Predicting posttraumatic growth among Hurricane Katrina survivors living with HIV: the role of self-efficacy, social support, and PTSD symptoms
Roman Cieślak , Charles C. Benight , Norine Schmidt , Aleksandra Łuszczyńska , Erin Cutrin , Rebecca A. Clark , Patricia Kissinger
AbstractThe study tested the model of adaptation after trauma by Benight and Bandura (2004) indicating that posttraumatic recovery may be predicted directly by coping self-efficacy (CSE) and indirectly by social support. These relations were investigated in the context of posttraumatic growth (PTG) among Hurricane Katrina survivors living with HIV. Additionally, it was hypothesized that among individuals with more intensive Posttraumatic Stress Disorder (PTSD) symptoms, those with strong CSE would experience the strongest PTG. Cross-sectional data were collected among 90 patients with HIV who reinitiated care at the HIV outpatient clinic. Questionnaires were administered approximately 14 months after the hurricane. Higher CSE was related to higher PTG among the survivors who suffered from more intensive PTSD symptoms. Received social support was directly related to only one index of PTG, relating to others. Furthermore, although there was a significant relationship between social support and CSE, the indirect conditional effect of received social support on PTG was not confirmed. Similar results were obtained across the indices of PTG, controlling for the level of exposure to hurricane-related trauma. Cross-sectional design and convenience character of the sample warrants replications.
|Tytuł czasopisma/serii||ANXIETY STRESS AND COPING, (0 pkt)|
|Objętość publikacji w arkuszach wydawniczych||0|
|Słowa kluczowe w języku angielskim||HIV, natural disaster, self-efficacy, social support, posttraumatic growth, PTSD|
|Liczba cytowań*||160 (2021-04-11)|
|Dorobek Naukowy - Preview URL||http://dn.swps.edu.pl/Podglad.aspx?WpisID=3381|
|Dorobek Naukowy - Approve URL||http://dn.swps.edu.pl/Biuro/ZatwierdzanieWpisu.aspx?WpisID=3381|
* Podana liczba cytowań wynika z analizy informacji dostępnych w Internecie i jest zbliżona do wartości obliczanej przy pomocy systemu Publish or Perish.