As AI addiction research grows, knowing where to find credible, peer-reviewed studies becomes increasingly valuable. For researchers, clinicians, educators, and informed individuals, scientific databases provide access to the evidence base that should inform our understanding of AI dependency.
Key Research Databases
- PubMed: The premier biomedical literature database, housing studies on AI addiction from psychology, psychiatry, and neuroscience journals
- PsycINFO: The APA's comprehensive database of psychological literature, including technology addiction research
- Web of Science: Multi-disciplinary database capturing AI addiction research across technology studies, social science, and health
- Scopus: Large abstract and citation database with growing AI dependency literature
- Google Scholar: Broad search engine for academic literature, useful for discovering newer or less formally indexed studies
Search Strategies
Effective searches combine terms like "artificial intelligence addiction," "AI dependency," "chatbot addiction," "generative AI compulsive use," and specific platform names with behavioral terms. Using multiple databases ensures comprehensive coverage.
Evaluating Research Quality
Not all studies are equal. Prioritize peer-reviewed publications in established journals, studies with adequate sample sizes, research with clear methodology, and findings that have been replicated across multiple studies.
Staying Current
Set up alerts in databases to receive notifications when new AI addiction research is published. The field is moving quickly, and staying current ensures your understanding reflects the latest evidence.
Want well-researched resources? Visit AI Am Addicted for information grounded in current scientific research.