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The rising demand for child care is putting a strain on parents of children with autism spectrum disorder (ASD), particularly the mothers. This study investigated Chinese mothers of children with ASD and examined the factors associated with maternal mental health. An online national survey was completed by the parents of 5077 ASD children and adolescents aged 0‍‒‍17 years. A total of 28.0% of the mothers reported poor mental health status. Mothers with children aged 10‍‒‍13 years had a lower chance of having poor mental health status than mothers with children aged 0‒2 years (odds ratio (OR) 0.63, 95% confidence interval (CI) 0.43‍‒‍0.91). Mothers of children with high-functioning autism were less likely to have poor mental health status than those of children with low-functioning autism (OR 0.76, 95% CI 0.62‍‒‍0.94). Having children with comorbidities was related with a higher risk of poor mental status (OR 1.56, 95% CI 1.35‒1.81), as were having conflicts with other family members (OR 1.44, 95% CI 1.22‍‒‍1.70) and providing full-time care (OR 1.22, CI 1.06‍‒‍1.41). A higher-than-average family income was associated with lower risk of having poor mental health status (OR 0.70, 95% CI 0.58‍‒‍0.82). Factors related to the children and family, and providing full-time care, have a significant effect on mothers' mental health status. Reducing obstacles to work and social interaction, as well as tackling the financial burden of raising an ASD child, may help improve the well-being of mothers.

Objective: This study explores the health information needs of individuals with autism spectrum disorder (ASD) and their caregivers in the post-COVID-19 era by analyzing discussions from Reddit, a popular social media platform. Methods: Utilizing a mixed-method approach that integrates qualitative content analysis with quantitative sentiment analysis, we analyzed user-generated content from the "r/autism" subreddit to identify recurring themes and sentiments. Results: The qualitative analysis uncovered key themes, including symptoms, diagnostic challenges, caregiver experiences, treatment options, and stigma, reflecting the diverse concerns within the ASD community. The quantitative sentiment analysis revealed a predominance of positive sentiment across discussions, although significant instances of neutral and negative sentiments were also present, indicating varied experiences and perspectives among community members. Among the machine learning models used for sentiment classification, the Bi-directional Long Short-Term Memory (Bi-LSTM) model achieved the highest performance, demonstrating a validation accuracy of 95.74%. Conclusions: The findings highlight the need for improved digital platforms and community resources to address the specific health information needs of the ASD community, particularly in enhancing access to reliable information and fostering supportive environments. These insights can guide future interventions and policies aimed at improving the well-being of autistic persons and their caregivers. [ABSTRACT FROM AUTHOR]

Objectives: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that includes abnormal communication, repetitive and limiting interests, and social dysfunction. This study aimed to identify the experiences of parents in raising children with ADS in Iran. Methods: A total of 18 parents of children with ASD were selected by purposive and convenient... [ABSTRACT FROM AUTHOR]