Evaluation of the psychometric indicators of the Comprehensive Autistic Trait Inventory in Iranian adults

Network Analysis of Core Symptoms of Internalizing and Externalizing Symptoms Among Children with Dyslexia in Saudi Arabia

Researches indicate that children with dyslexia are more likely to experience psychiatric symptoms throughout life compared to peers in the general population. Improving the classification of psychiatric symptoms in this population can be a valuable goal for strengthing therapeutic models. The current study aimed to evaluate the dynamic associations between internalizing and externalizing symptoms in children with dyslexia using network analysis. This cross-sectional study was conducted in Saudi Arabia from April to July 2024, involving 183 children aged 8-11 diagnosed with dyslexia, recruited through convenience sampling from local schools and clinics. The Child Behavior Checklist (CBCL) was utilized to assess a range of psychopathological symptoms, focusing on six clusters: affective problems, anxiety problems, somatic symptoms, ADHD symptoms, oppositional defiant problems, and conduct problems. Notably, "cries a lot" emerged as a central symptom in the affective network, while "dependent" was identified as the most pivotal symptom in the anxiety network. Centrality measures-betweenness, closeness, and strength-were employed to quantify the significance of each symptom. The findings suggest that these central symptoms may contribute to the development and persistence of psychiatric comorbidities in children with dyslexia. Interventions targeting these core symptoms could enhance psychological outcomes for this population. Overall, this study lays the groundwork for future research into tailored intervention strategies to address unique psychiatric comorbidities associated with dyslexia.

A Network Analysis of Depression and Cognitive Impairments in Fibromyalgia: A Secondary Analysis Study

INTRODUCTION

Fibromyalgia is a chronic condition often accompanied by cognitive impairments, such as difficulties with sustained attention, and emotional disturbances, particularly depression and anxiety. Understanding how these emotional and cognitive factors interact is crucial to improving treatment for fibromyalgia patients. This study aimed to investigate the network structure of these interactions, focusing on the relationship between depression, anxiety, and cognitive performance.

METHOD

A total of one hundred ten participants diagnosed with fibromyalgia completed self-reported assessments of depression and anxiety, alongside cognitive performance tests. Key measures included Continuous Performance Tasks (CPT) for impulsivity and sustained attention, the Stroop Interference Index (StI), Stroop Color Naming (StC), and Stroop Word Reading (StW). Network analysis was conducted to estimate the relationships between emotional and cognitive variables and assess their centrality within the network.

RESULTS

Errors in CPT emerged as the most significant indicators of the relationship between depression and cognitive performance, with high centrality values observed for the Stroop tasks (StI, StC, and StW). Additionally, Trait Anxiety (A_T) and Beck Depression Inventory (BDI) measures showed high centrality, underscoring the critical role of emotional states in the network of cognitive and emotional variables. The centrality values for cognitive flexibility, processing speed, and inhibitory control were found to be 0.85, 0.78, and 0.72, respectively.

CONCLUSION

This study highlights the strong association between depression symptoms and deficits in cognitive domains, emphasizing the need for integrated care approaches that address both cognitive and emotional health. Multidisciplinary treatment programs, including cognitive rehabilitation and psychological support, could improve patient outcomes by targeting the most influential variables in the cognitive-emotional network.

The mediating role of psychological well-being in the relationship between the light triad of personality and sense of concordance with treatment adherence in patients with type 2 diabetes: A network analysis and structural equation modeling study

BACKGROUND

This study aimed to investigate the intricate relationship among treatment adherence, the light triad of personality, self-coherence, and psychological well-being in individuals diagnosed with Type 2 Diabetes Mellitus (T2DM). Structural equation modeling (SEM) was employed to elucidate the direct and mediated pathways linking these variables, while network analysis sought to identify and characterize the underlying factors of the light triad of personality within the context of T2DM management.

METHOD

A path analysis-network analysis study using convenience sampling was conducted, recruiting 412 T2DM patients from ten private practices and general hospitals in Gilan province, Iran. Data collection utilized Antonovsky's Self of Coherence scale (SOC), The Light Triad Rating Scale, and The Reef's Psychological Well-being Questionnaire. Structural equation modeling assessed model fitness and determined direct and indirect links between variables. Analysis was conducted using R-Studio software (Version 4.2.1), SPSS (V.26), and AMOS software (V.24).

RESULTS

Confirmatory factor analysis and network analysis confirmed the three-factor structure of the Light Triad of Personality scale. Direct impacts of Light Triad of Personality (β = 0.34, p < .001) and self-coherence (β = 0.32, p < .001) on treatment adherence were observed. Psychological well-being played an indirect role in this relationship, with significant effects from Light Triad of Personality (β = 0.25, p < .001) and self-coherence (β = 0.08, p < .001) on treatment adherence. Bootstrapped exploratory graph analysis revealed an average of 3 dimensions within the network, indicating community structures.

CONCLUSION

SEM analysis demonstrated good model fit, suggesting the importance of designing interventional programs incorporating self-coherence and psychological well-being frameworks to enhance treatment adherence in T2DM patients.

Psychometric Properties of the Principal Instructional Leadership Scale (PILS) in Saudi Arabia

BACKGROUNDS

The principal instructional leadership describes how school principals oversee the curriculum, instruction, and assessment. The main aims of the current study were translation and evaluation of the psychometric properties of the Principal Instructional Leadership Scale (PILS) in a Saudi Arabian population.

METHODS

The translation and cross-cultural adaptation process has been conducted in five stages, including forward translation, translation synthesis, backward translation, expert committee, and pilot testing. Face, content, construct, and convergent validity were used to establish validity. Cronbach's alpha coefficient and McDonald's omega (Ω) were used for internal consistency.

RESULTS

To validate the PILS structure, the total sample (N = 724) was randomly split into two subgroups, each comprising 362 individuals, for Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis (EFA). Five factors obtained from EFA explain 71.07 % of the variance in PILS. The PILS encompasses domains of improving curriculum quality, teaching, and enhancing the effectiveness of adaptive learning, adding to the dimensions covered by previous instructional leadership measures. The five components show strong internal consistency (0.93 to 0.97). Both first-order and second-order CFAs confirmed the 5-factor model, meeting criteria (CFI > 0.91, GFI > 0.9, IFI > 0.9, RMSEA<0.05). All 21 items displayed suitable internal consistency (Cronbach's α > 0.8, McDonald's omega >0.7). Second-order average variance extracted validity (0.50) indicated PILS validity. Gender invariance analysis revealed no significant differences (∆CFI < 0.01, ΔRMSEA<0.01) in PILS structure between genders.

CONCLUSION

The reliability and validity of the Arabic rendition of PILS are commendable, making it suitable for evaluating principal instructional leadership in Saudi Arabia.

Psychometric properties of the Persian version of the Reinforcement Sensitivity Theory Personality Questionnaire (RST-PQ)

BACKGROUND

The Reinforcement Sensitivity Theory of Personality Questionnaire (RST-PQ) originated from the Revised Reinforcement Sensitivity Theory of Personality. This study was conducted to assess the psychometric properties of the Persian version of the RST-PQ among a group of Iranian adults.

METHOD

The cross-sectional study was carried out among 600 Iranian adults utilizing a convenient sampling method, following specific participant selection criteria to enhance the study methodology's transparency (including the age range between 18 and 35 years' participants without major psychiatric diagnoses). Participants completed both the Iranian version of the Reinforcement Sensitivity Theory Personality Questionnaire (RST-PQ) and the Five-Factor NEO-FFI questionnaire. Confirmatory factor analysis, employing the multiple indicators model (MIMIC) approach, was utilized in this study to control for demographic variables such as age and gender.

RESULTS

The confirmatory factor analysis results showed an acceptable fit of the proposed six-factor model based on the English version of RST-PQ (CFI = 0.905; RMSEA = 0.053). Also, Cronbach's alpha values confirmed the internal consistency of the proposed structure. In addition, competing models were also used to select the best-proposed model. In this way, different models were evaluated, assuming a change in the correlation intensity between BIS and the Fight-Flight-Freeze System (FFFS).

CONCLUSIONS

The convergent validity results with the Five-Factor Personality measure provided further support and were consistent with previous research findings. It is crucial to have an Iranian-language version of the RST-PQ to promote RST research and show how this theoretical framework aids in explaining and predicting various actions, whether they are abnormal or healthy.