인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The aim of this study was to evaluate the psychometric properties and construct validity of the PrePain questionnaire in both the general population and a long-term pain population. The PrePain questionnaire is an 11-item self-administered tool that assesses current pain intensity, long-term pain history, and attitudes, emotions, and behaviors related to pain using a visual analog scale (VAS). This non-randomized observational study included 200 participants: 100 individuals with long-term pain and 100 without. Participants were recruited from a specialist pain rehabilitation clinic and via social media. The study involved baseline and follow-up assessments using the PrePain questionnaire, the Short Health Anxiety Inventory (SHAI-14), and the Coping Strategies Questionnaire (CSQ). Statistical analyses included Spearman correlation for test-retest reliability, sign rank-test for sensitivity to change, Cronbach's α for internal consistency, principal component analysis for subscale analysis, and mixed-effects linear regression for test of criterion validity. A total of 187 participants completed the study. The PrePain questionnaire demonstrated acceptable face validity and moderate test-retest reliability (coefficients ranging from 0.58 to 0.73). Internal consistency was α = 0.63. Principal component analysis suggested a two or three-factor solution. Criterion validity was supported by significant correlations between PrePain items and SHAI-14 and CSQ catastrophizing, except for the pain sensitivity item. No significant changes were observed in the clinical group between baseline and follow-up assessments. The resuts provide preliminary evidence for the reliability of The PrePain questionnaire and its validity for assessing attitudes, emotions, and behaviors related to pain in both clinical and non-clinical populations. Further research is needed to explore its sensitivity to change and utility in clinical practice.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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