Measurement invariance of intuitive cancer risk perceptions across diverse populations: The Cognitive Causation and Negative Affect in Risk scales

Raymond E. Baser; Yuelin Li; Debra Brennessel; M. Margaret Kemeny; Jennifer L. Hay

doi:10.1177/1359105317693910

Measurement invariance of intuitive cancer risk perceptions across diverse populations: The Cognitive Causation and Negative Affect in Risk scales

Raymond E. Baser, Yuelin Li, Debra Brennessel, M. Margaret Kemeny, Jennifer L. Hay

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Intuitive cancer risk perceptions may inform strategies to motivate cancer prevention behaviors. This study evaluated factor structure and measurement invariance of two new measures of intuitive cancer risk, the Cognitive Causation and Negative Affect in Risk scales. Single- and multiple-group confirmatory factor analysis models were fit to responses from three diverse samples. The confirmatory factor analysis models fit the data well, with all comparative fit indices (CFI) ≥ 0.94. Items flagged by chi-square difference tests as potentially non-invariant were largely invariant between samples according to practical fit indices (e.g. ΔCFI). These novel scales may be particularly relevant in diverse, underserved populations.

Original language	English
Pages (from-to)	1221-1232
Number of pages	12
Journal	Journal of Health Psychology
Volume	24
Issue number	9
DOIs	https://doi.org/10.1177/1359105317693910
State	Published - 1 Aug 2019

Keywords

cancer risk perceptions
confirmatory factor analysis
construct validation
diversity
measurement
measurement invariance
risk

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abstract = "Intuitive cancer risk perceptions may inform strategies to motivate cancer prevention behaviors. This study evaluated factor structure and measurement invariance of two new measures of intuitive cancer risk, the Cognitive Causation and Negative Affect in Risk scales. Single- and multiple-group confirmatory factor analysis models were fit to responses from three diverse samples. The confirmatory factor analysis models fit the data well, with all comparative fit indices (CFI) ≥ 0.94. Items flagged by chi-square difference tests as potentially non-invariant were largely invariant between samples according to practical fit indices (e.g. ΔCFI). These novel scales may be particularly relevant in diverse, underserved populations.",

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Measurement invariance of intuitive cancer risk perceptions across diverse populations: The Cognitive Causation and Negative Affect in Risk scales

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Keywords

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