor"). Six health care-related datasets and four synthetic tabular data generation approaches have been chosen to conduct an analysis and evaluation to verify the utility of the proposed evaluation pipeline.Results The synthetic tabular data generated with the four selected approaches has maintained resemblance, utility, and privacy for most datasets and synthetic tabular data generation approach combination. In several datasets, some approaches have outperformed others, while in other datasets, more than one approach has yielded the same performance.Conclusion The results have shown that the proposed pipeline can effectively be used to evaluate and benchmark the synthetic tabular data generated by various synthetic tabular data generation approaches. Therefore, this pipeline can support the scientific community in selecting the most suitable synthetic tabular data generation approaches for their data and application of interest.

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Underlying dimensions of the five health-related quality-of-life measures used in utility assessment: evidence from the National Health Measurement Study.

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Underlying dimensions of the five health-related quality-of-life measures used in utility assessment: evidence from the National Health Measurement Study.

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