Network and Exploratory Factorial Analysis of the Depression Clinical Evaluation Test

Overview

Journal Int J Environ Res Public Health

Publisher MDPI

Specialties Environmental Health
Public Health

Date 2022 Sep 9

PMID 36078505

Authors

Maria Guillot-Valdes

Alejandro Guillen-Riquelme

Juan Carlos Sierra

Gualberto Buela-Casal

Affiliations

Soon will be listed here.

Abstract

Depression is a highly prevalent disorder with a wide range of symptomatology. Existing instruments for its assessment have only a few items for each factor. The Depression Clinical Evaluation Test (DCET) has been created to cover all depression symptoms at different times (month, year, and always) with several items for each facet. The content validity of this instrument has been judged by experts and, in this paper, we analyse its factorial structure and make a network analysis of it. The test (196 items) was administered to 602 adults without psychological disorders ( = 24.7, SD = 8.38, 72% women) both online and on paper. A network was estimated for each time point, using the absolute minimum selection and shrinkage operator. From the factor analysis, 12 factors were established for month, 11 for year, and 10 for always, leaving 94 items. The network analysis showed that the facets of depressive mood, anhedonia, and thoughts of Death, are central to all the estimated networks. The DCET is proposed as a valid and reliable multifactorial instrument to detect the variability of depressive symptoms in adults, guaranteeing its diagnostic usefulness.

References

ZUNG W . A SELF-RATING DEPRESSION SCALE. Arch Gen Psychiatry. 1965; 12:63-70. DOI: 10.1001/archpsyc.1965.01720310065008. View

Nunes Baptista M, Cunha F, Hauck N . The latent structure of depression symptoms and suicidal thoughts in Brazilian youths. J Affect Disord. 2019; 254:90-97. DOI: 10.1016/j.jad.2019.05.024. View

Beck A, Epstein N, Brown G, Steer R . An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988; 56(6):893-7. DOI: 10.1037//0022-006x.56.6.893. View

Orsolini L, Latini R, Pompili M, Serafini G, Volpe U, Vellante F . Understanding the Complex of Suicide in Depression: from Research to Clinics. Psychiatry Investig. 2020; 17(3):207-221. PMC: 7113180. DOI: 10.30773/pi.2019.0171. View

Brailovskaia J, Forkmann T, Glaesmer H, Paashaus L, Rath D, Schonfelder A . Positive mental health moderates the association between suicide ideation and suicide attempts. J Affect Disord. 2018; 245:246-249. DOI: 10.1016/j.jad.2018.11.005. View

Ruscio J, Brown T, Ruscio A . A taxometric investigation of DSM-IV major depression in a large outpatient sample: interpretable structural results depend on the mode of assessment. Assessment. 2009; 16(2):127-44. PMC: 3536496. DOI: 10.1177/1073191108330065. View

Fried E . The 52 symptoms of major depression: Lack of content overlap among seven common depression scales. J Affect Disord. 2016; 208:191-197. DOI: 10.1016/j.jad.2016.10.019. View

Wang Y, Hu Z, Feng Y, Wilson A, Chen R . Changes in network centrality of psychopathology symptoms between the COVID-19 outbreak and after peak. Mol Psychiatry. 2020; 25(12):3140-3149. PMC: 7488637. DOI: 10.1038/s41380-020-00881-6. View

Fried E, Epskamp S, Nesse R, Tuerlinckx F, Borsboom D . What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. J Affect Disord. 2015; 189:314-20. DOI: 10.1016/j.jad.2015.09.005. View

10.

Belvederi Murri M, Amore M, Respino M, Alexopoulos G . The symptom network structure of depressive symptoms in late-life: Results from a European population study. Mol Psychiatry. 2018; 25(7):1447-1456. DOI: 10.1038/s41380-018-0232-0. View

11.

Bernaras E, Jaureguizar J, Garaigordobil M . Child and Adolescent Depression: A Review of Theories, Evaluation Instruments, Prevention Programs, and Treatments. Front Psychol. 2019; 10:543. PMC: 6435492. DOI: 10.3389/fpsyg.2019.00543. View

12.

Siegmann P, Willutzki U, Fritsch N, Nyhuis P, Wolter M, Teismann T . Positive mental health as a moderator of the association between risk factors and suicide ideation/behavior in psychiatric inpatients. Psychiatry Res. 2019; 273:678-684. DOI: 10.1016/j.psychres.2019.01.091. View

13.

Cramer A, van Borkulo C, Giltay E, van der Maas H, Kendler K, Scheffer M . Major Depression as a Complex Dynamic System. PLoS One. 2016; 11(12):e0167490. PMC: 5145163. DOI: 10.1371/journal.pone.0167490. View

14.

Guillot-Valdes M, Guillen-Riquelme A, Buela-Casal G . Reliability and validity of the Basic Depression Questionnaire. Int J Clin Health Psychol. 2021; 19(3):243-250. PMC: 7969818. DOI: 10.1016/j.ijchp.2019.07.002. View

15.

Fonseca-Pedrero E . Network analysis: A new way of understanding psychopathology?. Rev Psiquiatr Salud Ment. 2017; 10(4):206-215. DOI: 10.1016/j.rpsm.2017.06.004. View

16.

Charan J, Biswas T . How to calculate sample size for different study designs in medical research?. Indian J Psychol Med. 2013; 35(2):121-6. PMC: 3775042. DOI: 10.4103/0253-7176.116232. View

17.

Gomez-Benito J, Sireci S, Padilla J, Hidalgo M, Benitez I . Differential Item Functioning: Beyond validity evidence based on internal structure. Psicothema. 2018; 30(1):104-109. DOI: 10.7334/psicothema2017.183. View

18.

Guillot-Valdes M, Guillen-Riquelme A, Buela-Casal G . Content Validity through Expert Judgment for the Depression Clinical Evaluation Test. Int J Clin Health Psychol. 2022; 22(2):100292. PMC: 9055062. DOI: 10.1016/j.ijchp.2022.100292. View

19.

Have M, Lamers F, Wardenaar K, Beekman A, de Jonge P, van Dorsselaer S . The identification of symptom-based subtypes of depression: A nationally representative cohort study. J Affect Disord. 2015; 190:395-406. DOI: 10.1016/j.jad.2015.10.040. View

20.

Epskamp S, Borsboom D, Fried E . Estimating psychological networks and their accuracy: A tutorial paper. Behav Res Methods. 2017; 50(1):195-212. PMC: 5809547. DOI: 10.3758/s13428-017-0862-1. View