Volume 2, Issue 3 (Summer 2014-- 2014)                   PCP 2014, 2(3): 195-200 | Back to browse issues page

XML Print

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

Delavar B, Dolatshahi B, Nouri M, Aryanfar K. Metacognition and Depression, State Anxiety and Trait Anxiety Symptoms. PCP 2014; 2 (3) :195-200
URL: http://jpcp.uswr.ac.ir/article-1-65-en.html
1- Department of Psychology, University of Social Welfare & Rehabilitation Sciences, Tehran, Iran. , baharakdelavar@yahoo.com
Abstract:   (3844 Views)

Objective: The objective of this study was analyzing the effect of meta-cognition elements on depression, trait and state anxiety symptoms. 

Methods: In this Study, the sample consisted of 224 students of University of Social Welfare and Rehabilitation Sciences that answered three questionnaires including Metacognitive Questionnaire (MCQ-30), Beck Depression inventory (BDI-II) and Spielberger State-Trait Anxiety Inventory. Pearson correlation coefficient and step-by-step regression to analyze were used for data analysis. 

Results: According to the results, there is a positive and significant correlation between total score of metacognition and four elements of beliefs (positive beliefs, negative beliefs, uncontrollability and low cognitive trust (P<0.01). In addition, summary of results indicated that out of metacognitive elements, only general negative beliefs may predict the variations of depression scores, (P<0.01). 
Conclusion: Summary of this study demonstrated that metacognitive beliefs are significantly effective on prediction of depression and anxiety. Moreover, out of metacognitive elements, only general negative beliefs, in comparison with other elements, may predict the depression.
Full-Text [PDF 470 kb]   (2947 Downloads)    
Type of Study: Research | Subject: Cognitive behavioral
Received: 2014/01/10 | Accepted: 2014/06/6 | Published: 2014/07/1

Add your comments about this article : Your username or Email:

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Designed & Developed by : Yektaweb