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Record W6981624730

Étude de la consommation de substances psychoactives et de ses facteurs associés : méta-analyse des études en populations étudiantes

2022· dissertation· en· W6981624730 on OpenAlexaboutno aff

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2022
Typedissertation
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisPopulationConsumption (sociology)Socioeconomic statusMental healthPublic health
DOInot available

Abstract

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The study of the consumption of psychoactive substances in the student population is a subject that has been increasingly addressed over the past 20 years, and constitutes a concern given the changes observed in this population of young subjects at risk of long-term consequences. . However, the great heterogeneity of the studies led us to carry out a meta-analysis, with as main objective, the comparison of consumption between health sectors and other university courses, and as secondary objectives, the impact of geographical and temporal factors, as well as the determinants of mental health. The meta-analysis was carried out using 13 databases, allowing the collection of 193 articles, of which 42 met the inclusion criteria, covering the period from 1978 to 2021, from 11 countries and including 117,217 subjects. After extraction and homogenization of the results, the analysis was carried out with the Jamovi software (version 1.6.23), according to the DerSimonian-Laird random model. Different moderators of interests were assessed using meta-regressions when the number of studies was sufficient. One in five students has used a "drug" at least once in their life, with average age and smoking status appearing to be positively associated. A third of the students have used cannabis at least once in their life, the positively associated moderators being the length of the study, the United States - Canada zone and the health sector. Concerning alcohol, 1% of the students had a daily consumption, with moderators positively associated with the Tunisia-India-Lebanon zone, a younger age and the consumption of amphetamines at least once in their life. Consumption in a "binge drinking" mode concerned 21% of students, with moderators positively associated with younger age, smoking status and the health sector of studies. Regarding prescriptionals psychoactive drugs, 13% of students had taken them at least once in their life, with the negatively associated moderators being the male-female ratio, smoking status and ecstasy consumption. However, for all of these results, there was considerable heterogeneity (I2 > 75%). Only 7 studies assessed anxiety and depressive symptoms (HAD scale), more frequently when dealing with health sector's students. Anxiety scores were higher than those of depression, 4 studies including 2 concerning the health sectors indicated abnormal anxiety scores. The 7 studies evaluating the perception of stress (PSS scale) showed higher scores when it came to students from non-health sectors. This work has made it possible to make an inventory of consumption in a student environment, taking into account their evolution and their geographical differences, as well as the determinants in terms of mental health even if the latter have been have been few explored. In accordance with changes in practices, polydrug use is frequent, and smoking status would be a relevant indicator. Health students were distinguished by higher consumption, a higher level of anxiety but a lower perception of stress compared to students in other courses. However, there are biases in this analysis, among others linked to a large number of French studies, and limits linked to the heterogeneity of the indicators used, the quality and the comparability of the studies included. This work opens up prospects aimed in particular at understanding the specificities of the health sector through a study that would provide answers to the questions raised by this meta-analysis, as well as the implementation of identification actions (example of smoking status), prevention and support within the various sectors of study.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.037
GPT teacher head0.308
Teacher spread0.271 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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