IDDF2021-ABS-0062 A novel decision aid improves knowledge and quality of pregnancy-related decision-making in IBD
Bibliographic record
Abstract
Background Women with inflammatory bowel disease (IBD) with poor IBD-specific reproductive knowledge experience more voluntary childlessness. This is associated with medication fear, which must be addressed given active IBD during preconception correlates with worse intrapartum disease and poor fetal outcomes. The Pregnancy IBD Decision Aid (PIDA) is an online tool offering personalised decision support on fertility, pregnancy, and medications in IBD (IDDF2021-ABS-0062 Figure 1. Screenshot of the Pregnancy IBD Decision Aid tool ). This study aimed to assess PIDA’s impact on knowledge and quality of decision-making among preconception and pregnant IBD patients, and to evaluate its feasibility. Methods Preconception and pregnant patients (18-45yrs) from Canada and Australia completed questionnaires before and after viewing PIDA. Quality of decision-making and IBD-specific pregnancy knowledge were assessed using: l Decisional Conflict Scale (DCS) l Self-Efficacy Scale (SES) l Crohn’s and Colitis Pregnancy Knowledge Score (CCPKnow). Patients and clinicians completed feasibility surveys following PIDA review. Paired t-test assessed PIDA’s limited effectiveness. Results DCS and SES were completed by 42 Crohn’s disease and 32 ulcerative colitis patients (preconception: n=41; pregnant: n=33). DCS improved for preconception and pregnant patients post-PIDA (effect size 0.44, p<0.0001). SES improved for preconception patients (effect size 0.32, p=0.0001), and in both cohorts CCPKnow also improved (n=76, effect size 0.66, p<0.0001). Seventy-three patients assessed PIDA’s feasibility. PIDA’s length (m=3.05±0.44), readability (m=3.09±0.5) and content amount (m=2.91±0.81) were perceived as appropriate (1=limited, 5=excessive). Perceived usefulness was high among patients (m=4.09±0.93; 1=least useful, 5=most useful). Clinicians (n=14) believed PIDA had appropriate length (m=3.3±0.6), readability (m=3.3±0.8), and content amount (m=3.4±0.8), and deemed PIDA useful for patients (m=4.6±0.8) and themselves (m=4.8±0.8). Conclusions PIDA improved patient knowledge and quality of decision-making. Patients developed a strengthened belief in their ability to make informed decisions, and patients/clinicians found PIDA feasible. Therefore, PIDA may reduce voluntary childlessness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".