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First-Aid Mental Health for the Pre-Medical Student

2023· book-chapter· en· W4390430326 on OpenAlexaff
Robert Lubin, Benjamin Katz, Michelle Marants, Mia Medney, Charles Rosin, Dean Sandler, Sophie Schonberger, Jamie R. Sharabani, Jacqueline Sherry, Gary Shteyman, Theodore Tran, E Weiss, Edward Zeltner, Matthew Zisu

Bibliographic record

VenueAdvances in higher education and professional development book series · 2023
Typebook-chapter
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsMcGill University
Fundersnot available
KeywordsMental healthAnxietyPsychologyMedical educationDepression (economics)Face (sociological concept)MedicinePsychiatrySociology

Abstract

fetched live from OpenAlex

College is intended to prepare students to become successful members of society. However, the academic demands of college can trigger stress and mental health problems. College students are in a unique position where they have to juggle academics, a social life, and, often, part-time jobs. As a result, college students are a particularly vulnerable group when it comes to stress and mental health issues. One subset of students facing the struggles of college achievements are pre-med students. Pre-med students face numerous challenges that can negatively impact their mental health. The academic pressures, financial stress, lack of social support, and relationship challenges, among others, can increase the risk of depression, anxiety, and other mental health disorders. The team of contributing authors on this chapter will address mental health in the higher education environment. This chapter will present a program for educators, peer students, and staff to provide mental health assistance for the premedical student.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.060
GPT teacher head0.465
Teacher spread0.405 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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