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Record W4294539320 · doi:10.32674/jis.v13i3.3148

International Graduate Students’ Mental Health Diagnoses, Challenges, and Support

2022· article· en· W4294539320 on OpenAlexaffabout
Kathleen Clarke

Bibliographic record

VenueJournal of International Students · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsMental healthGraduate studentsPsychologyStressorMedical educationInternational studiesClinical psychologyMedicinePsychiatryPolitical science

Abstract

fetched live from OpenAlex

Although there is a growing body of research that suggests the mental health of graduate students differs from that of their undergraduate counterparts, studies examining international students at the graduate level are scarce. This study therefore compares mental health diagnoses, challenges and stressors experienced, and use of mental health support, of international and non-international students who identified as being graduate/professional students. Data from the 2019 Canadian National College Health Assessment were used to compare the international graduate students (n = 1,876) to their non-international peers (n = 4,809). Significant differences were found on prevalence of conditions, certain specific challenges that are experienced, and help-seeking behaviours. Overall, international and non-international students may experience similar challenges, but international students are less likely to seek support. The findings suggest a need for graduate advisors and student affairs professionals to recognize the unique experiences of international graduate students particularly with their help-seeking behaviours.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
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 head0.119
GPT teacher head0.496
Teacher spread0.377 · 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

Citations9
Published2022
Admission routes2
Has abstractyes

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