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Record W2136785006 · doi:10.36834/cmej.36548

Developing a Program to Promote Stress Resilience and Self-Care in First Year Medical Students

2011· article· en· W2136785006 on OpenAlexvenueno aff
Suzie Thomas, Myra Haney, Chris Pelic, Darlene Shaw, Jeffrey G. Wong

Bibliographic record

VenueCanadian Medical Education Journal · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsAttendancePresentation (obstetrics)Medical educationSession (web analytics)Psychological resilienceResilience (materials science)PsychologyMedical schoolMental healthMedicineFamily medicineComputer scienceSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Facilitating stress resilience in future physicians is an important role of medical educators and administrators. We developed an extracurricular program and pilot tested the program on first year medical students. METHODS: Presentations on topics related to mental health, help-seeking, and stress resilience were presented (one topic per session). Attendance was voluntary. Attendees were requested to complete anonymous evaluations following each presentation. Primary outcome variables were rates of agreement that the presentation (1) was interesting, (2) provided valuable information, and (3) provided information relevant for the student's future practice as a physician. RESULTS: Each of the seven topics was attended on average by approximately half of the student body. Evaluations were very positive that presentations were interesting and provided information useful to maintaining balance during medical school (all had ≥85% rates of agreement). Evaluations by students were variable (41%-88% rates of agreement) on whether each presented information relevant for future practice. CONCLUSIONS: The results support that first-year medical students value explicit guidance on ways to bolster stress resilience and self-care during medical school. It is important to clarify with each presentation how the information is relevant to their future practice as a physician.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.309
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
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 integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.042
GPT teacher head0.451
Teacher spread0.408 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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