Digital dependence and Artificial Intelligence: implication on mental health information use and seeking behavior
1
Library Services, Southern Connecticut State University, New Haven, United States
2
Public Health, Southern Connecticut State University, New Haven, United States
3
Information & Library Science, Southern Connecticut State University, New Haven, United States
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
BACKGROUND:
Artificial intelligence (AI)–driven conversational agents are increasingly accessed for seeking health information, emotional support, and advice. Recent reports of self-harm following interactions with AI chatbots have drawn attention to risks associated with digital dependence and unmoderated information environments. These incidents highlight emerging challenges related to the ways individuals seek mental health information through AI systems, the vulnerabilities that arise when digital agents mediate help-seeking behavior, and the absence of protective safeguards for users particularly, young populations. Understanding these dynamics is essential for informing public health responses and information governance efforts.
METHODS:
Qualitative content analysis was conducted on nine news reports published between 2024-2025 by The Guardian, BBC, CNN, and CBS News. Articles were selected based on documented involvement of AI chatbots in self-harm or suicide cases. Multiple reports on the same incident were combined to strengthen case accuracy and completeness. These were treated as single cases, and inductive thematic coding was used to identify patterns in information-seeking behavior, emotional dependence on AI, system design gaps, and responsibility narratives.
RESULTS:
Two primary case clusters were identified: (1) Character.AI interactions characterized by immersive and emotionally charged dialogues, and (2) ChatGPT-related incidents in which parents alleged that harmful AI-generated responses influenced youth behavior. Across all reports, strong emotional projection onto chatbots, reliance on AI for sensitive mental health information, and limited awareness of algorithmic constraints were consistent. Media accounts emphasized deficiencies in crisis-response mechanisms, lack of youth-oriented safeguards, and broader digital-literacy gaps that may exacerbate harm. Conclusion. AI-mediated mental health information seeking presents an emerging public-health and information-governance challenge. There is the need for coordinated interventions involving public health systems, library information professionals, and technology developers. Recommended actions include strengthening digital-health literacy, implementing crisis-response safeguards, and developing regulatory frameworks that ensure AI technologies contribute to, rather than compromise, mental well-being.
Artificial intelligence (AI)–driven conversational agents are increasingly accessed for seeking health information, emotional support, and advice. Recent reports of self-harm following interactions with AI chatbots have drawn attention to risks associated with digital dependence and unmoderated information environments. These incidents highlight emerging challenges related to the ways individuals seek mental health information through AI systems, the vulnerabilities that arise when digital agents mediate help-seeking behavior, and the absence of protective safeguards for users particularly, young populations. Understanding these dynamics is essential for informing public health responses and information governance efforts.
METHODS:
Qualitative content analysis was conducted on nine news reports published between 2024-2025 by The Guardian, BBC, CNN, and CBS News. Articles were selected based on documented involvement of AI chatbots in self-harm or suicide cases. Multiple reports on the same incident were combined to strengthen case accuracy and completeness. These were treated as single cases, and inductive thematic coding was used to identify patterns in information-seeking behavior, emotional dependence on AI, system design gaps, and responsibility narratives.
RESULTS:
Two primary case clusters were identified: (1) Character.AI interactions characterized by immersive and emotionally charged dialogues, and (2) ChatGPT-related incidents in which parents alleged that harmful AI-generated responses influenced youth behavior. Across all reports, strong emotional projection onto chatbots, reliance on AI for sensitive mental health information, and limited awareness of algorithmic constraints were consistent. Media accounts emphasized deficiencies in crisis-response mechanisms, lack of youth-oriented safeguards, and broader digital-literacy gaps that may exacerbate harm. Conclusion. AI-mediated mental health information seeking presents an emerging public-health and information-governance challenge. There is the need for coordinated interventions involving public health systems, library information professionals, and technology developers. Recommended actions include strengthening digital-health literacy, implementing crisis-response safeguards, and developing regulatory frameworks that ensure AI technologies contribute to, rather than compromise, mental well-being.
| eISSN: | 2654-1459 |
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