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Record W2755588539 · doi:10.1080/15228835.2017.1366886

Examining Computer Use by Hospitalized Children and Youth

2017· article· en· W2755588539 on OpenAlex
David Nicholas, Anu Chahauver

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Technology in Human Services · 2017
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsHospital for Sick ChildrenUniversity of Calgary
Fundersnot available
KeywordsQualitative researchThe InternetDistractionComputer technologyNormalization (sociology)ConstructiveMedical educationPsychologyInternet privacyComputer scienceMedicineMultimediaWorld Wide Web

Abstract

fetched live from OpenAlex

Hospitalized children and their families face information and support needs that may be augmented by Internet access. Using a qualitative description methodology, this study examined computer/technology use by hospitalized children. Thirteen pediatric patients who accessed hospital-based computers while hospitalized and 11 parents participated in qualitative interviews. Children used computers for gaming, chatting with peers, homework, social media, and general browsing. Benefits of computer use included distraction from unpleasant treatments, social support, and normalization of experience. Barriers to use included computer inaccessibility, lack of privacy, and technology-based challenges. Computer access appears to offer a constructive role in ameliorating pediatric hospitalization experiences.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.393
Teacher spread0.329 · 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