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Record W2890418564 · doi:10.1080/17518423.2018.1518351

Positive Distraction in Pediatric Healthcare Waiting Spaces: Sharing Play Not Germs through Inclusive, Hands-Free Interactive Media

2018· article· en· W2890418564 on OpenAlexafffund
Elaine Biddiss, Tara Joy Knibbe, Darcy Fehlings, Patricia McKeever, Amy C. McPherson

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2018
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalPublic Health OntarioToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health ResearchHolland Bloorview Kids Rehabilitation Hospital FoundationYale University
KeywordsDistractionHands freeHealth careInteractive mediaPsychologyMedicineMultimediaComputer scienceHuman–computer interactionCognitive psychology

Abstract

fetched live from OpenAlex

Purpose: To investigate the value of shared opportunities for positive distraction in pediatric healthcare environments.Methods: Self-selected activities of 271 young people (5–19 years) with diverse neurodevelopmental conditions were observed in an ambulatory pediatric rehabilitation clinic. Shared opportunities included hands-free media (nature video or interactive media) and an aquarium. Anxiety was self-reported on the State Trait Anxiety Scale upon arrival and after 10 minutes in the waiting space.Results: Young people engaged more with shared opportunities for distraction (n = 170/271) than personal items brought from home (n = 119/271), p = 0.02. Personal electronic devices were used by 67 young people, but did not positively impact anxiety. Interactive media and the aquarium significantly reduced anxiety (p < 0.04) while the nature video appeared to increase anxiety (p = 0.036). Age influenced activity preference and anxiety. Shared, hands-free interactive media engaged individuals of diverse age and mobility.Conclusion: Shared opportunities for positive distraction in healthcare facilities are valuable, particularly hands-free interactive media.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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 teacher head, not a consensus.

Study designObservational
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

Citations10
Published2018
Admission routes2
Has abstractyes

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