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

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

Bibliographic record

VenuePhysiology · 2024
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsWestern University
Fundersnot available
KeywordsMindfulnessStress (linguistics)PsychologyPhysiologyMedical educationBiologyMedicineClinical psychology

Abstract

fetched live from 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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.037
GPT teacher head0.344
Teacher spread0.307 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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