Predicting Non-Suicidal Self-injury in Secondary High School Students Based on Affective and Emotional Composite Temperament Model (AFECT)

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background & Objective

Non-Suicidal Self-injury has a high frequency in adolescence, and several studies have pointed to the role of temperamental variables in the occurrence of these behaviors. This study aimed to predict self-injury behaviors in secondary high school students based on the Affective and Emotional Composite Temperament Model.

Materials & Methods

This study was descriptive-correlational and its statistical population was all secondary high school students in Namin in Ardabil province, in which 205 students were selected using a multi-stage cluster sampling method and were examined by Affective and Emotional Composite Temperament questionnaires and self-injury questionnaire. Data analysis was performed using SPSS software version 20, Pearson correlation test, and stepwise regression.

Results

The dimensions of Emotional Temperament with a stepwise correlation coefficient of 37%, can predict about 13% of the changes related to self-injury behaviors and volition negatively and inhibition positively were able to significantly predict self-injury behaviors. In addition, the dimensions of Affective Temperament can explain and predict with a correlation coefficient of 395%, about 16% of the changes related to self-injury behaviors and depressive, volatile and disinhibited behaviors negatively and euthymia positively could predict self-injury behaviors.

Conclusion

The results showed that the AFECT model can explain and predict self-injury behaviors in students. Therefore, the results of this study have important implications for use of the AFECT model intending to identify groups exposed to self-injury behaviors and can be used to design preventive interventions for these behaviors.

Language:
English
Published:
Journal of Advanced Biomedical Sciences, Volume:10 Issue: 3, 2020
Pages:
2466 to 2476
https://magiran.com/p2243480  
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