Speech markers of depression dimensions across cognitive status
Laili Soleimani, Yuxia Ouyang, Sunghye Cho, Arash Kia, Michal Schnaider Beeri, Hung‐Mo Lin, Ramit Ravona‐Springer, Nadia Ramsingh 等 11 位
Icahn School of Medicine at Mount Sinai Pennsylvania Academic Library Consortium University of Pennsylvania Rutgers, The State University of New Jersey
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Introduction Depression and its components significantly impact dementia prediction and severity, necessitating reliable objective measures for quantification. Methods We investigated associations between emotion‐based speech measures (valence, arousal, and dominance) during picture descriptions and depression dimensions derived from the geriatric depression scale (GDS, dysphoria, withdrawal‐apathy‐vigor (WAV), anxiety, hopelessness, and subjective memory complaint). Results Higher WAV was associated with more negative valence (estimate = ‐0.133, p = 0.030). While interactions of apolipoprotein E (APOE) 4 status with depression dimensions on emotional valence did not reach significance, there was a trend for more negative valence with higher dysphoria in those with at least one APOE4 allele (estimate = –0.404, p = 0.0846). Associations were similar irrespective of dementia severity. Discussion Our study underscores the potential utility of speech biomarkers in characterizing depression dimensions. In future research, using emotionally charged stimuli may enhance emotional measure elicitation. The role of APOE on the interaction of speech markers and depression dimensions warrants further exploration with greater sample sizes. Highlights Participants reporting higher apathy used more negative words to describe a neutral picture. Those with higher dysphoria and at least one APOE4 allele also tended to use more negative words. Our results suggest the potential use of speech biomarkers in characterizing depression dimensions.
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社会科学Mental Health via Writing
Emotion and Mood Recognition · Dementia and Cognitive Impairment Research
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