The impact of the COVID-19 pandemic on daily rhythms

Luong, Nguyen; Barnett, Ian; Aledavood, Talayeh

doi:10.1093/jamia/ocad140

Cited by 5 publications

(2 citation statements)

References 52 publications

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“…The arrival of the COVID-19 pandemic in early 2020 led to quarantines and lockdowns for billions of people worldwide ( 1 , 2 ). Confinement due to COVID-19 generated structural changes for the daily activities of most people ( 3 , 4 ). In this sense, one job measure adapted worldwide to avoid spreading the SARS-CoV-2 virus was changing from in-person work to remote working in a wide range of job areas ( 5 ).…”

Section: Introductionmentioning

confidence: 99%

Musculoskeletal disorders and quality of life for Chilean teachers during the COVID-19 pandemic at the academic year-end

Vega-Fernández,

Gonzalez-Torres,

Solis-Soto

et al. 2024

Front. Public Health

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IntroductionSchoolteachers have reported multiple demands contributing to poor perceptions regarding their quality of life and high rates of musculoskeletal disorders. However, there are few studies about the association between musculoskeletal disorders and quality of life from the end of the academic period during the COVID-19 pandemic.ObjectiveEvaluate musculoskeletal disorders rates and their association with quality of life perceptions among teachers from the last academic period during the COVID-19 pandemic.Participants and methodsA total sample of 161 Chilean schoolteachers was included in a cross-sectional study musculoskeletal disorders prevalence was evaluated using the Standardized Nordic Questionnaire, and quality of life was evaluated through the Short-Form 12 Health Survey Instrument. A logistic regression was applied to evaluate the association between musculoskeletal disorders and quality of life perceptions adjusted by gender, age, and contract type.Results98% of teachers have suffered from some type of musculoskeletal disorders during the last 12 months, and 64% have had six or more painful regions. Women showed a higher musculoskeletal disorders rate than men. The group of teachers with the most musculoskeletal disorders (≥p50) saw significantly greater risk of low scores on the physical (OR: 2.16; p < 0.05) and mental components (OR: 4.86; p < 0.01) of quality of life, regardless of gender, age, and contract type.ConclusionHigh musculoskeletal disorders rates suggest that preventive and informative actions must be taken regarding these disorders in order to protect teachers’ mental and physical health, considering the effects of the school year and the COVID-19 health crisis.

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Section: Introductionmentioning

confidence: 99%

Musculoskeletal disorders and quality of life for Chilean teachers during the COVID-19 pandemic at the academic year-end

Vega-Fernández,

Gonzalez-Torres,

Solis-Soto

et al. 2024

Front. Public Health

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“…Previous research in studying temporal rhythms of activity inferred from different personal digital devices has shown that people tend to have persistent activity rhythms over time [27–30]. However, these rhythms and their consistency are linked to personal and sociodemographic characteristics [31,32]. A recent study [33] suggests that daily activity rhythms inferred from smartphone GPS data are associated with anxiety levels in patients with MDD and bipolar disorder.…”

Section: Introductionmentioning

confidence: 99%

Mobile Monitoring of Mood (MoMo-Mood): a Multimodal Digital Phenotyping Study with Major Depressive Patients and Healthy Controls

Aledavood,

Luong,

Baryshnikov

et al. 2024

Preprint

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BackgroundMood disorders (MD) are among the most common mental health conditions worldwide, significantly contributing to mortality, morbidity, and disability rates. In today’s society, individuals generate digital traces through their interactions with wearable and consumer-grade personal digital devices. These traces can be collected, processed, and analyzed, offering a unique opportunity to quantify and monitor individuals with mental disorders in their natural living environments. Various forms of digital traces from the use of smartphones and other personal digital devices hold the potential to reveal new behavioral markers associated with depressive symptoms in patients with mood disorders.ObjectiveWe conducted an observational longitudinal study, MoMo-Mood Pilot, involving a cohort of patients with major depressive disorder (MDD) and a healthy control group without any diagnosed mental disorder to confirm the feasibility of our digital phenotyping study design. Upon confirming feasibility, we conducted a year-long, more extensive study, MoMo-Mood, with a similar design. This study comprised (1) three subcohorts of patients with a major depressive episode (MDE), including those with either MDD, bipolar disorder (BD), or concurrent borderline personality disorder (BPD), as well as (2) a healthy control group without any diagnosed mental disorder. We investigated whether differences in behavioral patterns, as quantified by passively collected digital trace data, could be observed at the group level, i.e., patients vs. healthy controls. We studied the volume and temporal patterns of smartphone screen and application usage, communication, sleep, mobility, and physical activity. Additionally, we examined which of the passively quantified behavioral features and sociodemographic factors are associated with the presence of depression in study participants at different points in time.MethodsMoMo-Mood Pilot and MoMo-Mood recruited 201 participants. The pilot study enrolled 14 patients with MDD and 23 healthy controls. The participants completed a 2-phase study: the first two weeks (theactive phase) involved collecting data from bed sensors, actigraphy, and smartphone data passively collected through the Niima platform. Additionally, participants had to actively engage with the study by answering five sets of questions daily, prompted on their smartphones throughout the day. In the second phase (thepassive phase), which lasted up to 1 year, only passive smartphone data and bi-weekly Patient Health Questionnaire (PHQ-9) assessments were collected. The MoMo-Mood study, which had a similar setting to the pilot study, enrolled 164 participants: 133 were patients diagnosed with current MDE through structured interviews (85 with MDD, 27 with BPD, and 21 with BD), and 31 were healthy controls. Survival analysis was performed to compare the adherence of healthy controls and the patient subcohorts. Statistical tests were performed to compare behavioral patterns, and a generalized linear mixed model was used to assess the association between different factors and the presence of depression.ResultsThe study design was proven feasible upon completing the pilot study. Survival analysis using the log-rank test showed no statistically significant difference in participants’ adherence between subcohorts. The overall communication volume was similar in both groups, but the weekly temporal patterns revealed distinct preferences as the controls typically made or received calls in the afternoon. In terms of location patterns, significant differences emerged: weekday location variance showed lower values for patients (Control = -10.04 ± 2.73, Patient = -11.91 ± 2.50, MWU testP-value = .004) and normalized entropy of location was also lower among patients (Control = 2.10 ± 1.38, Patient = 1.57 ± 1.10, MWU testP-value = .05). However, no differences were observed in weekend location patterns. The temporal communication patterns for controls were found to be more diverse than that of patients (MWU test, p<0.001). In contrast, patients’ smartphone usage temporal patterns were more varied than the controls. Investigating mobile-derived behaviors and their relationship with the concurrent presence of depression, we observed that the duration of outgoing calls over the past two weeks was negatively correlated with the presence of depression (beta = -7.93, 95% CI: -13.17 to- -2.69,P-value = .003). Conversely, longer durations of incoming calls (beta = 5.33, 95% CI: -0.08 to 10.75, p = 0.053) and a larger proportion of time spent at home (beta = 5.16, 95% CI: 0.78 to 9.54,P-value = .002) were positively associated with the presence of depression.ConclusionsThis work demonstrates the design of a longitudinal digital phenotyping study harnessing data from a cohort of patients with depression. It also shows the important features and data streams for future analyses of behavioral markers of mood disorders. However, among outpatients with mild to moderate depressive disorders, their group-level differences from healthy controls in any of the modalities alone remain overall modest. Therefore, future studies need to be able to combine data from multiple domains and modalities to detect more subtle differences, identify individualized signatures, and combine passive monitoring data with clinical ratings.

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Sleep during COVID-19 Pandemic: A Longitudinal Observational Study Combining Multisensor Data with Questionnaires (Preprint)

Luong,

Mark,

Kulshrestha

et al. 2023

JMIR mHealth and uHealth

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Background:The COVID-19 pandemic led to various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people's sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often overlook a comprehensive perspective that incorporates other factors that can also influence sleep, namely seasonal variations and physical activity.Objective: Our study aims to longitudinally examine the fine-grained changes in sleep patterns of working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors. We investigate the association between sleep and 5 sets of variables capturing characteristics of individuals including (i) demographics, (ii) sleep-related habits, (iii) physical activity behaviors, and external factors including (iv) pandemic-specific constraints, and (v) seasonal variations during the study period. Methods:We recruited working adults in Finland to participate in our one-year-long study (June 2021 -June 2022) conducted in the late stage of the COVID-19 pandemic. We collected multisensor data from fitness trackers worn by the participants as well as work and sleep-related measures through monthly questionnaires. Additionally, we used the stringency index for Finland at different points in time to estimate the degree of the pandemic-related lockdown restrictions in place during the study duration. We applied linear mixed models to study the changes in sleep patterns during the late stage of the pandemic and their association with the aforementioned five sets of variables. Results:The sleep patterns of 27,350 nights from 111 working adults were analyzed. We observed that more stringent pandemic measures were associated with longer total sleep time (TST) (?= 0.004, 95% CI 0.002 to 0.006, P<.001) and later midpoint of sleep (MS) (?= 0.02, 95% CI 0.02 to 0.03, P<.001). Being a snoozer (i.e., snoozing the alarm when waking up from sleep) was associated with higher variability in both TST (?= 0.18, 95% CI 0.07 to 0.30, P=.002) and MS (?= 0.19, 95% CI 0.06 to 0.34, P=.008). Service staff slept more than academic staff (?= 0.36, 95% CI 0.10 to 0.61, P=.006) with also lower variability in TST (?= -0.16, 95% CI -0.27 to -0.04, P=.006). Engaging in physical activity later in the day correlated with longer sleep duration (?= 0.03, 95% CI 0.02 to 0.04, P<.001). Conclusions:Our study provided a comprehensive view of the possible factors affecting sleep patterns during the late stage of the pandemic. Our results revealed that stringent measures implemented during the COVID-19 pandemic are associated with changes in sleep patterns. The more flexible work-life routine arising from the restriction is also linked with changes in sleeprelated habits among different occupations.

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The impact of the COVID-19 pandemic on daily rhythms

Cited by 5 publications

References 52 publications

Musculoskeletal disorders and quality of life for Chilean teachers during the COVID-19 pandemic at the academic year-end

Musculoskeletal disorders and quality of life for Chilean teachers during the COVID-19 pandemic at the academic year-end

Mobile Monitoring of Mood (MoMo-Mood): a Multimodal Digital Phenotyping Study with Major Depressive Patients and Healthy Controls

Sleep during COVID-19 Pandemic: A Longitudinal Observational Study Combining Multisensor Data with Questionnaires (Preprint)

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