Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add more filters

Database
Country/Region as subject
Language
Journal subject
Affiliation country
Publication year range
1.
Am J Health Promot ; 38(8): 1104-1111, 2024 Nov.
Article in English | MEDLINE | ID: mdl-38767129

ABSTRACT

PURPOSE: To test the validity of a COVID-19 public stigma scale and an attributional model of stigma during the early stages of the pandemic. DESIGN: We administered a cross-sectional survey that included scales related to COVID-19 stigma to U.S. adults. SETTING: We used Amazon MTurk online survey panel to recruit participants in June 2020. SUBJECTS: U.S. adults (N = 170) participated in the study. Participants were average age of 37 and majority were men (61.2%) and White (77.6%). MEASURES: The Stigma Towards Disease Scale (SDS) was adapted to measure public stigma directed towards COVID-19 (SDS-C19). Additional stigma-related measures were adapted for this study. ANALYSIS: Factorial structure of SDS-C19 was assessed using confirmatory factor analysis (CFA). Validity of SDS was examined using Pearson correlations with other stigma measures. We evaluated the attributional model of stigma using structural equation modeling. RESULTS: Internal consistency of SDS-C19 was high and a three-factor model reflecting cognitive, affective, and behavioral factors was supported (χ2 [71, N = 170] =140.954, P = .00, CFI= .946, TLI = .931, RMSEA = .076, SRMR = .087). The SDS-C19 had strong correlations with other stigma-related measures. A blame-mediated attribution model was supported (χ2 [8, N = 170] = 21.793, P = .00, CFI = .976, TLI =.956, RMSEA = .101, SRMR = .058). CONCLUSION: The SDS-C19 is a valid tool for assessing COVID-19 stigma. SDS-C19 and the attribution model can guide public health communication.


Subject(s)
COVID-19 , Social Stigma , Humans , COVID-19/psychology , COVID-19/epidemiology , Male , Female , Adult , Cross-Sectional Studies , Middle Aged , United States , Surveys and Questionnaires , SARS-CoV-2 , Psychometrics , Reproducibility of Results , Pandemics , Factor Analysis, Statistical
SELECTION OF CITATIONS
SEARCH DETAIL