Parental Burnout During the COVID-19 Pandemic: Risk Factors and Predictors

Hypothesis and research question:

Research Question 1: What is the level of parental burnout in the general parental population
three months following initiated viral mitigation protocols (i.e., physical distancing) as
compared to other similar pre-pandemic samples?

Hypothesis 1: Parental burnout will be higher in the present sample three months into the
pandemic as compared to similar pre-pandemic samples in similar populations.

Hypothesis 2: Levels of parental stress, parental satisfaction, general self-efficacy,
positive metacognitions, negative metacognitions, unhelpful coping strategies, marital
quality and insomnia, all at T2 will significantly predict levels of parental burnout at T2.

Exploratory: Do the predictors parental stress, parental satisfaction, general self-efficacy,
positive metacognitions, negative metacognitions, unhelpful coping strategies, all at
baseline (T1), predict parental burnout at T2, beyond and above these same aforementioned
predictors at T2 and pre-existing mental health condition, age, gender, and education?

Exploratory: Levels of parental burnout will be explored across subgroups in the sample.

Statistical analysis A hierarchical regression analysis will be conducted with Parental
burnout (PBI) as the dependent variable. In the first step, stable characteristics (control
variables) will be included: gender, education, and age. In the second step, parental stress,
parental satisfaction, general self-efficacy, positive metacognitions, negative
metacognitions, and unhelpful coping strategies, marital quality, and insomnia, all at T2
will be included.. In the final step, parental stress, parental satisfaction, general
self-efficacy, positive metacognitions, negative metacognitions, and unhelpful coping
strategies, all at T1 will be included.

Part correlations will be reported, presenting the effect size of the hypothesized predictors
on parental burnout. 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.

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.

Any questions addressed in the forthcoming paper which is not pre-specified in this protocol
will be explicitly defined as exploratory.

Inference criteria Given the estimated large sample size which the investigators hope to
collect 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 parental burnout 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 900 to 3000
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.