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Passive, mobile assessment of sleep, circadian timing, and keyboard dynamics to prospectively predict depression severity, cognition, emotion processing, and emotion regulation

Passive, mobile assessment of sleep, circadian timing, and keyboard dynamics to prospectively predict depression severity, cognition, emotion processing, and emotion regulation
对睡眠、昼夜节律和键盘动态进行被动、移动评估,以前瞻性地预测抑郁症的严重程度、认知、情绪处理和情绪调节
批准号:
10016797
负责人:
Heide Klumpp
金额:
$19.99万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-11 至 2022-06-30

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中文摘要
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英文摘要
Depression is a prevalent, debilitating illness characterized by emotional dysregulation and cognitive impairment. Yet, our understanding of depression remains inadequate due in part to features of the illness that are difficult to measure such as disturbances in sleep, circadian disorganization, and atypical moment-to-moment variation in affective state. Actigraphy and ‘BiAffect’ are well-suited to evaluate these aspects of depression. Actigraphy utilizes accelerometer technology to monitor rest-activity patterns and is validated to estimate naturalistic sleep and circadian timing. Disturbances in sleep, in particular insomnia, and circadian timing (e.g., delayed sleep timing) are highly prevalent in depression and evidence suggests they play a role in depression severity and symptomatology (e.g., emotional dysregulation, cognitive difficulties). BiAffect is an innovative smartphone app comprising a secure virtual keyboard that utilizes dynamic variation in typing behavior that is sensitive to mood and cognitive function dynamics. Separate lines of research provide support for these technologies in the study of depression. Recent pilot data comprising 28+ un-medicated patients with primary or comorbid depression showed more fragmented sleep over the course of 1 week was significantly associated with greater depression level. More fragmented sleep also corresponded with more atypical brain response during emotion processing (e.g., less mid-frontal neural activity during error detection), independent of depression severity. For BiAffect, our published data showed depression was significantly predicted by typing behavior and movement; specifically, greater severity was predicted by more interkey delay, more autocorrect rate, and more accelerometer displacement in 7 patients over a 6-week period suggesting less focus/concentration and/or more psychomotor activity (e.g., agitation) portended depression severity. Pilot data also demonstrated interkey delay dynamics reflected diurnal patterns indicating BiAffect may serve as a proxy of circadian organization. Altogether, findings provide support for the feasibility of BiAffect. The proposed 2-year study endeavors to validate the novel BiAffect app and fill important gaps in the literature. Over the course of 6 weeks we will combine wrist actigraphy with Biaffect in 70 participants with depression, 50 participants with insomnia, and 50 healthy controls. We expect actigraphy and BiAffect data will each prospectively predict weekly depression severity and cognitive function and bi-weekly neurocognitive and brain-behavioral response during emotion processing and emotion regulation. We expect these effects will be more robust in the depressed group relative to the insomnia group, which will be more robust compared to healthy controls.
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