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Quality of Life Research

Gepubliceerd in:

01-06-2009

Measuring stigma across neurological conditions: the development of the stigma scale for chronic illness (SSCI)

Auteurs: Deepa Rao, Seung W. Choi, David Victorson, Rita Bode, Amy Peterman, Allen Heinemann, David Cella

Gepubliceerd in: Quality of Life Research | Uitgave 5/2009

Abstract

Purpose

Most measures of stigma are illness specific and do not allow for comparisons across conditions. As part of a study of health-related quality of life for people with neurological disorders, our team developed an instrument to assess the stigma for people with chronic illnesses.

Methods

We based item content on literature review, responses from focus groups, and cognitive interviews. We then administered the items to people with neurological disorders for psychometric testing.

Results

Five hundred eleven participants completed items of the stigma scale. Exploratory factor analysis produced two factors that were highly correlated (r = 0.81). Confirmatory factor analysis produced high standardized loadings on an overall stigma factor (0.68–0.94), with poorer loadings on the two sub-domains (−0.12 to 0.53). These results demonstrated a sufficiently unidimensional scale that corresponded with the bifactor model. Item response theory modeling suggested good model fit, and differential item functioning analyses indicated that the 24-item scale showed potential for measurement equivalence across conditions.

Conclusions

Our efforts produced a stigma scale that had promising psychometric properties. Further study can provide additional information about the SSCI and its benefit in measuring the impact of stigma across conditions.

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Titel: Measuring stigma across neurological conditions: the development of the stigma scale for chronic illness (SSCI)
Auteurs: Deepa Rao
Seung W. Choi
David Victorson
Rita Bode
Amy Peterman
Allen Heinemann
David Cella
Publicatiedatum: 01-06-2009
Uitgeverij: Springer Netherlands
Gepubliceerd in: Quality of Life Research / Uitgave 5/2009
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-009-9475-1

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Abstract

Purpose

Methods

Results

Conclusions

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