Validation of the Post-Traumatic Growth Inventory in Adolescents Who Lost a Family Member in the Past 4 years: Effects of Time After the Death Event and Gender.

Post-traumatic growth is the psychological capacity to perceive positive changes facing high-stress or potentially traumatic events and may be especially useful in lessening their effects in adolescents' lives. Present study aimed to evaluate the psychometric properties of the Post-Traumatic Growth Inventory (PTGI) in 662 Peruvian adolescents who suffered the death of an immediate family member over the last 4 years. Firstly, an exploratory graphical analysis (EGA) was conducted to determine the best parsimonious structure of the instrument and confirmed with its respective factor models. The results report adequate fit indices in the EGA Bifactor model. Furthermore, another structural model is included, which reports significant latent effects of the time elapsed since the relative's death and gender (male) on PTGI general factor. Likewise, gender measure was significantly related to items 3, 7, and 11, which is linked to personal growth.

Identifying latent comorbidity patterns in adults with perceived cognitive impairment: Network findings from the behavioral risk factor surveillance system.

Background: People with cognitive impairment may be exposed to an increased risk of comorbidities; however, the clustering of comorbidity patterns in these patients is unclear. Objective: To explore the network structure of chronic comorbidity in a U.S. national sample spanning all 50 U.S. states with more than 170,000 participants reporting perceived cognitive impairment. Methods: This is a cross-sectional study conducted using Behavioral Risk Factor Surveillance System (BRFSS) secondary data collected in 2019 and covering 49 U.S. states, the District of Columbia, Guam, and the Commonwealth of Puerto Rico. A total of 15,621 non-institutionalized U.S. adult participants who reported "yes" to the subjective cognitive impairment question were considered, of whom 7,045 were men and 8,576 were women. All participants were aged 45 years or older. A statistical graphical model was used that included clustering algorithms and factorization of variables in a multivariate network relationship system [exploratory graphical analysis (EGA)]. Results: The results of the EGA show associations between the comorbid conditions evaluated. These associations favored the clustering of various comorbidity patterns. In fact, three patterns of comorbidities have been identified: (1) arthritis, asthma, respiratory diseases, and depression, (2) obesity, diabetes, blood pressure high, and blood cholesterol high, and (3) heart attack, coronary heart disease, stroke, and kidney disease. Conclusion: These results suggest the development of interdisciplinary treatment strategies in patients with perceived cognitive impairment, which could help to design an integrated prevention and management of the disease and other related health problems, such as Alzheimer's disease and related dementias.