Structure Equation Modeling Relationship between Symptoms of ADHD based on Depression and Anxiety and Mediating Role of Mind-Wandering and Motivation

Document Type : Original Article


1 Department of Psychology, Faculty of Education and Psychology, University of Isfahan, Isfahan, Iran

2 Department of Statistic, Faculty of Mathematics and Statistics, University of Isfahan, Isfahan, Iran


Introduction: Many people with Attention Deficit/Hyperactivity Disorder (ADHD) suffer from comorbidity of depression or anxiety. Also, in ADHD patients Mind-Wandering (MW) and lack of motivation are common. This study aimed to examine the mediating role of motivation and MW in the relationship between depression and anxiety with ADHD symptoms.
Method: This research was a correlational study which was run within the Structural Equation Modelling framework. The statistical population consisted of all university students of Isfahan in 2020-2021 with ADHD symptoms, of whom 211 were selected based on the stratified method at first and then by using the multi-stage clustering sampling method. The research instruments included the Barkley Adult ADHD Rating Scale-IV (BAARS-IV), Diagnostic Interview for Adult ADHD (DIVA), Mental Health questionnaire (SCL-90), Mind-Wandering questionnaire (MW), Internal Motivation Inventory (IMI), and Cattell Culture Fair Intelligence Test (CFIQ). The Maximum Likelihood Estimation and the Bootstrap test were used to evaluate the hypothesized model and indirect effects. The statistical procedures were run in SPSS24 and AMOS24.
Results: Findings revealed that the hypothesized model fit the observed data with good domain indices. Also, there was a significant indirect relationship between depression and anxiety with ADHD symptoms through the mediating role of MW. Moreover, there were significant direct relationships between depression and motivation, anxiety and MW, MW and ADHD symptoms.
Conclusion: The study findings confirmed the hypothesized model’s goodness of fit. Therefore, the use of this model is recommended to identify the factors affecting ADHD symptoms in university students.  


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