Burn Out Among Medical Family Doctors

Summary

Participation Requirements

Description

The BOUM protocol is designed to provide a better understanding of the current burnout prevalence among French general practitioners, as well as its risk and protective factors. In order to fulfil those objectives, the methodologist estimated a 1536 individuals sample size, using an expected prevale...

The BOUM protocol is designed to provide a better understanding of the current burnout prevalence among French general practitioners, as well as its risk and protective factors. In order to fulfil those objectives, the methodologist estimated a 1536 individuals sample size, using an expected prevalence of severe burnout ranged between 10% and 20% (from the the EGPRN study - Soler, J.K., et al., Burnout in European family doctors: the EGPRN study. Family Practice, 2008. 25(4): p. 245-265), thus allowing the investigators to retrieve results with a 95% confidence level and a 2% error margin. All analyses will be performed in a bilateral formulation for a 5% alpha error under the Stata® software (version 13, StataCorp, College Station, US). A difference will be considered statistically significant for p<0.05. The population will be described as frequency and percentage for the categorical variables, and as mean ± standard deviation or median [interquartile range] for the quantitative variables, according to their statistical distribution (normality studied by the Shapiro-Wilk test). Confidence intervals for population prevalence will be characterised with a binomial test. Comparisons between groups of burnout will be performed using Chi2 or Fisher's exact test for the categorical variables (followed by a Marascuillo post-hoc tests if needed), and by an ANOVA or Kruskal-Wallis test if normality and homoscedasticity not respected (Bartlett test) for the quantitative variables (followed by Tukey-Kramer or Dunn tests when necessary). Finally, considering the variables clinically relevant and those with a pertinent univariate analysis results, a multivariate analyse of ordinal polynomial regression type will be proposed; its results will be expressed as relative risk with 95% confidence intervals and presented as a Forest-plot.

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