Volume 13, Issue 4 (December 2015)                   Iranian Rehabilitation Journal 2015, 13(4): 40-48 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Ghadimianfar M, Dadkhah A. Prediction of Rehabilitation Nurses’ Psychological Well-Being by Personality Traits and Defense Mechanisms . Iranian Rehabilitation Journal 2015; 13 (4) :40-48
URL: http://irj.uswr.ac.ir/article-1-569-en.html
1- Science and Research Branch, Islamic Azad University, Tehran, Iran.
2- University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
Abstract:   (4552 Views)

Objectives: The purpose of the study is to predict the psychological well-being of nurses based on personality traits and defense mechanisms.

Methods: The research method was correlational and the statistical population consisted of all married female nurses in hospitals of the Qom city. The sample size estimated by Tabachnik and Fidel method 114 and with Overestimate attain to 120 people. These individuals selected by cluster random sampling method. Data collected by Ryff's Scales of Psychological well-being (RSPWB), big five personality inventory short form (NEO FFI) and defense style questionnaire (DSQ-40). Data analyzed by Pearson correlation coefficient and multivariate regression by the use of SPSS software (V20).

Results: Analysis of research data indicated that traits of extroversion (P  0.01), neuroticism (P  0.01), agreeableness (P 0.01), mature defensive style (P  0.01) and immature defense style (P  0.01) could explain variance of psychological well-being of nurses significantly.

Discussion: Considering to the findings of this research can concluded that personality traits and defense styles be able to predict the psychological well-being significantly.

Full-Text [PDF 102 kb]   (2507 Downloads)    
Article type: Original Research Articles |
Received: 2015/09/10 | Accepted: 2015/11/14 | Published: 2015/12/1

Send email to the article author


Designed & Developed by : Yektaweb