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Record W4413148188 · doi:10.1016/j.pmedr.2025.103210

Problematic internet use and cannabis consumption: A scoping review

2025· review· en· W4413148188 on OpenAlexafffund
Kellie-Anne Bélisle, Anne-Marie Auger, Catherine Hudon, Isabelle Dufour, Roni Deli Houssein, Rasoamiadana Volanirina Rasolofomamonjy, Magaly Brodeur

Bibliographic record

VenuePreventive Medicine Reports · 2025
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéUniversité de Sherbrooke
KeywordsCannabisThe InternetConsumption (sociology)Environmental healthMedicineInternet privacyPsychiatryComputer scienceWorld Wide WebSociology

Abstract

fetched live from OpenAlex

Objectives: As a growing body of research has linked cannabis consumption and problematic Internet use (PIU), more insight is needed to interpret this association. This scoping review aims to summarize the available literature on PIU and cannabis consumption and to underlie future avenues of research. Methods: We conducted an electronic search including all papers published from database inception until May 2023, using keywords related to PIU and cannabis use in the following databases: Academic Search Complete, APA PsychInfo, PubMed, SocINDEX, MEDLINE, CINAHL, and Psychology and Behavioral Sciences Collection. Studies eligible for this review had to meet the following criteria: (1) the primary theme had to be related to both PIU and cannabis consumption, (2) articles were published in a peer-reviewed journal, (3) articles were available in English or French, and (4) articles were not systematic reviews. Results: After screening 12,165 articles, 48 articles were retained for full-text reading and seven articles were included in this review. Conclusion: The available articles reveal a potential association between cannabis use and PIU, though operationalization heterogeneity challenges a conclusive interpretation of the results. Further research with improved measurement consistency is required to draw more robust conclusions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.433
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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