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Record W1499602589 · doi:10.1300/j465v25n01_07

Family Medicine Residents’ Beliefs, Attitudes and Performance with Problem Drinkers

2004· article· en· W1499602589 on OpenAlexafffund
Meldon Kahan, Lynn Wilson, Eleanor Liu, Diane Borsoi, Joan M. Brewster, Linda C. Sobell, Mark B. Sobell

Bibliographic record

VenueSubstance Abuse · 2004
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsSt Joseph's Health CentreUniversity of TorontoCentre for Addiction and Mental Health
FundersCentre for Addiction and Mental Health
KeywordsMedicineAlcohol consumptionFamily medicineFamily historyComplaintPsychiatryClinical psychologyAlcohol

Abstract

fetched live from OpenAlex

Fifty-six second-year family medicine residents completed a survey on their knowledge and beliefs about problem drinkers. Most residents felt responsible for screening and counseling, were confident in their clinical skills in these areas, and scored well on related knowledge questions. However, only 18% felt that problem drinkers would often respond to brief counseling sessions with physicians while 36% felt that moderate drinking was a reasonable goal for patients with severe alcohol dependence. Residents were then visited by unannounced simulated patients (SPs) presenting with alcohol-induced hypertension or insomnia. Residents detected the SP in 45 out of 104 visits. In the 59 undetected SP visits, residents asked about alcohol consumption in 47 visits (80%), discussed the relationship between alcohol use and the presenting complaint in 37 visits (63%), and recommended a specific weekly consumption in 35 visits (59%). Only 31% offered reduced drinking strategies, and most did not ask about features of alcohol dependence. These results suggest that residents have the fundamental clinical skills required to manage the problem drinker who gives a clear history and is receptive to advice. Educational efforts with residents should focus on the importance of systematic screening, taking an alcohol history under more challenging conditions, identifying the subtler presentations of alcohol problems, counselling the less receptive patient at an earlier stage of change, distinguishing the problem drinker from the alcohol-dependent patient, and offering specific behavioral strategies for the problem drinker.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.265
Teacher spread0.243 · 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.

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

Citations11
Published2004
Admission routes2
Has abstractyes

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