Predicting the Psychological Well-Being of Mothers of Children with Autism Based on Self-Control and Integrated Self-Knowledge

Objective: The aim of this study was to predict the psychological well-being of mothers of children with autism based on self-control and integrated self-knowledge. Methodology: This study was descriptive-survey in nature and applied in purpose. The sample consisted of 100 mothers of children with autism in Tehran, selected through stratified sampling. Standardized questionnaires were used, including Ryff’s Psychological Well-Being Scale (2002), the Integrated Self-Knowledge Scale (Ghorbani et al., 2008), and the Self-Control Scale (Tangney et al., 2004). Data analysis was performed using correlation and multiple regression tests. Findings: The results indicated a significant positive correlation among psychological well-being, self-control, and integrated self-knowledge in mothers of children with autism. The regression model was confirmed, with an adjusted R-square value of 0.864, showing that 86.4% of the variance in psychological well-being was explained by the two predictors. Furthermore, self-control had a stronger predictive effect on psychological well-being compared to integrated self-knowledge. Conclusion: The findings emphasize the crucial role of self-control and integrated self-knowledge in enhancing the psychological well-being of mothers of children with autism. Intervention programs aiming to strengthen these psychological resources can contribute to improving the quality of life for these mothers.

Authors

Publication Details

Journal
پویایی روانشناختی در اختلال‌های خلقی.
Published
2025-01-01
DOI
https://doi.org/10.61838/kman.pdmd.4.1.17
Primary Topic
Psychosocial Factors Impacting Youth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting the Psychological Well-Being of Mothers of Children with Autism Based on Self-Control and Integrated Self-Knowledge

Mohammad Parsa Azizi, Majid Ebrahimpoor, Zhinoos Niakan
پویایی روانشناختی در اختلال‌های خلقی.
Psychosocial Factors Impacting Youth
article

Predicting the Psychological Well-Being of Mothers of Children with Autism Based on Self-Control and Integrated Self-Knowledge

Mohammad Parsa Azizi, Majid Ebrahimpoor, Zhinoos Niakan
article en

Abstract

Objective: The aim of this study was to predict the psychological well-being of mothers of children with autism based on self-control and integrated self-knowledge. Methodology: This study was descriptive-survey in nature and applied in purpose. The sample consisted of 100 mothers of children with autism in Tehran, selected through stratified sampling. Standardized questionnaires were used, including Ryff’s Psychological Well-Being Scale (2002), the Integrated Self-Knowledge Scale (Ghorbani et al., 2008), and the Self-Control Scale (Tangney et al., 2004). Data analysis was performed using correlation and multiple regression tests. Findings: The results indicated a significant positive correlation among psychological well-being, self-control, and integrated self-knowledge in mothers of children with autism. The regression model was confirmed, with an adjusted R-square value of 0.864, showing that 86.4% of the variance in psychological well-being was explained by the two predictors. Furthermore, self-control had a stronger predictive effect on psychological well-being compared to integrated self-knowledge. Conclusion: The findings emphasize the crucial role of self-control and integrated self-knowledge in enhancing the psychological well-being of mothers of children with autism. Intervention programs aiming to strengthen these psychological resources can contribute to improving the quality of life for these mothers.

پویایی روانشناختی در اختلال‌های خلقی.Vol. 4(1)
Openalex Percentile: Top 86%
Psychosocial Factors Impacting Youth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.