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Record W4365795715 · doi:10.2196/45276

Web-Based Knowledge Translation Tool About Pediatric Acute Gastroenteritis for Parents: Pilot Randomized Controlled Trial

2023· article· en· W4365795715 on OpenAlexafffundvenue
Lisa Hartling, Sarah A Elliott, Matthew Munan, Shannon D. Scott

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchChildren's Hospital FoundationStollery Children’s Hospital Foundation
KeywordsMedicineEmergency departmentRandomized controlled trialIntervention (counseling)Health careFamily medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Acute gastroenteritis (AGE) in children is a leading cause of emergency department (ED) visits, resulting in substantial health care costs and stress for families and caregivers. The majority of pediatric AGE cases are caused by viral infections and can be managed at home using strategies to prevent dehydration. To increase knowledge of, and support health decision-making for, pediatric AGE, we developed a knowledge translation (KT) tool (fully automated web-based whiteboard animation video). OBJECTIVE: The aim of this study was to assess the potential effectiveness of the web-based KT tool in terms of knowledge, health care decision-making, use of resources, and perceived benefit and value. METHODS: A convenience sample of parents was recruited between December 18, 2020, and August 10, 2021. Parents were recruited in the ED of a pediatric tertiary care hospital and followed for up to 14 days after the ED visit. The eligibility criteria included parent or legal guardian of a child aged <16 years presenting to the ED with an acute episode of diarrhea or vomiting, ability to communicate in English, and agreeable to follow-up via email. Parents were randomized to receive the web-based KT tool (intervention) about AGE or a sham video (control) during their ED visit. The primary outcome was knowledge assessed before the intervention (baseline), immediately after the intervention, and at follow-up 4 to 14 days after ED discharge. Other outcomes included decision regret, health care use, and KT tool usability and satisfaction. The intervention group participants were invited to participate in a semistructured interview to gather additional feedback about the KT tool. RESULTS: A total of 103 parents (intervention: n=51, 49.5%, and control: n=52, 50.5%) completed the baseline and postintervention assessments. Of these 103 parents, 78 (75.7%; intervention: n=36, 46%, and control: n=42, 54%) completed the follow-up questionnaire. Knowledge scores after the intervention (mean 8.5, SD 2.6 vs mean 6.3, SD 1.7; P<.001) and at follow-up (mean 9.1, SD 2.7 vs mean 6.8, SD 1.6; P<.001) were significantly higher in the intervention group. After the intervention, parents in the intervention group reported greater confidence in knowledge than those in the control group. No significant difference in decision regret was found at any time point. Parents rated the KT tool higher than the sham video across 5 items assessing usability and satisfaction. CONCLUSIONS: The web-based KT tool improved parental knowledge about AGE and confidence in their knowledge, which are important precursors to behavior change. Further research is needed into understanding what information and delivery format as well as other factors influence parents' decision-making regarding their child's health. TRIAL REGISTRATION: ClinicalTrials.gov NCT03234777; https://clinicaltrials.gov/ct2/show/NCT03234777. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s40814-018-0318-0.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.105
GPT teacher head0.447
Teacher spread0.343 · 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 designRandomized 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

Citations6
Published2023
Admission routes3
Has abstractyes

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