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Record W6922396204 · doi:10.11575/prism/43959

Developing the first pan-Canadian survey on patient engagement in patient safety

2021· other· en· W6922396204 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2021
Typeother
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPatient safetyCornerstoneHarmHealth careAdaptation (eye)QuestionnairePatient careIdentification (biology)

Abstract

fetched live from OpenAlex

Abstract Background Patient safety is a worldwide problem, and the patient contribution to mitigate the risk of patient harm is now recognized as a cornerstone to its solution. In order to understand the nature of integrating patients into patient safety and healthcare organizations and to monitor their integration, a Canadian survey tool has been co-constructed by patients, researchers and the Canadian Patient Safety Institute (CPSI). This questionnaire has been adapted from the French version of the patient engagement (PE) in patient safety (PS) questionnaire created for the province of Quebec, Canada. Methodology The pan-Canadian PE in PS survey tool was developed in a five-step process: (1) a literature review and revision of the initial tool developed in the province of Quebec; (2) translation of the French questionnaire into an English version tool; (3) creation of a Canadian expert advisory group; (4) adaptation of the English version tool based on feedback from the expert advisory group (assessment and development of the construct’s dimensions, wording assessment and adaptation for pan-Canadian use, technical testing of the online platform for the survey); and (5) pilot testing and pre-validation of the tool before pan-Canadian use. Results and conclusion Eight pan-Canadian PE in PS surveys were completed from five Canadian provinces by the expert advisory group and six surveys were completed during the pilot project by participants from different provinces in Canada. This survey tool comprises 5 sections: (1) demographic identification of the participants (Q1 to Q5); (2) general questions (Q6 to Q17); (3) the patient engagement process (experience level of participants and organizational incentives for PE in general) (Q18 to Q33); (4) PE in PS processes, such as current activities, strategies, structures, resources and factors (Q34 to Q67); and (5) the context and impact of PE in PS initiatives in Canadian healthcare organizations (CHOs) (Q68 to Q75), including outcome identification, improvement mechanisms and strategies, evaluation mechanisms, and indicators.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.935
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.022
GPT teacher head0.207
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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