Distress and unemployment: The related economic and noneconomic factors in a sample of unemployed adults

Objectives To examine the associations between economic and noneconomic factors and psychological distressin a group of 748 unemployed adults during economic recession. Methods Data were collected through a questionnaire. Bivariate and logistic regression analyses were used to test the associations between distress and the deprivation of income and latent benefits of employment (time structure, activity, status, collective purpose and social contact). Results The participants’ mean of distress was higher than the national population mean, and 46.5% of the participants scored above that. All economic and noneconomic factors emerged as strong predictors of distress; particularly financial deprivation (OR 1.06; CI 95 % 1.04–1.09) and lack of structured time (OR 1.07; CI 95 % 1.05–1.09). Women (OR 1.40; CI 95 % 1.04–1.86) and people with lower education levels (OR 0.45; CI 95 % 0.34–0.61) were more affected. Conclusions The unemployed individuals score high on distress, especially those facing financial strain and lack of structured time, and women and individuals with lower education in particular. Given the recessionary context and high unemployment rates, these insights raise awareness for policies and actions targeting the needs of unemployed people.

The posttraumatic growth inventory: Factor structure and invariance in a sample ofbreast cancer patients and in a non-clinical sample

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.