Methods: In this study, we incorporated 17 Likert-scale questions reflecting three subsconstructs: substance use, pressure from negative affect, and perfectionism. Analyses were conducted using a nested model strategy in a latent variable modeling framework. The data was collected from several clinical sites in West coast of US. The data of adult patients’ first visit were selected as sample, reflecting 260 patient reports on 17 variables. We deployed an unconstrained 1-factor model, an unconstrained 3-factor model, and a constrained 3-factor model. The three latent factors in the later models were allowed to covary. We assessed each model for absolute fit and considered the relative fits of the constrained model against both unconstrained models.
Results: For 1-factor model, the standardized loadings of the indicators ranged from 0.33 to 0.69, but the absolute fit of the model was not adequate. The results of 3-factor unconstrained model reflected a good fit, χ2(88,N=260)=141.648, p<0.001, RMSEA=0.055 with 90%CI [0.039,0.069]. The constrained 3-factor model was conducted with factor variances fixed at 1.0 and it showed a good absolute fit with χ2(116,N=260)=275.407, p<0.000, CFI=0.920, RMSEA=0.068 with 90%CI [0.057,0.080]. Moreover, RMSEA of constrained 3-factor model fell within the 90%CI for RMSEA of 3-factor unconstrained, which indicated that the 3-factor model fit relatively well with the data. Coefficient alphas for substance use subscale was 0.92, 0.63 for pressure from negative affect, and 0.74 for perfectionism.
Conclusions: These results establish baseline psychometric properties of the three subscales in at once occasion in a US sample. Our broader goal is to ensure that our measures can be employed effectively in a structured data-tracking system over time and across cultures. Hence, this baseline psychometric report is pivotal to our next steps in both longitudinal analysis of factorial invariance and cross-cultural validation study. Longer term goals involve development of adaptive real-time algorithmic prediction systems based on this construct constellation.