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Record W4235716287 · doi:10.21203/rs.3.rs-37019/v1

A Multi-Method Exploratory Study of Health Professional Students’ Experiences with Compliance Behaviours

2020· preprint· en· W4235716287 on OpenAlexaff
Efrem Violato, Sharla King, Okan Bulut

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCompliance (psychology)Exploratory researchPsychologyHealth professionalsMedical educationApplied psychologyMedicineSocial psychologyHealth carePolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract Research in healthcare, including with students, has begun to document experiences with negative compliance, specifically conformity and obedience. There is a growing body of experimental work however, the majority of literature on negative compliance is anecdotal and theoretical. Currently lacking is a direct measure of the frequency at which health professional students have negative experiences with conformity and obedience integrated with psychological factors, the outcomes of negative compliance, and students’ perceptions. To develop empirical knowledge about the frequency of negative compliance and student perceptions during health professional education a multi-methods survey approach was used. The survey was administered to health professional students across ten disciplines at four institutions. The results indicated students regularly experience obedience and conformity and are influenced by impression management and displacement of responsibility. Moral distress was identified as a consistent negative outcome. Student self-reported experiences aligned with the empirical findings. The findings of the present study demonstrate the pervasiveness of experiences with negative compliance during health professional’s education. The findings have educational and practical implications, as well as pointing to the need for further integration of social and cognitive psychology in explaining compliance in healthcare. The results are likely generalizable to a population level however replication is encouraged to better understand the true frequency of negative compliance at a population level.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.002
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 head0.465
GPT teacher head0.631
Teacher spread0.167 · 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.

Study designQualitative
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
Published2020
Admission routes1
Has abstractyes

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