Digital phenotyping of student mental health during COVID-19: an observational study of 100 college students.

Objective: This study assessed the feasibility of capturing smartphone based digital phenotyping data in college students during the COVID-19 pandemic with the goal of understanding how digital biomarkers of behavior correlate with mental health. Participants: Participants were 100 students enrolled in 4-year universities. Methods: Each participant attended a virtual visit to complete a series of gold-standard mental health assessments, and then used a mobile app for 28 days to complete mood assessments and allow for passive collection of GPS, accelerometer, phone call, and screen time data. Students completed another virtual visit at the end of the study to collect a second round of mental health assessments. Results: In-app daily mood assessments were strongly correlated with their corresponding gold standard clinical assessment. Sleep variance among students was correlated to depression scores (ρ = .28) and stress scores (ρ = .27). Conclusions: Digital Phenotyping among college students is feasible on both an individual and a sample level. Studies with larger sample sizes are necessary to understand population trends, but there are practical applications of the data today.

Emergent Admissions to the Epilepsy Monitoring Unit in the Setting of COVID-19 Pandemic-related, State-mandated Restrictions: Clinical Decision Making and Outcomes.

Due to the coronavirus disease 2019 (COVID-19) pandemic, the state of Texas-limited elective procedures to conserve beds and personal protective equipment (PPE); therefore, between March 22 and May 18, 2020, admission to the epilepsy monitoring unit (EMU) was limited only to urgent and emergent cases. We evaluated clinical characteristics and outcomes of these patients who were admitted to the EMU. Nineteen patients were admitted (one patient twice) with average age of 36.26 years (11 female) and average length of stay 3 days (range: 2-9 days). At least one event was captured on continuous EEG (cEEG) and video monitoring in all 20 admissions (atypical in one). One patient had both epileptic (ES) and psychogenic non-epileptic seizures (PNES) while 10 had PNES and 9 had ES. In 8 of 9 patients with ES, medications were changed, while in 5 patients with PNES, anti-epileptic drugs (AED) were stopped; the remaining 5 were not on medications. Of the 14 patients who had seen an epileptologist pre-admission, 13 (or 93%) had their diagnosis confirmed by EMU stay; a statistically significant finding. While typically an elective admission, in the setting of the COVID-19 pandemic, urgent and emergent EMU admissions were required for increased seizure or event frequency. In the vast majority of patients (13 of 19), admission lead to medication changes to either better control seizures or to change therapeutics as appropriate when PNES was identified.

Digital phenotyping for mental health of college students: a clinical review.

Experiencing continued growth in demand for mental health services among students, colleges are seeking digital solutions to increase access to care as classes shift to remote virtual learning during the COVID-19 pandemic. Using smartphones to capture real-time symptoms and behaviours related to mental illnesses, digital phenotyping offers a practical tool to help colleges remotely monitor and assess mental health and provide more customised and responsive care. This narrative review of 25 digital phenotyping studies with college students explored how this method has been deployed, studied and has impacted mental health outcomes. We found the average duration of studies to be 42 days and the average enrolled to be 81 participants. The most common sensor-based streams collected included location, accelerometer and social information and these were used to inform behaviours such as sleep, exercise and social interactions. 52% of the studies included also collected smartphone survey in some form and these were used to assess mood, anxiety and stress among many other outcomes. The collective focus on data that construct features related to sleep, activity and social interactions indicate that this field is already appropriately attentive to the primary drivers of mental health problems among college students. While the heterogeneity of the methods of these studies presents no reliable target for mobile devices to offer automated help-the feasibility across studies suggests the potential to use these data today towards personalising care. As more unified digital phenotyping research evolves and scales to larger sample sizes, student mental health centres may consider integrating these data into their clinical practice for college students.