Propiedades psicométricas del Inventario de Crecimiento Postraumático en el contexto de la pandemia de COVID-19: Invarianza del modelo bifactorial.
Saved in:
| Title: | Propiedades psicométricas del Inventario de Crecimiento Postraumático en el contexto de la pandemia de COVID-19: Invarianza del modelo bifactorial. |
|---|---|
| Alternate Title: | Psychometric properties of the Post-traumatic Growth Inventory in the context of COVID-19 pandemic: Bifactor model invariance. |
| Authors: | Cassaretto, Mónica1 mcassar@pucp.edu.pe, Gargurevich, Rafael1 |
| Source: | Revista de Psicopatologia y Psicologia Clinica. aug2024, Vol. 29 Issue 2, p121-132. 12p. |
| Abstract (English): | The Posttraumatic Growth Inventory (PTGI; Tedeschi & Calhoun, 1996) assesses growth experiences following traumatic events, such as those experienced during the COVID-19 pandemic. However, its factor structure is still under debate, suggesting that a bifactor model might best represent the structure of the test. This study examined the psychometric properties of this instrument with a sample of 615 Peruvian adults. Confirmatory factor analyses revealed that a bifactor model, which included a general factor and five specific factors, proved to be the best fit to the data (SBS-χ2 (df)= 909.26(184), CFI =1, RMSEA =.066, SRMR =.046). We found evidence of configural invariance between the group that reports deceased relatives by COVID-19 and the group that does not. In addition, adequate internal consistency indices were found. This study supports adequate psychometric properties of the PTGI. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | El Inventario de Crecimiento Postraumático (ICPT; Tedeschi y Calhoun, 1996) evalúa las experiencias de crecimiento tras eventos traumáticos, como los vividos durante la pandemia de la COVID-19. Sin embargo, su estructura factorial sigue siendo objeto de debate. Al respecto, se sugiere que un modelo bifactor podría representar de manera óptima la estructura de la prueba. Este estudio analiza las propiedades psicométricas de este instrumento con 615 adultos peruanos. Los análisis factoriales confirmatorios revelan que un modelo bifactorial, que incluye un factor general y cinco factores específicos, es el que mejor se ajusta a los datos (SBS-χ2 (df) = 909.26(184), CFI = 1, RMSEA = .066, SRMR = .046). Se observa evidencia de invarianza configural entre el grupo que reporta familiares fallecidos por la COVID-19 y el grupo que no lo hace. Además, se encuentran índices adecuados de consistencia interna. Este estudio respalda las adecuadas propiedades psicométricas del ICPT. [ABSTRACT FROM AUTHOR] |
| Copyright of Revista de Psicopatologia y Psicologia Clinica is the property of Asociacion Espanola de Psicologia Clinica y Psicopatologia and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | MedicLatina |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: lth DbLabel: MedicLatina An: 178757017 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Propiedades psicométricas del Inventario de Crecimiento Postraumático en el contexto de la pandemia de COVID-19: Invarianza del modelo bifactorial. – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: Psychometric properties of the Post-traumatic Growth Inventory in the context of COVID-19 pandemic: Bifactor model invariance. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cassaretto%2C+Mónica%22">Cassaretto, Mónica</searchLink><relatesTo>1</relatesTo><i> mcassar@pucp.edu.pe</i><br /><searchLink fieldCode="AR" term="%22Gargurevich%2C+Rafael%22">Gargurevich, Rafael</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Revista+de+Psicopatologia+y+Psicologia+Clinica%22">Revista de Psicopatologia y Psicologia Clinica</searchLink>. aug2024, Vol. 29 Issue 2, p121-132. 12p. – Name: Abstract Label: Abstract (English) Group: Ab Data: The Posttraumatic Growth Inventory (PTGI; Tedeschi & Calhoun, 1996) assesses growth experiences following traumatic events, such as those experienced during the COVID-19 pandemic. However, its factor structure is still under debate, suggesting that a bifactor model might best represent the structure of the test. This study examined the psychometric properties of this instrument with a sample of 615 Peruvian adults. Confirmatory factor analyses revealed that a bifactor model, which included a general factor and five specific factors, proved to be the best fit to the data (SBS-χ2 (df)= 909.26(184), CFI =1, RMSEA =.066, SRMR =.046). We found evidence of configural invariance between the group that reports deceased relatives by COVID-19 and the group that does not. In addition, adequate internal consistency indices were found. This study supports adequate psychometric properties of the PTGI. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Abstract (Spanish) Group: Ab Data: El Inventario de Crecimiento Postraumático (ICPT; Tedeschi y Calhoun, 1996) evalúa las experiencias de crecimiento tras eventos traumáticos, como los vividos durante la pandemia de la COVID-19. Sin embargo, su estructura factorial sigue siendo objeto de debate. Al respecto, se sugiere que un modelo bifactor podría representar de manera óptima la estructura de la prueba. Este estudio analiza las propiedades psicométricas de este instrumento con 615 adultos peruanos. Los análisis factoriales confirmatorios revelan que un modelo bifactorial, que incluye un factor general y cinco factores específicos, es el que mejor se ajusta a los datos (SBS-χ2 (df) = 909.26(184), CFI = 1, RMSEA = .066, SRMR = .046). Se observa evidencia de invarianza configural entre el grupo que reporta familiares fallecidos por la COVID-19 y el grupo que no lo hace. Además, se encuentran índices adecuados de consistencia interna. Este estudio respalda las adecuadas propiedades psicométricas del ICPT. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Revista de Psicopatologia y Psicologia Clinica is the property of Asociacion Espanola de Psicologia Clinica y Psicopatologia and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=lth&AN=178757017 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5944/rppc.38670 Languages: – Code: spa Text: Spanish PhysicalDescription: Pagination: PageCount: 12 StartPage: 121 Titles: – TitleFull: Propiedades psicométricas del Inventario de Crecimiento Postraumático en el contexto de la pandemia de COVID-19: Invarianza del modelo bifactorial. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cassaretto, Mónica – PersonEntity: Name: NameFull: Gargurevich, Rafael IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: aug2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 11365420 Numbering: – Type: volume Value: 29 – Type: issue Value: 2 Titles: – TitleFull: Revista de Psicopatologia y Psicologia Clinica Type: main |
| ResultId | 1 |
