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Record W4226269869 · doi:10.1177/23743735221092557

Health Care Perspectives of Adult Patients with Lower Educational Attainment in Inflammatory Bowel Disease: A Qualitative Study

2022· article· en· W4226269869 on OpenAlexaffabout
Eric Harvey, Maria El Bizri, Geoffrey C. Nguyen, Deborah A. Marshall, Raza Mirza, Maida Sewitch

Bibliographic record

VenueJournal of Patient Experience · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoMount Sinai HospitalUniversity of CalgaryMcGill University Health Centre
FundersFerring
KeywordsMedicineThematic analysisQualitative researchHealth careInflammatory bowel diseaseEducational attainmentDiseaseFamily medicineNursing

Abstract

fetched live from OpenAlex

Patients with lower educational attainment are underrepresented in inflammatory bowel disease (IBD) research. To increase our understanding of the health care perspectives of patients with less than a university degree, semi-structured interviews were conducted among 23 outpatients at the McGill University Health Centre IBD Centre (Montreal, Canada). Thematic analysis was used to analyze the qualitative data. Perspectives focused on communication with health care professionals, access to care, symptoms and treatment, and outside support. Access to an IBD specialist was the most important aspect of care. Good care, kind and receptive staff, and a lengthy delay to diagnosis were frequently reported experiences. IBD specialists, nurses, and family and friends were most helpful in managing disease. Physical and emotional symptoms, reduced social engagement, and medications were difficult aspects of living with IBD. An ideal IBD clinic would provide access to traditional and non-traditional services and assist with obtaining support to help patients engage in social activities, increase affordability of care, and maintain employment. Study findings may be helpful in designing equitable models of health care delivery.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.475

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.289
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes2
Has abstractyes

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