RESUMO
Cognitive decline, particularly in dementia, presents complex challenges in early detection and diagnosis. While Item Response Theory (IRT) has been instrumental in identifying patterns of cognitive impairment through psychometric tests, its parametric models often require large sample sizes and strict assumptions. This creates a need for more adaptable, less demanding analytical methods. This study aimed to evaluate the effectiveness of Mokken scale analysis (MSA), a nonparametric IRT model, in identifying hierarchical patterns of cognitive impairment from psychometric tests. Using data from 1164 adults over 60 years old, we applied MSA to the orientation subscale of ACE-III. Our analysis involved calculating scalability, monotone homogeneity, invariant item ordering (IIO) and response functions. The MSA effectively retrieved the hierarchical order of cognitive impairment patterns. Most items showed strong scalability and consistent patterns of cognitive performance. However, challenges with IIO were observed, particularly with items having adjacent difficulty parameters. The findings highlight MSA's potential as a practical alternative to parametric IRT models in cognitive impairment research. Its ability to provide valuable insights into patterns of cognitive deterioration, coupled with less stringent requirements, makes it a useful tool for clinicians and researchers.
RESUMO
OBJECTIVE: The Occupational Depression Inventory (ODI) assesses work-attributed depressive symptoms. The ODI has demonstrated robust psychometric and structural properties. To date, the instrument has been validated in English, French, and Spanish. This study examined the psychometric and structural properties of the ODI's Brazilian-Portuguese version. METHODS: The study involved 1612 civil servants employed in Brazil (MAGE = 44, SDAGE = 9; 60% female). The study was conducted online across all Brazilian states. RESULTS: Exploratory structural equation modeling (ESEM) bifactor analysis indicated that the ODI meets the requirements for essential unidimensionality. The general factor accounted for 91% of the common variance extracted. We found measurement invariance to hold across sexes and age groups. Consistent with these findings, the ODI showed strong scalability (H = 0.67). The instrument's total score accurately ranked respondents on the latent dimension underlying the measure. Furthermore, the ODI exhibited excellent total-score reliability (e.g., McDonald's ω = 0.93). Occupational depression correlated negatively with work engagement and each of its components (vigor, dedication, and absorption), speaking to the ODI's criterion validity. Finally, the ODI helped clarify the issue of burnout-depression overlap. Relying on ESEM confirmatory factor analysis (CFA), we found burnout's components to correlate more strongly with occupational depression than with each other. Using a higher-order ESEM-within-CFA framework, we found a correlation of 0.95 between burnout and occupational depression. CONCLUSION: The ODI displays robust psychometric and structural properties within the Brazilian context. The ODI constitutes a valuable resource for occupational health specialists and may help advance research on job-related distress.