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Enregistrement W4398185665 · doi:10.1152/physiol.2024.39.s1.2423

Investigating feedback-associated stress and mindfulness in undergraduate physiology students and other higher education programs

2024· article· en· W4398185665 sur OpenAlexaffabout
Christine Bell, Cecilia S. Dong, Erin Isings, Samantha Jones, Hugh Samson, Lisa McCorquodale, Thomas G. W. Telfer

Notice bibliographique

RevuePhysiology · 2024
Typearticle
Langueen
DomainePsychology
ThématiqueMotivation and Self-Concept in Sports
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésMindfulnessStress (linguistics)PsychologyPhysiologyMedical educationBiologyMedicineClinical psychology

Résumé

récupéré en direct d'OpenAlex

Study objective: Students who engage with and learn from academic feedback have developed what is known as feedback literacy skills. Being able to learn from feedback is an exceptionally powerful way of growing as a student; however, the process of receiving feedback can be stressful. This can lead to behaviours such as avoidance, denial or diminishing the importance of feedback, which can impact learning. Providing students with the skills needed to learn from feedback and to manage feedback associated stress is therefore increasingly relevant to student success and wellbeing. Feedback literacy skills include managing affect (emotions), focus, and self-advocacy, which are skills that are supported by mindfulness. Mindfulness is being present, on purpose, and without judgement, and is a proven practice that helps to reduce and manage stress. This study is of post-secondary students’ perceptions concerning feedback literacy, mindfulness, and stress, and their thoughts on digital mindfulness tools intended to support students who experience feedback-associated stress. Hypothesis: Students with higher mindfulness skills will also have higher feedback literacy skills and will also have lower stress. Methodology: Students were recruited from across several disciplines (+1000 students), including Physiology and Pharmacology, Dentistry, Occupational Therapy, Information and Media Studies, and Law, along with students supported by the Learning Development and Success Centre at Western University. The study included an online survey ( n=237) and focus groups ( n=6). Gender and program were both included in the survey; however, due to limited sample size, no additional analysis of these factors was conducted. Coding and thematic analysis was conducted by three faculty and two graduate research assistants. Summary of results: The survey data demonstrates that students with greater mindfulness have significantly greater feedback literacy, as well as lower stress. Thematic analysis of focus group data shows a broad range of affective and behavioural responses were shaped by how students perceive their own abilities, circumstances, and feedback itself. Thematic analysis also suggests there is a developmental trajectory for both mindfulness and feedback literacy as graduate students discussed more mindfulness and feedback literacy skills. Discipline-specific views on mindfulness and stress were also apparent. Conclusion: Survey results indicate that students who are more mindful have higher feedback literacy skills; however, when mindfulness and feedback literacy were discussed in focus groups, data suggests that few students considered explicitly linking mindfulness to academic feedback. Students across the various programs expressed vastly different familiarity with mindfulness and feedback literacy. All students expressed interest regarding the development of digital mindfulness tools to alleviate feedback-associated stress and offered recommendations for their implementation. These recommendations were discipline-specific and included the development of program competencies with respect to feedback literacy and wellness. Internal grants from the University of Western Ontario and the Schulich School of Medicine and Dentistry. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,037
Tête enseignante GPT0,344
Écart entre enseignants0,307 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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