The Impact of Information Sources on Mental Health During the COVID-19 Pandemic

Hypotheses and research questions: Hypothesis 1: Media consumption across all information sources will significantly be associated with depression and anxiety symptoms, with increased media consumption in general associated with higher levels of health anxiety, depression, and general anxiety. Hypothesis 2: Using social media and online interactive platforms to obtain news about the pandemic in comparison to using traditional media (e.g., TV, radio, and newspapers) will be associated with higher levels of health anxiety, depression, and general anxiety. Actively staying away from information will further significantly be associated with higher levels of higher levels of health anxiety, depression, and general anxiety. Research Question 1: Is there a differential effect among different information sources on health anxiety, depression and general anxiety? To what extend and how are different information sources related to symptoms of health anxiety, depression, and general anxiety. Exploratory: Additionally, the investigators will exploratory investigate to what extent the amount of use of different information sources impact health anxiety, depression, and general anxiety. The investigators will also examine effect sizes with part correlations, to investigate information sources with the most and least detrimental impact on health anxiety, depression, and general anxiety. Furthermore, the investigators will report which information platforms participants reported as most useful with regards to information concerning how to best deal with the pandemic. Statistical analysis: Three multiple regression analyses will be conducted. 1) with PHQ-9 as the dependent variable; and 2) the second with GAD-7 at as the dependent variable; and 3) the third with Health Anxiety as the dependent variable. All analyses will include the different sources of information as predictor variables, while controlling for the effects of pre-existing mental health condition, gender, age, and education. Part correlations will be reported for each regression analysis, presenting the effect size of the hypothesized predictors associated with health anxiety, depression and general anxiety. A part (semi-partial) correlation gives the least biased and easiest interpretable estimate of the strength of a predictive relationship (Dudgeon, 2016). It is the correlation between the outcome and the aspects of the predictor unique from all the other predictors. As a type of correlation, its size can be evaluated according to Cohen's (1988) criteria: small \>=0.10, medium \>=0.30, large \>=0.50. The sources of information include: 1) National television and radio channels; 2) national and regional, and local newspapers; 3) Use of social media for information; 4) use of blogs, podcasts, forums or other Internet sources; 5) information obtained from peers (i.e., friends and family); 6) Other sources of information; 7) actively staying away from information. Multicollinearity and other statistical assumptions will be checked using examined. Multicollinearity will be assessed with common guidelines (VIF \< 5 and Tolerance \> 0.2; Hocking, 2003; O'Brian, 2007). 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., multiple 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 analyses include multiple regression as long as assumptions are 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 information source predictors of mental health through regression analyses, and the second part aiming to examine directional relations amongst specific sources of information 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 1053 to 3510 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.