Capítulo de libro:
Can self-compassion predict future anxiety and depression?: A cross-lagged panel model analysis in a Dominican Republic sample

Vista sencilla de ítem
dc.contributor.authorJiménez Payano, Daniel
dc.contributor.authorGarcía, Luisa
dc.contributor.authorNazir, Asha
dc.contributor.authorBonilla, Luz
dc.contributor.authorVeras, Greicy
dc.contributor.authorRodríguez, Leidy
dc.contributor.authorRivas, Elain
dc.contributor.authorTejada, María
dc.contributor.authorFlores Kanter, Pablo Ezequiel
dc.date.accessioned2023-01-05T17:20:08Z
dc.date.available2023-01-05T17:20:08Z
dc.date.issued2021
dc.description.abstract"Emotional dysregulation, in the form of anxiety and depression, has a significant economic, social and psychological impact on a global scale. Several approaches have been developed in the hope of helping people to better regulate these emotions, with mixed results. Specifically, third-wave therapies seem to perform particularly well. These therapies share the variable of self-compassion, which both in evolutive and practical terms appears to be a key variable in regulating difficult emotional states such as anxiety and depression. The objective of this research was to verify the adjustment of an explanatory model of anxiety and depression, which considers the effect of self-compassion. A sample of 371 residents in Dominican Republic was used and a cross-lagged panel model analysis was carried out. The measurement model fit the data well. Also, it is possible to verify that self-compassion at time 1 predicts depression and anxiety at Time 2 in a theoretically coherent direction. Clinical implications for non-WEIRD countries are discussed."
dc.identifier.isbn978-1-53619-410-4
dc.identifier.urihttps://ri.itba.edu.ar/handle/123456789/4139
dc.language.isoen
dc.titleCan self-compassion predict future anxiety and depression?: A cross-lagged panel model analysis in a Dominican Republic sample
dc.typeCapítulo de libro
dspace.entity.typeCapítulo de libro

Archivos

Bloque original
Mostrando 1 - 1 de 1
No hay miniatura disponible
Nombre:
Capitulo_Jiménez
Tamaño:
1.21 MB
Formato:
Adobe Portable Document Format
Descripción:
Capitulo_Jiménez
Descargar
Bloque de licencias
Mostrando 1 - 1 de 1
No hay miniatura disponible
Nombre:
license.txt
Tamaño:
1.5 KB
Formato:
Item-specific license agreed upon to submission
Descripción:
Descargar

Colecciones

Neurociencias