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Record W2901988721 · doi:10.5430/jnep.v9n3p109

Development and validation of educational videos addressing indwelling catheterization

2018· article· en· W2901988721 on OpenAlexvenueno aff
Marina Bertelli Rossi, Rui Carlos Negrão Baptista, Rosali Isabel Barduchi Ohl, Tânia Arena Moreira Domingues, Alba Lúcia Bottura Leite de Barros, Juliana de Lima Lopes

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsLikert scaleMedicineDelphi methodMedical educationPsychologyNursingComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Objective: Developed and validate educational videos addressing the female and male indwelling catheterization techniques in adult patients.Methods: Methodological study divided into two stages: development and validation of a script and the filming, editing and validation of videos. The script was written in the storyboard format, which was validated by eight nurse experts using the Delphi technique. The educational videos were filmed according to this validated script and were validated by 71 undergraduate nursing students using a five-point Likert scale.Results: The final script was composed of eight items: concept, reasons, material, instructions, male and female indwelling catheterization, indwelling catheter care, and complications. Five rounds were needed for the script to be validated by experts, a process that lasted nine months. The scenes were filmed, edited and inserted in the animated texts. The final versions were watched by 71 first-year undergraduate nursing students from a public university located in São Paulo. The mean scores assigned by the students to the eight items were greater than four. The item that obtained the highest mean was “complications related to indwelling catheterization”, with a mean score of 4.80. The item with the lowest score was “reasons” with a mean of 4.38. Assessment of the set of items (“did you understand this video?”) also obtained a mean score of 4.38. Agreement among students was also significant (p < .001).Conclusions: The script was developed and validated by experts, while the educational videos that resulted from this script were validated by first-year undergraduate nursing students.

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)0.028
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.098
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.278
GPT teacher head0.534
Teacher spread0.256 · 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 designBench or experimental
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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Citations12
Published2018
Admission routes1
Has abstractyes

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