Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterised by difficulties in communication and repetitive behaviors. The early detection of ASD is a clinical priority in education centres and medical services. COREAT is a computer adaptation of the Repetitive Behavior Scale-Revised (RBS-R) which has been designed to facilitate the diagnosis of individuals with ASD and intellectual disability. This article describes the development, an initial evaluation of the feasibility and the preliminary outcomes of COREAT. The development of COREAT consists of two phases. Phase 1: Performing a prior analysis of the psychometric properties of the RBS-R scale. Phase 2: Developing the mobile application (pilot tests, testing real cases n = 11, and final feedback). Descriptive data of the pilot study shows that 91.31% of participants indicate that COREAT is very accessible and intuitive. COREAT proves to be a useful diagnostic resource for professionals and families. Cross-cultural differences must be analysed.

Findings from a research synthesis of the relationships between family needs and parent, family, and child functioning are reported. The synthesis included 31 studies conducted in 12 different countries. The studies were conducted between 1987 and 2021 and included 4,543 participants. Eight different family needs scales or adaptations of the scales were completed by the study participants (mothers, fathers, or grandmothers of children with developmental disabilities, autism spectrum disorders, or medical conditions). The outcome measures included caregiver psychological health, parenting stress, parenting burden, parenting beliefs, family coping strategies, family functioning, family support, and child functioning. The correlations between family needs and the outcome measures were used as the sizes of effects for evaluating the strength of the relationships between measures. Results showed that unmet family needs were associated with more negative and less positive family and family member functioning and fewer unmet family needs were associated with more positive and less negative family and family member functioning. The sizes of effect for parenting stress and burden were larger than were the sizes of effects for each of the other outcome measures. Child condition and study quality moderated the relationship between family needs and parenting stress and burden but not the other outcome measures. The results are discussed in terms of one component of family systems intervention models.

This paper presents an investigation that aims to: 1) explore the relations between core symptoms of adult Attention Deficit and Hyperactivity Disorder (ADHD) and several typical Internet activities, and 2) compare the predictive power of two core symptoms of ADHD- inattention and hyperactivity/impulsivity- in predicting Internet addiction. Methods: A total of 2016 Chinese college students participated in this study. The ADHD symptoms were assessed using Conners self-rating scales and DSM-5 semi-structured interviews. Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (SCID-5) was used to exclude other psychiatric disorders. Chen’s Internet addiction scale (CIAS) was used to evaluate Internet addiction. Information about Internet activities (e.g., online gaming) was collected through a self-constructed questionnaire. Results: The ratio of Internet addiction problems among individuals with ADHD symptoms is significantly higher than in ordinary individuals (48.9% vs. 14.3%). Further, each core ADHD symptom has unique relations with different types of Internet activities. Specifically, both core ADHD symptoms are negatively associated with information downloading and online learning, and positively associated with online gaming, while online shopping is only associated with hyperactivity/impulsivity. Furthermore, both core ADHD symptoms are significant predictors of Internet addiction, especially inattention. Conclusion: College students with ADHD symptoms are at a higher risk of having Internet addiction than peers without ADHD symptoms. For individuals with ADHD symptoms and excessive online gaming and/or online shopping behaviors, the probability of having Internet addiction is even higher. These findings have important implications for identifying risk factors of Internet addiction and preventing Internet addiction in Higher Education settings.

This study was conducted to explore the five-factor structure of the Need for Closure scale on Indian samples using exploratory and confirmatory factor analysis. Data were initially collected from 450 samples which were reduced to 235 cases later based on the lie score criteria of the Need for Closure Scale. To rule out the problems caused by all questionnaire items like low reliability and low communalities, parceling of the items (creating three parcels from each facet) was done before the multivariate analysis (EFA and CFA). In the results, EFA showed that the five-factor structure of the NFC scale explains 52% of the variance. The goodness of fit statistics in the CFA model met the criteria (χ2 = 190.153, GFI = 0.908, TLI = 0.855, CFI = 0.890, RMSEA = 0.077) for the reasonable fit of the single factor structure of the NFC construct. In conclusion, this study presented the good psychometric properties of the NFC scale. It can be used to assess the individual's need for closure in the wider contexts of Indian studies.

The present study aims at identifying the relationship between social competence and the level of emotional intelligence among teachers of resource rooms for learning disabilities in Amman. The study population consisted of various educational directorates within the capital Amman governorate. They were 212 teachers – 31 males and 181 females. The sample of the study consisted of randomly chosen 60 teachers – 15 males and 45 females. They were tested first with Bar-On Model of Social and Emotional Intelligence, which is a sixty-paragraph self-assessment scale consisting of six aspects: social competence, personal competence, adaptability, stress management, general mood and positive impression. A researcher-designed social competence scale was also employed for teachers of resource rooms with learning disabilities in regular schools, which consisted of six aspects of social skills: expression of emotions, non-verbal communication, conversation, friendship, listening and participation. It has been found that there is a statistically significant positive relationship between the level of emotional intelligence and social competence in the sample of the study. In addition, there is a statistically significant relationship between the level of emotional intelligence and social competence among members of the sample due to the sex variable in favour of females.

In this study, a cluster analysis was performed by creating a data set from students' personality traits and academic procrastination behaviours. Correlation analysis was done to examine the relationship between the variables, and the characteristics of the formed clusters and the association of the clusters with the perceived socioeconomic status were examined. Cluster analysis is a simple and practical method for classifying a set of complex data based on certain variables and making them more meaningful and using the results as an aid to decision-making. Clustering algorithms handle such data effectively, making it more meaningful. Following the analysis, it was revealed that two clusters had formed. The first of the clusters includes 65.2 % of the sample population; the level of procrastination and the mean score of neurotic personality traits were calculated higher than the other cluster. The remaining part of the sample population (34.8 %) constitutes the second cluster. The mean scores of studying systematically habits and extroversion, agreeableness, conscientiousness, and openness to experience personality traits of the students forming this cluster are higher than the other cluster. No association was observed between the clusters and the perceived socioeconomic levels of the students. The distributions of socioeconomic levels within the clusters are similar to each other. When the correlations of these variables are examined; positive relationships were found between the level of procrastination and neurotic personality traits. Procrastination behaviour and neurotic personality traits were also negatively correlated with other variables.