Valid group comparisons can be made with the Patient Health Questionnaire (PHQ-9): A measurement invariance study across groups by demographic characteristics

Autoři: David Villarreal-Zegarra aff001;  Anthony Copez-Lonzoy aff001;  Antonio Bernabé-Ortiz aff002;  G. J. Melendez-Torres aff006;  Juan Carlos Bazo-Alvarez aff007
Působiště autorů: Instituto Peruano de Orientación Psicológica, Lima, Peru aff001;  CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru aff002;  Universidad San Ignacio de Loyola, Lima, Peru aff003;  Asociación Peruana de Profesionales de las Adicciones, Lima, Peru aff004;  Universidad Científica del Sur, Lima, Peru aff005;  Peninsula Technology Assessment Group, College of Medicine and Health, University of Exeter, Exeter, United Kingdom aff006;  Instituto de Investigación, Universidad Católica Los Ángeles de Chimbote, Chimbote, Peru aff007;  Methodology Research Group, Department of Primary Care and Population Health, University College London (UCL), London, United Kingdom aff008;  PSYCOPERU Peruvian Research Institute of Educational and Social Psychology, Lima, Peru aff009
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0221717



Analyze the measurement invariance and the factor structure of the Patient Health Questionnaire-9 (PHQ-9) in the Peruvian population.


Secondary data analysis performed using cross-sectional data from the Health Questionnaire of the Demographic and Health Survey in Peru. Variables of interest were the PHQ-9 and demographic characteristics (sex, age group, level of education, socioeconomic status, marital status, and area of residence). Factor structure was evaluated by standard confirmatory factor analysis (CFA), and measurement invariance by multi-group CFA, using standard goodness-of-fit indices criteria for interpreting results from both CFAs. Analysis of the internal consistency (α and ω) was also pursued.


Data from 30,449 study participants were analyzed, 56.7% were women, average age was 40.5 years (standard deviation (SD) = 16.3), 65.9% lived in urban areas, 74.6% were married, and had 9 years of education on average (SD = 4.6). From standard CFA, a one-dimensional model presented the best fit (CFI = 0.936; RMSEA = 0.089; SRMR = 0.039). From multi-group CFA, all progressively restricted models had ΔCFI<0.01 across almost all groups by demographic characteristics. PHQ-9 reliability was optimal (α = ω = 0.87).


The evidence presents support for the one-dimensional model and measurement invariance of the PHQ-9 measure, allowing for reliable comparisons between sex, age groups, education level, socioeconomic status, marital status, and residence area, and recommends its use within the Peruvian population.

Klíčová slova:

Medicine and health sciences – Mental health and psychiatry – Mood disorders – Depression – Health care – Primary care – Public and occupational health – Socioeconomic aspects of health – Social sciences – Sociology – Education – Educational attainment – People and places – Population groupings – Age groups – Earth sciences – Geography – Geographic areas – Urban areas – Research and analysis methods – Mathematical and statistical techniques – Statistical methods – Factor analysis – Research assessment – Research validity – Physical sciences – Mathematics – Statistics


1. World Health Organization. Depression and Other Common Mental Disorders. Global Health Estimates. Geneve: World Health Organization; 2017.

2. Marcus M, Yasamy MT, van Ommeren M, Chisholm D, Saxena S. Depression: A global public health concern. WHO Department of Mental Health and Substance Abuse. 2012;1:6–8.

3. Ministerio de Salud del Perú. Estudio de Carga de Enfermedad en el Perú - 2004. Perú: Ministerio de Salud del Perú; 2006.

4. World Health Organization. The global burden of disease: 2004 update. Geneva: WHO; 2008.

5. Boyd RC, Butler L, Benton TD. Understanding Adolescents’ Experiences with Depression and Behavioral Health Treatment. The Journal of Behavioral Health Services & Research. 2018;45(1):105–11. doi: 10.1007/s11414-017-9558-7 28488156

6. Williams JW, Pignone M, Ramirez G, Stellato CP. Identifying depression in primary care: a literature synthesis of case-finding instruments. General hospital psychiatry. 2002;24(4):225–37. 12100833

7. Jiao B, Rosen Z, Bellanger M, Belkin G, Muennig P. The cost-effectiveness of PHQ screening and collaborative care for depression in New York City. PloS one. 2017;12(8):e0184210. doi: 10.1371/journal.pone.0184210 28859154; PubMed Central PMCID: PMC5578679.

8. Gonzalez-Pier E, Gutierrez-Delgado C, Stevens G, Barraza-Llorens M, Porras-Condey R, Carvalho N, et al. Priority setting for health interventions in Mexico's System of Social Protection in Health. Lancet (London, England). 2006;368(9547):1608–18. Epub 2006/11/07. doi: 10.1016/s0140-6736(06)69567-6 17084761.

9. Byrne BM. Structural equation modeling with EQS: Basic concepts, applications, and programming, second edition: Taylor and Francis; 2013. 1–440 p.

10. Putnick DL, Bornstein MH. Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review. 2016;41:71–90. doi: 10.1016/j.dr.2016.06.004 27942093

11. Patel JS. Measurement Invariance of the Patient Health Questionnaire-9 (Phq-9) Depression Screener in U.S. Adults Across Sex, Race/Ethnicity, and Education Level: Nhanes 2005–2014. EEUU: Purdue University; 2017.

12. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. JAMA. 1999;282(18):1737–44. doi: 10.1001/jama.282.18.1737 10568646

13. Yu S, Yang H, Guo X, Zheng L, Sun Y. Metabolic syndrome and depressive symptoms among rural Northeast general population in China. BMC public health. 2017;17(1):43. Epub 2017/01/08. doi: 10.1186/s12889-016-3913-0 28061774; PubMed Central PMCID: PMC5219740.

14. Choi GS, Shin YS, Kim JH, Choi SY, Lee SK, Nam YH, et al. Prevalence and risk factors for depression in Korean adult patients with asthma: is there a difference between elderly and non-elderly patients? Journal of Korean medical science. 2014;29(12):1626–31. Epub 2014/12/04. doi: 10.3346/jkms.2014.29.12.1626 25469061; PubMed Central PMCID: PMC4248582.

15. Gregorich SE. Do Self-Report Instruments Allow Meaningful Comparisons Across Diverse Population Groups? Testing Measurement Invariance Using the Confirmatory Factor Analysis Framework. Medical care. 2006;44(11 Suppl 3):S78–S94. doi: 10.1097/01.mlr.0000245454.12228.8f PubMed PMID: PMC1808350. 17060839

16. Gonzalez-Blanch C, Medrano LA, Munoz-Navarro R, Ruiz-Rodriguez P, Moriana JA, Limonero JT, et al. Factor structure and measurement invariance across various demographic groups and over time for the PHQ-9 in primary care patients in Spain. PloS one. 2018;13(2):e0193356. Epub 2018/02/24. doi: 10.1371/journal.pone.0193356 29474410; PubMed Central PMCID: PMC5825085.

17. Keum BT, Miller MJ, Inkelas KK. Testing the factor structure and measurement invariance of the PHQ-9 across racially diverse U.S. college students. Psychol Assess. 2018. Epub 2018/03/23. doi: 10.1037/pas0000550 29565614.

18. Baas KD, Cramer AO, Koeter MW, van de Lisdonk EH, van Weert HC, Schene AH. Measurement invariance with respect to ethnicity of the Patient Health Questionnaire-9 (PHQ-9). J Affect Disord. 2011;129(1–3):229–35. Epub 2010/10/05. doi: 10.1016/j.jad.2010.08.026 20888647.

19. Galenkamp H, Stronks K, Snijder MB, Derks EM. Measurement invariance testing of the PHQ-9 in a multi-ethnic population in Europe: the HELIUS study. BMC psychiatry. 2017;17(1):349. Epub 2017/10/27. doi: 10.1186/s12888-017-1506-9 29065874; PubMed Central PMCID: PMC5655879.

20. Kocalevent RD, Hinz A, Brahler E. Standardization of the depression screener patient health questionnaire (PHQ-9) in the general population. Gen Hosp Psychiatry. 2013;35(5):551–5. Epub 2013/05/15. doi: 10.1016/j.genhosppsych.2013.04.006 23664569.

21. Yu X, Tam WW, Wong PT, Lam TH, Stewart SM. The Patient Health Questionnaire-9 for measuring depressive symptoms among the general population in Hong Kong. Comprehensive psychiatry. 2012;53(1):95–102. Epub 2011/01/05. doi: 10.1016/j.comppsych.2010.11.002 21193179.

22. Vares EA, Salum GA, Spanemberg L, Caldieraro MA, Fleck MP. Depression Dimensions: Integrating Clinical Signs and Symptoms from the Perspectives of Clinicians and Patients. PloS one. 2015;10(8):e0136037. doi: 10.1371/journal.pone.0136037 26313556; PubMed Central PMCID: PMC4552383.

23. Granillo MT. Structure and function of the Patient Health Questionnaire-9 among Latina and non-Latina White female college students. Journal of the society for social work and Research. 2012;3(2):80–93.

24. Guo B, Kaylor-Hughes C, Garland A, Nixon N, Sweeney T, Simpson S, et al. Factor structure and longitudinal measurement invariance of PHQ-9 for specialist mental health care patients with persistent major depressive disorder: Exploratory Structural Equation Modelling. J Affect Disord. 2017;219:1–8. Epub 2017/05/16. doi: 10.1016/j.jad.2017.05.020 28501679.

25. Chilcot J, Rayner L, Lee W, Price A, Goodwin L, Monroe B, et al. The factor structure of the PHQ-9 in palliative care. J Psychosom Res. 2013;75(1):60–4. Epub 2013/06/12. doi: 10.1016/j.jpsychores.2012.12.012 23751240.

26. Elhai JD, Contractor AA, Tamburrino M, Fine TH, Prescott MR, Shirley E, et al. The factor structure of major depression symptoms: a test of four competing models using the Patient Health Questionnaire-9. Psychiatry Res. 2012;199(3):169–73. Epub 2012/06/16. doi: 10.1016/j.psychres.2012.05.018 22698261.

27. Petersen JJ, Paulitsch MA, Hartig J, Mergenthal K, Gerlach FM, Gensichen J. Factor structure and measurement invariance of the Patient Health Questionnaire-9 for female and male primary care patients with major depression in Germany. J Affect Disord. 2015;170:138–42. Epub 2014/09/23. doi: 10.1016/j.jad.2014.08.053 25240840.

28. van Dijk SEM, Adriaanse MC, van der Zwaan L, Bosmans JE, van Marwijk HWJ, van Tulder MW, et al. Measurement properties of depression questionnaires in patients with diabetes: a systematic review. Qual Life Res. 2018;27(6):1415–30. doi: 10.1007/s11136-018-1782-y 29396653; PubMed Central PMCID: PMC5951879.

29. Instituto Nacional de Estadistica e Informatica. Microdatos: Base de datos de la Encuesta Demografica y de Salud Familiar—ENDES Perú: Instituto Nacional de Estadistica e Informatica; 2017. Available from:

30. Instituto Nacional de Estadística e Informática. Perú: encuesta demográfica y de salud familiar ENDES 2014. Perú: Instituto Nacional de Estadística e Informática; 2015.

31. Baader MT, Molina FJL, Venezian BS, Rojas CC, Farías SR, Fierro-Freixenet C, et al. Validación y utilidad de la encuesta PHQ-9 (Patient Health Questionnaire) en el diagnóstico de depresión en pacientes usuarios de atención primaria en Chile. Rev Chil Neuropsiquiatr. 2012;50:10–22.

32. Manea L, Gilbody S, McMillan D. A diagnostic meta-analysis of the Patient Health Questionnaire-9 (PHQ-9) algorithm scoring method as a screen for depression. General hospital psychiatry. 2015;37(1):67–75. Epub 2014/12/03. doi: 10.1016/j.genhosppsych.2014.09.009 25439733.

33. Papalia DE, Villamizar S, Alberto G. Desarrollo humano: con aportaciones para Iberoamérica1997.

34. Brown TA. Confirmatory factor analysis for applied research. Second ed. New York: The Guilford Press; 2015.

35. Hair JF, Anderson RE, Tatham RL, Black WC. Análisis multivariante: Prentice Hall Madrid; 1999.

36. Hu L-t, Bentler PM. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods. 1998;3(4):424.

37. Brown TA. Confirmatory factor analysis for applied research: Guilford Publications; 2014.

38. Widaman KF, Reise SP. Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. The science of prevention: Methodological advances from alcohol and substance abuse research. 1997:281–324.

39. McDonald RP. Test theory: A unified treatment. New York: Taylor & Francis Group; 1999.

40. Ten Berge JM, Sočan G. The greatest lower bound to the reliability of a test and the hypothesis of unidimensionality. Psychometrika. 2004;69(4):613–25.

41. Kelley K, Pornprasertmanit S. Confidence intervals for population reliability coefficients: Evaluation of methods, recommendations, and software for composite measures. Psychol Methods. 2016;21(1):69–92. doi: 10.1037/a0040086 26962759.

42. Rosseel Y. lavaan: An R Package for Structural Equation Modeling. Journal of statistical software. 2012;48(2):36. Epub 2012-05-24. doi: 10.18637/jss.v048.i02

43. Oberski D. lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models. Journal of statistical software. 2014;57(1):27. Epub 2014-03-13. doi: 10.18637/jss.v057.i01

44. Jorgensen TD, Pornprasertmanit S, Schoemann AM, Rosseel Y. semTools: Useful tools for structural equation modeling: R package version 0.5–1; 2018. Available from: = semTools.

45. Epskamp S. semPlot: Unified visualizations of structural equation models. Structural Equation Modeling. 2015;22(3):474–83. doi: 10.1080/10705511.2014.937847

46. Escovar EL, Craske M, Roy-Byrne P, Stein MB, Sullivan G, Sherbourne CD, et al. Cultural influences on mental health symptoms in a primary care sample of Latinx patients. Journal of anxiety disorders. 2018;55:39–47. Epub 2018/03/27. doi: 10.1016/j.janxdis.2018.03.005 29576380; PubMed Central PMCID: PMC5918638.

47. Frazier L, Yu E, Sanner J, Liu F, Udtha M, Cron S, et al. Gender Differences in Self-Reported Symptoms of Depression among Patients with Acute Coronary Syndrome. Nurs Res Pract. 2012;2012:109251. doi: 10.1155/2012/109251 22567222; PubMed Central PMCID: PMC3337485.

48. Altemus M, Sarvaiya N, Neill Epperson C. Sex differences in anxiety and depression clinical perspectives. Frontiers in neuroendocrinology. 2014;35(3):320–30. Epub 2014/06/03. doi: 10.1016/j.yfrne.2014.05.004 24887405; PubMed Central PMCID: PMC4890708.

49. Doi S, Ito M, Takebayashi Y, Muramatsu K, Horikoshi M. Factorial validity and invariance of the Patient Health Questionnaire (PHQ)-9 among clinical and non-clinical populations. PloS one. 2018;13(7):e0199235. Epub 2018/07/20. doi: 10.1371/journal.pone.0199235 30024876; PubMed Central PMCID: PMC6053131.

50. Cockerham WC, Hamby BW, Oates GR. The Social Determinants of Chronic Disease. Am J Prev Med. 2017;52(1s1):S5–s12. Epub 2016/12/19. doi: 10.1016/j.amepre.2016.09.010 27989293; PubMed Central PMCID: PMC5328595.

51. Instituto de Evaluación de Tecnologías en Salud e Investigación. Guía de Práctica Clínica de Rehabilitación Cardiaca. Perú: EsSalud; 2018.

52. Ministerio de Salud. Guía clínica depresión en personas de 15 años y más. Chile: Ministerio de Salud; 2013.

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