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Record W4407754905 · doi:10.1186/s13722-025-00543-4

“We need all hands on deck”: characterizing addiction medicine training in Canada—a mixed methods study of fellowship program directors

2025· article· en· W4407754905 on OpenAlex
Clara Lu, Kathryn Chan, Leslie Martin, Nadia Fairbairn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAddiction Science & Clinical Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoMcMaster UniversityBritish Columbia Centre on Substance UseUniversity of Ottawa
FundersMichael Smith Health Research BCPeter Boris Centre for Addictions Research
KeywordsMedical educationAddiction medicineThematic analysisAccreditationWorkforceAddictionDescriptive statisticsPsychologyGovernment (linguistics)Health psychologyQualitative researchMedicineNursingPublic healthPolitical sciencePsychiatrySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Addiction Medicine training in Canada has evolved substantially in the last few years with the establishment of accreditation standards and several new fellowship programs. The novelty of these formal training programs, created in response to complex and ever-expanding clinical needs in Addiction Medicine, creates unique educational circumstances that must be understood to support future growth. This study characterizes the current state of these postgraduate training programs in Canada through the perspectives of Program Directors (PDs). METHODS: This study is a mixed methods study of 12 PDs. In Phase 1, participants completed a quantitative survey analyzed through descriptive statistics. In Phase 2, participants underwent a qualitative semi-structured interview that was coded with a thematic analysis approach. Mixing occurred both during the interim analysis between phases and during the interpretation stage. RESULTS: 28 trainees enrolled in a fellowship program in 2021-22 across 10 programs, and 27 trainees enrolled in 2022-23 across 11 programs. In each year, there were significantly fewer available spots than applications (31% and 29%, respectively). PDs identified a funding "bottleneck" as the most difficult and important challenge facing programs, with trainees supported by diverse and unstable funding sources. Qualitative analysis highlighted the need for sustainable funding models, flexibility toward alternative training pathways (shorter durations of training and re-entry from practice), and establishment of a national community of practice to support the co-creation of a robust addictions medical education infrastructure. CONCLUSION: For Addiction Medicine training to meet workforce demands, PDs stressed that funding was the challenge of prime importance. Future studies should examine the perspectives of Addiction Medicine fellows, the clinical and research impacts of fellowship graduates, and the cost-effectiveness of fellowship funding models.

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.

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)0.009
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.118
GPT teacher head0.504
Teacher spread0.386 · 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