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Record W4400837527 · doi:10.3389/fped.2024.1357462

Enhancing informed consent through multimedia tools in pediatric spinal surgery: a comprehensive review

2024· review· en· W4400837527 on OpenAlexaff
Marina Rosa Filezio, Nishan Sharma, Jennifer Thull‐Freedman, Fábio Ferri-de-Barros, Maria Santana

Bibliographic record

VenueFrontiers in Pediatrics · 2024
Typereview
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFacilitatorComprehensionMedicineModalitiesContext (archaeology)Informed consentProcess (computing)Medical educationAlternative medicinePsychologyComputer science

Abstract

fetched live from OpenAlex

Pediatric spine surgery is a high complexity procedure that can carry risks ranging from pain to neurological damage, and even death. This comprehensive mini review explores current best practice obtaining valid and meaningful informed consent (IC) prior to pediatric spinal surgery, including modalities that support effective comprehension and understanding. An evaluation of the literature was performed to explore understanding of surgical IC by patients or their guardians and the role of multimedia tools as a possible facilitator. The evidence discussed throughout this review, based on legal and ethical perspectives, reveals challenges faced by patients and guardians in achieving comprehension and understanding, especially when facing stressful medical situations. In this context, the introduction of multimedia tools emerges as a patient-centered strategy to help improve comprehension and decrease pre-operative uncertainty. This review highlights the need for a tailored approach in obtaining IC for pediatric patients and suggests a potential role of shared decision-making (SDM) in the surgical discussion process.

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)0.001
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0030.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0000.001

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 head0.383
GPT teacher head0.490
Teacher spread0.107 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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