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A Short Mindfulness Activity to Reduce Anxiety State of Dissection and Prosection Students Prior to their First Cadaver Based Laboratory Experience

2016· article· en· W4389024591 on OpenAlexaffabout
William Albabish, Jessica L. Bigg, Genevieve Newton, Lorraine Jadeski

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAnxietyVisual analogue scaleMindfulnessPsychologyClinical psychologyPhysical therapyDissection (medical)State-Trait Anxiety InventoryMedicinePsychiatrySurgery

Abstract

fetched live from OpenAlex

Research conducted on medical students had shown that while many students express a positive attitude toward their first cadaveric laboratory experience, some students undergo mental distress in the form of increased anxiety state. Although recent studies have shown that this anxiety diminishes away after the students’ first laboratory experience, the use of better preparatory tools to ease the transition is recommended. The goal of this study was to examine whether a short mindfulness exercise has any positive effect on the increased anxiety state students face prior to their first cadaver-based laboratory. Moreover, this study also sought to investigate whether there is a difference in pre-laboratory anxiety state between the dissection and prosection cohorts. A short (<1 minute) voluntary mindfulness exercise was incorporated into the pre-laboratory sessions of third-year undergraduate human anatomy students enrolled in the dissection (n=222) and prosection (n=86) laboratories at the University of Guelph (Ontario, Canada). Self-reported anxiety state was measured using a validated visual analogue scale (VAS), and a validated 6-item abbreviated form of the Spielberger state-trait anxiety inventory survey (6-STAI). Surveys were administered at various time points (Pre-mindfulness (VAS and 6-STAI), Post-mindfulness (VAS), Post-Laboratory 1 (VAS and 6-STAI), Pre-Laboratory 3 (VAS and 6-STAI), and Pre-Laboratory 7 (VAS and 6-STAI)). A repeated measures ANOVA with a Greenhouse-Geisser correction determined that mean anxiety state levels reported on the VAS scale showed a statistically significant difference between time points (F(2.439, 556.046) = 119.856, P < 0.0005). Post hoc tests using the Bonferroni correction revealed a statistically significant reduction (P < 0.0005) of students’ anxiety state before and immediately after the mindfulness exercise (34.43 ± 21.68 vs. 27.17 ± 19.94, respectively) as reported on the VAS scales. Both VAS scale and 6-STAI questionnaire results showed no statistical significance in reported anxiety state between the dissection and prosection cohorts during different time points (P=0.337 and P=0.248 respectively). In conclusion, the results indicate that a short mindfulness exercise is an effective method to reduce pre-laboratory anxiety state in human anatomy students; moreover, there seems to be no effect on anxiety state levels between dissection and prosection students. Support or Funding Information Sponsoring Society: AAA/Anatomy Self-reported anxiety state using a validated visual analogue scale (VAS) Self-reported anxiety state using the validated 6-item abbreviated form of the Spielberger state-trait anxiety inventory survey (6-STAI) Self-reported anxiety state using a validated visual analogue scale (VAS) Self-reported anxiety state using the validated 6-item abbreviated form of the Spielberger state-trait anxiety inventory survey (6-STAI)

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.323
Teacher spread0.308 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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