Biopsychosocial Response to the COVID-19 Lockdown in People with Major Depressive Disorder and Multiple Sclerosis.

BACKGROUND: Changes in lifestyle, finances and work status during COVID-19 lockdowns may have led to biopsychosocial changes in people with pre-existing vulnerabilities such as Major Depressive Disorders (MDDs) and Multiple Sclerosis (MS). METHODS: Data were collected as a part of the RADAR-CNS (Remote Assessment of Disease and Relapse-Central Nervous System) program. We analyzed the following data from long-term participants in a decentralized multinational study: symptoms of depression, heart rate (HR) during the day and night; social activity; sedentary state, steps and physical activity of varying intensity. Linear mixed-effects regression analyses with repeated measures were fitted to assess the changes among three time periods (pre, during and post-lockdown) across the groups, adjusting for depression severity before the pandemic and gender. RESULTS: Participants with MDDs (N = 255) and MS (N = 214) were included in the analyses. Overall, depressive symptoms remained stable across the three periods in both groups. A lower mean HR and HR variation were observed between pre and during lockdown during the day for MDDs and during the night for MS. HR variation during rest periods also decreased between pre- and post-lockdown in both clinical conditions. We observed a reduction in physical activity for MDDs and MS upon the introduction of lockdowns. The group with MDDs exhibited a net increase in social interaction via social network apps over the three periods. CONCLUSIONS: Behavioral responses to the lockdown measured by social activity, physical activity and HR may reflect changes in stress in people with MDDs and MS. Remote technology monitoring might promptly activate an early warning of physical and social alterations in these stressful situations. Future studies must explore how stress does or does not impact depression severity.

Impact of restrictive COVID-19 measures on daily momentary affect in an epidemiological youth sample in Hong Kong: An experience sampling study.

Restrictive COVID-19 measures can have significant mental health impacts, particularly on young people. How such measures may influence day-to-day momentary affect, nonetheless, remains to be explored. Experience sampling data were collected from 165 young people (aged 15-24) as part of a larger epidemiological youth mental health study in Hong Kong. We examined the impact of one of the most stringent COVID-19 measures - dine-in restrictions - on momentary positive and negative affect and current contexts and activities of these young people. The effects of a milder form of COVID-19 measure - school suspension - were separately examined. Multilevel analysis revealed that those in the dine-in ban group, compared to dining-as-usual, showed significantly reduced momentary positive affect (ß = -0.17, SE = 0.06, p = 0.003). Its effect remained significant even when accounting for baseline depressive and anxiety symptoms and socioeconomic status (ß = -0.15, SE = 0.05, p = 0.008). The effect of dine-in ban on reduced momentary positive affect was found specifically when participants were in indoor locations (e.g., home, office), alone, and engaged in passive leisure activities. This pattern was not observed when participants were at school or at other outdoor locations, with friends, or engaged in active leisure activities. No significant effect of school suspension on momentary affect was observed. More severe COVID-19 measures, such as dine-in ban, can have significant impacts on the momentary positive affect of young people. Certain contexts and activities may offer protection against the consequences of COVID-19 measures. The current findings may help to inform future designs of mental health interventions and public health policies. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03183-y.

Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study.

BACKGROUND: The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. OBJECTIVE: We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. METHODS: Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse-Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants' location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. RESULTS: This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=-0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=-0.07, P<.001) the subsequent periodicity of mobility. CONCLUSIONS: Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.

Stay Home, Drink at Home? A Daily Diary Study on College Students' Alcohol and Social Media Use during the COVID-19 Pandemic.

BACKGROUND: COVID-19 and measures to contain it may have impacted college students' behavior, including their drinking behavior. Students' drinking may have decreased-for example, due to the closure of bars-but problematic drinking may have increased-for example, due to (solitary) drinking at home. Another behavior that has increased due to COVID-19 and the accompanying social isolation is students' social networking site (SNS) use. This is worrisome because students' SNS use has been shown to increase their alcohol use. Nevertheless, little research has investigated these behaviors and the possible link between them during a lockdown. Therefore, this study aimed to examine (1) whether students engaged in drinking during a lockdown, (2) whether they displayed their drinking behavior on SNSs, and (3) whether exposure to and posting of alcohol-related content was linked to their daily alcohol use. METHODS: 337 college students (Mage = 20.63 years, SDage = 1.55 years; 50.3% male) participated in a two-week daily diary study. Descriptive statistical analyses and generalized linear mixed modeling (GLMM) were deployed. RESULTS: Descriptive analysis results showed that during the week, students' drinking occurred with friends in dormitories, while in the weekend, this behavior shifted to drinking with friends and parents at home. Moreover, students mostly saw visual and posted textual posts of this drinking on SNSs. Furthermore, GLMM revealed associations between exposure to alcohol postings, sharing of alcohol postings, and students' probability of drinking on the same day. CONCLUSION: This study provides important insights into students' alcohol use and its underlying mechanisms during health crises.

Investigating the impact of COVID-19 lockdown on adults with a recent history of recurrent major depressive disorder: a multi-Centre study using remote measurement technology.

BACKGROUND: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes a clinical illness Covid-19, has had a major impact on mental health globally. Those diagnosed with major depressive disorder (MDD) may be negatively impacted by the global pandemic due to social isolation, feelings of loneliness or lack of access to care. This study seeks to assess the impact of the 1st lockdown - pre-, during and post - in adults with a recent history of MDD across multiple centres. METHODS: This study is a secondary analysis of an on-going cohort study, RADAR-MDD project, a multi-centre study examining the use of remote measurement technology (RMT) in monitoring MDD. Self-reported questionnaire and passive data streams were analysed from participants who had joined the project prior to 1st December 2019 and had completed Patient Health and Self-esteem Questionnaires during the pandemic (n = 252). We used mixed models for repeated measures to estimate trajectories of depressive symptoms, self-esteem, and sleep duration. RESULTS: In our sample of 252 participants, 48% (n = 121) had clinically relevant depressive symptoms shortly before the pandemic. For the sample as a whole, we found no evidence that depressive symptoms or self-esteem changed between pre-, during- and post-lockdown. However, we found evidence that mean sleep duration (in minutes) decreased significantly between during- and post- lockdown (- 12.16; 95% CI - 18.39 to - 5.92; p <  0.001). We also found that those experiencing clinically relevant depressive symptoms shortly before the pandemic showed a decrease in depressive symptoms, self-esteem and sleep duration between pre- and during- lockdown (interaction p = 0.047, p = 0.045 and p <  0.001, respectively) as compared to those who were not. CONCLUSIONS: We identified changes in depressive symptoms and sleep duration over the course of lockdown, some of which varied according to whether participants were experiencing clinically relevant depressive symptoms shortly prior to the pandemic. However, the results of this study suggest that those with MDD do not experience a significant worsening in symptoms during the first months of the Covid - 19 pandemic.

The Impact of COVID-19 on Adolescents' Daily Lives: The Role of Parent-Child Relationship Quality.

COVID-19 lockdown measures have profoundly impacted adolescent' daily life, with research suggesting an increase in irritability, stress, loneliness, and family conflict. A potential protective factor is parent-child relationship quality; however, no studies have investigated this. We used data from SIGMA, a longitudinal, experience sampling cohort study, in which N = 173 adolescents aged 11 to 20 were tested before and during COVID-19. Multilevel analyses showed decreased daily-life irritability and increased loneliness from pre- to mid-pandemic. Daily-life stress levels were unchanged. Relationship quality was negatively associated with irritability and loneliness and buffered against the increase in loneliness. Effect sizes were small and do not support a strong effect of the first lockdown on irritability, stress, loneliness, and family conflict in adolescents.

Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19.

BACKGROUND: In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed. OBJECTIVE: We aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)-base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19. METHODS: We analyzed data extracted from smartphone and wearable devices, and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the United Kingdom, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, the maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post hoc Dunn tests to assess differences in these features among baseline, prelockdown, and during lockdown periods. We also studied behavioral differences by age, gender, BMI, and educational background. RESULTS: We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between prelockdown and during lockdown periods (P<.001 for all five countries). We saw reduced sociality as measured through mobility features and increased virtual sociality through phone use. People were more active on their phones (P<.001 for Italy, Spain, and the United Kingdom), spending more time using social media apps (P<.001 for Italy, Spain, the United Kingdom, and the Netherlands), particularly around major news events. Furthermore, participants had a lower heart rate (P<.001 for Italy and Spain; P=.02 for Denmark), went to bed later (P<.001 for Italy, Spain, the United Kingdom, and the Netherlands), and slept more (P<.001 for Italy, Spain, and the United Kingdom). We also found that young people had longer homestay than older people during the lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. CONCLUSIONS: RADAR-base, a freely deployable data collection platform leveraging data from wearables and mobile technologies, can be used to rapidly quantify and provide a holistic view of behavioral changes in response to public health interventions as a result of infectious outbreaks such as COVID-19. RADAR-base may be a viable approach to implementing an early warning system for passively assessing the local compliance to interventions in epidemics and pandemics, and could help countries ease out of lockdown.