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Record W4221120058 · doi:10.1176/appi.pn.2022.04.4.42

What Do IMGs Need and How Can They Be Supported?

2022· article· en· W4221120058 on OpenAlexaboutno aff
Michael Myers, Edmond H. Pi

Bibliographic record

VenuePsychiatric News · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthSession (web analytics)Library scienceTable of contentsPsychologyQuarter (Canadian coin)Medical educationMedicinePsychiatryHistory

Abstract

fetched live from OpenAlex

Back to table of contents Previous article Next article Annual MeetingFull AccessWhat Do IMGs Need and How Can They Be Supported?Michael Myers, M.D., Edmond H. Pi, M.D.Michael MyersSearch for more papers by this author, M.D., Edmond H. PiSearch for more papers by this author, M.D.Published Online:25 Mar 2022https://doi.org/10.1176/appi.pn.2022.04.4.42AbstractInternational medical graduates are the backbone of psychiatry, and have experiences and needs that differ from their U.S. counterparts.International medical graduates (IMGs) comprise a quarter of the physicians and a third of the psychiatrists in the United States. More than a fourth of psychiatry trainees are IMGs. What’s more is that IMGs are the lifeblood of our mental health system, particularly in the public sector. Every year the Annual Meeting showcases excellent programming by and for IMGs (and for the many, interested others), and this year is no exception. We are excited to highlight here four standout sessions:The IMG Journey: Snapshots Across the Professional Lifespan (May 21, 8 a.m.-9:30 a.m.)In this highly interactive session, Vishal Madaan, M.D., Muhammad Zeshan, M.D., Naziya Hassan, M.D., and Consuelo C. Cagande, M.D.—who range in their careers from a resident to senior professor—will cover themes of acculturation, mentor-mentee relationships, supervision, unique issues in psychotherapy, career trajectories, and much more.International Medical Graduates and the Care of Older Adults With Mental Health Disorders in the United States (May 22, 1:30 a.m.-3 p.m.)Although IMGs make up almost half of the workforce of geriatric psychiatrists in this country, our population is aging, and more trained geriatric psychiatrists are sorely needed. In this session, Rajesh R. Tampi, M.S., M.D., will review the roles of IMGs as private practitioners, educators, academicians, and researchers and talk about ways APA can work to attract more IMGs into the geriatric field.Supporting IMGs Throughout Their Careers (May 24, 10:30 a.m.-noon)Since the pandemic began, IMGs are reporting disproportionate rates of burnout and dying by suicide at higher rates than ever before. They often do not receive the same resources as domestic psychiatrists. In a small group discussion with APA CEO and Medical Director Saul Levin, M.D., M.P.A., and early career psychiatrist and APA Scientific Program Committee member Elie Aoun, M.D. IMGs will have an opportunity to discuss the unique challenges they face and brainstorm ways in which APA might be able to assist.Double Minorities: Exploring Systemic Barriers Against Non-U.S. International Medical Graduates in Academic Psychiatry (May 25, 1:30 p.m.-3 p.m.)Chair Ramotse Saunders, M.D., and presenters Muniza A. Majoka, M.B.B.S., and Ali Maher Haidar, M.D., will review general stresses for IMGs but also specific issues for women and members of racial/ethnic minorities and the LGBTQ community. They invite attendees to engage with them in a far-ranging discussion to facilitate and foster academic careers for IMGs including peer and intergenerational mentoring, ally training, implicit bias training, and anti-racism/sexism initiatives.We hope to see you at APA’s Annual Meeting in May! Please join us as we celebrate IMGs’ successes through the years and identify ways that APA can better support them. ■Michael Myers, M.D., is a professor of clinical psychiatry at SUNY Downstate Health Sciences University in Brooklyn, N.Y.Edmond H. Pi, M.D., is professor emeritus of clinical psychiatry at the University of Southern California Keck School of Medicine. Both are members of APA’s Scientific Program Committee. ISSUES NewArchived

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.381
Teacher spread0.346 · 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 designNot applicable
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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