National Longitudinal Mediators of Psychological Distress During Stringent COVID-19 Lockdown
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
We leverage powerful time-series data from a national longitudinal sample measured before the COVID-19 pandemic and during the world’s eighth most stringent COVID-19 lockdown (New Zealand, March-April 2020, N = 940) and apply Bayesian multilevel mediation models to rigorously test five theories of pandemic distress. Findings: (1) during lockdown, rest diminished distress; without rest psychological distress would have been ~ 1.74 times greater; (2) an elevated sense of community reduced distress, a little, but elevated government satisfaction was inert. Thus, the psychological benefits of lockdown extended to political discontents; (3) most lockdown distress arose from dissatisfaction from personal relationships. Social captivity, more than isolation, proved challenging; (4-5) Health and business satisfaction were stable; were they challenged substantially more distress would have ensued. Thus, lockdown benefited psychological health by affording safety, yet only because income remained secure. These national longitudinal findings clarify the mental health effects of stringent infectious disease containment.
Article activity feed
-
SciScore for 10.1101/2020.09.15.20194829: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Though rates of overall missingness were low, to avoid biasing estimates, we multiply imputed missing values using the Amelia package in R(Honaker et al., 2011). Ameliasuggested: (AMELIA, RRID:SCR_009119)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage …
SciScore for 10.1101/2020.09.15.20194829: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Though rates of overall missingness were low, to avoid biasing estimates, we multiply imputed missing values using the Amelia package in R(Honaker et al., 2011). Ameliasuggested: (AMELIA, RRID:SCR_009119)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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.
-
-