درخت حوزه‌های تخصصی

Adolescence is characterized by physical, cognitive, emotional, social, and behavioral changes capable of resulting in the development of a healthy and autonomous individual, as well as contributing to self-injurious behavior. This review aimed to analyze the 11 available papers on risk factors for self-mutilation in adolescents. Integrative review performed in MEDLINE and LILACS databases using primary studies published between 2018 and 2023, in Portuguese, English, and Spanish with the descriptors “Self-destructive Behavior”; "Adolescent"; and “Risk Factors” combined with the Boolean operator AND. After analyzing the data, two main themes emerged. The first theme, referred to as "intrapersonal risk factors," encompassed a range of categories including depression, anxiety, post-traumatic stress disorder, attention deficit hyperactivity disorder, substance/alcohol abuse, disruptive, impulse and conduct control disorders, cyclothymic-hypersensitive temperament, impulsivity, avoidance/coping-focused on affect, and emotional dysregulation. The second theme, labeled as "interpersonal risk factors," consisted of categories such as bullying, parental neglect, parental psychopathology, social exclusion, peers with people with self-destructive behavior, hetero-aggressiveness, and sexual and gender minority populations. The findings of this review highlight the importance of increased awareness, early detection, and targeted interventions for self-mutilation. This study lays the ground for future research and interventions in mental health. Future studies could further explore psychological factors, societal influences, effective treatments, and prevention methods for self-mutilation. By expanding upon current knowledge, clinicians and researchers can better support individuals struggling with self-harm, leading to improved outcomes and reduced harm.  

Abstract This study aimed to investigate the contribution of Cognitive, Emotional, and Spiritual intelligence (IQ, EQ, and SQ respectively) in explaining Problem-solving styles. To do this, 544 Iranian adults (14-80 years; 261 females and 283 males) participated in this study and were asked to answer the Problem-solving Questionnaire, Raven’s Progressive Matrices IQ Test, Bradbury-Greaves’ Emotional Intelligence Questionnaire, and the Spiritual Intelligence Questionnaire. Considering that the growth and formation of spiritual intelligence start in adolescence and will accompany a person until the end of his life, the sample of this research was selected from adolescence to adulthood. For data analysis, simultaneous multivariate regression was used, and the results showed that EQ (Emotional intelligence) and SQ (Spiritual intelligence ) were able to significantly predict the adaptive Problem-solving style (including creative Problem solving, confidence, and approach), IQ, EQ, and SQ were able to predict substantially the non-adaptive Problem-solving style (including helplessness, control, and avoidance) each person seems to be more successful in solving some problems due to the extent to which he/she uses different intelligence.  

Objective: An important cognitive control process is the ability to inhibit, that mature at different rates during childhood to adolescence. The aim of our research was to construct and validate computer-based Stroop animal size test in children for measuring selective attention and response inhibition. Research Methodology: In this survey study, we prepared the test, after the approval of experts and software development, at first test-retest reliability with a two week was evaluated in a separate sample (N=50, 5-12 years old children), then data was collected from 92 children 5-12 years old (46 girls and 46 boys) included 22 children with attention deficit/hyperactivity disorder (ADHD) studied in the academic year 2022-2023 in Alborz province. Participants decided the real size of animals by pressing response keys on computer. ANOVA, Multivariate analysis, Pearson correlation coefficients and Cronbach α were used to assess reliability and validity (p<0.05). Findings: The findings showed test-retest reliability in significant range (p<0.01). The correlation was high for Stroopnum, (r=0.83), Inconsistent answers, (r=0.72), Wrong answers, (r=0.89) but lower for Consistent answers, (r=0.28) and Reaction time, (r=0.41). To assess the internal consistency, Cronbach Alpha 0.91 computed. ANOVA analysis for comparing children's function in different age groups was (p<0.000). Conclusion: Multivariate analysis was used in comparing children with ADHD to the control group, results showed significant difference between groups in Stroop components, (p<0.007). This computerized Stroop animal size test had satisfactory reliability and validity, that can measure cognitive functions such as selective attention and inhibition in children.