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Record W2026501094 · doi:10.1300/j465v29n01_04

Medical Students’ Experiences with Addicted Patients

2008· article· en· W2026501094 on OpenAlexaffabout
Deana Midmer, Meldon Kahan, Lynn Wilson

Bibliographic record

VenueSubstance Abuse · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsSt Joseph's Health CentreUniversity of Toronto
Fundersnot available
KeywordsAddictionPsychosocialAddiction medicineMedicineMedical adviceMedical schoolFamily medicinePsychologyPsychiatryMedical education

Abstract

fetched live from OpenAlex

UNLABELLED: Project CREATE was an initiative to strengthen undergraduate medical education in addictions. As part of a needs assessment, forty-six medical students at Ontario's five medical schools completed a bi-weekly, interactive web-based survey about addiction-related learning events. In all, 704 unique events were recorded, for an average of 16.7 entries per student. The most commonly discussed topic was alcohol withdrawal and the complications of alcohol use. The most common learning venues were lectures and clinical encounters in the emergency department or hospital. The proportion of advice-related topics (e.g., advice to drinkers and smokers) to advice plus non-advice related topics (e.g., medical complications) was greater for outpatient and community settings than for acute care and didactic settings (ratio 1.29, chi sq 15.85, p < 0.01). Students reacted strongly to the psychosocial impact of addictions on patients, yet they viewed addiction as a personal choice, not an illness. CONCLUSION: Medical students are not being trained to diagnose addiction or provide advice and counseling. Medical schools need to provide students with positive clinical experiences supervised by physicians experienced in addictions.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.396
Teacher spread0.356 · 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 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

Citations3
Published2008
Admission routes2
Has abstractyes

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