Development and Validation of the DA3 Scale for Assessing Depression, Anxiety, and Apathy in Older Adults

DA3量表在评估老年人抑郁、焦虑和冷漠方面的开发与验证

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Abstract

OBJECTIVES: To validate the Depression, Anxiety, and Apathy (DA3) scale for assessing symptoms of depression, anxiety, and apathy in community-dwelling mid- and late-life adults with and without cognitive impairment. DESIGN: Cross-sectional psychometric validation study. SETTING: Community-based longitudinal study of brain health. PARTICIPANTS: A total of 252 participants (mean age, 68.8 ± 9.4 years; 68.5% women; 71.3% non-Hispanic White; 66.8% cognitively normal) completed the study. MEASUREMENTS: The DA3 scale was compared with established measures of mood including the Hospital Anxiety and Depression Scale (HADS), Apathy Scale (AS), Generalized Anxiety Disorder-7 (GAD7), Patient Health Questionnaire-8 (PHQ8), and Neuropsychiatric Inventory Questionnaire (NPI-Q). Psychometric properties were assessed using reliability and validity measures, confirmatory factor analysis (CFA), and Mokken scale analysis. RESULTS: The DA3 demonstrated strong internal consistency (Cronbach's alpha, 0.670-0.781). CFA supported a three-factor model corresponding to distinct depression, anxiety, and apathy dimensions, with excellent goodness-of-fit. Mokken analysis confirmed acceptable-to-strong scalability (H coefficients, 0.36-0.54). The DA3 subscales demonstrated strong convergent validity with established measures (e.g., HADS, AS, GAD-7, and PHQ-8). Cut-off scores of five on each subscale achieved optimal agreement with gold standard measures. Performance of the DA3 was consistent across sociodemographic, neuropsychological, and cognitive subgroups. CONCLUSIONS: The DA3 is a unitary, brief, valid, and reliable tool for assessing depression, anxiety, and apathy in community-dwelling older adults, including those with cognitive impairment. Its strong psychometric properties support its use in both clinical and research settings. Future studies should examine its longitudinal utility to better understand its role in tracking mood symptoms over time.

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