The motherhood choices decision aid for women with rheumatoid arthritis increases knowledge and reduces decisional conflict: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: For many women with Rheumatoid Arthritis (RA) motherhood decisions are complicated by their condition and complex pharmacological treatments. Decisions about having children or expanding their family require relevant knowledge and consultation with their family and physician as conception and pregnancy has to be managed within the RA context. Relevant information is not readily available to women with RA. Therefore a randomized controlled study was conducted to evaluate the effectiveness of a new motherhood decision aid (DA) developed specifically for women with RA. METHODS: One hundred and forty-four women were randomly allocated to either an intervention or control group. All women completed a battery of questionnaires at pre-intervention, including, the Pregnancy in Rheumatoid Arthritis Questionnaire (PiRAQ), the Decisional Conflict Scale (DCS), the Hospital Anxiety and Depression Scale (HADS), and the Arthritis Self-Efficacy Scale (ASES), and provided basic demographic information. Women in the DA group were sent an electronic version of the DA, and completed the battery of questionnaires for a second time post-intervention. RESULTS: Women who received the DA had a 13 % increase in relevant knowledge (PiRAQ) scores and a 15 % decrease in scores on the decisional conflict (DCS), compared to the control group (1 %, 2 % respectively). No adverse psychological effects were detected as evident in unchanged levels of depression and anxiety symptoms. CONCLUSIONS: The findings of this study suggest that this DA may be an effective tool in assisting women with RA when contemplating having children or more children. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, http://www.anzctr.org.au/ , ACTRN12615000523505.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".