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Record W2562906081 · doi:10.26719/2016.22.8.619

Benchmarking the health of health sciences students at Kuwait University: a towards a cultue of health

2016· article· en· W2562906081 on OpenAlexaff
Nowali Al-Sayegh, Nadia Al-Shuwai, Seham Ramadan, Tahani Al-Qurba, Saud Al‐Obaidi, Elizabeth Dean

Bibliographic record

VenueEastern Mediterranean Health Journal · 2016
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsUniversity of British Columbia
FundersKuwait University
KeywordsBiomedical sciencesMedicineHealth scienceHumanitiesMedical educationNursing

Abstract

fetched live from OpenAlex

Health professional entry-to-practice programmes are intense, competitive and prolonged. The aims of this study were to benchmark the health of health sciences students at Kuwait University, thereby informing student health services, and to establish a base for individual student's health assessments throughout the programmes. We used a convenience sample of 176 students. Assessment included a health/wellness questionnaire (smoking, nutrition, physical activity, sleep and stress) and objective measures (resting heart rate, blood pressure, waist-to-hip ratio and random blood glucose). Students had suboptimal activity, diet, stress and sleep. Health was suboptimal based on significant proportions of students in unhealthy categories for resting heart rate, blood pressure and body composition. Health status of health sciences students at Kuwait University is not consistent with healthy health professionals in training, who should serve as role models for the public. A culture of health on campus is recommended to maximize the health of students and their capacity as health role models.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.397
Teacher spread0.304 · 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 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

Citations6
Published2016
Admission routes1
Has abstractyes

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