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Record W4210720213 · doi:10.1080/08897077.2021.2010256

Impact of the International Collaborative Addiction Medicine Research Fellowship on Physicians’ Future Engagement in Addiction Research

2022· article· en· W4210720213 on OpenAlexafffund
Ján Klimas, Huiru Dong, Michee-Ana Hamilton, Walter Cullen, Jeffrey H. Samet, Evan Wood, Nadia Fairbairn

Bibliographic record

VenueSubstance Abuse · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsUniversity of British ColumbiaBritish Columbia Centre on Substance Use
FundersNational Institute on Drug AbuseCanada Research ChairsNational Institutes of HealthMichael Smith Health Research BC
KeywordsMedicineInterquartile rangeFamily medicineAddiction medicineConfidence intervalCohort studyAddictionPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Background: To evaluate how an international one-year intensive research training program for addiction medicine physicians contributed to subsequent research involvement and productivity. Methods: We prospectively compared addiction medicine physician fellows admitted to a one-year training program with non-admitted controls, using baseline questionnaire and peer-reviewed publication data. Participants’ publication activity was assessed from fellowship application date onwards using biomedical databases (e.g., PubMed, Embase). Results: Between July 2014 and June 2020, which is six years of cohorts, 56 (39 women) physicians, both fellows ( n = 25) and non-admitted applicants ( n = 31), were observed and included in the study, contributing 261 person-years of observation. At baseline, in the fellows’ cohort: 76% of participants (19/25) reported past research involvement, 24% (6/25) had one or more advanced graduate degrees (e.g., MPH), and the median number of peer-reviewed, first author publications was one (Interquartile Range [IQR] = 0–2). At baseline, in the controls’ cohort: 84% of participants (26/31) reported past research involvement, 39% (12/31) had one or more advanced graduate degrees, and the median number of peer-reviewed, first author publications was zero. The physicians’ training included internal medicine ( n = 8), family medicine ( n = 33), psychiatry ( n = 5) and others ( n = 4). At follow up, there was a significant difference between fellows ( n = 25) and controls ( n = 31) in total number of publications (Rate Ratio [RR] = 13.09, 95% Confidence Interval [CI], 5.01 − 34.21, p < 0.001), as well as first author publications (RR = 5.59, 95% CI, 2.23 − 14.06, p < 0.001). Conclusion: In the six-year observation period, fellows’ productivity indicates undertaking this fellowship was associated with significant research outputs in comparison to controls, signaling successful training of addiction physicians to help recruit addiction medicine physicians to participate in addiction research.

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)0.026
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.006
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 head0.660
GPT teacher head0.619
Teacher spread0.041 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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