Danbee Kang, Eunjee Kang, Kyeongrok Choi, Sooyeon Kim, Woo Shun Lee, Juhee Cho
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引用次数: 0
Abstract
Purpose: We developed and validated facial line distress scale-glabellar lines (FINE-GL) to evaluate the severity and psychosocial distress associated with GL.
Patients and methods: In Phase I, a preliminary item pool for the FINE-GL was developed through a literature review and expert consultation. This was followed by cognitive interviews to ensure comprehensibility of the items. In Phase II, we conducted a cross-sectional survey at a tertiary hospital and two local clinics in Korea. Exploratory factor analysis (EFA) was conducted to identify the underlying factor structure of the FINE-GL, and internal consistency and test-retest reliability were also examined.
Results: We yielded 20 items in four domains. The model fit was good. Coefficient alphas ranged from 0.92 to 0.95 for sub-domains and 0.97 for the total. The FINE-GL was moderately correlated with the appearance appraisal score and body image. In the test-retest, the range of ICC was 0.77-0.90.
Conclusion: FINE-GL is a reliable, valid, and comprehensive patient-reported outcome measure for assessing GL severity and distress. This will be helpful to determine a patient's eligibility for inclusion of study and to measure primary or secondary effectiveness endpoints for glabellar line treatment.
期刊介绍:
Patient Preference and Adherence is an international, peer reviewed, open access journal that focuses on the growing importance of patient preference and adherence throughout the therapeutic continuum. The journal is characterized by the rapid reporting of reviews, original research, modeling and clinical studies across all therapeutic areas. Patient satisfaction, acceptability, quality of life, compliance, persistence and their role in developing new therapeutic modalities and compounds to optimize clinical outcomes for existing disease states are major areas of interest for the journal.
As of 1st April 2019, Patient Preference and Adherence will no longer consider meta-analyses for publication.