Evidence map›Paper›PMID 40302174›Full record

ReviewAnnals of the New York Academy of Sciences2025

The role of artificial intelligence in general, and large language models specifically, for understanding addictive behaviors.

Christian Montag, Haibo Yang, Anise M S Wu, Raian Ali, Jon D Elhai

Abstract readReview
In one paragraph

Review in Annals of the New York Academy of Sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Christian MontagDepartment of Molecular Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany.ORCID 0000-0001-8112-0837
Haibo YangAcademy of Psychology and Behavior, Tianjin Normal University, Tianjin, China.
Anise M S WuDepartment of Psychology, Faculty of Social Sciences, University of Macau, Macao, China.
Raian AliCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Jon D ElhaiDepartment of Psychology, University of Toledo, Toledo, Ohio, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) presents a general-purpose technology built into diverse products including language assistants on smartphones, recommender systems in e-commerce and social media, and applications in social and industrial robotics. AI became a globally discussed topic when the large language model ChatGPT was launched in November 2022. In the aftermath, scientists in the field of (online) addictive behaviors and internet use disorders have discussed which features or modalities of AI systems underlying video games or social media platforms might result in adverse consequences for users. Therefore, the present short communication sheds light on recent discussions in the realm of addictive behaviors on the eve of the coming AI wave. Furthermore, terms such as ChatGPT addiction are critically discussed and we not only theoretically explain how different AI modalities interact with governing regulation bodies such as the EU with their AI Act, but also personal/psychological factors, paving the way to unique perceived immersive design levels.

Indexed as

Artificial IntelligenceBehavior, AddictiveInternet Addiction DisorderLanguageHumansLarge Language ModelsSocial MediaVideo GamesaddictionArtificial Intelligence ActDigital Services Actinternet use disorderslarge language models

Identifiers

PMID40302174
PMCPMC12220279

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.