Objective: This study aimed to assess the impact of reducing screen time and replacing it with social media platforms and assistive technologies on the development of social and communication skills in children with autism spectrum disorder (ASD).

Method: A total of 30 children aged 4 to 8 years with a confirmed diagnosis of ASD were selected and randomly assigned to either an experimental group (n = 15) or a control group (n = 15). Over the course of eight weeks, the experimental group engaged in activities using social media apps and assistive technologies designed to enhance communication and social skills, while the control group continued with their regular screen time activities. Pre-test, post-test, and follow-up (four-week after post-test) assessments were conducted to measure the children's progress in social and communication skills.

Results: The experimental group showed significant improvements in communication and social skills, with communication scores increasing from a pre-test mean of 21.2 (SD = 3.1) to a post-test mean of 14.1 (SD = 2.4), and maintaining at 13.9 (SD = 2.5) during follow-up. Social skills improved from a pre-test mean of 31.2 (SD = 4.0) to a post-test mean of 14.1 (SD = 3.0), remaining stable at 14.0 (SD = 3.2) at follow-up. In contrast, the control group showed minimal changes in both communication (pre-test: 20.9, post-test: 20.5, follow-up: 20.3) and social skills (pre-test: 30.9, post-test: 30.7, follow-up: 30.6). Analysis of covariance (ANCOVA) results indicated significant differences between the groups in communication (F (1, 28) = 8.47, P = 0.006, η² = 0.32) and social skills (F (1, 28) = 7.21, P = 0.010, η² = 0.28). Paired samples t-tests in the experimental group also revealed significant improvements from pre-test to post-test for both communication (mean difference = 10.21, t = 5.67, P < 0.001) and social skills (mean difference = 9.89, t = 5.43, P = 0.002), with effects maintained during follow-up.

Conclusion: These findings emphasize the potential of using social media and assistive technologies as effective tools in fostering social and communication skill development in children with ASD.

Objective: Eating disorders (EDs) are prevalent in adulthood and often originate in adolescence, influenced by various psychological factors, including childhood experiences. This research investigated how self-compassion, distress tolerance, and impulsivity function as mediators between early experiences of emotional invalidation during childhood and individuals’ eating patterns and attitudes in adulthood.

Method: The study involved 1,217 students (86.2% female), recruited through convenience sampling. Participants completed standardized questionnaires assessing eating behaviors, eating attitudes, self-compassion, distress tolerance, and impulsivity. The proposed model was tested using structural equation modeling (SEM).

Results: Impulsivity and self-compassion significantly mediated the relationship between childhood invalidation and both eating behavior (β = 0.161, P < 0.05) and eating attitude (β = 0.077, P < 0.01). Distress tolerance did not serve as a significant mediator in the model. Invalidating childhood environment was directly related to impulsivity (β = 0.303, P < 0.001) and self-compassion (β = -0.350, P < 0.001). Self-compassion and impulsivity were significant predictors of eating behavior and attitudes.

Conclusion: Childhood experiences of invalidation contribute to maladaptive eating behaviors and attitudes through the mediating roles of impulsivity and self-compassion. Notably, impulsivity had a stronger indirect effect on both outcomes compared to self-compassion. The results indicate that fostering self-compassion and managing impulsive tendencies may serve as important focal points for interventions designed to prevent or treat eating disorders.

Objective: Suicide is a global public health problem with significant adverse effects on individuals and society, especially among adolescents. Klonsky’s three-step theory (3ST) of suicide explains suicidal ideation through three factors, namely hopelessness, psychological pain, and connectedness in two steps. No study has investigated connectedness (step 2) in combination with psychological pain and hopelessness (step 1) in prediction of suicidal ideation among adolescents. Thus, we empirically tested the first two steps of the 3ST in a sample of Iranian adolescents.

Method: A total of 466 adolescents aged 12 to 20 years (356 females and 110 males) were recruited using convenience sampling. This cross-sectional study was conducted between September to November 2024. The participants completed self-report questionnaires on suicidal ideation, hopelessness, psychological pain, and connectedness. Hierarchical linear regression analysis was conducted to explore the impact of the interaction of hopelessness and psychological pain on suicidal ideation. In addition, we explored whether connectedness reduced the escalation of suicidal ideation in adolescents experiencing high psychological pain and hopelessness levels.

Results: The findings showed that the interaction of hopelessness and psychological pain accounted for 59% of the variance in suicidal ideation (P < 0.001). Connectedness was found as a protective factor for suicidal ideation in adolescents who experience high levels of both psychological pain and hopelessness (r = 0.24, P < 0.001).

Conclusion: These findings support the applicability of the first two steps of the 3ST for Iranian adolescents. Future research should examine all three steps of this theory in a clinical sample of adolescents.

Abstract

Objective: This study aimed to evaluate the effectiveness of fully automated Digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) interventions in reducing insomnia severity through a systematic review and meta-analysis of randomized controlled trials (RCTs).

Method: A systematic search was conducted across multiple databases, including PubMed, PsycINFO, Web of Science, Scopus, and Google Scholar, to identify RCTs evaluating fully automated dCBT-I. Eligible studies were included those assessing adults diagnosed with insomnia using validated criteria or scales, utilizing digital delivery platforms, and reporting quantitative insomnia severity outcomes. A meta-analysis was performed using a random-effects model, with standardized mean differences (SMDs) and 95% confidence intervals (CIs) as the primary effect measures. Subgroup and sensitivity analyses were conducted to explore sources of heterogeneity.

Results: A total of 49 RCTs involving 20,118 participants were included. Fully automated dCBT-I significantly reduced insomnia severity compared to control conditions (WMD: -3.42; 95% CI: -4.35 to -2.48; P < 0.001). Subgroup analyses revealed greater effectiveness in studies using rigorous diagnostic criteria, as well as among U.S.-based populations. Despite substantial heterogeneity (I² > 98%), sensitivity analyses confirmed the robustness of findings. Funnel plot asymmetry suggested minor potential publication bias, though Egger’s test did not confirm significant bias (P = 0.494).

Conclusion: Fully automated dCBT-I programs effectively reduce insomnia severity, offering a scalable, accessible solution to overcome barriers in traditional CBT-I delivery. However, variability in study methodologies and the predominance of studies from high-income countries highlight the need for further research. Future directions include incorporating objective sleep measures, assessing long-term outcomes, and adapting interventions to diverse cultural and economic contexts. Fully automated dCBT-I holds transformative potential for addressing insomnia on a global scale.