Symptom Checklist-90-Revised: A structural examination in relation to family functioning

Abstract

The accurate assessment of psychopathological behaviours of adolescents and young adults is imperative. Symptom Checklist-90-Revised (SCL-90-R) is one of the most comprehensive and widely used scales addressing this purpose internationally. Interestingly, associations between the different SCL-90 symptoms and family functioning have been highlighted. Nevertheless, the scale’s factorial structure has often been challenged. To contribute in this area, this study scrutinizes the psychopathological dimensions of the Symptom Checklist-90-Revised (SCL-90-R) in a large cohort of high school students (Mean age = 16.16; SD = .911) from Greece. It addresses this aim by: a) using first order and bi-factor confirmatory factor analysis, and exploratory structural equation models and; b) investigating the factors’ associations with family functioning. A total of 2090 public Greek High School students completed the SCL-90-R and the Family Adaptability and Cohesion Scale IV (FACES-IV) covering family functioning, satisfaction and communication. Six different solutions, yielded by separate permutations of CFA, ESEM, and bifactor models, were evaluated. Based on global fit, the clarity, reliabilities and the family functioning links of the dimensions in the models, the ESEM oblique model with the theorized nine factors emerged as the optimum. This model had adequate fit, and symptom dimensions were well defined. Also six of the nine factors demonstrated external associations with family functioning, satisfaction and communication. The clinical assessment benefits of these results are discussed.

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“…To assess anxiety, the State Trait Anxiety Inventory-State (STAI-S) ( 36 ), HADS, POMS, and the Revised Symptom-Checklist-90 (SCL-90-r) ( 37 ) were used in 9 studies involving 1,532 patients. The results of subgroup analyses of the four groups showed statistical significance, and the total results also showed that intervention group had a better improvement in anxiety control than the control group [SMD, −1.36; 95% CI: (−2.13, −0.60); P=0.0005; random-effects model], with significant heterogeneity between subgroups (I 2 =98%, P<0.00001) ( Figure 6 ).…”

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“…First, IRT models were estimated with IRT-PRO (Cai et al, 2011 ). Model fit was concurrently determined by: (i) traditional fit indices ( χ 2Loglikelihood ); (ii) marginal likelihood information statistics M 2 (one and two-way marginal tables to correct for potentially sparse information); (iii) RMSEA (< 0.06 = sufficient fit; Hu & Bentler, 1999 ; Gomez et al, 2021a ); and (iv) estimation of error prediction based on Akaike information criterion (AIC; Akaike, 1974 ) and Bayesian information criterion (BIC; Schwarz, 1978 ). Given the potential sensitivity of M 2 to large samples ( N > 900), emphasis was placed on RMSEA to assess model fit (De Ayala, 2008 ).…”

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“…For example, Olsen et al [ 27 ] reported that the SCL-90 Psychoticism subscale was problematic in a Danish sample, while Prunas et al [ 28 ] opted for an 8-component solution and showed that the eight dimensions partially recombined the items into conceptually coherent domains, such as relational distress or general dysphoria. In clinical samples, the expected factor structure was replicated neither, and the SCL-90 questionnaire was recommended more as a screening instrument for general distress to be supplemented by other diagnostic instruments [ 29 , but see 30 ].…”