Background: Mothers of children with autism spectrum disorder (ASD) often experience significant stress, which can adversely affect their quality of life (QoL) and increase their reliance on social support. This study aimed to explore the relationship between social support and QoL among mothers of ASD children and identify associated factors. Methods: A cross-sectional study was conducted from December 2022 to March 2023, involving 218 mothers of ASD children in Saudi Arabia. An online questionnaire was distributed via autism associations. Inclusion criteria were mothers of children under 18 diagnosed with ASD, excluding those with diagnosed mental illnesses. Social support and QoL were measured using the Multidimensional Scale of Perceived Social Support (MSPSS) and the Quality of Life in Autism Questionnaire (QoLA). Statistical analysis was performed using Jamovi software. Results: The mean MSPSS and QoLA scores were 4.87 and 100.88, respectively, with a significant positive correlation (Spearman’s rho = 0.509, p < 0.001). Social support was positively associated with higher education and negatively with having more than one autistic child. QoLA scores were significantly predicted by family income (>SAR 10,000 or US 2667) and MSPSS score (p < 0.001). Conclusions: Social support enhances maternal QoL and is influenced by educational level and income, highlighting the need for targeted interventions to support mothers with multiple ASD children. While individual support is important, prioritizing societal accessibility may offer more effective long-term solutions by proactively addressing systemic challenges faced by autistic individuals and their families.

Background: Mothers of children with autism spectrum disorder (ASD) face numerous challenges in meeting their children’s needs. This study aimed to assess parent-reported child behavioural and emotional outcomes and the levels of anxiety, depression, and stress among mothers of children with ASD. It also explored the correlations between parent-reported child behavioural and emotional outcomes and maternal mental health, as well as potential factors associated with these outcomes. Methods: A cross-sectional study was conducted between 30 December 2022 and 23 March 2023. An online questionnaire was distributed through autism associations across Saudi Arabia. The survey included (1) demographic data; (2) the Autism Family Experience Questionnaire (AFEQ) for children’s behavioural and emotional outcomes; and (3) the Depression, Anxiety, and Stress Scale-21 (DASS-21). Statistical analyses were performed using Jamovi software. Results: The study included 218 mothers of children with ASD. Extremely severe anxiety was reported by 41.3% of mothers, while 30.7% had normal stress and 30.7% had normal depression scores. The mean AFEQ symptom score was 37.4 ± 5.02. Univariate analysis revealed significant associations between parent-reported child behavioural and emotional outcomes and maternal mental health. In the multivariate analysis, higher family income (5000–10,000 SAR, p < 0.001; >10,000 SAR, p = 0.009) was associated with more favourable outcomes, while having more than one child with ASD was associated with less favourable outcomes (p = 0.015). Anxiety was positively associated with having two (p = 0.003) or three children (p = 0.029), while depression was negatively associated with having more than three children (p = 0.001). Conclusions: Higher family income was associated with more favourable parent-reported child behavioural and emotional outcomes, whereas having more than one child with ASD was associated with less favourable outcomes and higher maternal anxiety.

Aim: This study aimed to assess the impact of online health information and AI-based tools on treatment decisions, trust, and care-seeking behaviors among migraine patients in Arab speaking countries from MENA region. Methods: A multinational, cross-sectional online survey was conducted among 4276 adults with migraine across 13 MENA countries. Data collected included sociodemographic characteristics, migraine history, digital health literacy (eHEALS), AI tool usage, and trust in health information sources. Results: The mean eHealth literacy score was 29.9 ± 6.2. Overall, 75.6% demonstrated adequate digital health literacy. Neurologists and physicians were the most trusted sources, whereas social media influencers were the least trusted. Approximately one-third of participants reported modifying migraine treatment or delaying medical consultation based on online information. In multivariable analyses, higher trust in online information was strongly associated with delayed medical consultation (aOR 6.48, 95% CI 5.53–7.58, p < 0.001). In contrast, use of AI tools was associated with lower odds of reporting treatment modification based on online advice (aOR 0.29, 95% CI 0.17–0.49, p < 0.001). Higher trust in online information was consistently associated with both delayed care and treatment changes. Younger age, male sex, and active online information-seeking independently predicted AI use. Conclusion: Digital health engagement, including trust in online sources and AI tool use, was significantly associated with migraine-related decision behaviors in this multinational MENA cohort. While AI use was linked to more cautious treatment behaviors, higher trust in online information was associated with delayed medical consultation and treatment modification. These findings highlight the importance of strengthening digital health literacy and promoting reliable online resources.