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Record W4404587966 · doi:10.1080/07448481.2024.2431714

A cross-sectional comparison of the association between self-reported sources of stress and psychological distress among Canadian undergraduate and graduate students

2024· article· en· W4404587966 on OpenAlexaffabout
Madison MacKinnon, Brooke Linden

Bibliographic record

VenueJournal of American College Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsStressorPsychological distressClinical psychologyPsychologyAssociation (psychology)Cross-sectional studyGraduate studentsDistressCollege healthStress (linguistics)Mental healthMedicinePsychiatryFamily medicinePsychotherapist

Abstract

fetched live from OpenAlex

Objective: This study aimed to (1) descriptively compare stressors experienced by postsecondary students at the undergraduate versus graduate levels of study, and (2) evaluate the relationship between stressors and psychological distress, controlling for the effects of level of study. Participants: Undergraduate (n = 3774) and graduate (n = 889) students across 15 Canadian universities who completed the Post-Secondary Student Index electronic survey in October of 2020. Methods: Mean severity score for stressors were compared between level of study. Regression analyses evaluated the association of student specific stressors and overall stress. Results: Undergraduate students generally had higher levels of perceived stress compared to graduate students, notably in areas of academics, the learning environment, and campus culture. Multiple stressors were associated with an increase in stress; a prior mental health diagnosis was the main predictor in increased stress. Conclusions: Stressors differed between level of study. Results can inform supports, particularly regarding exams/assignments weighing and communication of expectations for institutions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.482
Teacher spread0.387 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2024
Admission routes2
Has abstractyes

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