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The eleven-item Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-11): Cross-cultural psychometric evaluation across 42 countries

2023· article· en· W4383345473 on OpenAlexafffund
Chih‐Ting Lee, Chung‐Ying Lin, Mónika Koós, Léna Nagy, Shane W. Kraus, Zsolt Demetrovics, Marc N. Potenza, Rafael Ballester‐Arnal, Dominik Batthyány, Sophie Bergeron, Joël Billieux, Julius Burkauskas, Georgina Cárdenas‐López, Joana Carvalho, Jesús Castro‐Calvo, Lijun Chen, Giacomo Ciocca, Ornella Corazza, Rita I. Csákó, David P. Fernandez, Elaine F. Fernandez, Hironobu Fujiwara, Johannes Fuß, Roman Gabrhelík, Ateret Gewirtz‐Meydan, Biljana Gjoneska, Mateusz Gola, Joshua B. Grubbs, Hashim Talib Hashim, Md. Saiful Islam, Mustafa Ismail, Martha C. Jiménez‐Martínez, Tanja Jurin, Ondrej Kalina, Verena Klein, András Költő, Sangkyu Lee, Karol Lewczuk, Christine Löchner, Silvia López‐Alvarado, Kateřina Lukavská, Percy Mayta‐Tristán, Ionut Milea, D.J. Miller, Oľga Orosová, Gábor Orosz, Fernando P. Ponce, Gonzalo R. Quintana, Gabriel C. Quintero Garzola, Jano Ramos‐Diaz, Kévin Rigaud, Ann Rousseau, Marco de Tubino Scanavino, Marion K. Schulmeyer, Pratap Sharan, Mami Shibata, Vera Sigre‐Leirós, Luke Sniewski, Ognen Spasovski, Vesta Steiblienė, Dan J. Stein, Julian Strizek, Berk C. Ünsal, Marie‐Pier Vaillancourt‐Morel, Marie Claire Van Hout, Beáta Bőthe

Bibliographic record

VenueJournal of Psychiatric Research · 2023
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité de Montréal
FundersNational Research, Development and Innovation OfficeSistema Nacional de InvestigadoresNemzeti Kutatási, Fejlesztési és Innovaciós AlapJapan Society for the Promotion of ScienceFonds de Recherche du Québec-Société et CultureNational Cheng Kung UniversitySecretaría Nacional de Ciencia, Tecnología e InnovaciónNarodowe Centrum NaukiNarodowym Centrum NaukiUniverzita Karlova v PrazeAuckland University of Technology, New ZealandNational Research Foundation of KoreaRégion Hauts-de-FranceSmoking Research FoundationNational Social Science Fund of ChinaAgence Nationale de la RechercheNational Office for Philosophy and Social SciencesMinistry of EducationSocial Sciences and Humanities Research Council of CanadaNational Research FoundationNational Science and Technology Council
KeywordsCronbach's alphaPsychologySexual orientationConfirmatory factor analysisClinical psychologyMeasurement invarianceTest (biology)Construct validityDevelopmental psychologyPsychometricsSocial psychologyStructural equation modeling

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.192
GPT teacher head0.492
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations29
Published2023
Admission routes2
Has abstractno

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Same venueJournal of Psychiatric ResearchSame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207