No analysis in the literature has attempted to address the following 3 aims: (1) Determine the correlation between daily Fitbit minutes slept and daily self-reported sleep data, (2) Determine the correlation between Fitbit number of waking events and self-reported mood, and (3) Explore qualitative relationships between Fitbit waking events and self-reported contextual factors for sleep. If Fitbit can be found to be a reliable device that can uncover early markers for mental health disorders, then Fitbit could be used as a screening tool to identify early markers of mental stress in different populations such as ADSM. This study aimed to evaluate if Fitbit sleep data can be validated as reliable compared with self-reported sleep and mood. The paucity of data creates an opportunity to design research studies to fill current gaps in the literature.

None of these studies attempted to explore the relationship between self-reported mood, sleep, and contextual factors as markers of early mental health disorders.Īlthough Fitbit has been found to be a valid instrument for measuring sleep data, it has not been used to evaluate potential underlying mental health disorders. Finally, a small study of 10 participants looking at Fitbit Alta sleep metrics and self-reported sleep diaries found a positive correlation between the 2 measures. An additional study by the same author found that the total time slept and number of waking events most strongly correlated with the participants’ experience of sleep. The most common reasons for increased number of waking events were spouses, children, pets, garbage trucks, and alcohol. Another study also attempted to explore the relationship between sleep and contextual factors with 12 participants looking at Fitbit data over 2 weeks compared with an online sleep tool called Sleep Explorer. A study of 22 participants using the SleepTight tracking algorithm to evaluate contextual factors such as caffeine and exercise did not show a statistically significant correlation with good, neutral, or poor sleep over a month. Many studies have measured total sleep time, time awake, and number of waking events but have not investigated causes for why the waking events happened. Another study compared the Fitbit Flex, the same device used in this study, against PSG and found a correlation of 97.4% for total sleep time in good sleepers and 88.6% for participants with insomnia. Fitbit has an intradevice reliability of 96.5%-99.1% for measuring sleep efficiency and total sleep time compared with the gold standard of PSG in a study of 24 healthy volunteers. Fitbits have also been found to positively correlate with patient-reported outcomes such as sleep and step count. Specifically, Fitbit has been found to be a valid method of obtaining sleep metrics compared to the gold standard polysomnography (PSG). These trackers have been used by both the Army and Navy to promote health and are ubiquitous in the ADSM population. Devices such as the Fitbit are light, portable, and inexpensive and can obtain passive sleep data. Personal fitness devices are wearable sensors (usually worn on the wrist) that allow for direct tracking of biometric data. Sleep disturbances due to underlying mental health conditions can be measured using contextual factors such as fear, worry, or life stressors. A majority of patients with PTSD suffer from sleep disturbances.

Patients with generalized anxiety disorder have double the risk of having sleep disturbances as compared to healthy controls. Up to 90% of patients with major depressive disorder have sleep disturbances. There is a well-defined relationship between mental health disorders, such as anxiety, depression, and PTSD, and sleep disturbances. Since it is known that treatment is effective, the key to better serving ADSM is early identification of underlying mental health disorders. Routine screening and early referral for mental health disorders can help improve quality of life for ADSM. In 2013, 20% of ADSM had a mental health disease, with the Army showing the highest prevalence of mental health disease, at 30%.

While mental health disease is prevalent throughout the United States, it affects a disproportionately large proportion of the active duty service member (ADSM) population. Mental health disorders can cause significant reduction in function and quality of life.

Anxiety, depression, and post-traumatic stress disorder (PTSD) are increasingly common types of mental health disorders in the United States.

Fit bits and sleep disorder