Is ChatGPT safe for kids?

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1. 1

   ChatGPT (Wikipedia)

   WikipediaPublished Oct 10, 2026Checked Oct 10, 2026

   “ChatGPT is a generative AI chatbot developed by OpenAI. Originally released on November 30, 2022, the product uses large language models—specifically generative pre-trained transformers (GPTs)—to generate text, speech, and images in response to user prompts. ChatGPT accelerated the AI boom, an ongoing period marked by rapid investment and public attention toward the field of artificial intelligence (AI). OpenAI operates the service on a freemium model. Users can interact with ChatGPT through text, audio, and image prompts. ChatGPT was quickly adopted, reaching 100 million monthly active users two months after its release and 900 million weekly active users in February 2026. Proponents say that it has the potential to transform numerous professional fields, and it has instigated public debate about the nature of creativity and the future of knowledge work. The chatbot has also been criticized for its limitations and potential for unethical use. It may generate incorrect or nonsensical answers that sound plausible, known as hallucinations. Biases in its training data have been reflected in its responses.”

2. 2

   AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults.

   JAMA pediatrics (McBain et al.)Published Aug 1, 2026Checked Oct 10, 2026

   “Among those who sought advice from AI chatbots, 42.8% did so at least monthly, and 91.7% rated the advice as somewhat or very helpful. Most adolescents reported they had not disclosed AI chatbot use for mental health advice to anyone (63.3%). Use of an AI chatbot for mental health advice was more common among females compared with males (adjusted odds ratio [aOR], 2.10; 95% CI, 1.36-3.23), respondents aged 18 to 21 years compared with respondents aged 12 to 14 years (aOR, 3.65; 95% CI, 1.98-6.74), and those who had spoken with a physician about their mental health in the prior 6 months compared with those who had not (aOR, 1.89; 95% CI, 1.18-3.03).Conclusions and relevanceIn this nationally representative survey study of US adolescents and young adults, a fifth reported using AI chatbots for mental health advice. AI chatbots are already embedded in many youths' mental health information ecosystem, underscoring the need for parents and clinicians to proactively discuss chatbot use to promote safety, appropriate expectations, and linkages to evidence-based care.”

3. 3

   A scoping review on the mental health harms of LLM-based chatbots.

   NPJ digital medicine (Diel et al.)Published Aug 20, 2026Checked Oct 10, 2026

   “N = 119 articles were included that (1) focus on LLM-based chatbots, and (2) focus on the harms of use on mental health. Literature was divided into five categories. Conceptual works mention harms based on chatbot limitations (hallucinations, sycophancy, bias), data security issues, and risks for severe or high-risk psychiatric cases (e.g., suicide, psychosis). Vignette studies show that LLM-based chatbots respond inappropriately to mental health queries compared with clinical standards. Cognitive overreliance on chatbots is associated with decreased cognitive and academic performance. Problematic use of LLM-based chatbots, marked by symptoms of emotional or social dependency and withdrawal, correlates with mental health symptoms. Articles on AI psychosis propose several potential links between delusional beliefs and LLM-based chatbot use, such as risks of chatbots reinforcing and validating delusional beliefs.This structured, integrative overview shows that theoretical and empirical work identify various hypothetical and observed harms associated with the use of LLM chatbots in mental health.”

4. 4

   How US Youth Use AI Chatbots: Conversation Patterns From Naturalistic Keystroke Observations.

   Journal of medical Internet research (Maheux et al.)Published Jul 27, 2026Checked Oct 10, 2026

   “Word counts were highest for user-app-days involving violence, followed by sexual role-play, romantic role-play, and emotional support, suggesting greater engagement when using GenAI in these ways. Co-occurrence analyses showed that tool use often appeared alone, whereas violence, sexual role-play, and romantic role-play frequently co-occurred within a user-app-day, including instances suggestive of violent sexual role-play.ConclusionsFindings suggest that youth engagement with GenAI varies substantially across users. Tool use is most common, requiring more nuanced investigation into the precise ways youth use GenAI to potentially support or thwart their development. GenAI engagement also may involve developmentally salient and potentially risky themes of sexuality, romance, and violence, especially among younger users. More research is needed that pairs GenAI engagement with psychological measures of well-being to examine the impacts of AI interactions and promote safety-focused design features.”

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   Generative AI in Youth Mental Health Apps: Rapid Review.

   JMIR mental health (Høgsdal et al.)Published Aug 19, 2026Checked Oct 10, 2026

   “The most common method of integrating generative AI into mental health apps for young people was through chatbots. Overall, young people rated the apps as having good usability and quality. Some studies also provided data on effectiveness, showing promising results for outcomes such as depression, anxiety, and distress. None of the studies systematically assessed harmful effects using standardized methods, nor did they report any adverse outcomes related to mental health.ConclusionsYoung people are generally positive about apps that include generative AI. There is some evidence suggesting that such tools may contribute to a preventive or health-promoting effect on young people's mental health. However, the existing research is limited and characterized by methodological constraints. The lack of reported adverse mental health outcomes might reflect a lack of investigation rather than evidence of no harm. Further research should explore the potential short- and long-term effects of integrating generative AI into mental health apps for young people, as well as systematically mapping possible adverse events.”

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   Generative Artificial Intelligence Use and Adolescent Mental Health.

   Current pediatrics reports (Nagata et al.)Published Sep 21, 2026Checked Oct 10, 2026

   “Problematic patterns of use, including dependency and emotional reliance, may be particularly relevant among adolescents with preexisting psychiatric vulnerabilities. Current evidence suggests that these relationships may be bidirectional: psychological distress can motivate GenAI use for companionship, emotional support, or escape, while problematic use may reinforce maladaptive beliefs, displace real-world relationships, and amplify existing vulnerabilities. However, evidence remains predominantly cross-sectional, limiting causal inference.SummaryGenAI may interact with and amplify underlying psychiatric vulnerabilities during adolescence, highlighting the importance of understanding patterns and motivations of use. Pediatricians and other clinicians caring for adolescents could consider not only the frequency of GenAI use but also motivations for use, problematic dependency, and socioemotional reliance. Identifying high-risk usage patterns of GenAI through longitudinal research, particularly among youth with preexisting psychiatric risks, may inform the development of tailored screening, intervention, and prevention strategies.”

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   Evidence and Future Directions for Pediatric Health Care Chatbots: Systematic Review.

   Journal of medical Internet research (Yang et al.)Published Sep 25, 2026Checked Oct 10, 2026

   “Health and psychosocial outcomes were mixed, often showing null findings in objective clinical metrics despite some subjective improvements. Behavioral and cognitive outcomes generally showed favorable changes but relied heavily on subjective evaluations. Although chatbots demonstrated explicit developmental tailoring, with designs shifting from caregiver-mediated approaches in early childhood to autonomous, privacy-focused platforms for adolescents, definitive conclusions regarding their robust associations with health-related outcomes cannot be drawn. This is primarily due to pervasive methodological limitations, including the lack of active comparator groups, reliance on short-term metrics, and significant study heterogeneity.ConclusionsPediatric health care chatbots are emerging across diverse health care contexts, but the current evidence remains limited and heterogeneous. This review identified developmentally relevant considerations, including caregiver involvement, age-appropriate communication, and developmental differences, that may warrant explicit attention in future chatbot design, evaluation, and implementation.”