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Original Article

A Persian Validation of the Occupational Depression Inventory

Published Online:April 15, 2024https://doi.org/10.1027/1015-5759/a000830

Abstract

Abstract: The present study examined the psychometric and structural properties of the Persian version of the Occupational Depression Inventory (ODI). The ODI focuses on depressive symptoms that employed individuals specifically ascribe to their work. A sample of 355 Iranian schoolteachers was surveyed. Exploratory structural equation modeling (ESEM) bifactor analysis indicated that the ODI meets the requirements for essential unidimensionality. ESEM bifactor analysis and scalability analysis supported the use of the ODI’s total score. The instrument exhibited high reliability. Cross-cultural measurement invariance was supported. As for the concurrent validity of the ODI, occupational depression correlated, in the expected direction, with job satisfaction, life satisfaction, well-being, work engagement, sick leave, and antidepressant intake. No association was observed with sex, age, length of employment, and a history of depressive disorders over the past year. The ODI displayed a balance of convergent and discriminant validity vis-a-vis an attribution-free measure of depressive symptoms. The prevalence of occupational depression was estimated at 2.8% in our sample. Our findings endorse the Persian version of the ODI and confirm the instrument’s overall robustness.

References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. First citation in articleCrossref, Google Scholar

  • Bianchi, R., & Schonfeld, I. S. (2020). The Occupational Depression Inventory: A new tool for clinicians and epidemiologists. Journal of Psychosomatic Research, 138, Article 110249. https://doi.org/10.1016/j.jpsychores.2020.110249 First citation in articleCrossref, Google Scholar

  • Bianchi, R., & Schonfeld, I. S. (2023). Examining the evidence base for burnout. Bulletin of the World Health Organization, 101(11), 743–745. https://doi.org/10.2471/BLT.23.289996 First citation in articleCrossref, Google Scholar

  • Bianchi, R., Verkuilen, J., Sowden, J. F., & Schonfeld, I. S. (2023). Towards a new approach to job-related distress: A three-sample study of the Occupational Depression Inventory. Stress and Health, 39(1), 137–153. https://doi.org/10.1002/smi.3177 First citation in articleCrossref, Google Scholar

  • Hill, C., de Beer, L. T., & Bianchi, R. (2021). Validation and measurement invariance of the Occupational Depression Inventory in South Africa. PLoS One, 16(12), Article e0261271. https://doi.org/10.1371/journal.pone.0261271 First citation in articleCrossref, Google Scholar

  • Jansson-Fröjmark, M., Badinlou, F., Lundgren, T., Schonfeld, I. S., & Bianchi, R. (2023). Validation of the Occupational Depression Inventory in Sweden. BMC Public Health, 23, Article 1505. https://doi.org/10.1186/s12889-023-16417-w First citation in articleCrossref, Google Scholar

  • Montazeri, A., Vahdaninia, M., Ebrahimi, M., & Jarvandi, S. (2003). The Hospital Anxiety and Depression Scale (HADS): Translation and validation study of the Iranian version. Health and Quality of Life Outcomes, 1, Article 14. https://doi.org/10.1186/1477-7525-1-14 First citation in articleCrossref, Google Scholar

  • Muthén, L. K., & Muthén, B. O. (1998–2021). Mplus user’s guide (8th ed.). Muthén & Muthén. First citation in articleGoogle Scholar

  • R Core Team. 2022 R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/ First citation in articleGoogle Scholar

  • Schaarschmidt, U., & Fischer, A. W. (1996). AVEM-Arbeitsbezogenes Verhaltens- und Erlebensmuster: Psychodiagnostisches Verfahren. Testreihe: Computerversion des Verfahrens [Work-related behavior and experience patterns: Psychodiagnostic procedure. Test series: Computer version of the procedure]. Swets & Zeitlinger. First citation in articleGoogle Scholar

  • Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66(4), 701–716. https://doi.org/10.1177/0013164405282471 First citation in articleCrossref, Google Scholar

  • Schonfeld, I. S. (2001). Stress in 1st-year women teachers: The context of social support and coping. Genetic, Social, and General Psychology Monographs, 127(2), 133–168. First citation in articleGoogle Scholar

  • Streiner, D. L., Norman, G. R., & Cairney, J. (2015). Health measurement scales: A practical guide to their development and use (5th ed.). Oxford University Press. First citation in articleCrossref, Google Scholar

  • Topp, C. W., Østergaard, S. D., Søndergaard, S., & Bech, P. (2015). The WHO-5 Well-Being Index: A systematic review of the literature. Psychotherapy and Psychosomatics, 84(3), 167–176. https://doi.org/10.1159/000376585 First citation in articleCrossref, Google Scholar

  • van der Ark, L. A. (2012). New developments in Mokken Scale analysis in R. Journal of Statistical Software, 48(5), 1–27. https://doi.org/10.18637/jss.v048.i05 First citation in articleCrossref, Google Scholar