Predictors of Mental Well-being During the COVID-19 Pandemic

Overview

Study description: The present study seeks to investigate factors associated with well-being in the general population during the COVID-19 pandemic, three months following the introduction of the strict social distancing interventions in Norway. Hypotheses and research questions: Research Question 1: What is the level of mental well-being following three months of strict mitigation strategies (i.e., physical distancing) in the general adult population during the COVID-19 pandemic? The mean level of mental well-being will be benchmarked against the mean level of mental well-being in similar pre-pandemic samples. Hypothesis 1: Physical activity, being employed, positive metacognitions, negative metacognitions, and unhelpful coping strategies at T1 will significantly predict well-being (T2). Being employed and increased reports of physical activity at T2 will predict higher levels of mental well-being at the measurement period (T2) and serve as protective factors. Increased positive metacognitions, negative metacognitions and unhelpful coping strategies measured with CAS-1 at T2 will predict lower levels of well-being (T2). Additionally, we will examine whether the obtained predictive relationships hold when depressive symptoms (PHQ-9) and anxiety symptoms (GAD-7) at T2 will be controlled for. Exploratory: Do the predictors physical activity, positive metacognitions, negative metacognitions, unhelpful coping strategies, all at baseline (T1), predict mental well-being at T2, beyond and above these same aforementioned predictors at T2 and age, gender, and education? In all predictive analyses, age, gender, and education will be controlled for. Exploratory: We will exploratory investigate the differences in levels of mental well-being across different demographic subgroups in the sample.

Hypotheses and research questions: Research Question 1: What is the level of mental well-being following three months of strict mitigation strategies (i.e., physical distancing) in the general adult population during the COVID-19 pandemic? The mean level of mental well-being will be benchmarked against the mean level of mental well-being in similar pre-pandemic samples. Hypothesis 1: Physical activity, being employed, positive metacognitions, negative metacognitions, and unhelpful coping strategies at T1 will significantly predict well-being (T2). Being employed and increased reports of physical activity at T2 will predict higher levels of mental well-being at the measurement period (T2) and serve as protective factors. Increased positive metacognitions, negative metacognitions and unhelpful coping strategies measured with CAS-1 at T2 will predict lower levels of well-being (T2). Additionally, we will examine whether the obtained predictive relationships hold when depressive symptoms (PHQ-9) and anxiety symptoms (GAD-7) at T2 will be controlled for. Exploratory: Do the predictors physical activity, positive metacognitions, negative metacognitions, unhelpful coping strategies, all at baseline (T1), predict mental well-being at T2, beyond and above these same aforementioned predictors at T2 and age, gender, and education? In all predictive analyses, age, gender, and education will be controlled for. Exploratory: The investigators will exploratory investigate the differences in levels of mental well-being across different demographic subgroups in the sample. Statistical analysis: A hierarchical regression analysis will be conducted with SWEMWBS as the dependent variable. In the first step stable characteristics (control variables) will be included: age, gender and education. In the second step physical activity, being employed, positive metacognitions, negative metacognitions, and unhelpful coping strategies at T2 will be included. Part correlations will be examined for each step, presenting the effect size of the hypothesized predictors on mental well-being. In the third step, anxiety and depression at T2 will be included as control variables. In the final step, physical activity, being employed, positive metacognitions, negative metacognitions, and unhelpful coping strategies at T1 will be included. Multicollinearity and other statistical assumptions will be checked. Multicollinearity will be assessed with common guidelines (VIF \< 5 and Tolerance \> 0.2; Hocking, 2003; O'Brian, 2007). Descriptive statistics with frequency tables including N, means, SDs and other standard descriptive statistics will examine the research question concerning general levels of mental well-being. Subgroup differences will be examined. All analyses and questions addressed in the forthcoming paper that are not pre-specified in this pre-registered protocol will be defined as exploratory. Sensitivity analyses and random subsample replications of the main findings will be conducted following selection of a random sample of participants that ensure a proportionate ratio between the collected sample and the adult population of Norway. Possible transformations: All variables will be assessed in their original and validated format as is recommended practice, as long as this is possible with regards to statistical assumptions underlying the pre-defined analyses (i.e., hierarchical regression). However, if this is not possible with regards to the statistical assumptions behind the analyses, transformation (e.g., square root or log-transformations) may be needed to apply interval-based methods. The investigators will examine the degree of skewness and evaluate this against the assumptions and analyses before choosing the appropriate analysis. The pre-registered and planned analysis include hierarchical regression as long as assumptions underlying this analysis is met. Alternatively, a non-parametric test will be used. Inference criteria Given the large sample size in this study, the investigators pre-define their significance level: p \< 0.01 to determine significance. Sample size and power calculation: The present study is part of a larger project with the first part aiming to investigate predictors of mental well-being through regression analyses, and the second part aiming to examine directional relations amongst specific symptoms and their centrality through complex systems approaches (i.e., network analysis). Consequently, power calculations are based on power required for network analyses. Following power analysis guidelines by Fried \& Cramer (2017), it is recommended that the number of participants are three times larger than the number of estimated parameters. However, more conservative recommendations by Roscoe (1975) for multivariate research, recommends sample size that is ten times larger than the number of estimated parameters. Thus, following these two approaches respectively, between 1584 to 5280 participants are required. Data will be collected for three weeks, and participants are based on a representative and random sample of Norwegian adults, randomly selected and provided equal opportunity to partake in the study, providing digital consent. Missing data: The TSD system (Services for Sensitive Data), a platform used in Norway to store person-sensitive data verifies participants officially through a kind of national ID number to give them full right to withdraw their data at any time, following the European GDPR (General Data Protection Regulation) laws. Accordingly, participants are allowed to withdraw their own data at any time. The survey includes mandatory fields of response. Participation is voluntarily, and withdrawal of provided data is possible at any moment. The investigators do not expect participants to withdraw their data and thus expect no missing data. However, if participants do withdraw their data, the investigators will conduct state-of-art missing data analyses and investigate whether data is missing at random.