Prospective predictors of risk and resilience trajectories during the early stages of the COVID-19 pandemic: a longitudinal study
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Abstract
Background
The COVID-19 pandemic is a rapidly evolving stressor with significant mental health consequences. We aimed to delineate distinct anxiety-response trajectories during the early stages of the pandemic and to identify baseline risk and resilience factors as predictors of anxiety responses.
Methods
Using a crowdsourcing website, we enrolled 1,362 participants, primarily from the United States (n = 1064) and Israel (n = 222) over three time-points from April-September 2020. We used latent growth mixture modeling to identify anxiety trajectories over time. Group comparison and multivariate regression models were used to examine demographic and risk and resilience factors associated with class membership.
Results
A four-class model provided the best fit. The resilient trajectory (stable low anxiety) was the most common (n = 961, 75.08%), followed by chronic anxiety (n = 149, 11.64%), recovery (n = 96, 7.50%) and delayed anxiety (n = 74, 5.78%). While COVID-19 stressors did not differ between trajectories, resilient participants were more likely to be older, living with another person and to report higher income, more education, fewer COVID-19 worries, better sleep quality, and more dispositional resilience factors at baseline. Multivariate analyses suggested that baseline emotion regulation capabilities and low conflictual relationships uniquely distinguished participants in distinct trajectories.
Conclusions
Consistent with prior resilience research following major adversities, a majority of individuals showed stable low levels of low anxiety in response to the COVID-19 pandemic. Knowledge about dispositional resilience factors may prospectively inform mental health trajectories early in the course of ongoing adversity.
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SciScore for 10.1101/2021.10.08.21264752: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: The study was approved by the Institutional Review Board of the University of Pennsylvania. Sex as a biological variable not detected. Randomization All analyses were conducted in Mplus version 8 (Muthén & Muthén, 2017) using a robust full information maximum likelihood (FIML) estimation procedure for handling missing data which assumes missing data are unrelated to the outcome variable (i.e., missing at random) (Enders, 2001). Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from …SciScore for 10.1101/2021.10.08.21264752: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: The study was approved by the Institutional Review Board of the University of Pennsylvania. Sex as a biological variable not detected. Randomization All analyses were conducted in Mplus version 8 (Muthén & Muthén, 2017) using a robust full information maximum likelihood (FIML) estimation procedure for handling missing data which assumes missing data are unrelated to the outcome variable (i.e., missing at random) (Enders, 2001). Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:However, our findings should be considered alongside several important study limitations. First, we used an on-line “snow-ball” recruitment method, which reduced the representativeness of our sample and the generalizability of the findings. Specifically, people who complete online surveys differ from people who do not, and thus the proportions of people in each trajectory should not be taken as population-level estimates (Pierce, McManus, et al., 2020). Second, our cohort included participants from the US and Israel, countries characterized by considerable differences in virus spread, government restrictions, and health care. Indeed, living in Israel predicted membership in the resilient group. Notably, however, at time T1 data collection, the restrictions on residents were similar in both Israel and the US. Moreover, a recent study in the US, the United Kingdom, and Israel similarly found that Israeli participants exhibited lower levels of general anxiety compared to others (Bareket-Bojmel, Shahar, & Margalit, 2020), which might reflect cultural differences in expressing anxiety symptoms. Importantly, the trajectory patterns were largely robust to these differences, and similar findings emerged when the sample was restricted to only the US participants. In sum, we found distinct patterns of adaptation to the COVID-19 pandemic in our longitudinal cohort. These patterns were prospectively predicted by dispositional resilience factors and by COVID-19 stressors, suggesting that ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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