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Record W1977458213 · doi:10.1080/10550490802268223

Interpersonal Group Psychotherapy for Comorbid Alcohol Dependence and Non‐Psychotic Psychiatric Disorders

2008· article· en· W1977458213 on OpenAlexaff
Jan Malát, Molyn Leszcz, Juan Minango, Nigel E. Turner, Jane Collins, Eleanor Liu, Tony Toneatto

Bibliographic record

VenueAmerican Journal on Addictions · 2008
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of British ColumbiaMcGill University Health CentreUniversity of TorontoMount Sinai HospitalCentre for Addiction and Mental Health
Fundersnot available
KeywordsBeck Depression InventoryPsychiatryPsychiatric comorbidityInterpersonal psychotherapyGroup psychotherapyComorbidityAlcohol dependencePopulationClinical psychologyPsychologyDepression (economics)Intervention (counseling)Randomized controlled trialAlcoholMedicineInternal medicine

Abstract

fetched live from OpenAlex

Alcohol-dependent patients (N = 15) with comorbid non-psychotic psychiatric disorders were treated with Modified Interpersonal Group Therapy (MIGT) for eight weeks, 16 sessions, in a pilot intervention trial. Analysis of the group participants demonstrated that they achieved statistically significant improvements at post-treatment in four of five self-report outcome measures: number of drinking days, number of heavy drinking days, the Brief Symptom Inventory, and the Beck Depression Inventory. Furthermore, the improvements in heavy drinking days and the Brief Symptom Inventory were maintained at two and eight months post-treatment. This study yields preliminary evidence in support of MIGT as a useful treatment approach for an alcohol-dependent population with psychiatric comorbidity.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.319
Teacher spread0.299 · 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 designNon-randomized trial
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

Citations11
Published2008
Admission routes1
Has abstractyes

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