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Record W2336630343

Academic and Mental Health Needs of Students on a Canadian Campus

2016· article· en· W2336630343 on OpenAlexaffvenueabout
Alexandra Robinson, Theresa M. Jubenville, Katerina Renny, Sharon L. Cairns

Bibliographic record

VenueCanadian Journal of Counselling and Psychotherapy · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMental healthAnxietyPsychologyPsychological distressPopulationCollege healthDistressMedicineFamily medicineClinical psychologyMedical educationPsychiatryEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

The focus of the current study was to examine student-identified academic and mental health concerns, the prevalence of psychological distress in the student population, student utilization of counselling services, and perceived barriers to accessing counselling services. A convenience sample of students ( N = 400) from a large university in western Canada completed a four-page questionnaire that included The General Population – Clinical Outcomes in Routine Evaluation (CORE-GP) and researcher-generated questions. Survey results indicated that 63.1% of students identified having academic concerns, 36.1% of students identified anxiety as a concern, and 31.9% endorsed depressive symptomology as a mental health concern. The criteria for clinical psychological distress were met by 42% of males and 43% of females, yet only a small portion of students identified accessing counselling services for these concerns. Students reported numerous barriers that impeded access to counselling services. Recommendations for targeting student-identified concerns and addressing potential barriers to counselling services are offered.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.043
GPT teacher head0.419
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 teacher head, not a consensus.

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

Quick stats

Citations37
Published2016
Admission routes3
Has abstractyes

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