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Record W1913027277

Perspective sur l’utilisation de la vidéo pour la formation des professionnels de la santé

2011· article· fr· W1913027277 on OpenAlexaff
Gabrielle Ferland, Isabelle Goyer, Denis Lebel, Jean‐François Bussières

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Resume Objectif : L’objectif de cet article consiste a presenter une approche pratique de formation continue en etablissement de sante. Mise en contexte : La preoccupation de la prestation securitaire de soins decoule notamment de la documentation scientifique sur la survenue d’erreurs medicamenteuses et sur l’appreciation des risques inherents au circuit du medicament. Les pharmaciens et les assistants techniques en pharmacie doivent participer activement a la mise a jour de leurs competences. Resultats : Nous presentons un profil des differentes approches pour la formation du personnel (c.- a-d. interlocuteurs, supports technologiques, temps, retroaction, deroulement, strategies, outils de production et de diffusion, exemples). Nous avons elabore une approche de production/diffusion des contenus a l’aide du logiciel Camtasia StudioMD. Nous avons realise une vingtaine de productions Web de cinq a douze minutes requerant une vingtaine d’heures de travail par production, le tout fait par des etudiants. Discussion : La production de videos est une activite pouvant etre confiee a des etudiants en pharmacie, en collaboration avec des pharmaciens experts en contenu afin de cibler efficacement les contenus, de structurer les messages cles, de developper, de realiser, de publier et d’evaluer le scenario de production. Nous pensons que cette approche est plus realiste que les videos proposees par les societes externes, dont les couts de developpement se chiffrent par dizaines de milliers de dollars. Conclusion : Cette etude pilote demontre la faisabilite d’une approche pratique de l’utilisation de la video en ligne pour la formation des professionnels de la sante. Elle a permis de determiner une demarche pour la realisation de videos a peu de frais. Abstract Objective: To present a practical approach for continuing education in hospitals and related healthcare settings. Context: Concern for safe delivery of health care stems mainly from the scientific literature on drugrelated errors and from appreciation of the inherent risks to the medication use and medication management process. Pharmacists and pharmacy technical assistants should actively participate in updating their skills. Results: We introduce a profile of the various approaches to personnel training (i.e., participants, technological support, time, feedback, procedure, strategies, production tools and distribution, examples). Using the Camtasia Studio software, we developed an approach to content production/distribution, and have created some 20 Web productions 5–12 minutes in length, involving about 20 hours of work per production, all of it done by students. Discussion: Video production is a task that can be delegated to pharmacy students, in collaboration with pharmacists as content experts in order to effectively target the content and structuring of key messages; and to develop, complete, and evaluate the production scenario. We think that this approach is more realistic than the videos provided by external organizations, of which production costs are estimated to be tens of thousands of dollars. Conclusion: This pilot study demonstrates the feasibility of a practical approach using online videos for the continuing education of healthcare professionals. A low-cost way to produce videos was achieved. Key words: continuing education, video

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.004
Scholarly communication0.0100.007
Open science0.0010.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0280.004

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 head0.167
GPT teacher head0.457
Teacher spread0.290 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2011
Admission routes1
Has abstractyes

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