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Record W2792838640 · doi:10.1093/ecco-jcc/jjx180.487

P360 TrueColours ulcerative colitis (TCUC): Will patients with UC complete digital questionnaires in real-time?

2018· article· en· W2792838640 on OpenAlexaboutno aff
Alissa Walsh, Michele Peters, Chris Hinds, Andrey Kormilitzin, Vanashree Sexton, Pavetha Seeva, Oliver Brain, Satish Keshav, Holm H. Uhlig, Alison Simmons, John Geddes, Guy M. Goodwin, Gary S. Collins, Simon Travis

Bibliographic record

VenueJournal of Crohn s and Colitis · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUsabilityQuality of life (healthcare)System usability scaleRetention ratePhysical therapyFaecal calprotectinInternal medicineInflammatory bowel diseaseDiseaseWeb usabilityNursing

Abstract

fetched live from OpenAlex

TCUC is a comprehensive real-time web-based programme for UC patients. It monitors multiple parameters via electronic questionnaires: symptoms, quality of life (QoL), and outcomes (e.g. hospitalisation). Medications are entered and personalised treatment guidance formulated. This information, graphically displayed on a traffic light system, is available to the patient and clinical team via the TCUC website (https://ouh.truecolours.nhs.uk/ibd/en/), and is housed on a secure National Health Service server. The objectives were to assess feasibility, usability and adherence of TCUC. A prospective, non-randomised 6-month pilot study recruited patients from the Oxford inflammatory bowel disease service. Recruitment and retention rates were calculated. Questionnaires were scheduled either daily (simple clinical colitis activity index, SCCAI), fortnightly (QoL, IBD-Control-8, CUCQ-8 and EQ5D-5L), or once only (outcomes, www.ichom.org). Patients received email prompts linked to scheduled questionnaires. Monthly home faecal calprotectin measurements were incorporated, monthly blood tests collected and flexible sigmoidoscopy performed at entry and after 6 months. Usability was assessed via the System Usability Scale (SUS) (n = 59) as well as qualitative interviews (n = 28). SUS broadly classifies usability of a system from poor (< 70) to superior ( >90). A deductive approach was used for the qualitative coding and analysis. Recruitment rate was 66 out of 240 invitations sent (28%). Retention rate was 57 of 66 patient recruited (86%). Of 66 patients, 29 (44%) were male, median age 41 years (IQR 17), median duration of disease 5.6 years (IQR 10.7), distribution of disease (Montreal classification: E1 18%, E2 38%, E3 33%, unknown 11%), activity of disease at entry (remission 38%, mild 35%, moderate 26%, severe 1%), tertiary education 58%, biologic use 47%. Adherence to daily SCCAI questionnaires: 76%, fortnightly QoL questionnaires: 95%, and International Consortium for Health Outcome Measurement questionnaires: 100%. Uptake of faecal calprotectin home testing was 73% (48/66), with median number of tests 4 (IQR 3). Median SUS score was 92.5 (IQR 15). Qualitative interviews confirmed that TCUC was efficient, effective, and easy to learn. Improvements suggested were optimisation of the graphical display on smartphones and decreasing the number of QoL questionnaires from three to one, with a preference for IBD–Control. Patients with UC will collect digital data in real-time, with good adherence to symptom, QoL, and outcome questionnaires as well as faecal calprotectin home testing. Usability was classified as “superior” but further improvements are possible. Larger studies are required to determine cost-effectiveness.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.005

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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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 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

Citations4
Published2018
Admission routes1
Has abstractyes

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