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Record W4391637051 · doi:10.1080/07448481.2024.2308267

Psychological and physiological effects of an acute bout of yoga before a simulated academic exam in university students

2024· article· en· W4391637051 on OpenAlexaff
Cynthia J. Thomson, Iris Lesser, Gillian L. Hatfield

Bibliographic record

VenueJournal of American College Health · 2024
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsAnxietyHeart rate variabilityTest anxietyPsychologyClinical psychologyHeart rateCrossover studyPerceived Stress ScalePhysical therapyVisual analogue scaleMedicineStress (linguistics)Alternative medicinePsychiatryInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

Objective: Test anxiety is common among nursing students. Yoga is one form of physical activity which may be beneficial for pretest anxiety. Participants: Thirteen undergraduate students (85% nursing majors, 15% awaiting program entry, 20 ± 4.9 years of age) completed the crossover design study. Methods: Participants completed a yoga or control intervention (independent quiet study) on opposing testing days. At three time points, participants provided ratings of anxiety (visual analog scales), saliva samples for cortisol and alpha amylase, and seated heart rate variability (HRV, time and frequency domains) was recorded. Results: Yoga prior to a simulated exam had a positive impact on subjective measures of stress but did not positively impact cortisol or HRV compared to the control condition. Conclusions: There may be benefits to participating in 30 min of moderate intensity yoga for reduced perception of stress before a scholarly examination. Further research regarding the impacts of acute yoga on physiological measures of HRV and/or cortisol are warranted.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.417
Teacher spread0.385 · 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 designNon-randomized trial
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

Citations3
Published2024
Admission routes1
Has abstractyes

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