인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
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.
논문 기본 정보
- 저자정보
초록·키워드
This study aimed to examine the trajectories of depressive symptoms among patients newly diagnosed with arthritis, using data from the Korean Longitudinal Study of Aging (2006–2022). Depressive symptoms were assessed with the 10-item Center for Epidemiologic Studies Depression Scale. Latent growth modeling was applied to examine linear and quadratic trajectories of depressive symptoms and to identify sociodemographic and health-related predictors influencing these trajectories. Model fit was evaluated using chi-square test, CFI, RMSEA, SRMR indices. Data from 769 participants diagnosed between 2008 and 2014 were analyzed. The quadratic growth model provided a superior fit (χ²= 41.26, df=12, CFI=0.978, RMSEA=0.056, SRMR=0.044) compared to the linear model, indicating a nonlinear trajectory characterized by an initial rise in depressive symptoms around diagnosis followed by gradual stabilization to near pre-diagnosis levels. Age (β= 0.102, p<.001), number of diseases (β=0.551, p=.005), and marital status (β=–0.922, p=.040) had significant effects on the initial level of depressive symptoms. For the linear rate of change of depressive symptoms, final education (beta=-0.339, p=.041) and the number of diseases (beta= 0.161, p=.040) had a significant impact. Regarding the quadratic rate of change in depressive symptoms, final education (beta=0.034, p=.042) and the number of diseases (beta=-0.020, p=.012) had a significant effect. These findings underscore the dynamic nature of depressive symptoms in arthritis and the need for timely, tailored mental health interventions.
본문·목차
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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UCI(KEPA) : I410-151-26-02-094594479