Pleiotropic modulation of the gut-brain-lung axis by ketamine and its enantiomers.

The rapid development of artificial intelligence (AI) technologies, particularly large language models (LLMs), has created new opportunities for health information dissemination and patient or caregiver education. LLMs such as ChatGPT, Google Gemini, and DeepSeek have become widely accessible to the public, enabling individuals to seek medical guidance outside of traditional clinical settings. Beyond information generation, AI‐based approaches including machine learning algorithms have also shown promise in supporting diagnostic classification in child and adolescent psychiatry, such as differentiating patients with major depressive disorder from healthy controls based on neurocognitive profiles (Saglam et al. ). This change has significant implications for mental health, where timely access to accurate information can be critical for early intervention and family support. Anorexia nervosa (AN) is a severe psychiatric disorder of childhood and adolescence associated with substantial psychiatric and medical morbidity. Lifetime prevalence has been estimated at up to 3.6% in women and 0.3% in men, and only about two‐thirds of affected individuals achieve long‐term recovery (Hebebrand et al. ). Recent evidence also indicates a marked increase in inpatient treatment rates for AN during the COVID‐19 pandemic, highlighting the disorder's sensitivity to environmental factors and the importance of timely recognition at the family level (Hebebrand et al. ). Early‐onset presentations introduce additional diagnostic challenges, as younger children may exhibit distinct clinical characteristics and evidence guiding age‐specific assessment and treatment for this population remains limited (Ayrolles et al. ). Even diagnostic thresholds, such as the ICD‐11 recommendation that AN‐related underweight be considered in relation to the fifth body mass index percentile for age, may be difficult for parents without clinical training to interpret. As a result, parents often occupy a critical but demanding role as first‐line observers of early warning signs, while their recognition of illness may be hindered by limited mental health literacy, stigma, and restricted access to specialized services. Parents frequently use online resources when trying to understand their children's health problems. A systematic review evaluating 33 studies indicated that parents worldwide are heavy consumers of online health information for their children across highly diverse circumstances (Kubb and Foran ). Importantly, many parents did not routinely discuss the information they found with physicians and expressed a need for more guidance in identifying trustworthy resources (Kubb and Foran ). This pattern is particularly relevant in the field of child and adolescent mental health. A qualitative study involving parents of children with ADHD reported that online searches and social media communities played a central role in shaping parents' understanding of the diagnosis, navigating the care pathway, and managing differing professional perspectives (Bringer et al. ). Together, these findings establish that parents do not passively consume online health information; rather, they actively integrate it into their help‐seeking decisions in ways that can either facilitate or delay access to appropriate care. In conditions such as AN, where delayed recognition may lead to prolonged illness duration and serious medical complications, the quality of information obtained from digital sources may have important clinical implications.