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Record W3111173224 · doi:10.1111/medu.14435

Cognitive flow in health care settings: A systematic review

2020· review· en· W3111173224 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMedical Education · 2020
Typereview
Languageen
FieldPsychology
TopicFlow Experience in Various Fields
Canadian institutionsUniversity of British ColumbiaQueen's UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPsycINFOBurnoutMEDLINEHealth carePsychological interventionContext (archaeology)HappinessPsychologyPopulationMedical educationMedicineNursingApplied psychologyClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

INTRODUCTION: The state of cognitive flow, colloquially known as being 'in the zone', has been linked with enhanced performance, happiness, career satisfaction and decreased burnout. However, the concept has not been adopted strongly in health care training, continuing professional development, or daily practice. A systematic review with a narrative synthesis was undertaken to map the evidence for flow in health care. METHODS: A search was conducted in MEDLINE, PsycInfo, and EMBASE in July 2019 and updated in October 2020 for manuscripts discussing flow in all health care disciplines. Articles published between 1806 and 13 October 2020 were included. Two authors independently reviewed titles and abstracts (and subsequently full texts where necessary) for inclusion. Disagreements were resolved by consensus. Data were extracted on location, manuscript type, population and context, measures, and key findings. RESULTS: A total of 4923 unique abstracts were initially retrieved, and 15 articles were included in the final review. We report on the experience, benefits and strategies to support flow in health care. Flow may benefit providers by enhancing career enjoyment, wellness and performance, while mitigating exhaustion, burnout, and stress. Although research from other domains has focused on supporting flow through individualised training, our results highlight the importance of system and environmental factors. CONCLUSIONS: Supporting professional and trainee flow in health care requires a holistic approach, including individual training and system-level interventions.

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.

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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.454
Teacher spread0.426 · 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