2 resultados para static structure factor

em Instituto Superior de Psicologia Aplicada - Lisboa


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The Posttraumatic Growth Inventory (PTGI) is frequently used to assess positive changes following a traumatic event. The aim of the study is to examine the factor structure and the latent mean invariance of PTGI. A sample of 205 (M age = 54.3, SD = 10.1) women diagnosed with breast cancer and 456 (M age = 34.9, SD = 12.5) adults who had experienced a range of adverse life events were recruited to complete the PTGI and a socio-demographic questionnaire. We use Confirmatory Factor Analysis (CFA) to test the factor-structure and multi-sample CFA to examine the invariance of the PTGI between the two groups. The goodness of fit for the five-factor model is satisfactory for breast cancer sample (χ2(175) = 396.265; CFI = .884; NIF = .813; RMSEA [90% CI] = .079 [.068, .089]), and good for non-clinical sample (χ2(172) = 574.329; CFI = .931; NIF = .905; RMSEA [90% CI] = .072 [.065, .078]). The results of multi-sample CFA show that the model fit indices of the unconstrained model are equal but the model that uses constrained factor loadings is not invariant across groups. The findings provide support for the original five-factor structure and for the multidimensional nature of posttraumatic growth (PTG). Regarding invariance between both samples, the factor structure of PTGI and other parameters (i.e., factor loadings, variances, and co-variances) are not invariant across the sample of breast cancer patients and the non-clinical sample.

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A confirmatory attempt is made to assess the validity of a hierarchic structural model of fears. Using a sample comprising 1,980 adult volunteers in Portugal, the present study set out to delineate the multidimensional structure and hierarchic organization of a large set of feared stimuli by contrasting a higher-order model comprising general fear at the highest level against a first-order model and a unitary fear model. Following a refinement of the original model, support was found for a five-factor model on a first-order level, namely (1) Social fears, (2) Agoraphobic fears, (3) Fears of bodily injury, death and illness, (4) Fears of display to aggressive scenes, and (5) Harmless animals fears. These factors in turn loaded on a General fear factor at the second-order level. However, the firstorder model was as parsimonious as a hierarchic higher-order model. The hierarchic model supports a quantitative hierarchic approach which decomposes fear disorders into agoraphobic, social, and specific (animal and bloodinjury) fears.