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Record W2012830906 · doi:10.1080/10401334.2014.945393

A Framework for Understanding International Medical Graduate Challenges During Transition Into Fellowship Programs

2014· article· en· W2012830906 on OpenAlexaffabout
Sanjeev Sockalingam, Attia Khan, Adrienne Tan, Raed Hawa, Susan Abbey, Timothy Jackson, Ari Zaretsky, Allan Okrainec

Bibliographic record

VenueTeaching and Learning in Medicine · 2014
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoHealth Sciences CentreUniversity Health Network
Fundersnot available
KeywordsMedical educationTransition (genetics)Graduate medical educationGraduate studentsPsychologyMedicineAccreditationChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Previous studies have highlighted unique needs of international medical graduates (IMG) during their transition into medical training programs; however, limited data exist on IMG needs specific to fellowship training. PURPOSES: We conducted the following mixed-method study to determine IMG fellow training needs during the transition into fellowship training programs in psychiatry and surgery. METHODS: The authors conducted a mixed-methods study consisting of an online survey of IMG fellows and their supervisors in psychiatry or surgery fellowship training programs and individual interviews of IMG fellows. The survey assessed (a) fellows' and supervisors' perceptions on IMG challenges in clinical communication, health systems, and education domains and (b) past orientation initiatives. In the second phase of the study, IMG fellows were interviewed during the latter half of their fellowship training, and perceptions regarding orientation and adaptation to fellowship in Canada were assessed. Survey data were analyzed using descriptive and Mann-Whitney U statistics. Qualitative interviews were analyzed using grounded theory methodology. RESULTS: The survey response rate was 76% (35/46) and 69% (35/51) for IMG fellows and supervisors, respectively. Fellows reported the greatest difficulty with adapting to the hospital system, medical documentation, and balancing one's professional and personal life. Supervisors believed that fellows had the greatest difficulty with managing language and slang in Canada, the healthcare system, and an interprofessional team. In Phase 2, fellows generated themes of disorientation, disconnection, interprofessional team challenges, a need for IMG fellow resources, and a benefit from training in a multicultural setting. CONCLUSIONS: Our study results highlight the need for IMG specific orientation resources for fellows and supervisors. Maslow's Hierarchy of Needs may be a useful framework for understanding IMG training needs.

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)0.028
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.007
Science and technology studies0.0190.047
Scholarly communication0.0220.023
Open science0.0050.016
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.185
GPT teacher head0.473
Teacher spread0.288 · 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 designQualitative
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

Citations32
Published2014
Admission routes2
Has abstractyes

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