Literature DB >> 9842781

Stress reactions of children and adolescents in war and siege conditions.

S A Husain1, J Nair, W Holcomb, J C Reid, V Vargas, S S Nair.   

Abstract

OBJECTIVE: This was a study of posttraumatic stress symptoms in children and adolescents during siege conditions in Sarajevo.
METHOD: Seven hundred ninety-one students aged 7-15 years were surveyed to assess symptoms of posttraumatic stress and level of deprivation.
RESULTS: Girls reported more stress than boys. Loss of family members and deprivation of basic needs were associated with more symptoms.
CONCLUSIONS: Personal experiences of siege are related to increased stress.

Entities:  

Mesh:

Year:  1998        PMID: 9842781     DOI: 10.1176/ajp.155.12.1718

Source DB:  PubMed          Journal:  Am J Psychiatry        ISSN: 0002-953X            Impact factor:   18.112


  8 in total

1.  Group crisis intervention for children during ongoing war conflict.

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2.  Prevalence of posttraumatic stress disorder among adolescents in school and its impact on their well-being: a cross-sectional study.

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Journal:  Pan Afr Med J       Date:  2021-05-19

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4.  Psychological disturbances of war-traumatized children from different foster and family settings in Bosnia and Herzegovina.

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Journal:  Croat Med J       Date:  2006-02       Impact factor: 1.351

5.  An overview of Indian research in anxiety disorders.

Authors:  J K Trivedi; Pawan Kumar Gupta
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6.  The Impact of Parental Detention on the Psychological Wellbeing of Palestinian Children.

Authors:  Amer Shehadeh; Gerrit Loots; Johan Vanderfaeillie; Ilse Derluyn
Journal:  PLoS One       Date:  2015-07-17       Impact factor: 3.240

7.  Validation of the French version of the Child Post-Traumatic Stress Reaction Index: psychometric properties in French speaking school-aged children.

Authors:  Bertrand Olliac; Philippe Birmes; Eric Bui; Charlotte Allenou; Alain Brunet; Isabelle Claudet; Jérôme Sales de Gauzy; Hélène Grandjean; Jean-Philippe Raynaud
Journal:  PLoS One       Date:  2014-12-02       Impact factor: 3.240

8.  Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms.

Authors:  Yuta Takahashi; Kazuki Yoshizoe; Masao Ueki; Gen Tamiya; Yu Zhiqian; Yusuke Utsumi; Atsushi Sakuma; Koji Tsuda; Atsushi Hozawa; Ichiro Tsuji; Hiroaki Tomita
Journal:  Sci Rep       Date:  2020-12-10       Impact factor: 4.379

  8 in total

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