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Record W4308732129 · doi:10.1136/wjps-2022-000466

Development and evaluation of a patient decision aid for pediatric interval appendectomy

2022· article· en· W4308732129 on OpenAlexaff
Victoria Larocca, Irina Oltean, Viviane Grandpierre, Ahmed Nasr

Bibliographic record

VenueWorld Journal of Pediatric Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineInterval (graph theory)Intensive care medicineGeneral surgeryMedical physicsMathematics

Abstract

fetched live from OpenAlex

Objective: One option for the treatment of perforated appendicitis in pediatric patients is interval appendectomy (IA). A patient decision aid (PDA) can be useful in the decision-making process regarding IA. The purpose of this study was to evaluate parents' decisional conflict before and after engaging with a developed PDA. Methods: Participants included (a) parents who are considering IA surgery for their child, (b) have not yet had their follow-up appointment postdischarge, and (c) were fluent in either the official languages of English or French. This study used a pretest and post-test design to measure participants' decisional conflict and treatment option choice. Perceptions and acceptability of the PDA were also assessed. Results: A total of 18 participants completed the study (16 mothers). Major findings include significant decreases in all Decisional Conflict Scale items from pre-PDA to post-PDA engagement, except for one item. The majority of participants perceived the PDA to be useful, easy to find information regarding risks and provided enough information to help them make a decision regarding their child's treatment. Conclusions: This is the first study to develop and evaluate a PDA among parents who are making a decision regarding IA surgery. The results showed a significant decrease in decisional conflict after using the PDA. The results also showed that the PDA was generally accepted among parents and had positive perceptions regarding length, content, and balance. The use of PDA for this population can help ease feelings of decisional conflict and equip parents with the information to make informed decisions.

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)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.306
Teacher spread0.259 · 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 designNon-randomized trial
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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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