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Record W2794366440 · doi:10.1093/jcag/gwy008.090

A89 THE IBD SYMPTOM INVENTORY: MEASUREMENT CHARACTERISTICS AND VALIDITY IN A CLINIC SAMPLE

2018· article· en· W2794366440 on OpenAlexaffabout
Kathryn A. Sexton, John R. Walker, Laura E. Targownik, Lesley A. Graff, Clove Haviva, Brooke Beatie, Sarah K. Petty, Matthew T. Bernstein, Harminder Singh, Norine Miller, Çharles N. Bernstein

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineLikert scaleUlcerative colitisInflammatory bowel diseaseQuality of life (healthcare)Physical therapyInternal consistencyOutpatient clinicDiseasePsychometricsInternal medicineClinical psychologyPsychologyNursing

Abstract

fetched live from OpenAlex

Most measures of IBD symptoms are clinician administered, and existing self-report measures suffer from narrow breadth, inadequate measurement properties, or burdensome length. The IBD Symptoms Inventory (IBDSI) was developed to assess a broader range of patient-reported IBD symptoms. To evaluate the measurement properties of a new self-report measure of IBD symptoms. Consecutive IBD patients attending an outpatient GI clinic were invited to participate while waiting for their appointment. Participants completed a survey which included the IBDSI, the IBD Questionnaire (Guyatt et al., 1989), and the Manitoba IBD Index (Clara et al., 2009). The IBDSI was developed by adapting symptom items from existing clinician-rated or diary-format symptom inventories; following factor analytic work, 35 items were retained assessing symptoms on 5 subscales: bowel symptoms, abdominal discomfort, fatigue, bowel complications, and systemic complications. As part of standard care, participants were administered the Harvey Bradshaw Index for Crohn’s disease (HBI; Harvey & Bradshaw, 1980) or the Powell-Tuck Index for ulcerative colitis (PTI; Powell-Tuck et al., 1978) by a clinical nurse specialist with extensive experience in IBD. A gastroenterologist completed a global assessment of disease activity on a 4-point Likert scale (0=inactive to 3=severely active symptoms). 267 patients (58.1% female; CD n=142, UC n=125; ages 18–81 years, M=43.4, SD=14.6) provided informed consent and completed the surveys. The IBDSI showed excellent internal consistency (α=0.93 for the total score, 0.55–0.88 for subscale scores), correlated highly with low IBD-related quality of life on the IBDQ (r=-.89), symptom frequency on the MIBDI (r=.67), and clinician-rated global assessment (r=.70). ROC analyses found that a score ≥ 24 (in CD) or ≥ 17 (in UC) showed excellent sensitivity and specificity for the HBI and PTI cut offs of ≥ 5 for active disease (AUC = .93 and .95), respectively. The IBDSI is a reliable and valid patient-reported measure of a broad range of common IBD symptoms. The IBDSI showed strong measurement properties, with a supported factor structure, very good internal consistency, evidence of convergent validity, and excellent sensitivity and specificity to clinician-rated measures assessing active disease, and is thus recommended for use in either clinic or research settings. A shorter version of the measure (24 items) with similar measurement characteristics is available. Use of the measure could allow clinicians to score and follow symptom reports as a means to quantify the impact of interventions. Kathryn Sexton is supported by a CAG/CIHR post-doctoral fellowship. CAG, CIHR

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)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.044
GPT teacher head0.262
Teacher spread0.218 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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