The mobile everyday cognition scale (mECog): development and pilot testing

认知 比例(比率) 心理学 认知心理学 计算机科学 地理 神经科学 地图学
作者
Sawyer Harmon,Courtney G. Kocum,Rylea M. Ranum,Greta Hermann,Sarah Tomaszewski Farias,Andrew M. Kiselica
出处
期刊:Clinical Neuropsychologist [Taylor & Francis]
卷期号:: 1-20
标识
DOI:10.1080/13854046.2024.2383333
摘要

Objective: Subjective cognitive decline (SCD) is an important part of the aging process and may be a sign of neurodegenerative disease. Current measures of SCD are subject to the limits of retrospective recall of symptoms over a long span of time, which might be addressed by using ecological momentary assessment (EMA) methods. However, there are no currently available measures of SCD validated for use in EMA. Thus, our goal was to develop and pilot test the mobile Everyday Cognition Scale (mECog). Method: 31 community-dwelling older adults completed in lab measures of cognition and mental health symptoms, followed by daily mECog ratings on a smart phone for 28 days. Results: Most participants completed at least 75% of mECog assessments (n = 27, 87%), and the average number of assessments completed was 22. Further, respondents rated the mobile assessment platform and measures as easy to use and non-interfering with daily life. Test-retest reliability of mECog scores was very strong (RKRN = .99), and within-person reliability was moderate (RCN = .41). mECog scores demonstrated strong positive associations with scores from the original ECog (ρ = .62–69, p < .001) and short form ECog (ρ = .63-.69, p < .001) and non-significant associations with demographics (ρ = –0.25–.04, p = .21-.94) and mental health symptoms (ρ = –0.06-.34, p = .08–.99). mECog scores also exhibited small-to-moderate negative correlations with objective cognitive test scores, though these relationships did not reach statistical significance (ρ = –0.32 to −0.22, p = .10–.27). Conclusions: Results suggest that mobile assessment of SCD via the mECog is feasible and acceptable. Further, mECog scores demonstrated good psychometric properties, including evidence of strong reliability, convergent validity, and divergent validity.
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