Background. Concerns have been raised about whether self-report measures of pain catastrophizing reflect the construct as defined in the cognitive-behavioral literature. We investigated the content of these self-report measures; that is, whether items assess the construct 'pain catastrophizing' and not other theoretical constructs (i.e., related constructs or pain outcomes) using the discriminant content validity method. Method. Items (n=58) of six pain catastrophizing measures were complemented with items (n=34) from questionnaires measuring pain-related worrying, vigilance, pain severity, distress, and disability. Via an online survey, 94 participants rated to what extent each item was relevant for assessing pain catastrophizing, defined as "to view or present pain or pain-related problems as considerably worse than they actually are" and other relevant constructs (pain-related worrying, vigilance, pain severity, distress, and disability). Results. Data were analyzed using Bayesian hierarchical models. The results revealed that the items from pain-related worrying, vigilance, pain severity, distress, and disability questionnaires were distinctively related to their respective constructs. This was not observed for the items from the pain catastrophizing questionnaires. The content of the pain catastrophizing measures was equally well, or even better, captured by pain-related worrying or pain-related distress. Conclusion. Based upon current findings, a recommendation may be to develop a novel pain catastrophizing questionnaire. However, we argue that pain catastrophizing cannot be assessed by self-report questionnaires. Pain catastrophizing requires contextual information, and expert judgment, which cannot be provided by self-report questionnaires. We argue for a person-centered approach, and propose to rename 'pain catastrophizing' measures in line with what is better measured: 'pain-related worrying'.
|Publication status||Published - 4 Mar 2020|
- Content validity
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)