Reliability and validity of the Japanese version of the Chemotherapy-induced Alopecia Distress Scale

Breast Cancer(2024)

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Abstract
Background The Chemotherapy-induced Alopecia Distress Scale (CADS) is a patient-reported outcome measure for assessing distress associated with Chemotherapy-induced alopecia (CIA). This study aimed to confirm the psychometric validity of the Japanese version of the CADS (CADS-J). Methods A total of 132 patients with breast cancer who developed CIA were asked to complete the CADS-J twice at 2 week intervals to confirm test–retest reliability. The body image domain of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ) breast cancer-specific module, the self-esteem scale from the Rosenberg Self-Esteem Scale, and the emotional domain of the EORTC QLQ Core 30 were used to confirm the convergent validity of the CADS-J. The overall quality of life and physical domains of the EORTC QLQ Core 30 were used to confirm the discriminant validity of the CADS-J. Results In total, 125 participants provided valid responses. The mean age was 52.2 years. The overall Cronbach’s alpha for the CADS-J was 0.903. The intraclass correlation coefficients of the first and second responses were r = 0.874, r = 0.952, r = 0.911, and r = 0.959 for the physical domain, emotional domain, activity domain, and relationship domain, respectively. In terms of convergent validity, the total CADS-J score was moderately correlated with body image ( r = − 0.63), self-esteem ( r = − 0.48), and the emotional domain ( r = − 0.61). Regarding discriminant validity, the total CADS-J score was weakly correlated with the overall quality of life ( r = − 0.34) and physical domain ( r = − 0.24). Conclusions The CADS-J is psychometrically reliable and valid for evaluating the distress caused by CIA. It is expected to be used in daily practice and as an endpoint in various studies.
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Key words
Breast cancer,Chemotherapy-induced alopecia,Chemotherapy-induced Alopecia Distress Scale,Psychometric validation
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