Psychometric properties of the Dutch version of the posttraumatic growth inventory among cancer patients

Abstract Objective: To examine psychometric properties of the Brazilian version of the Posttraumatic Growth Inventory (PTGI). Method: A total of 300 university students were evaluated though instruments that investigated trauma history, depression and posttraumatic symptoms, and personality traits through the Big Five model. Pearson's correlation was used to assess internal consistency, inter-item reliability and construct validity. Principal component analysis and confirmatory factor analysis were performed to investigate the factor structure of the PTGI. Results: Results confirmed the original five-factor structure. The results showed good internal consistency for the total scale (α = 0.91) and its subscales, ranging from α = 0.85 to α = 0.70. Also, evidence of construct and convergent validity was observed through correlations with posttraumatic and depression symptoms and personality measures. Conclusions: These preliminary results suggest that the Brazilian PTGI is reliable and showed adequate evidence of validity.

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The Posttraumatic Growth Inventory: Factor Structure and Invariance in a Sample of Breast Cancer Patients and in a Non-Clinical Sample

The Spanish Journal of Psychology ◽

10.1017/sjp.2016.65 ◽

2016 ◽

Vol 19 ◽

Cited By ~ 4

Author(s):

Catarina Ramos ◽

Isabel Leal ◽

Ana Lúcia Marôco ◽

Richard G. Tedeschi

Keyword(s):

Breast Cancer ◽

Posttraumatic Growth ◽

Cancer Patients ◽

Factor Structure ◽

Goodness Of Fit ◽

Clinical Sample ◽

Five Factor Model ◽

Breast Cancer Patients ◽

Factor Loadings ◽

Posttraumatic Growth Inventory

AbstractThe 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 (Mage = 54.3, SD = 10.1) women diagnosed with breast cancer and 456 (Mage = 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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Posttraumatic growth and its measurement: A closer look at the PTGI’s psychometric properties and structure

10.31234/osf.io/6ncsw ◽

2021 ◽

Author(s):

Bibiana Jozefiakova ◽

Natalia Kascakova ◽

Matus Adamkovic ◽

Jozef Hasto ◽

Petr Tavel

Keyword(s):

Psychometric Properties ◽

Posttraumatic Growth ◽

Factor Structure ◽

Latent Variable ◽

Latent Variable Model ◽

Latent Factors ◽

Variable Model ◽

Effective Interventions ◽

Posttraumatic Growth Inventory ◽

Negative Connotation

Despite its negative connotation, surviving trauma can result in improvements in some of the domains of one’s life. This phenomenon is known as posttraumatic growth and is usually measured using the Posttraumatic Growth Inventory (PTGI). Given the ambiguous results of the existing validation studies, the present study aimed to verify the psychometric properties of the Slovak version of the (PTGI) in a representative sample of Slovak citizens. Although the results suggest that a modified one-factor structure fitted the data best, other issues such as extremely high correlations between the latent factors, related to the PTGI’s factor structure were observed. It is likely that the application of the latent variable model does not represent the essence of PTG adequately and the network approach thus appears to be a far more suitable conceptualization of PTG. More detailed information on between-person differences and within-person changes in PTG could help to tailor more effective interventions or preventative programs.

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