Factor structure and measurement invariance across various demographic groups and over time for the PHQ-9 in primary care patients in Spain

Abstract

The Patient Health Questionnaire (PHQ-9) is a widely-used screening tool for depression in primary care settings. The purpose of the present study is to identify the factor structure of the PHQ-9 and to examine the measurement invariance of this instrument across different sociodemographic groups and over time in a sample of primary care patients in Spain. Data came from 836 primary care patients enrolled in a randomized controlled trial (PsicAP study) and a subsample of 218 patients who participated in a follow-up assessment at 3 months. Confirmatory factor analysis (CFA) was used to test one- and two-factor structures identified in previous studies. Analyses of multiple-group invariance were conducted to determine the extent to which the factor structure is comparable across various demographic groups (i.e., gender, age, marital status, level of education, and employment situation) and over time. Both one-factor and two-factor re-specified models met all the pre-established fit criteria. However, because the factors identified in the two-factor model were highly correlated (r = .86), the one-factor model was preferred for its parsimony. Multi-group CFA indicated measurement invariance across different demographic groups and across time. The present findings suggest that physicians in Spain can use the PHQ-9 to obtain a global score for depression severity in different demographic groups and to reliably monitor changes over time in the primary care setting.

Measurement invariance of the patient health questionnaire‐9 (PHQ‐9) depression screener in U.S. adults across sex, race/ethnicity, and education level: NHANES 2005–2016

“…However, missingness in the sample was below the 10% guideline (Little, Jorgensen, Lang, & Moore, ). Second, due to the cross‐sectional nature of the NHANES data, we were not able to assess measurement invariance over time, as done by González‐Blanch et al (). Future studies are needed to determine whether measurement invariance of the selected two‐factor solution for the PHQ‐9 holds over time.…”

“…Consistent with current recommendations (Rhemtulla, Brosseau‐Liard, & Savalei, ), we used the means and variance adjusted weighted least squares (WLSMV) estimation method because of the ordinal scale. To determine the factor structure, we conducted five single‐group CFAs on our full sample ( n = 31,366), each of which examined a plausible model that has received support (Model 1, Cameron, Crawford, Lawton, & Reid, ; Dum, Pickren, Sobell, & Sobell, ; Galenkamp et al, ; González‐Blanch et al, ; Huang et al, ; Keum et al, ; Kocalevent, Hinz, & Brähler, ; Model 2, Chilcot et al, ; Elhai et al, ; Krause, Bombardier, & Carter, ; Petersen et al, ; Model 3, Baas et al, ; Petersen et al, ; Model 4, Elhai et al, ; Petersen et al, ; Model 5 Kalpakjian et al, ; Krause, Reed, & McArdle, ; Richardson & Richards, ; see Table ). In justifying our baseline model, we considered fit indices (root mean square error of approximation [RMSEA], Tucker‐Lewis index [TLI], and comparative fit index [CFI]) and current depression theory.…”

“…Although a few investigations have examined the measurement invariance of the PHQ‐9, these studies have been limited in two ways. One, they have not examined a consistent factor structure, with some claiming the PHQ‐9 has one factor (Baas et al, ; Cameron, Crawford, Lawton, & Reid, ; Crane et al, ; Galenkamp, Stronks, Snijder, & Derks, ; González‐Blanch et al, ; Huang, Chung, Kroenke, Delucchi, & Spitzer, ; Keum, Miller, & Inkelas, ; Merz, Malcarne, Roesch, Riley, & Sadler, ) and others claiming two factors (Petersen et al, ), making the generalizability of findings confusing. Two, they have utilized nonrepresentative samples – namely, primary care patients (Huang et al, ), college students (Keum et al, ), people with HIV (Crane et al, ), Latina women (Merz et al, ), and non‐U.S.…”

“…Two, they have utilized nonrepresentative samples – namely, primary care patients (Huang et al, ), college students (Keum et al, ), people with HIV (Crane et al, ), Latina women (Merz et al, ), and non‐U.S. samples (Baas et al, ; Cameron et al, ; Galenkamp et al, ; González‐Blanch et al, ; Petersen et al, ). Consequently, it is not known which PHQ‐9 factor structure provides the best fit and justification across major U.S. sociodemographic groups and whether the PHQ‐9 can be used in these groups without bias.…”

“…One, they have not examined a consistent factor structure, with some claiming the PHQ-9 has one factor (Baas et al, 2011;Cameron, Crawford, Lawton, & Reid, 2013;Crane et al, 2010;Galenkamp, Stronks, Snijder, & Derks, 2017;González-Blanch et al, 2018;Huang, Chung, Kroenke, Delucchi, & Spitzer, 2006;Keum, Miller, & Inkelas, 2018;Merz, Malcarne, Roesch, Riley, & Sadler, 2011) and others claiming two factors (Petersen et al, 2015), making the generalizability of findings confusing. Two, they have utilized nonrepresentative samplesnamely, primary care patients (Huang et al, 2006), college students (Keum et al, 2018), people with HIV (Crane et al, 2010), Latina women (Merz et al, 2011), and non-U.S. samples (Baas et al, 2011;Cameron et al, 2013;Galenkamp et al, 2017;González-Blanch et al, 2018;Petersen et al, 2015). Consequently, it is not known which PHQ-9 factor structure provides the best fit and justification across major U.S. sociodemographic groups and whether the PHQ-9 can be used in these groups without bias.…”