Methodological issues in assessing job stress and burnout in psychosocial research Methodological issues in assessing job stress and burnout 

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Paolo Campanini


job stress, burnout, methodological issues


In recent years, researchers identified a “reproducibility crisis” of scientific studies. In assessing job stress and burnout in psychosocial research two biases that prevent the results from being generalized are common: sample bias (included web survey) and common method bias using questionnaires. These issues are commented and remedies are proposed to prevent or contain biases.

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WHO. International Statistical Classification of Diseases and Related Health Problems (ICD). WHO, Geneva,
Brera AS, Arrigoni C, Dellafiore F, et al. Burnout syndrome and its determinants among healthcare workers during the first wave of the Covid-19 outbreak in Italy: a cross-sectional study to identify sex-related differences. Med Lav. 2021; 112 (4):
Converso D, Sottimano I, Balducci C. Violence exposure and burnout in healthcare sector: mediating role of work ability. Med Lav [Internet]. 2021;23:112(1):58-67
Vignoli M, Mazzetti G, Converso D, Guglielmi D. How workers’ emotional dissonance explains the association between customers’ relations, burnout and health in an Italian supermarket chain. Med Lav. 2021;112(3):200-208
Viotti S, Guglielmetti C, Gilardi S, Guidetti G. The role of colleague incivility in linking work-related stressors and job burnout. A cross-sectional study in a sample of faculty administrative employees. Med Lav 2021;112(3):209-218
Eysenbach G. Improving the Quality of Web Surveys: The Checklist for Reporting Results of Internet E-Surveys (CHERRIES). J Med Internet Res 2004;6(3):e34
Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP. CommonMethod Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. J Applied Psychology. 2003;88(5):879-903.
Cote JA, Buckley R. Estimating trait, method, and error variance: Generalizing across 70 construct validation studies. J Marketing Research. 1987;24:315-318. 
Lance CE, Dawson B, Birkelbach D, Hoffman BJ. Method Effects, Measurement Error, and Substantive Conclusions. Organizational Research Methods. 2000;13:3:435-455
Kahneman D, Slovic P, Tversky A: Judgment under uncertainty: Heuristics and biases: Cambridge University Press, 1982
Kahneman D, Tversky A. On the Reality of Cognitive Illusions. Psychological Review. 1996;103(3):582-591
Watson D, Clark LA. Negative affectivity: The disposition to experience negative aversive emotional states. Psychological Bulletin. 1984;96:465–490
Spector PE, Chen PY, O’Connell BJ. A longitudinal study of relations between job stressors and job strains while controlling for prior negative affectivity and strains. Journal of Applied Psychology. 2000;85: 211-218
Wicherts JM, Borsboom D, Kats J, Molenaar D. T‍he poor availability of psychological research data for reanalysis. Am. Psychol. 2006;61:726-728
Al-Shahi Salman R, Beller E, Kagan J, et al. Increasing value and reducing waste in biomedical research regulation and management. Lancet. 2014;383(9912):176-185
10 Chan AW, Song F, Vickers A, et al. Increasing value and reducing waste: addressing inaccessible research. Lancet. 2014;383(9913):257-266. doi:10.1016/S0140-6736(13)62296-5 
Baker, M. 1,500 scientists lift the lid on reproducibility. Nature. 2016;533:452–454. 
Hardwicke TE, Wallach JD, Kidwell MC, Bendixen T, Crüwell S, Ioannidis JPA. An empirical assessment of transparency and reproducibility-related research practices in the social sciences (2014-2017). R Soc Open Sci. 2020;7(2):190806
Hardwicke TE, Thibault RT, Kosie JE, Wallach JD, Kidwell MC, Ioannidis JPA. Estimating the Prevalence of Transparency and Reproducibility-Related Research Practices in Psychology (2014-2017). Perspect Psychol Sci. 2021;1745691620979806