A daily diary study into the effects on mental health of COVID-19 pandemic-related behaviors.

BACKGROUND: Recommendations for promoting mental health during the COVID-19 pandemic include maintaining social contact, through virtual rather than physical contact, moderating substance/alcohol use, and limiting news and media exposure. We seek to understand if these pandemic-related behaviors impact subsequent mental health. METHODS: Daily online survey data were collected on adults during May/June 2020. Measures were of daily physical and virtual (online) contact with others; substance and media use; and indices of psychological striving, struggling and COVID-related worry. Using random-intercept cross-lagged panel analysis, dynamic within-person cross-lagged effects were separated from more static individual differences. RESULTS: In total, 1148 participants completed daily surveys [657 (57.2%) females, 484 (42.1%) males; mean age 40.6 (s.d. 12.4) years]. Daily increases in news consumed increased COVID-related worrying the next day [cross-lagged estimate = 0.034 (95% CI 0.018-0.049), FDR-adjusted p = 0.00005] and vice versa [0.03 (0.012-0.048), FDR-adjusted p = 0.0017]. Increased media consumption also exacerbated subsequent psychological struggling [0.064 (0.03-0.098), FDR-adjusted p = 0.0005]. There were no significant cross-lagged effects of daily changes in social distancing or virtual contact on later mental health. CONCLUSIONS: We delineate a cycle wherein a daily increase in media consumption results in a subsequent increase in COVID-related worries, which in turn increases daily media consumption. Moreover, the adverse impact of news extended to broader measures of psychological struggling. A similar dynamic did not unfold between the daily amount of physical or virtual contact and subsequent mental health. Findings are consistent with current recommendations to moderate news and media consumption in order to promote mental health.

Reddit language indicates changes associated with diet, physical activity, substance use, and smoking during COVID-19.

COVID-19 has adversely impacted the health behaviors of billions of people across the globe, modifying their former trends in health and lifestyle. In this paper, we compare the psychosocial language markers associated with diet, physical activity, substance use, and smoking before and after the onset of COVID-19 pandemic. We leverage the popular social media platform Reddit to analyze 1 million posts between January 6, 2019, to January 5, 2021, from 22 different communities (i.e., subreddits) that belong to four broader groups-diet, physical activity, substance use, and smoking. We identified that before the COVID-19 pandemic, posts involved sharing information about vacation, international travel, work, family, consumption of illicit substances, vaping, and alcohol, whereas during the pandemic, posts contained emotional content associated with quarantine, withdrawal symptoms, anxiety, attempts to quit smoking, cravings, weight loss, and physical fitness. Prevalent topic analysis showed that the pandemic was associated with discussions about nutrition, physical fitness, and outdoor activities such as backpacking and biking, suggesting users' focus shifted toward their physical health during the pandemic. Starting from the week of March 23, 2020, when several stay-at-home policies were enacted, users wrote more about coping with stress and anxiety, alcohol misuse and abuse, and harm-reduction strategies like switching from hard liquor to beer/wine after people were socially isolated. In addition, posts related to use of substances such as benzodiazepines (valium, xanax, clonazepam), nootropics (kratom, phenibut), and opioids peaked around March 23, 2020, followed by a decline. Of note, unlike the general decline observed, the volume of posts related to alternatives to heroin (e.g., fentanyl) increased during the COVID-19 pandemic. Posts about quitting smoking gained momentum after late March 2020, and there was a sharp decline in posts about craving to smoke. This study highlights the significance of studying social media discussions on platforms like Reddit which are a rich ecological source of human experiences and provide insights to inform targeted messaging and mitigation strategies, and further complement ongoing traditional primary data collection methods.

Life under stay-at-home orders: a panel study of change in social interaction and emotional wellbeing among older Americans during COVID-19 pandemic.

BACKGROUND: Recent research has shown the mental health consequence of social distancing during the COVID-19 pandemic, but longitudinal data are relatively scarce. It is unclear whether the pattern of isolation and elevated stress seen at the beginning of the pandemic persists over time. This study evaluates change in social interaction over six months and its impact on emotional wellbeing among older adults. METHODS: We drew data from a panel study with six repeated assessments of social interaction and emotional wellbeing conducted monthly May through October 2020. The sample included a total of 380 White, Black and Hispanic participants aged 50 and over, of whom 33% had low income, who residing in fourteen U.S. states with active stay-at-home orders in May 2020. The analysis examined how change in living arrangement, in-person interaction outside the household, quality of relationship with family and friends, and perceived social support affected trajectories of isolation stress, COVID worry and sadness. RESULTS: While their living arrangements (Odds Ratio [OR] = 0.95, 95% Confidence Interval [CI] = 0.87, 1.03) and relationship quality (OR = 0.94, 95% CI = 0.82, 1.01) remained stable, older adults experienced fluctuations in perceived social support (linear Slope b = -1.42, s.e. = 0.16, p < .001, quadratic slope b = 0.50, s.e. = 0.08, p < .001, cubic slope b = -0.04, s.e. = 0.01, p < .001) and increases in in-person conversations outside the household (OR = 1.19, 95% CI = 1.09, 1.29). Living with a spouse/partner stabilized isolation stress (change in linear slope b = 1.16, s.e. = 0.48, p < .05, in quadratic slope b = -0.62, s.e. = 0.26, p < .05, and in cubic slope = 0.09, s.e. = 0.04, p < .05) and COVID worry (change in quadratic slope b = -0.66, s.e. = 0.32, p < .05 and in cubic slope = 0.09, s.e. = 0.04, p < .05) over time. Individuals with better relationship quality with friends had decreased sadness over time (OR = 0.90, 95% CI = 0.82, 0.99). Changes in social support were associated with greater fluctuations in isolation stress and COVID worry. CONCLUSIONS: During the pandemic, social interactions are protective and lack of stability in feeling supported makes older adults vulnerable to stress. Efforts should focus on (re)building and maintaining companionship and support to mitigate the pandemic's negative impact.

A 680,000-person megastudy of nudges to encourage vaccination in pharmacies.

Encouraging vaccination is a pressing policy problem. To assess whether text-based reminders can encourage pharmacy vaccination and what kinds of messages work best, we conducted a megastudy. We randomly assigned 689,693 Walmart pharmacy patients to receive one of 22 different text reminders using a variety of different behavioral science principles to nudge flu vaccination or to a business-as-usual control condition that received no messages. We found that the reminder texts that we tested increased pharmacy vaccination rates by an average of 2.0 percentage points, or 6.8%, over a 3-mo follow-up period. The most-effective messages reminded patients that a flu shot was waiting for them and delivered reminders on multiple days. The top-performing intervention included two texts delivered 3 d apart and communicated to patients that a vaccine was "waiting for you." Neither experts nor lay people anticipated that this would be the best-performing treatment, underscoring the value of simultaneously testing many different nudges in a highly powered megastudy.

The relationship between text message sentiment and self-reported depression.

BACKGROUND: Personal sensing has shown promise for detecting behavioral correlates of depression, but there is little work examining personal sensing of cognitive and affective states. Digital language, particularly through personal text messages, is one source that can measure these markers. METHODS: We correlated privacy-preserving sentiment analysis of text messages with self-reported depression symptom severity. We enrolled 219 U.S. adults in a 16 week longitudinal observational study. Participants installed a personal sensing app on their phones, which administered self-report PHQ-8 assessments of their depression severity, collected phone sensor data, and computed anonymized language sentiment scores from their text messages. We also trained machine learning models for predicting end-of-study self-reported depression status using on blocks of phone sensor and text features. RESULTS: In correlation analyses, we find that degrees of depression, emotional, and personal pronoun language categories correlate most strongly with self-reported depression, validating prior literature. Our classification models which predict binary depression status achieve a leave-one-out AUC of 0.72 when only considering text features and 0.76 when combining text with other networked smartphone sensors. LIMITATIONS: Participants were recruited from a panel that over-represented women, caucasians, and individuals with self-reported depression at baseline. As language use differs across demographic factors, generalizability beyond this population may be limited. The study period also coincided with the initial COVID-19 outbreak in the United States, which may have affected smartphone sensor data quality. CONCLUSIONS: Effective depression prediction through text message sentiment, especially when combined with other personal sensors, could enable comprehensive mental health monitoring and intervention.

Evidence against risk as a motivating driver of COVID-19 preventive behaviors in the United States.

Does an individual's risk profile predict their social distancing and mask wearing in the U.S. during the COVID-19 pandemic? Common sense and some health behavior theories suggest that as a perceived threat increases, an individual should be more likely to take preventive measures. We explore this hypothesis using survey responses collected from 1114 U.S. adults during April and October 2020, and find that neither perceived nor actual risk predicted these preventive behaviors. Instead, being an essential worker, partisanship, and believing compliance was important were more reliable predictors. These results provide guidance for better pandemic response policies and challenge models of health behavior.

Bots and Misinformation Spread on Social Media: Implications for COVID-19.

As of March 2021, the SARS-CoV-2 virus has been responsible for over 115 million cases of COVID-19 worldwide, resulting in over 2.5 million deaths. As the virus spread exponentially, so did its media coverage, resulting in a proliferation of conflicting information on social media platforms-a so-called "infodemic." In this viewpoint, we survey past literature investigating the role of automated accounts, or "bots," in spreading such misinformation, drawing connections to the COVID-19 pandemic. We also review strategies used by bots to spread (mis)information and examine the potential origins of bots. We conclude by conducting and presenting a secondary analysis of data sets of known bots in which we find that up to 66% of bots are discussing COVID-19. The proliferation of COVID-19 (mis)information by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic.