RESUMO
Background: Child maltreatment is a significant global problem concerning over 25% of children around the world. Traditionally, the assessment of children's welfare was characterized by the creation of instruments and models from the deficit-based theoretical framework. Purpose: This study aims to develop an instrument to measure protective factors (the Adolescent and Children Risk of Abuse and Maltreatment Protective Factors Scale, ACRAM-PFS) and gather evidence on its psychometric properties. ACRAM-PFS is an 18-items scale for the assessment of protective factors of child maltreatment developed from the socioecological framework. Method: Structural validity, reliability and convergent-related validity were studied for this measure in a sample of 616 children and adolescents, with age ranging from 0 to 18 years old (M = 12.14; SD = 5.22). Cases were informed by 286 child welfare workers. The sample was split in two subsamples, one to perform an Exploratory Factor Analysis (EFA) and the second to perform a Confirmatory Factor Analysis (CFA). Results: The CFA corroborate the three-factor structure that includes the children and adolescents' resources, the family/caregiver's resources and the community resources (χ2 = 278.005, df = 132, p < .001, CFI = 0.955, SRMR = .084, RMSEA = .061, [90% CI: .051-.071]). Results of convergent-related validity indicated significant correlation with CTQ-SF and protective factors dimension of C-CAPS. Discussion: The results support that ACRAM-PFS is a rigorous measure for assessing protective factors for child maltreatment. The scale can serve as a key tool for designing strengths-based intervention strategies tailored to the actual needs of children and adolescents. The present study provides the implications for the development of protective factor scales in the field of child welfare.
RESUMO
THEORETICAL BACKGROUND: A challenge of the ageing of the population is cognitive performance, given its association to optimal ageing. Documented predictors of cognition have included socio-demographics, education or physical factors. However, the association of social and intellectual activity participation to cognition has been less studied. AIM: This study presents a predictive model of cognitive functioning including these alternative factors as well as more seminal ones to explain cognition in old age. MATERIALS AND METHODS: The sample was composed by 45475 older adult participants in the 8th Wave of the Survey of Health, Aging and Retirement in Europe, that took place between 2019 and 2020. A correlational design was specified to test the effects of age, gender, years of education, physical inactivity, number of chronic diseases, social activity participation and intellectual activity participation on temporal orientation, numeracy, verbal fluency and memory. A completely a priori Structural Equation Model with latent variables was tested. RESULTS: The sample had an average of 70 years of age, was well-educated and physically active and engaged in reading. There was a higher proportion of females. The model showed an optimal fit to the data, explaining 8.7%-36.0% of the different cognitive components' variance. Age, years of education and intellectual activity displayed the largest effects across the cognitive domains. CONCLUSIONS: Findings suggest that social and intellectual activity participation are of relative importance to predict cognition in old age, even when considering other well-documented factors affecting older adults' cognitive functioning.
