Computational protocol: Factors related to work and life satisfaction of veterinary practitioners in Germany

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Protocol publication

[…] Data were transferred from LimeSurvey and the hardcopy questionnaires to Microsoft Excel and subsequently analysed in IBM SPSS V.23 (Statistical Package for Social Sciences) for exploration and description. Quantitative data (eg, working hours per week, pretax annual income, results of importance of job characteristics and work and life satisfaction) were assessed graphically and by Kolmogorov-Smirnov tests for normality. Non-normally distributed variables and scores were described using medians. The association between gender and continuous variables (importance of job characteristics, percentage of own income to the complete household income) was analysed using a Mann-Whitney U test. The level of significance was set to P<0.05. Arithmetic means of the scores were used to rank the different job characteristics in every subgroup (female employed practitioners (FEP), male employed practitioners (MEP), female self-employed practitioners (FSEP), male self-employed practitioners (MSEP)) and to compare these rankings with Friedrich (2007). The lavaan package from the software R (www.lavaan.ugent.be ) was used to develop and run SEMs in order to analyse the interaction and association between the dependent variables (work satisfaction, life satisfaction) and the independent variables (satisfaction with the supervisor, satisfaction with income, satisfaction with colleagues, satisfaction with professional development, satisfaction with working time, satisfaction with family life, satisfaction with leisure time, satisfaction with standard of living, satisfaction with health). The hypothesised relations were defined on the basis of those survey components available from the study. SEM conjoins the methodology of path analysis and multiple regression, and uses basic correlation analysis, regression models and confirmatory factor analysis. Four SEMs were constructed: (1) FEP, (2) MEP, (3) FSEP and (4) MSEP. In the SEM, latent and observed variables were completely standardised (β) and the regression coefficients were standardised. The theoretically relevant variables were placed in the model according to subcategories in our questionnaire (eg, life and work satisfaction). Afterwards the models were adapted corresponding to observed correlations between variables. Model fit was estimated with a comparative fit index close to 0.95, a Tucker-Lewis index of greater than 0.90, a standardised root mean square residual of less than 0.08 and a root mean square error of approximation of close to 0.06. The level of statistical significance was set to P<0.05 for all SEMs. […]

Pipeline specifications

Software tools SPSS, lavaan
Application Miscellaneous