Statistical analysis: two way ANOVA
Wellbeing of researchers: Investigating if the experienced stress level at work is effected by gender and genetic predisposition to burnout. During this study, we will look at the gender and genetic risk for burnout of the researcher and if it is related to t...
Wellbeing of researchers: Investigating if the experienced stress level at work is effected by
gender and genetic predisposition to burnout.
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Statistics 3
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, BURNOUT RISK AND GENDER AFFECTING STRESS
Introduction
Previous studies show that researchers experience a higher level of stress in the workplace.
Behavioural-genetic and biological theories describe that both stress coping models and genetic
predispositions to burnout influence the individual's level of experienced stress. During this study,
we will look at the gender and genetic risk for burnout of the researcher and if it is related to the
level of stress during work. Specifically, we hypothesize that females will have a higher rate of
genetic risk to burnout. In addition, we expect females with a genetic predisposition to score higher
on stress than males with a genetic predisposition.
Methods
Participants
The sample has 400 participants, of which 151 (38%) are male and 249 (62%) Female. The
age varies between 20 and 59 years (M = 40.24, SD = 11.06).
Materials
A questionnaire was administered to researchers. The first independent variable is the
genetic risk for burnout. The variable is categorical and has two levels; being at risk (factor A) or
not being at risk (factor A2). The participants had to indicate whether burnout was present in their
families. Based on this, 105 (26%) individuals were classified as having a predisposition for
burnout, while 295 (74%) were not.
The second independent variable is gender. This variable is also divided into two levels;
factor B1 (male) and factor B2 (female).
The dependent variable is the level of stress experienced by the researchers. Possible scores
are from 0 to 100, a low score indicating low perceived stress and a high score indicating high
perceived stress. In this sample these scores ranged from 19.83 to 100 ( M = 64.01, SD = 15.18).
Statistical analysis
This study uses IBM SPSS statistics 28.00 for all analyses. To test our hypotheses, we will
use a two way ANOVA as we have two categorical independent variables and one quantitative
dependent variable. First, we have to see whether our sample meets the assumptions for the
ANOVA. For assessing the main effects, we are looking at whether the population means of the
dependent variable (stress level of researchers) are equal across factor level A1 (having a genetic
risk for burnout) vs Factor level A2 (not having a genetic risk for burnout). To test this hypothesis,
we will compute an F ratio. The same principle assesses the main effect of factors B1 (male) and B2
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