Psychological Research in Individuals with Exceptional Needs

The Curriculum Content of a Metacognition-Based Program for Reducing Learning Disorders Among Elementary School Students

Esmat Nabipoor iD , Maryam Baratali ^* iD , Jahanbakhsh Rahmani iD

Learning disorders during elementary school are among the important issues in the educational system, as they can negatively affect students’ academic performance, self-confidence, and social adjustment. In recent years, metacognition-based approaches have attracted attention as an effective strategy for reducing these disorders because of their emphasis on self-awareness, self-regulation, and control of the learning process. However, designing a coherent and purposeful metacognition-based curriculum for reducing learning disorders among elementary school students remains one of the essential needs in the field of elementary education. The purpose of the present study was to identify the curriculum content of a metacognition-based program for reducing learning disorders among elementary school students. This study was conducted using a qualitative approach and thematic analysis with an exploratory inductive approach. Data were collected through the study of documents, scientific texts, and relevant research literature. The research domain included documents available in reputable databases and websites from 2007 to 2025 in the field of learning disorders and metacognition, as well as English-language documents published between 1991 and 2025. The data collection technique was an exploratory inductive approach, the data collection tool was note-taking, and the data analysis method was three-stage coding. The findings showed that, in the curriculum content dimension, the curriculum had an integrative and multilevel nature, and the implementation methods emphasized direct instruction, active strategies, multisensory approaches, metacognition-oriented strategies, and collaborative methods. The conclusion of the study indicated that curriculum content should be organized in accordance with the developmental characteristics and individual differences of elementary school students and should include practical and play-based activities, short and gradual exercises, feasible home assignments, and formative assessment tools so that it can sustainably reduce learning difficulties, increase learners’ self-awareness, and improve academic performance.

A Comparative Examination and Analysis of Conceptual Frameworks and Intelligence Assessment Instruments in Blind and Low-Vision Adolescents: Challenges, Approaches, and Requirements

Elham Aghamohamadi iD , Asghar Minaei ^* iD , Noorali Farrokhi iD , Salar Faramarzi iD , Jalil Younesi iD

The aim of the present study was to comparatively examine and analyze the conceptual frameworks and intelligence assessment instruments used with blind and low-vision adolescents, identify existing challenges and limitations, and explain the requirements for designing tests appropriate to the cognitive and sensory characteristics of this group. This study was conducted using a qualitative approach based on thematic synthesis. For this purpose, a systematic search of scientific sources was carried out in reputable national and international databases. Studies published between 2003 and 2025 were reviewed. From an initial pool of 83 documents, after applying the inclusion and exclusion criteria and assessing methodological quality, 31 studies, including 24 international studies and 7 national studies, were selected for final analysis. The data were analyzed according to the stages of thematic synthesis, including initial coding, extraction of descriptive themes, and formation of analytical themes. The analysis of the studies led to the identification of 11 main themes, including spatial visualization intelligence, verbal–auditory intelligence, auditory–tactile memory, nonvisual information processing, nonverbal–tactile reasoning, emotional–social intelligence, executive functions, adaptive and practical intelligence, musical–auditory abilities, neurological–sensory components, and methodological challenges in intelligence assessment. The results showed that some of these components overlap with the dimensions of Cattell–Horn–Carroll theory, whereas others require conceptual reinterpretation or expansion within the context of blindness. The findings also indicated that many existing instruments, due to their implicit or explicit reliance on visual processing, face limitations in construct validity, assessment fairness, and adaptation to the characteristics of individuals with visual impairment. The findings of the study suggest that intelligence assessment in blind and low-vision adolescents requires a transition from purely adaptive approaches toward evidence-based conceptual frameworks aligned with the cognitive and sensory characteristics of this group. Accordingly, Cattell–Horn–Carroll theory can provide an appropriate foundation for developing indigenous, multisensory tests free from visual bias and can facilitate more accurate assessment of the cognitive abilities of these individuals.

Comparison of Social Education Training and Brain-Based Parenting on Adaptability and Social Loneliness in Mothers of Children with Attention-Deficit/Hyperactivity Disorder

Aram Gharibi Asl iD , Zahra Yousefi ^* iD , Flor Khayatan iD

The present study aimed to compare the effects of social education training and brain-based parenting on adaptability and social loneliness in mothers of children with attention-deficit/hyperactivity disorder. This was a quasi-experimental study with a pretest–posttest and follow-up design, including two experimental groups and one control group. The statistical population consisted of all children with ADHD aged 7 to 11 years and their mothers. The statistical sample included 60 children and their mothers, who were selected through purposive sampling and randomly assigned to the experimental and control groups. While the control group was placed on a waiting list, the experimental groups received eight 90-minute sessions of social education training and brain-based parenting training. All participants were assessed before, after, and one month after the interventions using the Parenting Adaptability Questionnaire (Yousefi, 2021) and the Social Loneliness Scale developed by DiTommaso et al. (2004). Data were analyzed at two levels: descriptive statistics, including mean and standard deviation, and inferential statistics, including repeated-measures analysis of variance and Bonferroni post hoc test. The results showed that both methods had a significant effect on improving the research variables (p < .05), and no significant difference was found between the two methods. Based on these findings, it can be concluded that both methods are effective in improving psychological constructs among mothers of children with ADHD.

Inclusive Coaching : Supporting Children and Youth With Intellectual Developmental Disabilities Engaging in Sport

Justin Heenan ^* iD , Sierra Sumner iD

Special Olympics is an international movement committed to promoting inclusion and building community through sports and physical activity for individuals with intellectual disabilities. In Canada, the organization supports more than 40,000 athletes, offering structured athletic opportunities from early childhood through to adulthood. This critical literature review synthesizes 18 sources on coaching within Special Olympics, including peer-reviewed research around coaching Special Olympics, to examine trends, themes, and gaps in the field. Literature was reviewed from March 2025 to December 2025. It emphasizes the continuous, community-based nature of Special Olympics programming, which occurs regularly in local settings, rather than as infrequent high-profile events. The findings highlight both the benefits of athlete participation and the critical role of effective coaching, while also revealing a need for additional research focused on coaching practices, particularly among coaches who work with children and youth. Strengthening the evidence base in the Canadian context is essential to enhance coaching strategies, support athlete growth, support and guide future research opportunities and promote sustained success within the Special Olympics community.

Explainable Artificial Intelligence Modeling of Social Participation in Children with Intellectual Disabilities: A SHAP-Based CatBoost Analysis of Adaptive Behavior, Communication Competence, and Parental Involvement

Ayako Nishimura iD , Ágnes Tóth ^* iD

The present study aimed to develop and interpret an explainable artificial intelligence model of social participation in children with intellectual disabilities by examining the predictive contributions of adaptive behavior, communication competence, and parental involvement using a SHAP-based CatBoost algorithm. This cross-sectional predictive modeling study was conducted among 412 children with mild to moderate intellectual disabilities aged 8–16 years who were recruited from special education schools, rehabilitation centers, and inclusive educational settings across Hungary. Social participation was assessed using the Participation and Environment Measure for Children and Youth (PEM-CY), while adaptive behavior, communication competence, and parental involvement were measured using standardized psychometric instruments. Following data preprocessing and screening procedures, a CatBoost machine learning model was developed to predict social participation outcomes. Model performance was evaluated using the coefficient of determination (R²), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). To enhance interpretability, SHapley Additive exPlanations (SHAP) analyses were conducted to determine the relative importance and direction of predictor contributions. Pearson correlation analyses demonstrated significant positive associations between social participation and adaptive behavior (r = .781, p < .001), communication competence (r = .724, p < .001), and parental involvement (r = .647, p < .001). The CatBoost model exhibited excellent predictive performance, explaining 89.2% of the variance in social participation within the test dataset (R² = .892), with RMSE = 4.97, MAE = 3.89, and MAPE = 5.84%. SHAP analyses identified adaptive behavior as the strongest predictor of social participation (42.7% relative importance), followed by communication competence (32.8%) and parental involvement (19.7%). Together, these three variables accounted for more than 95% of the model’s total explanatory influence. Furthermore, SHAP dependence analyses revealed nonlinear interactions, indicating that the positive effects of adaptive behavior became increasingly pronounced at higher levels of communication competence and parental involvement. The findings demonstrate that social participation among children with intellectual disabilities is primarily influenced by adaptive behavior, communication competence, and parental involvement. The SHAP-based CatBoost model provided highly accurate and interpretable predictions, highlighting the value of explainable artificial intelligence for understanding participation outcomes in developmental disability research. These results support the development of family-centered and skills-focused interventions aimed at enhancing social inclusion and community participation among children with intellectual disabilities.

Comparison of the Effectiveness of Transcranial Direct Current Stimulation and Cognitive Emotion Regulation Training on Impulsivity in Adults with Attention-Deficit/Hyperactivity Disorder

Yasaman Samiee iD , Zahra Sadin iD , Shiva Haghinomandan iD , Fatemeh Haghi Nomandan iD , Farshad Samadi ^* iD

https://doi.org/10.61838/kman.prien.5568

This study was conducted to compare the effectiveness of two non-invasive interventions, namely transcranial direct current stimulation (tDCS) and cognitive emotion regulation training, in reducing impulsivity among adults with Attention-Deficit/Hyperactivity Disorder (ADHD). The study employed a quasi-experimental design with a pretest–posttest control group. A total of 45 adults diagnosed with ADHD were selected through convenience sampling and randomly assigned to three groups of 15 participants each: a transcranial direct current stimulation group, a cognitive emotion regulation training group, and a control group. The transcranial direct current stimulation group received anodal stimulation over the left dorsolateral prefrontal cortex (DLPFC) at an intensity of 2 mA for 20 minutes across 10 sessions. The cognitive emotion regulation training group participated in 10 sessions of 90 minutes each, receiving cognitive emotion regulation training based on standardized protocols. The control group was placed on a waiting list. Data were collected using the Barratt Impulsiveness Questionnaire and the ADHD Impulsivity Scale during the pretest and posttest phases. Data were analyzed using analysis of covariance (ANCOVA) in SPSS version 26. The results of the ANCOVA indicated that, after controlling for pretest effects, significant differences existed among the groups in posttest impulsivity scores. Pairwise comparisons revealed that both transcranial direct current stimulation and cognitive emotion regulation training significantly reduced overall impulsivity and its subscales (motor impulsivity, cognitive impulsivity, and non-planning impulsivity) compared with the control group. Furthermore, cognitive emotion regulation training produced greater reductions in impulsivity scores than transcranial direct current stimulation, particularly in the cognitive impulsivity subscale. Based on the findings, both transcranial direct current stimulation and cognitive emotion regulation training are effective approaches for reducing impulsivity in adults with ADHD. However, cognitive emotion regulation training demonstrated greater effectiveness due to its influence on the cognitive-emotional mechanisms associated with impulsivity.

CatBoost Prediction of Social Anxiety Among Students with Specific Learning Disabilities: Contributions of Rejection Sensitivity, Self-Compassion, and Peer Victimization

Eirik Solheim iD , Valentina Rojas ^* iD , Lucía Bentancor iD

https://doi.org/10.61838/kman.prien.5423

The present study aimed to develop and evaluate a CatBoost machine learning model for predicting social anxiety among students with specific learning disabilities based on rejection sensitivity, self-compassion, and peer victimization, while determining the relative contribution of each predictor to model performance. This cross-sectional predictive study was conducted among 428 students with specific learning disabilities enrolled in secondary schools in Santiago, Chile. Participants completed standardized measures assessing social anxiety, rejection sensitivity, self-compassion, and peer victimization. Following data preprocessing and preliminary statistical analyses, a CatBoost machine learning algorithm was implemented to predict social anxiety levels. The dataset was divided into training (80%) and testing (20%) subsets, and hyperparameter optimization was performed using five-fold cross-validation. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Feature importance analysis and SHAP (Shapley Additive Explanations) values were calculated to identify the relative influence and directional effects of the predictors. The CatBoost model demonstrated strong predictive performance, accounting for 81.2% of the variance in social anxiety scores within the testing dataset (R² = .812). The model yielded low prediction errors (RMSE = 5.08, MAE = 3.94, MAPE = 8.46%), indicating high accuracy and generalizability. Feature importance analysis revealed that rejection sensitivity was the strongest predictor of social anxiety (41.82%), followed by peer victimization (34.67%) and self-compassion (23.51%). SHAP analyses showed that higher levels of rejection sensitivity and peer victimization were associated with increased social anxiety, whereas higher self-compassion was associated with lower social anxiety. Correlational analyses further indicated significant positive associations between social anxiety, rejection sensitivity, and peer victimization, alongside a significant negative association between social anxiety and self-compassion. The findings demonstrate that social anxiety among students with specific learning disabilities is strongly influenced by interpersonal vulnerability factors and psychological resilience resources. Rejection sensitivity and peer victimization represent significant risk factors, whereas self-compassion serves as an important protective factor. CatBoost modeling provides an effective and interpretable approach for identifying students at risk and may support the development of targeted school-based prevention and intervention programs aimed at improving emotional well-being and social functioning.

A LightGBM Analysis of Emotional Well-Being in Children with Autism Spectrum Disorder: Predictive Contributions of Sensory Sensitivity, Parent–Child Attachment, and Social Competence

Elīna Ozoliņa iD , Nomvula Dlamini ^* iD , Mercy Atieno iD

https://doi.org/10.61838/kman.prien.5442

The present study aimed to investigate the predictive contributions of sensory sensitivity, parent–child attachment, and social competence to emotional well-being among children with Autism Spectrum Disorder (ASD) using a Light Gradient Boosting Machine (LightGBM) model and explainable artificial intelligence techniques. This cross-sectional predictive study was conducted among 428 children diagnosed with Autism Spectrum Disorder in South Africa. Emotional well-being served as the target variable, while sensory sensitivity, parent–child attachment, and social competence were entered as predictor variables. Data were collected using standardized caregiver-report instruments with established psychometric properties. After preliminary data screening and preprocessing, the dataset was randomly divided into training and testing subsets using an 80:20 ratio. A LightGBM algorithm was implemented to develop the predictive model, and hyperparameter optimization was performed through five-fold cross-validation. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean squared error (MSE). Feature importance analysis and Shapley Additive Explanations (SHAP) were employed to determine the relative contribution and direction of influence of each predictor variable. The LightGBM model demonstrated strong predictive performance, explaining 82.1% of the variance in emotional well-being within the testing dataset (R² = 0.821). Correlation analyses revealed significant positive associations between emotional well-being and both parent–child attachment (r = 0.68, p < .01) and social competence (r = 0.74, p < .01), whereas sensory sensitivity was significantly negatively associated with emotional well-being (r = −0.61, p < .01). Feature importance analysis indicated that social competence was the most influential predictor (39.8%), followed by parent–child attachment (33.3%) and sensory sensitivity (26.9%). SHAP analyses confirmed these findings, demonstrating that higher levels of social competence and stronger parent–child attachment increased predicted emotional well-being, whereas elevated sensory sensitivity reduced emotional well-being predictions. The findings indicate that emotional well-being among children with ASD is strongly shaped by social, relational, and sensory factors. Social competence emerged as the most influential predictor, highlighting the importance of adaptive social functioning for positive emotional outcomes. Secure parent–child attachment also contributed substantially to emotional well-being, while sensory sensitivity functioned as a significant risk factor. The high predictive accuracy of the LightGBM model demonstrates the value of machine learning approaches for identifying key determinants of emotional well-being and supports the development of targeted interventions focusing on social skills enhancement, family relationships, and sensory regulation to improve psychological outcomes among children with ASD.

Psychological Research in Individuals with Exceptional Needs

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The Mediating Role of Self-Efficacy and Social Support in the Effect of Psychological Hardiness on the Quality of Life of Physically Disabled People

Psychometric Properties of the Persian Version of the Autism Social Skills Profile

The Relationship Between the School Social-Emotional Climate and Student Bullying Through the Mediating Variable of Alexithymia

The Mediating Role of Islamic Lifestyle in the Relationship Between Social Media Use and Sleep Disorder with Academic Achievement

The Effectiveness of Problem-Solving Training on Coping Behavior and Academic Adjustment in Students with Learning Disabilities

The Relationship of Responsibility, Self-Esteem, and Peer Interaction with Perceived Social Competence in Gifted Students

Comparison of the Effectiveness of Mindfulness Intervention and Perceptual–Motor Games on Attention Problems in Students with Attention-Deficit/Hyperactivity Disorder

CatBoost Prediction of Social Anxiety Among Students with Specific Learning Disabilities: Contributions of Rejection Sensitivity, Self-Compassion, and Peer Victimization

A LightGBM Analysis of Emotional Well-Being in Children with Autism Spectrum Disorder: Predictive Contributions of Sensory Sensitivity, Parent–Child Attachment, and Social Competence

Machine Learning Prediction of Vocational Success Among Young Adults with Intellectual Disabilities: The Roles of Self-Determination, Career Adaptability, and Family Empowerment

Comparison of the Effectiveness of Transcranial Direct Current Stimulation and Cognitive Emotion Regulation Training on Impulsivity in Adults with Attention-Deficit/Hyperactivity Disorder

Machine Learning–Based Prediction of Reading Comprehension Deficits from Attention Control, Processing Speed, Phonological Awareness, and Academic Anxiety in Children with Dyslexia

Effectiveness of Rational Emotive Behavior Therapy on Oppositional Defiant Disorder and Sexual Deviance in Working Children

The Effectiveness of Schema Therapy on Loneliness and Hope for Life in Mothers of Children with Autism

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The Curriculum Content of a Metacognition-Based Program for Reducing Learning Disorders Among Elementary School Students

A Comparative Examination and Analysis of Conceptual Frameworks and Intelligence Assessment Instruments in Blind and Low-Vision Adolescents: Challenges, Approaches, and Requirements

Comparison of Social Education Training and Brain-Based Parenting on Adaptability and Social Loneliness in Mothers of Children with Attention-Deficit/Hyperactivity Disorder

Inclusive Coaching : Supporting Children and Youth With Intellectual Developmental Disabilities Engaging in Sport

Explainable Artificial Intelligence Modeling of Social Participation in Children with Intellectual Disabilities: A SHAP-Based CatBoost Analysis of Adaptive Behavior, Communication Competence, and Parental Involvement

Comparison of the Effectiveness of Transcranial Direct Current Stimulation and Cognitive Emotion Regulation Training on Impulsivity in Adults with Attention-Deficit/Hyperactivity Disorder

CatBoost Prediction of Social Anxiety Among Students with Specific Learning Disabilities: Contributions of Rejection Sensitivity, Self-Compassion, and Peer Victimization

A LightGBM Analysis of Emotional Well-Being in Children with Autism Spectrum Disorder: Predictive Contributions of Sensory Sensitivity, Parent–Child Attachment, and Social Competence