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Record W4280521474 · doi:10.1037/ocp0000327

Flaws and all: How mindfulness reduces error hiding by enhancing authentic functioning.

2022· article· en· W4280521474 on OpenAlexafffund
Ellen Choi, Hannes Leroy, Anya Johnson, Helena Nguyen

Bibliographic record

VenueJournal of Occupational Health Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsToronto Metropolitan UniversityTed Rogers Centre for Heart Research
FundersMitacsWestern University
KeywordsMindfulnessPsychologyApplied psychologyCognitive psychologyClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Hiding errors can undermine safety by amplifying the risks of undetected errors. This article extends research on occupational safety by investigating error hiding in hospitals and applies self-determination theory to examine how mindfulness decreases error hiding through authentic functioning. We examined this research model in a randomized control trial (mindfulness training vs. active control group vs. waitlist control group) within a hospital setting. First, we used latent growth modeling to confirm that our variables were related as hypothesized, both statically or cross-sectionally as well as dynamically as they evolved over time. Next, we analyzed whether changes in these variables were a function of the intervention and confirmed the effects of the mindfulness intervention on authentic functioning and indirectly on error hiding. To elaborate on the role of authentic functioning, in a third step, we qualitatively explored the phenomenological experience of change experienced by participants in mindfulness and Pilates training. Our findings reveal that error hiding is attenuated because mindfulness encourages a receptive view of one's whole self, and authentic functioning enables an open and nondefensive way of relating to positive and negative information about oneself. These results add to research on mindfulness in organizations, error hiding, and occupational safety. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.095
GPT teacher head0.440
Teacher spread0.345 · 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 designNot applicable
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

Citations15
Published2022
Admission routes2
Has abstractyes

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