Adaptation and psychometric testing of the Chinese version of the Revised Illness Perception Questionnaire for cervical cancer patients
EUROPEAN JOURNAL OF ONCOLOGY NURSING(2020)
Abstract
Purpose: Illness perception is an important factor that influences psychological distress, coping behaviors, and illness outcomes, and this factor is often assessed by the Revised Illness Perception Questionnaire (IPQ-R). Data regarding illness perception among cervical cancer patients are limited, especially in China. The study aimed to adapt and psychometrically test the Chinese version of the IPQ-R for Cervical Cancer (CIPQ-R-CC). Methods: This was a methodological study. Before the survey, the identity and causal subscales (originally 14 and 18 items, respectively) were adapted. Data were collected from 220 cervical cancer patients (N = 220) from June 2018 to February 2019. Psychometric properties were assessed using explanatory factor analysis, confirmatory factor analysis, Pearson correlation coefficients, one-way analysis of variance, t-tests and Cronbach's alpha coefficients. Results: Eight identity items and twenty-six causal items were included in the CIPQ-R-CC, which showed acceptable content validity (I-CVI = 0.78-1.00, S-CVI = 0.97-0.99). A five-factor solution was obtained from the cause subscale by explanatory factor analysis, and these factors explained 60.19% of the total variance. For Part III of the CIPQ-R-CC, after deleting nine items and respecifying five error covariances, the proposed seven-factor model was confirmed. There were low to moderate correlations between the latent factors (r<0.52). Known-group validity was demonstrated in some groups with different demographic characteristics. The Cronbach's alpha coefficients were also acceptable (0.60-0.88). Conclusion: The CIPQ-R-CC is a reliable and valid tool for assessing illness perception among Chinese cervical cancer patients. Future studies are needed to verify its factor structure and to confirm its theoretical connotation.
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Key words
Cervical cancer,Illness perception,Nursing,Psychometric evaluation,Instrument development,Factor analysis
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