Preview

Psychiatry (Moscow) (Psikhiatriya)

Advanced search

Psychometric Properties of the Occupational Depression Inventory (ODI)

https://doi.org/10.30629/2618-6667-2026-24-2-131-151

Abstract

Background: existing tools for assessing depression do not take into account its contextualized nature. One of the prevailing spheres of human activity is labor activity, which may cause the occurrence of depression associated with professional activity. Occupational depression is a depressive state associated with chronic work stress. Because occupational activity may be a significant factor in the development of depressive symptoms, the Occupational Depression Inventory (ODI) was developed to assess context-related depression, but it requires a comprehensive evaluation of its psychometric properties.

The aim of study was to systematically review the psychometric properties of the ODI based on existing research articles.

Materials and Methods: a systematic literature search and selection was conducted in the following databases: Lens.org, PubMed, OpenAlex, Crossref, Microsoft Academic, JSTOR, ScienceDirect, and Google Scholar. 246 publications were retrieved for preliminary screening. After screening and validation against inclusion/exclusion criteria, 16 publications were selected assessing the psychometric properties of the ODI on a sample of a total of 17 290 respondents from 15 countries in 10 different languages.

Results: ODI is a valid and reliable tool for diagnosing work-related depression in many countries. The ODI demonstrates cross-cultural invariance, clinical relevance to current diagnostic standards, and functionality in different technical settings of psychological diagnosis.

Conclusion: the ODI is a promising tool for screening occupational depression in research practice. Studies of prognostic validity, test-retest reliability, and adaptation for different occupational groups are needed to expand clinical application.

About the Author

A. A. Cherniavskii
National Research University “HSE University”; O.P. Jindal Global University
Russian Federation

Aleksandr A. Cherniavskii, Master's student of the educational program “Positive Psychology”, participant of the scientific and educational group “Laboratory of Personal Development” and the program “Unified track of education Master's Degree-Postgraduate”, HSE University; exchange-student of Jindal School of Psychology and Counseling, O.P. Jindal Global University

Moscow, Sonipat



References

1. Wang J, Wu X, Lai W, Long E, Zhang X, Li W, Zhu Y, Chen C, Zhong X, Liu Z, Wang D, Lin H. Prevalence of depression and depressive symptoms among outpatients: a systematic review and meta-analysis. BMJ Open. 2017;7(8):e017173. doi: 10.1136/bmjopen-2017-017173 PMID: 28838903; PMCID: PMC5640125

2. Lim GY, Tam WW, Lu Y, Ho CS, Zhang MW, Ho RC. Prevalence of depression in the community from 30 countries between 1994 and 2014. Scientific Reports. 2018;8(1):2861. doi: 10.1038/s41598-018-21243-x

3. Richards D. Prevalence and clinical course of depression: a review. Clin Psychol Rev. 2011;31(7):1117–25. doi: 10.1016/j.cpr.2011.07.004 Epub 2011 Jul 23. PMID: 21820991.

4. Arias-de la Torre J, Vilagut G, Ronaldson A, Serrano-Blanco A, Martín V, Peters M, Valderas JM, Dregan A, Alonso J. Prevalence and variability of current depressive disorder in 27 European countries: a population-based study. Lancet Public Health. 2021;6(10):e729–e738. doi: 10.1016/S24682667(21)00047-5 Epub 2021 May 4. PMID: 33961802; PMCID: PMC8460452.

5. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (5th ed., text revision). Washington, DC: American Psychiatric Publishing: 2022.

6. World Health Organization. International statistical classification of diseases and related health problems (11th ed.). 2019. URL: https://icd.who.int/

7. Madsen IE, Sørensen JK, Bruun JE, Framke E, Burr H, Melchior M, Sivertsen B, Stansfeld S, Kivimäki M, Rugulies R. Emotional demands at work and risk of hospital-treated depressive disorder in up to 1.6 million Danish employees: a prospective nationwide register-based cohort study. Scand J Work Environ Health. 2022;48(4):302–311. doi: 10.5271/sjweh.4020 Epub 2022 Mar 9. PMID: 35262742; PMCID: PMC9524161.

8. Bakker AB, Demerouti E. The job demands-resources model: State of the art. Journal of managerial psychology. 2007;22(3):309–328. doi: 10.1108/02683940710733115

9. Melchior M, Caspi A, Milne BJ, Danese A, Poulton R, Moffitt TE. Work stress precipitates depression and anxiety in young, working women and men. Psychol Med. 2007;37(8):1119–29. doi: 10.1017/S0033291707000414 Epub 2007 Apr 4. PMID: 17407618; PMCID: PMC2062493.

10. Bianchi R, Schonfeld IS, Laurent E. Burnout-depression overlap: a review. Clin Psychol Rev. 2015;36:28– 41. doi: 10.1016/j.cpr.2015.01.004 Epub 2015 Jan 17. PMID: 25638755.

11. Rössler W. Depression und Burnout. Praxis (Bern 1994). 2014;103(18):1067–70. doi: 10.1024/1661-8157/a001776 PMID: 25183615

12. Bianchi R, Schonfeld IS. The Occupational Depression Inventory: A new tool for clinicians and epidemiologists. J Psychosom Res. 2020;138:110249. doi: 10.1016/j.jpsychores.2020.110249 Epub 2020 Sep 15. PMID: 32977198.

13. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. doi: 10.1371/journal.pmed.1000097 Epub 2009 Jul 21. PMID: 19621072; PMCID: PMC2707599.

14. DiStefano C, Liu J, Jiang N, Shi D. Examination of the Weighted Root Mean Square Residual: Evidence for Trustworthiness? Structural Equation Modeling: A Multidisciplinary Journal. 2017;25(3):453–466. doi: 1 0.1080/10705511.2017.1390394

15. Kline RB. Principles and practice of structural equation modeling. Guilford publications. 2023.

16. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999;6(1):1–55. doi: 10.1080/10705519909540118

17. Rodriguez A, Reise SP, Haviland MG. Evaluating bifactor models: Calculating and interpreting statistical indices. Psychol Methods. 2016;21(2):137–50. doi: 10.1037/met0000045 Epub 2015 Nov 2. PMID: 26523435.

18. Malapane TA, Ndlovu NK. Assessing the reliability of Likert scale statements in an e-commerce quantitative study: A Cronbach alpha analysis using SPSS Statistics. Systems and Information Engineering Design Symposium (SIEDS). 2024:90–95.

19. Dunn TJ, Baguley T, Brunsden V. From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation. Br J Psychol. 2014;105(3):399–412. doi: 10.1111/bjop.12046 Epub 2013 Aug 6. PMID: 24844115.

20. Guttman L. A basis for analyzing test-retest reliability. Psychometrika. 1945;10:255–82. doi: 10.1007/BF02288892 PMID: 21007983.

21. Zijlmans EAO, Tijmstra J, van der Ark LA, Sijtsma K. Item-Score Reliability in Empirical-Data Sets and Its Relationship With Other Item Indices. Educ Psychol Meas. 2018;78(6):998–1020. doi: 10.1177/0013164417728358 Epub 2017 Sep 27. PMID: 30542214; PMCID: PMC6236637.

22. Stochl J, Jones PB, Croudace TJ. Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers. BMC Med Res Methodol. 2012;12:74. doi: 10.1186/1471-2288-12-74 PMID: 22686586; PMCID: PMC3464599.

23. Sijtsma K, van der Ark LA. A tutorial on how to do a Mokken scale analysis on your test and questionnaire data. Br J Math Stat Psychol. 2017;70(1):137– 158. doi: 10.1111/bmsp.12078 Epub 2016 Dec 13. Erratum in: Br J Math Stat Psychol. 2017;70(3):565. doi: 10.1111/bmsp.12115 PMID: 27958642.

24. Gilbert GE, Prion S. Making sense of methods and measurement: Lawshe's content validity index. Clinical simulation in nursing. 2016;12(12):530–531. doi: 10.1016/j.ecns.2016.08.002

25. Cohen J. A power primer. Psychol Bull. 1992;112(1):155– 9. doi: 10.1037//0033-2909.112.1.155 PMID: 19565683.

26. Prion S, Haerling KA. Making sense of methods and measurement: Spearman-rho ranked-order correlation coefficient. Clinical Simulation in Nursing. 2014;10(10):535–536. doi: 10.1016/j.ecns.2014.07.005

27. Sullivan GM, Feinn R. Using Effect Size-or Why the P Value Is Not Enough. J Grad Med Educ. 2012;4(3):279–82. doi: 10.4300/JGME-D-12-00156.1 PMID: 23997866; PMCID: PMC3444174.

28. Nieminen P. Application of Standardized Regression Coefficient in Meta-Analysis. BioMedInformatics. 2022;2(3):434–458. doi: 10.3390/biomedinformatics2030028

29. Schonfeld IS, Bianchi R, Luehring-Jones P. Consequences of job stress for the mental health of teachers. Educator stress: An occupational health perspective. 2017;3:55–75. doi: 10.1007/978-3-319-53053-6_3

30. Bianchi R, Fiorilli C, Angelini G, Dozio N, Palazzi C, Palazzi G, Vitiello B, Schonfeld IS. Italian version of the Occupational Depression Inventory: Validity, reliability, and associations with health, economic, and work-life characteristics. Front Psychiatry. 2022;13:1061293. doi: 10.3389/fpsyt.2022.1061293 PMID: 36620692; PMCID: PMC9813419.

31. Bianchi R, Cavalcante DC, Queirós C, Santos BDM, Verkuilen J, Schonfeld IS. Validation of the Occupational Depression Inventory in Brazil: A study of 1612 civil servants. J Psychosom Res. 2023;167:111194. doi: 10.1016/j.jpsychores.2023.111194 Epub 2023 Feb 15. PMID: 36801658.

32. Bianchi R, Manzano-García G, Montañés-Muro P, Schonfeld EA, Schonfeld IS. Occupational depression in a Spanish-speaking sample: associations with cognitive performance and work-life characteristics. Revista de Psicología del Trabajo y de las Organizaciones. 2022;38(1):59–74. doi: 10.5093/jwop2022a5

33. Bianchi R, Verkuilen J, Sowden JF, Schonfeld IS. Towards a new approach to job-related distress: A three-sample study of the Occupational Depression Inventory. Stress Health. 2023;39(1):137–153. doi: 10.1002/smi.3177 Epub 2022 Jun 20. PMID: 35700982; PMCID: PMC10084211.

34. Bianchi R, Schonfeld IS. Occupational Depression, Cognitive Performance, and Task Appreciation: A Study Based on Raven's Advanced Progressive Matrices. Front Psychol. 2021;12:695539. doi: 10.3389/fpsyg.2021.695539 PMID: 34616332; PMCID: PMC8488105.

35. Bianchi R, Schonfeld IS. Is the Occupational Depression Inventory predictive of cognitive performance? A focus on inhibitory control and effortful reasoning. Personality and Individual Differences. 2022;184.111213. doi: 10.1016/j.paid.2021.111213

36. Elliðadóttir BB, Ólafsdóttir LB. Translating the Occupational Depression Inventory (ODI) to Icelandic: a preliminary investigation of factor structure and reliability of the scale. 2024. (Doctoral dissertation).

37. Fortuna D, Golonka K. When you avoid your feelings, you may feel even worse: how depersonalization puts you at risk of depression. Front Psychiatry. 2024;15:1481439. doi: 10.3389/fpsyt.2024.1481439 PMID: 39493425; PMCID: PMC11528536.

38. Golonka K, Malysheva KO, Fortuna D, Gulla B, Lytvyn S, De Beer LT, Schonfeld IS, Bianchi R. A validation study of the Occupational Depression Inventory in Poland and Ukraine. Sci Rep. 2024;14(1):4403. doi: 10.1038/s41598-024-54995-w PMID: 38388806; PMCID: PMC10883996.

39. Hill C, de Beer LT, Bianchi R. Validation and measurement invariance of the Occupational Depression Inventory in South Africa. PLoS One. 2021;16(12):e0261271. doi: 10.1371/journal.pone.0261271 PMID: 34914772; PMCID: PMC8675679.

40. Jansson-Fröjmark M, Badinlou F, Lundgren T, Schonfeld IS, Bianchi R. Validation of the Occupational Depression Inventory in Sweden. BMC Public Health. 2023;23(1):1505. doi: 10.1186/s12889-023-16417-w PMID: 37553626; PMCID: PMC10411009.

41. Kalani S, Khanlari P, Bianchi R. A Persian validation of the Occupational Depression Inventory. European Journal of Psychological Assessment. 2024 Advance online publication. doi: 10.1027/1015-5759/a000830

42. Sowden JF, Schonfeld IS, Bianchi R. Are Australian teachers burned-out or depressed? A confirmatory factor analytic study involving the Occupational Depression Inventory. J Psychosom Res. 2022;157:110783. doi: 10.1016/j.jpsychores.2022.110783 Epub 2022 Mar 17. PMID: 35325775.

43. Larsen BO. Occupational Depression and Workplace Bullying: A Correlational Study. 2024. (Master's thesis, NTNU).

44. Otnes TM. Norwegian Version of the Occupational Depression Inventory: Validity, Reliability and Associations with Work Stressors and Work-Life Characteristics. 2024. (Bachelor's thesis, NTNU).

45. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13. doi: 10.1046/j.1525-1497.2001.016009606.x PMID: 11556941; PMCID: PMC1495268.

46. Health measurement scales: a practical guide to their development and use (5th edition). Aust N Z J Public Health. 2016;40(3):294–5. doi: 10.1111/1753-6405.12484 PMID: 27242256.

47. Streiner DL, Norman GR, Cairney J. Health measurement scales: a practical guide to their development and use. Oxford university press. 2024

48. Bianchi R, Schonfeld IS, Sowden JF, Cavalcante DC, Queirós C, Hebel VM, Volmer J, Fiorilli C, Angelini G, Golonka K, Manzano-García G. Measurement invariance of the Occupational Depression Inventory: a study of 12,589 participants across 14 countries. Work & Stress. 2024;38(4):420–36.

49. Gosling SD, Mason W. Internet research in psychology. Annu Rev Psychol. 2015;66:877–902. doi: 10.1146/annurev-psych-010814-015321 Epub 2014 Sep 22. PMID: 25251483.

50. Kachi Y, Inoue A, Eguchi H, Kawakami N, Shimazu A, Tsutsumi A. Occupational stress and the risk of turnover: a large prospective cohort study of employees in Japan. BMC Public Health. 2020;20(1):174. doi: 10.1186/s12889-020-8289-5 PMID: 32019535; PMCID: PMC7001282.

51. Barger SD, Cribbet MR, Muldoon MF. Participant-Reported Health Status Predicts Cardiovascular and All-Cause Mortality Independent of Established and Nontraditional Biomarkers: Evidence From a Representative US Sample. J Am Heart Assoc. 2016;5(9):e003741. doi: 10.1161/JAHA.116.003741 PMID: 27572824; PMCID: PMC5079034.

52. Cuijpers P, Vogelzangs N, Twisk J, Kleiboer A, Li J, Penninx BW. Comprehensive meta-analysis of excess mortality in depression in the general community versus patients with specific illnesses. Am J Psychiatry. 2014;171(4):453–62. doi: 10.1176/appi.ajp.2013.13030325 PMID: 24434956.

53. Simon GE, Rutter CM, Peterson D, Oliver M, Whiteside U, Operskalski B, Ludman EJ. Does response on the PHQ-9 Depression Questionnaire predict subsequent suicide attempt or suicide death? Psychiatr Serv. 2013;64(12):1195–202. doi: 10.1176/appi.ps.201200587 PMID: 24036589; PMCID: PMC4086215.

54. Kochetkov NV, Marinova TYu, Orlov VA, Raskhodchikova MN, Haymovskaya NA. Current Foreign Studies of Professional Burnout in Teachers. Journal of Modern Foreign Psychology. 2023;12(2):43–52. (In Russ.). doi: 10.17759/jmfp.2023120204

55. Meier ST, Kim S. Meta-regression analyses of relationships between burnout and depression with sampling and measurement methodological moderators. Journal of Occupational Health Psychology. 2022;27(2):195.

56. Pogosova NV, Isakova SS, Sokolova OY, Ausheva AK, Zhetisheva RA, Arutyunov AA. Occupational Burnout, Psychological Status and Quality of Life in Primary Care Physicians Working in Outpatient Settings. Kardiologiia. 2021;61(6):69–78. (In Russ.). doi: 10.18087/cardio.2021.6.n1538

57. Petrikov SS, Kholmogorova AB, Suroegina AYu, Mikita OYu, Roy AP, Rakhmanina AA. Professional Burnout, Symptoms of Emotional Distress and Distress in Medical Workers During the COVID-19 Epidemic. Counseling Psychology and Psychotherapy. 2020;28(2):8–45. (In Russ.). doi: 10.17759/cpp.2020280202

58. Vodopianova NE, Starchenkova ES, Nasledov AD. Standartizirovannyi oprosnik «Professionalnoe vygoranie» dlia spetsialistov sotsionomicheskikh professii. Vestnik Sankt-Peterburgskogo universiteta. Psikhologiia. Sotsiologiia. 2013;12(4):17–27. (In Russ.).

59. Veltishchev DIu, Kovalevskaia OB, Seravina OF. Sviaz professionalnogo vygoraniia s depressiei: obzor zarubezhnykh issledovanii. Psychiatry (Moscow) (Psikhiatriya). 2017;74(2):62–68. (In Russ.). doi: 10.30629/2618-6667-2017-74-62-68

60. Garanyan NG, Sharapova AV, Sorokova MG, Mikita OY, Boyko SL. Translation, Approbation, and Preliminary Psychometric Evaluation of the Russian Version of the Job Anxiety Scale by B. Muschalla and M. Linden. Counseling Psychology and Psychotherapy. 2020;28(4):9–34. doi 10.17759/cpp.2020280402 (In Russ.).


Review

For citations:


Cherniavskii A.A. Psychometric Properties of the Occupational Depression Inventory (ODI). Psychiatry (Moscow) (Psikhiatriya). 2026;24(2):131-151. (In Russ.) https://doi.org/10.30629/2618-6667-2026-24-2-131-151

Views: 303

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1683-8319 (Print)
ISSN 2618-6667 (Online)