Accuracy of Self-Reported Items for the Screening of Depression in the General Population
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Indicators of Depression
2.3. Sociodemographic Factors and Use of Health Services
2.4. Data Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- World Health Organization. Depression and Other Common Mental Disorders: Global Health Estimates; CC BY-NC-SA 3.0 IGO; World Health Organization: Geneva, Switzerland, 2017; pp. 1–24. [Google Scholar]
- Calvó-Perxas, L.; Garre-Olmo, J.; Vilalta-Franch, J. Prevalence and sociodemographic correlates of depressive and bipolar disorders in Catalonia (Spain) using DSM-5 criteria. J. Affect. Disord. 2015, 184, 97–103. [Google Scholar] [CrossRef] [PubMed]
- Simon, G.E.; Goldberg, D.P.; Von Korff, M.; Ustün, T.B. Understanding cross-national differences in depression prevalence. Psychol. Med. 2002, 32, 585–594. [Google Scholar] [CrossRef] [PubMed]
- Haro, J.M.; Arbabzadeh-Bouchez, S.; Brugha, T.S.; De Girolamo, G.; Guyer, M.E.; Jin, R.; Lepine, J.P.; Mazzi, F.; Reneses, B.; Vilagut, G.; et al. Concordance of the Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO World Mental Health Surveys. Int. J. Methods Psychiatr. Res. 2006, 15, 167–180. [Google Scholar] [CrossRef] [PubMed]
- Gilbody, S.; House, A.O.; Sheldon, T.A. Screening and case finding instruments for depression. Cochrane Database Syst. Rev. 2005, 2005, CD002792. [Google Scholar] [CrossRef] [PubMed]
- Gelaye, B.; Tadesse, M.G.; Williams, M.A.; Fann, J.R.; Vander Stoep, A.; Andrew Zhou, X.H. Assessing validity of a depression screening instrument in the absence of a gold standard. Ann. Epidemiol. 2014, 24, 527–531. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Levis, B.; Benedetti, A.; Thombs, B.D. Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: Individual participant data meta-analysis. BMJ 2019, 365, l1476. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Beck, A.T.; Steer, R.A.; Ball, R.; Ranieri, W.F. Comparison of Beck depression inventories -IA and -II in psychiatric outpatients. J. Pers. Assess. 1996. [Google Scholar] [CrossRef]
- Vilagut, G.; Forero, C.G.; Barbaglia, G.; Alonso, J. Screening for Depression in the General Population with the Center for Epidemiologic Studies Depression (CES-D): A Systematic Review with Meta-Analysis. PLoS ONE 2016, 11, e0155431. [Google Scholar] [CrossRef] [PubMed]
- Bagby, R.M.; Ryder, A.G.; Schuller, D.R.; Marshall, M.B. The Hamilton Depression Rating Scale: Has the gold standard become a lead weight? Am. J. Psychiatry 2004, 161, 2163–2177. [Google Scholar] [CrossRef]
- Kroenke, K.; Spitzer, R.L.; Williams, J.B. The PHQ-9: Validity of a brief depression severity measure. J. Gen. Intern. Med. 2001, 16, 606–613. [Google Scholar] [CrossRef] [PubMed]
- Tomitaka, S.; Kawasaki, Y.; Ide, K.; Akutagawa, M.; Yamada, H.; Ono, Y.; Furukawa, T.A. Distributional patterns of item responses and total scores on the PHQ-9 in the general population: Data from the National Health and Nutrition Examination Survey. BMC Psychiatry 2018, 18, 108. [Google Scholar] [CrossRef] [Green Version]
- Moriarty, A.S.; Gilbody, S.; McMillan, D.; Manea, L. Screening and case finding for major depressive disorder using the Patient Health Questionnaire (PHQ-9): A meta-analysis. Gen. Hosp. Psychiatry 2015, 37, 567–576. [Google Scholar] [CrossRef] [PubMed]
- Eurostat. European Health Interview Survey Second Wave (EHIS); Eurostat: Luxembourg, 2015. [Google Scholar]
- Elliott, J.; Shepherd, P. Cohort profile: 1970 British Birth Cohort (BCS70). Int. J. Epidemiol. 2006, 35, 836–843. [Google Scholar] [CrossRef] [Green Version]
- Power, C.; Elliott, J. Cohort profile: 1958 British birth cohort (National Child Development Study). Int. J. Epidemiol. 2006, 35, 34–41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Maske, U.E.; Buttery, A.K.; Beesdo-Baum, K.; Riedel-Heller, S.; Hapke, U.; Busch, M.A. Prevalence and correlates of DSM-IV-TR major depressive disorder, self-reported diagnosed depression and current depressive symptoms among adults in Germany. J. Affect. Disord. 2016, 190, 167–177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Maske, U.E.; Hapke, U.; Riedel-Heller, S.G.; Busch, M.A.; Kessler, R.C. Respondents’ report of a clinician-diagnosed depression in health surveys: Comparison with DSM-IV mental disorders in the general adult population in Germany. BMC Psychiatry 2017, 17, 39. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sanchez-Villegas, A.; Schlatter, J.; Ortuno, F.; Lahortiga, F.; Pla, J.; Benito, S.; Martinez-Gonzalez, M.A. Validity of a self-reported diagnosis of depression among participants in a cohort study using the Structured Clinical Interview for DSM-IV (SCID-I). BMC Psychiatry 2008, 8, 43. [Google Scholar] [CrossRef] [Green Version]
- Gjerdincjen, D.; Crow, S.; McGovern, P.; Miner, M.; Center, B. Postpartum depression screening at well-child visits: Validity of a 2-question screen and the PHQ-9. Ann. Fam. Med. 2009, 7, 63–70. [Google Scholar] [CrossRef]
- Maske, U.E.; Busch, M.A.; Jacobi, F.; Beesdo-Baum, K.; Seiffert, I.; Wittchen, H.-U.; Riedel-Heller, S.; Hapke, U. Current major depressive syndrome measured with the Patient Health Questionnaire-9 (PHQ-9) and the Composite International Diagnostic Interview (CIDI): Results from a cross-sectional population-based study of adults in Germany. BMC Psychiatry 2015, 15, 77. [Google Scholar] [CrossRef] [Green Version]
- Dijkstra-Kersten, S.M.A.; Biesheuvel-Leliefeld, K.E.M.; Van der Wouden, J.C.; Penninx, B.W.J.H.; Van Marwijk, H.W.J. Associations of financial strain and income with depressive and anxiety disorders. J. Epidemiol. Community Health 2015, 69, 660–665. [Google Scholar] [CrossRef]
- Arias-de la Torre, J.; Vilagut, G.; Martín, V.; Molina, A.J.; Alonso, J. Prevalence of major depressive disorder and association with personal and socio-economic factors. Results for Spain of the European Health Interview Survey 2014–2015. J. Affect. Disord. 2018, 239, 203–207. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Diez-Quevedo, C.; Rangil, T.; Sanchez-Planell, L.; Kroenke, K.; Spitzer, R.L. Validation and utility of the patient health questionnaire in diagnosing mental disorders in 1003 general hospital Spanish inpatients. Psychosom. Med. 2001, 63, 679–686. [Google Scholar] [CrossRef] [PubMed]
- Wu, Y.; Levis, B.; Riehm, K.E.; Saadat, N.; Levis, A.W.; Azar, M.; Rice, D.B.; Boruff, J.; Cuijpers, P.; Gilbody, S.; et al. Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: A systematic review and individual participant data meta-analysis. Psychol. Med. 2019, 50, 1368–1380. [Google Scholar] [CrossRef] [PubMed]
- 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. Gen. Hosp. Psychiatry 2015, 37, 67–75. [Google Scholar] [CrossRef]
- Szklo, M.; Nieto, J. Epidemiology, Beyond the Basics, 3rd ed.; Jones & Bartlett Publishers: Sudbury, MA, USA, 2014. [Google Scholar]
- StataCorp. Stata Statistical Software: Release 14; StataCorp: College Station, TX, USA, 2015. [Google Scholar] [CrossRef]
- Manea, L.; Gilbody, S.; McMillan, D. Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): A meta-analysis. Can. Med. Assoc. J. 2012, 184, E191–E196. [Google Scholar] [CrossRef] [Green Version]
- Gilbody, S.; Sheldon, T.; House, A. Screening and case-finding instruments for depression: A meta-analysis. Can. Med. Assoc. J. 2008, 178, 997–1003. [Google Scholar] [CrossRef] [Green Version]
- Ayuso-Mateos, J.L.; Vázques-Barquero, J.L.; Dowrick, C.; Lehtinen, V.; Dalgard, O.S.; Casey, P.; Wilkinson, C.; Lasa, L.; Page, H.; Dunn, G.; et al. Depressive disorders in Europe: Prevalence figures from the ODIN study. Br. J. Psychiatry 2001, 179, 308–316. [Google Scholar] [CrossRef]
- Beck, A.T.; Steer, R.A.; Carbin, M.G. Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clin. Psychol. Rev. 1988, 8, 77–100. [Google Scholar] [CrossRef]
- Reitsma, H.; Rutjes, A.; Whiting, P.; Vlassov, V.; Leeflang, M.; Deeks, J. Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy. Available online: https://methods.cochrane.org/sdt/handbook-dta-reviews (accessed on 29 October 2020).
- Knudsen, A.K.; Hotopf, M.; Skogen, J.C.; Øverland, S.; Mykletun, A. The health status of nonparticipants in a population-based health study. Am. J. Epidemiol. 2010, 172, 1306–1314. [Google Scholar] [CrossRef] [Green Version]
- Arias-de la Torre, J.; Valderas, J.M.; Benavides, F.G.; Alonso, J. Cardboard floor: About the barriers for social progression and their impact on the representativeness of epidemiological studies. J. Epidemiol. Community Health 2020. [Google Scholar] [CrossRef]
Total Sample (n = 22,065) | PHQ-8+ (n = 1461) | SRD+ (n = 1988) | |
---|---|---|---|
% (95% CI) | % (95% CI) | % (95% CI) | |
Gender | |||
Men | 49.2 (48.5–50.0) | 3.9 (3.5–4.4) | 4.7 (4.3–5.3) |
Women | 50.8 (50.0–51.5) | 7.7 (7.1–8.4) | 10.5 (9.8–11.2) |
Marital status | |||
Single | 26.1 (25.3–26.9) | 3.6 (3.0–4.3) | 4.6 (4.0–5.4) |
Married or cohabiting | 62.8 (62.0–63.6) | 5.6 (5.1–6.1) | 7.3 (6.8–7.9) |
Widowed | 6.9 (6.6–7.2) | 15.1 (13.5–16.9) | 19.2 (17.4–21.1) |
Separated or divorced | 4.2 (3.9–4.5) | 8.5 (6.9–10.6) | 12.7 (10.8–15.0) |
Level of education | |||
University | 18.9 (18.1–19.8) | 2.4 (1.9–3.0) | 3.5 (3.0–4.2) |
Secondary | 51.1 (50.1–52) | 4.9 (4.5–5.5) | 6.2 (5.6–6.8) |
Primary or Illiterate | 30.0 (29.0–31.0) | 9.6 (8.7–10.5) | 12.8 (12.0–13.8) |
Country of birth | |||
Not Spain | 12.9 (12.1–13.8) | 4.5 (3.4–5.8) | 5.5 (4.3–7.0) |
Spain | 87.1 (86.3–87.9) | 6.1 (5.7–6.5) | 8.0 (7.5–8.5) |
Working status | |||
Employed | 45.3 (44.4–46.3) | 2.7 (2.3–3.2) | 3.8 (3.3–4.3) |
Unemployed | 15.1 (14.4–15.8) | 8.6 (7.4–9.9) | 9.1 (7.9–10.4) |
Retired/pre-retired | 20.1 (19.4–20.7) | 9.4 (8.5–10.3) | 13.1 (12.1–14.2) |
Homemaker | 8.6 (8.1–9.0) | 9.8 (8.3–11.5) | 13.3 (11.6–15.2) |
Other | 10.9 (10.3–11.5) | 5.6 (4.5–6.9) | 7.7 (6.4–9.1) |
Social class | |||
I | 11.4 (10.7–12.1) | 2.2 (1.7–3.0) | 3.0 (2.4–3.8) |
II | 8.3 (7.8–8.8) | 3.9 (3.0–5.0) | 5.4 (4.4–6.7) |
III | 19.0 (18.4–19.8) | 4.3 (3.7–51) | 6.1 (5.3–7.0) |
IV | 14.6 (14.0–15.2) | 5.2 (4.4–6.1) | 8.1 (7.1–9.2) |
V | 32.5 (31.6–33.5) | 7.2 (6.5–7.9) | 9.0 (8.2–9.8) |
VI | 14.2 (13.4–15.0) | 9.7 (8.4–11.1) | 11.4 (10.1–12.9) |
Age | |||
15–34 years old | 26.8 (26.0–27.3) | 3.0 (2.4–3.7) | 2.6 (2.1–3.3) |
35–49 years old | 29.9 (29.5–30.7) | 4.5 (3.9–5.1) | 5.5 (4.9–6.3) |
50–64 years old | 22.7 (22.0–23.4) | 7.6 (6.8–8.6) | 11.1 (10.1–12.1) |
≥65 years old | 20.6 (20.0–21.3) | 9.8 (8.9–10.8) | 13.5 (12.5–14.6) |
Use of health services | |||
No | 65.2 (64.4–66.0) | 3.3 (3.0–3.7) | |
Yes | 34.8 (34.0–35.7) | 10.6 (9.8–11.6) | 13.0 (12.1–13.9) |
Se % (95% CI) | Sp % (95% CI) | AUC (95% CI) | GA % (95% CI) | PPV % (95% CI) | NPV % (95% CI) | |
---|---|---|---|---|---|---|
SRD | 52.9 | 95.1 | 0.74 | 92.7 | 40.4 | 97.0 |
(52.8–53.0) | (95.1–95.2) | (0.72–0.76) | (92.7–92.7) | (40.4–40.5) | (97.0–97.0) |
Model 1 (n = 1461) | Model 2 (n = 20,604) | |||||||
---|---|---|---|---|---|---|---|---|
OR (95% CI) | p | aOR (95% CI) | p | OR (95% CI) | p Value | aOR (95% CI) | p | |
SRD | ||||||||
Gender | 0.057 | 0.265 | <0.001 | <0.001 | ||||
Men | 1.00 | 1.00 | 1.00 | 1.00 | ||||
Women | 1.31 (0.99–1.73) | 1.17 (0.89–1.55) | 2.39 (2.05–2.80) | 2.08 (1.76–2.47) | ||||
Marital status | 0.002 | 0.011 | <0.001 | 0.038 | ||||
Single | 1.00 | 1.00 | 1.00 | 1.00 | ||||
Married or cohabiting | 1.27 (0.86–1.87) | 1.21 (0.81–1.83) | 1.54 (1.24–1.91) | 0.78 (0.60–1.01) | ||||
Widowed | 1.48 (0.96–2.29) | 1.25 (0.75–2.08) | 4.57 (3.57–5.87) | 1.04 (0.76–1.40) | ||||
Separated or divorced | 2.59 (1.42–4.72) | 2.41 (1.28–4.52) | 2.54 (1.88–3.44) | 1.07 (0.76–1.50) | ||||
Level of education | 0.238 | 0.163 | <0.001 | 0.029 | ||||
University | 1.00 | 1.00 | 1.00 | 1.00 | ||||
Secondary | 1.39 (0.84–2.31) | 1.00 (0.56–1.78) | 1.50 (1.18–1.90) | 1.25 (0.96–1.63) | ||||
Primary or Illiterate | 1.44 (0.88–2.36) | 0.77 (0.42–1.43) | 3.60 (2.86–4.53) | 1.53 (1.14–2.06) | ||||
Country of birth | 0.012 | 0.022 | 0.132 | 0.811 | ||||
Not Spain | 1.00 | 1.00 | 1.00 | 1.00 | ||||
Spain | 1.97 (1.16–3.34) | 1.89 (1.10–3.24) | 1.28 (0.93–1.76) | 0.96 (0.69–1.34) | ||||
Working status | <0.001 | 0.001 | <0.001 | 0.013 | ||||
Employed | 1.00 | 1.00 | 1.00 | 1.00 | ||||
Unemployed | 1.51 (1.01–2.26) | 1.43 (0.95–2.16) | 1.93 (1.52–2.45) | 1.73 (1.34–2.24) | ||||
Retired/pre-retired | 1.72 (1.22–2.42) | 1.64 (0.94–2.88) | 3.46 (2.85–4.19) | 1.33 (1.00–1.79) | ||||
Homemaker | 2.03 (1.30–3.18) | 1.57 (0.92–2.69) | 3.27 (2.55–4.19) | 1.25 (0.72–1.71) | ||||
Other | 2.90 (1.67–5.05) | 2.51 (1.41–4.47) | 1.53 (1.15–2.04) | 2.83 (1.86–4.32) | ||||
Social class | 0.019 | 0.007 | <0.001 | <0.001 | ||||
I | 1.00 | 1.00 | 1.00 | 1.00 | ||||
II | 1.15 (0.52–2.52) | 1.01 (0.46–2.25) | 1.80 (1.23–2.63) | 1.65 (1.13–2.42) | ||||
III | 1.15 (0.57–2.30) | 1.28 (0.61–2.67) | 2.07 (1.50–2.85) | 1.63 (1.16–2.29) | ||||
IV | 1.85 (0.92–3.71) | 1.90 (0.90–4.02) | 2.58 (1.88–3.54) | 1.88 (1.33–2.65) | ||||
V | 2.01 (1.07–3.80) | 2.15 (1.08–4.29) | 2.42 (1.80–3.27) | 1.69 (1.22–2.36) | ||||
VI | 1.53 (0.79–2.95) | 1.68 (0.81–3.45) | 3.45 (2.50–4.77) | 2.29 (1.60–3.27) | ||||
Age | 0.017 | 0.607 | <0.001 | <0.001 | ||||
15–34 years old | 1.00 | 1.00 | 1.00 | 1.00 | ||||
35–49 years old | 1.17 (0.69–2.00) | 1.00 (0.53–1.78) | 2.60 (1.83–3.71) | 4.39 (2.65–7.24) | ||||
50–64 years old | 2.08 (1.25–3.48) | 1.59 (0.88–2.88) | 5.23 (3.72–7.35) | 7.47 (4.69–11.88) | ||||
≥65 years old | 1.55 (0.93–2.48) | 1.18 (0.55–2.51) | 7.05 (5.04–9.86) | 7.45 (4.39–12.66) | ||||
Use of health services | 0.080 | 0.307 | <0.001 | <0.001 | ||||
No | 1.00 | 1.00 | 1.00 | 1.00 | ||||
Yes | 1.27 (0.97–1.67) | 1.15 (0.88–1.52) | 2.55 (2.21–2.94) | 1.86 (1.60–2.17) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Arias-de la Torre, J.; Vilagut, G.; Serrano-Blanco, A.; Martín, V.; Molina, A.J.; Valderas, J.M.; Alonso, J. Accuracy of Self-Reported Items for the Screening of Depression in the General Population. Int. J. Environ. Res. Public Health 2020, 17, 7955. https://doi.org/10.3390/ijerph17217955
Arias-de la Torre J, Vilagut G, Serrano-Blanco A, Martín V, Molina AJ, Valderas JM, Alonso J. Accuracy of Self-Reported Items for the Screening of Depression in the General Population. International Journal of Environmental Research and Public Health. 2020; 17(21):7955. https://doi.org/10.3390/ijerph17217955
Chicago/Turabian StyleArias-de la Torre, Jorge, Gemma Vilagut, Antoni Serrano-Blanco, Vicente Martín, Antonio José Molina, Jose M Valderas, and Jordi Alonso. 2020. "Accuracy of Self-Reported Items for the Screening of Depression in the General Population" International Journal of Environmental Research and Public Health 17, no. 21: 7955. https://doi.org/10.3390/ijerph17217955