PARASOCIAL DEPENDENCY ASSOCIATED WITH ARTIFICIAL INTELLIGENCE CHATBOTS
Open accessAbstract
Artificial intelligence has increasingly become commonplace in everyday life without much consideration for effects outside of the commercial or academic realms. In the aftermath of the significant shifts in perception and usage of media following COVID-19 lockdown regulations, media usage rates are still significantly higher than in preceding years. Particularly, these patterns are seen in young people as they approach adulthood, whose social development was greatly impacted by strict social distancing policies. This study investigates the links between stunted social development skills, increased media usage, and the advent of individual-oriented artificial intelligence (AI) chatbots. Referenced literature highlights para-social theory, investigating the lens of self-formed attachments to distant or fictional person-adjacentfigures to fulfill existing social and emotional needs. To investigate these findings, nineteen current college-age students, in high school at the height of the COVID-19 lockdown, were individually interviewed about their AI, media, and social habits. Findings suggest that there is in fact, a correlation between difficulties socializing and increased individual media habits. This study is exploratory into a developing field and ultimately suggests further research is needed..
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Bunim interviewed 19 individuals who used LLM-CB companions during COVID-19; individuals reported difficulties socializing and increased their use.
“Bunim interviewed 19 individuals who used LLM-CB companions during COVID-19: individuals reported difficulties socializing, and increased their use131.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [131]
The available thesis-cover excerpt mentions increased media use after COVID-19 lockdowns, and the table of contents lists Method (p. 12) and Discussion (p. 23), but neither provides the study’s participant count or findings. Searches for 19 participants, interviews, difficulty socializing, and increased chatbot use returned no passage establishing the attributed account. (LLM, conf=0.72)
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A scoping review on the mental health harms of LLM-based chatbots
Diel, A., Torous, J., Cuijpers, P., Kleesiek, J., Nensa, F., Weber, N., Faust, F., Lalgi, T. J., Mellis, F. S., Teufel, M., et al. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-03054-x · Cited by 4 · see citing works
- Authors
- Bunim, E.
- Corresponding author
- Bunim, Emma
- Venue
- Zenodo
- Publisher
- Zenodo
- Published
- 2024-12-27
- OpenAlex
- W6967797922
- Cited by
- 1
- References
- 0
- Citations by year
- 2026: 1
- Type
- dissertation
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Media Influence and Health
- Keywords
- parasocial attachment, AI chatbots, social development (developmental psychology), media use, COVID-19 lockdown, social distancing, university students, high school students, social skills, emotional needs, young adults
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