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Record W3216125661 · doi:10.1177/10497323211046577

“The Rest of my Childhood was Lost”: Canadian Children and Adolescents’ Experiences Navigating Inflammatory Bowel Disease

2021· article· en· W3216125661 on OpenAlexafffundabout
Claudia Barned, Alexis Fabricius, Alain Stintzi, David R. Mack, Kieran C. O’Doherty

Bibliographic record

VenueQualitative Health Research · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of OttawaUniversity of GuelphMontreal Clinical Research InstituteChildren's Hospital of Eastern OntarioUniversity Health Network
FundersCanadian Institutes of Health ResearchCrohn's and Colitis CanadaOntario Ministry of Economic Development and InnovationOntario Genomics Institute
KeywordsThematic analysisInflammatory bowel diseaseDiseaseMedicinePsychologyQualitative researchDevelopmental psychologySociologyPathology

Abstract

fetched live from OpenAlex

Children and adolescents with Inflammatory Bowel Disease (IBD) face significant and unique challenges related to their condition. The aim of this study was to better understand some of these challenges, and to explore how Canadian youth respond to them. We interviewed 25 pediatric patients with IBD, ranging in age from 10–17, to find out about their illness experiences. Using a thematic analysis, we discerned three themes: challenges related to diagnosis , making sense of change , and navigating sociability . Taken together, they paint a picture of young people facing great uncertainty prior to diagnosis, pronounced changes to selfhood as they make lifestyle adjustments, and facing difficulties with the implications of reduced sociability because of their disease. We conclude by providing recommendations for the development of resources aimed at helping newly diagnosed pediatric patients navigate these issues.

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)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.179
GPT teacher head0.552
Teacher spread0.373 · 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

Citations14
Published2021
Admission routes3
Has abstractyes

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