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Calibrating well-being, quality of life and common mental disorder items: psychometric epidemiology in public mental health research.

ABSTRACT: BACKGROUND:The assessment of 'general health and well-being' in public mental health research stimulates debates around relative merits of questionnaire instruments and their items. Little evidence regarding alignment or differential advantages of instruments or items has appeared to date. AIMS:Population-based psychometric study of items employed in public mental health narratives. METHOD:Multidimensional item response theory was applied to General Health Questionnaire (GHQ-12), Warwick-Edinburgh Mental Well-being Scale (WEMWBS) and EQ-5D items (Health Survey for England, 2010-2012; n = 19 290). RESULTS:A bifactor model provided the best account of the data and showed that the GHQ-12 and WEMWBS items assess mainly the same construct. Only one item of the EQ-5D showed relevant overlap with this dimension (anxiety/depression). Findings were corroborated by comparisons with alternative models and cross-validation analyses. CONCLUSIONS:The consequences of this lack of differentiation (GHQ-12 v. WEMWBS) for mental health and well-being narratives deserves discussion to enrich debates on priorities in public mental health and its assessment.

SUBMITTER: Bohnke JR

PROVIDER: S-EPMC4967770 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Calibrating well-being, quality of life and common mental disorder items: psychometric epidemiology in public mental health research.

Böhnke Jan R JR Croudace Tim J TJ

The British journal of psychiatry : the journal of mental science 20151203 2

<h4>Background</h4>The assessment of 'general health and well-being' in public mental health research stimulates debates around relative merits of questionnaire instruments and their items. Little evidence regarding alignment or differential advantages of instruments or items has appeared to date.<h4>Aims</h4>Population-based psychometric study of items employed in public mental health narratives.<h4>Method</h4>Multidimensional item response theory was applied to General Health Questionnaire (GH ...[more]

PMID: 26635327

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Project description:BackgroundTechnology-assisted clinical interventions are increasingly common in the health care field, often with the proposed aim to improve access to and cost-effectiveness of care. Current technology platforms delivering interventions are largely mobile apps and online websites, although efforts have been made to create more personalized and embodied technology experiences. To extend and improve on these platforms, the field of robotics has been increasingly included in conversations of how to deliver technology-assisted, interactive, and responsive mental health and psychological well-being interventions. Socially assistive robots (SARs) are robotic technology platforms with audio, visual, and movement capabilities that are being developed to interact with individuals socially while also assisting them with management of their physical and psychological well-being. However, little is known about the empirical evidence or utility of using SARs in mental health interventions.ObjectiveThe review synthesizes and describes the nascent empirical literature of SARs in mental health research and identifies strengths, weaknesses, and opportunities for improvement in future research and practice.MethodsSearches in Medline, PsycINFO, PsycARTICLES, PubMed, and IEEE Xplore yielded 12 studies included in the final review after applying inclusion and exclusion criteria. Abstract and full-text reviews were conducted by two authors independently.ResultsThis systematic review of the literature found 5 distinct SARs used in research to investigate the potential for this technology to address mental health and psychological well-being outcomes. Research on mental health applications of SARs focuses largely on elderly dementia patients and relies on usability pilot data with methodological limitations.ConclusionsThe current SARs research in mental health use is limited in generalizability, scope, and measurement of psychological outcomes. Opportunities for expansion of research in this area include diversifying populations studied, SARs used, clinical applications, measures used, and settings for those applications.

Project description:Urbanization and ageing have important implications for public mental health and well-being. Cities pose major challenges for older citizens, but also offer opportunities to develop, test, and implement policies, services, infrastructure, and interventions that promote mental well-being. The MINDMAP project aims to identify the opportunities and challenges posed by urban environmental characteristics for the promotion and management of mental well-being and cognitive function of older individuals.MINDMAP aims to achieve its research objectives by bringing together longitudinal studies from 11 countries covering over 35 cities linked to databases of area-level environmental exposures and social and urban policy indicators. The infrastructure supporting integration of this data will allow multiple MINDMAP investigators to safely and remotely co-analyse individual-level and area-level data. Individual-level data is derived from baseline and follow-up measurements of ten participating cohort studies and provides information on mental well-being outcomes, sociodemographic variables, health behaviour characteristics, social factors, measures of frailty, physical function indicators, and chronic conditions, as well as blood derived clinical biochemistry-based biomarkers and genetic biomarkers. Area-level information on physical environment characteristics (e.g. green spaces, transportation), socioeconomic and sociodemographic characteristics (e.g. neighbourhood income, residential segregation, residential density), and social environment characteristics (e.g. social cohesion, criminality) and national and urban social policies is derived from publically available sources such as geoportals and administrative databases. The linkage, harmonization, and analysis of data from different sources are being carried out using piloted tools to optimize the validity of the research results and transparency of the methodology.MINDMAP is a novel research collaboration that is combining population-based cohort data with publicly available datasets not typically used for ageing and mental well-being research. Integration of various data sources and observational units into a single platform will help to explain the differences in ageing-related mental and cognitive disorders both within as well as between cities in Europe, the US, Canada, and Russia and to assess the causal pathways and interactions between the urban environment and the individual determinants of mental well-being and cognitive ageing in older adults.

Dataset Information

Calibrating well-being, quality of life and common mental disorder items: psychometric epidemiology in public mental health research.

Publications

Calibrating well-being, quality of life and common mental disorder items: psychometric epidemiology in public mental health research.

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