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

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.

Figures

Figure 1

The process by which stigma affects the person with an undesired condition.

Figure 2. Information function and trait distribution for the Stigma Scale for Chronic Illness items

Note: The information function and standard error are shown as lines within the plot. The distribution of individual trait scores are depicted as a histogram. The hash marks are locations of the category threshold parameters that indicate that the test provides good measurement at moderate to severe levels of stigma.

Figure 3. Probabilities of item endorsement for people with epilepsy and stroke

Note: RMSD = Root Mean Square Deviation.