Fitbit depression detection in an undergraduate student population
LE3 .A278 2021
Bachelor of Science
Depression is the most prevalent mental health disorder in society today, especially in the undergraduate student population. This study examines the potential of the Fitbit Charge 4 to detect early depression, using measures of sleep disruption and movement. Undergraduate Psychology students (N=22) attending Acadia University during the year 2020-2021 participated in the study by wearing a Fitbit for at least seven days and nights and also filling out the CESD-R self-report depression questionnaire. Sleep data was available for all but one participant, and only a subset of participants (N=11) agreed to share their activity data. I hypothesized that Fitbit measures of sleep disruption (e.g., number of awakenings, low total sleep time) and low activity (e.g.,low total step count) would be correlated with higher measures of depression on the CESD-R. Most of the variables examined did not correlate with depression. However, the study did find that those with later waketimes were more depressed than those who got up earlier in the day, and also that increased variation in nightly sleep time was significantly correlated with depression, These results suggest that poor sleep hygiene and circadian factors may be associated with student depression, such that students who are less depressed wake up earlier and at the same time each day. These results support the hypothesis that the Fitbit could be a useful tool to detect depression in this student population, and that more research is warranted.
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