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Record W3135587808 · doi:10.1093/jcag/gwab002.168

A170 A NOVEL DECISION AID IMPROVES KNOWLEDGE AND QUALITY OF PREGNANCY-RELATED DECISION-MAKING IN IBD

2021· article· en· W3135587808 on OpenAlexaffabout
G Wang, Neda Karimi, Joseph Descallar, Katie O’Connor, Joseph L. Pipicella, Laura Willmann, Astrid‐Jane Williams, Vivian Huang

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicinePregnancyInflammatory bowel diseaseUlcerative colitisDiseaseFamily medicineFertilityQuality of life (healthcare)GynecologyObstetricsPhysical therapyInternal medicinePopulationNursingEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background Women with inflammatory bowel disease (IBD) with poor IBD-specific reproductive knowledge experience more voluntary childlessness. Poor knowledge is associated with fear of IBD medications in pregnancy; this must be addressed as active IBD at preconception (PC) correlates with worse intrapartum disease and poor fetal outcomes. The Pregnancy IBD Decision Aid (PIDA), developed by an international multidisciplinary team following International Patient Decision Aids Standards, is an interactive online tool that offers personalised decision support on fertility, pregnancy, and medications in IBD (Fig). Aims To assess PIDA’s impact on knowledge and quality of decision-making among PC and pregnant patients with IBD, and to evaluate its feasibility as a tool for patients and clinicians. Methods PC and pregnant women aged 18–45 with IBD, recruited in Canada and Australia, completed questionnaires pre and post PIDA to assess quality of decision-making (Decisional Conflict Scale, DCS; Self-Efficacy Score, SES) and IBD in pregnancy knowledge (Crohn’s and Colitis Pregnancy Knowledge Score, CCPKnow). DCS assesses if a decision is informed, aligned with personal values, and would be implemented. SES measures belief in one’s ability to make informed decisions. Patients and clinicians (gastroenterology, obstetrics, primary care) also completed feasibility surveys. Paired t-test assessed for differences pre and post PIDA. Results DCS and SES were completed by 74 patients (42 Crohn’s disease, 32 ulcerative colitis); 41 PC and 33 pregnant. DCS improved significantly post PIDA (effect size 0.44, p<0.0001); this was observed in PC patients regarding pregnancy planning with IBD, and in pregnant patients regarding peripartum IBD medication management. SES of PC but not pregnant patients improved significantly post PIDA (effect size 0.32 vs 0.24, p=0.0001 vs 0.0525). In both cohorts, CCPKnow improved significantly post PIDA (n=76, effect size 0.66, p<0.0001). Patients (n=73) assessed PIDA feasibility. Mean scores for length (3.05±0.44), readability (3.09±0.5), and content amount (2.91±0.81) were perceived as appropriate (1=limited, 5=excessive). Perceived usefulness of PIDA was high among all patients (4.09±0.93; 5=most useful). Clinicians (n=14) believed PIDA had appropriate length, readability, and content amount, and deemed PIDA useful to patients (4.6±0.8) and themselves (4.8±0.8) for clinical practice. Conclusions PIDA improved knowledge and quality of decision-making in PC and pregnant patients with IBD. Patients developed a strengthened belief in their ability to make informed, effective decisions, and both patients and clinicians found PIDA feasible. PIDA is an accessible tool that can empower women with IBD to make evidence-based decisions about pregnancy and may ultimately reduce voluntary childlessness. Funding Agencies Mount Sinai Hospital Resident Research Grant; Gastroenterological Society of Australia Rose Amarant Grant; Women and Children’s Health Research Institute (WCHRI); Clinical/Community Research Integration Support Program (CRISP); Merck Better Care, Healthy Communities Funding Program

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.017
GPT teacher head0.305
Teacher spread0.288 · 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 designNon-randomized trial
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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