tetano
Editor, Senior Moderator
J Med Virol
. 2022 Oct 18.
doi: 10.1002/jmv.28236. Online ahead of print.
Factor Structure of the 10-item CES-D Scale Among Patients with Persistent COVID-19
Robinson Ramírez-Vélez[SUP] 1 2 [/SUP], Laiene Olabarrieta-Landa[SUP] 3 [/SUP], Diego Rivera[SUP] 3 [/SUP], Mikel Izquierdo[SUP] 1 3 [/SUP]
Affiliations
Abstract
Background: The presence of persistent coronavirus disease 2019 (COVID-19) might be associated with significant levels of psychological distress that would meet the threshold for clinical relevance. The Center for Epidemiologic Studies Depression Scale (CES-D) version 10 has been widely used in assessing psychological distress among general and clinical populations from different cultural backgrounds. To our knowledge, however, researchers have not yet validated these findings among patients with persistent COVID-19.
Method: A cross-sectional validation study was conducted with 100 patients from the EXER-COVID project (69.8% women; mean (±standard deviation) ages 47.4±9.5 years). Confirmatory factor analyses (CFAs) were performed on the 10-item CES-D to test four model fits: (a) unidimensional model, (b) two-factor correlated model, (c) three-factor correlated model, and (d) second-order factor model. The Diagonal Weighted Least Squares (DWLS) estimator was used, as it is commonly applied to latent variable models with ordered categorical variables.
Results: The reliability indices of the CES-D 10 items in patients with persistent COVID-19 were as follows: depressive affect factor ( αOrd=
0.82; ωu−cat =0.78), somatic retardation factor ( αOrd= 0.78; ωu−cat =0.56), and positive affect factor ( αOrd= 0.56; ωu−cat =0.55). The second-order model fit showed good Omega reliability ( ωho= 0.87). Regarding CFAs, the unidimensional-factor model shows poor goodness of fit, especially residuals analysis [RMSEA= 0.081 (CI95%= 0.040-0.119), SRMR= 0.101]. The two-factor correlated model, three-factor correlated model, and second-order factor model showed an adequate goodness of fit, and the chi-squared difference test ( ΔX2 ) did not show significant differences between goodness of fit for these models ( ΔX2=4.1128 ; p =0.127). Several indices showed a good fit with the three-factor correlated model: GFI=0.974, CFI= 0.990, RNI =0.990 and IFI =0.990, which were all above 0.95, the traditional cut-off establishing adequate fit. On the other hand, RMSEA =0.049 (CI95% = 0.000-0.095), where an RMSEA <0.06 to 0.08 indicates an adequate fit. Item loadings on the factors were statistically significant ( λj≥0.449 ; p's <0.001), indicating that the items loaded correctly on the corresponding factors and relationship between factors ( ϕ≥0.382
; p's ≤0.001 CONCLUSIONS: To our knowledge, this is the first study to provide validity and reliability to CES-D 10 items in a persistent COVID-19 Spanish patient sample. The validation and reliability of this short screening tool allows us to increase the chance of obtaining complete data in a particular patient profile with increased fatigue and brain fog that limit patients' capacity to complete questionnaires. This article is protected by copyright. All rights reserved.
Keywords: COVID-19; Depression; Mental Illness; Statistical Factor Analyses..
. 2022 Oct 18.
doi: 10.1002/jmv.28236. Online ahead of print.
Factor Structure of the 10-item CES-D Scale Among Patients with Persistent COVID-19
Robinson Ramírez-Vélez[SUP] 1 2 [/SUP], Laiene Olabarrieta-Landa[SUP] 3 [/SUP], Diego Rivera[SUP] 3 [/SUP], Mikel Izquierdo[SUP] 1 3 [/SUP]
Affiliations
- PMID: 36258275
- DOI: 10.1002/jmv.28236
Abstract
Background: The presence of persistent coronavirus disease 2019 (COVID-19) might be associated with significant levels of psychological distress that would meet the threshold for clinical relevance. The Center for Epidemiologic Studies Depression Scale (CES-D) version 10 has been widely used in assessing psychological distress among general and clinical populations from different cultural backgrounds. To our knowledge, however, researchers have not yet validated these findings among patients with persistent COVID-19.
Method: A cross-sectional validation study was conducted with 100 patients from the EXER-COVID project (69.8% women; mean (±standard deviation) ages 47.4±9.5 years). Confirmatory factor analyses (CFAs) were performed on the 10-item CES-D to test four model fits: (a) unidimensional model, (b) two-factor correlated model, (c) three-factor correlated model, and (d) second-order factor model. The Diagonal Weighted Least Squares (DWLS) estimator was used, as it is commonly applied to latent variable models with ordered categorical variables.
Results: The reliability indices of the CES-D 10 items in patients with persistent COVID-19 were as follows: depressive affect factor ( αOrd=
0.82; ωu−cat =0.78), somatic retardation factor ( αOrd= 0.78; ωu−cat =0.56), and positive affect factor ( αOrd= 0.56; ωu−cat =0.55). The second-order model fit showed good Omega reliability ( ωho= 0.87). Regarding CFAs, the unidimensional-factor model shows poor goodness of fit, especially residuals analysis [RMSEA= 0.081 (CI95%= 0.040-0.119), SRMR= 0.101]. The two-factor correlated model, three-factor correlated model, and second-order factor model showed an adequate goodness of fit, and the chi-squared difference test ( ΔX2 ) did not show significant differences between goodness of fit for these models ( ΔX2=4.1128 ; p =0.127). Several indices showed a good fit with the three-factor correlated model: GFI=0.974, CFI= 0.990, RNI =0.990 and IFI =0.990, which were all above 0.95, the traditional cut-off establishing adequate fit. On the other hand, RMSEA =0.049 (CI95% = 0.000-0.095), where an RMSEA <0.06 to 0.08 indicates an adequate fit. Item loadings on the factors were statistically significant ( λj≥0.449 ; p's <0.001), indicating that the items loaded correctly on the corresponding factors and relationship between factors ( ϕ≥0.382
; p's ≤0.001 CONCLUSIONS: To our knowledge, this is the first study to provide validity and reliability to CES-D 10 items in a persistent COVID-19 Spanish patient sample. The validation and reliability of this short screening tool allows us to increase the chance of obtaining complete data in a particular patient profile with increased fatigue and brain fog that limit patients' capacity to complete questionnaires. This article is protected by copyright. All rights reserved.
Keywords: COVID-19; Depression; Mental Illness; Statistical Factor Analyses..