Evaluating a Web-Based Training Program for Nurses on Shared Decision-Making and Screening for Down Syndrome: Protocol for a Randomized Control Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Pregnant women have difficulty choosing from amongst the wide variety of available prenatal screening options. To help pregnant women and their partners make informed decisions based on their values, needs, and preferences, a decision aid (DA) and a web-based shared decision making (SDM) training program for health professionals have been developed. In Canada, nurses have responsibilities regarding maternity care and thus the potential to do decision coaching on prenatal screening. However, there is a gap of knowledge concerning the effectiveness of SDM interventions in this area of nursing practice. OBJECTIVE This study aims to assess the impact of an SDM training program on nurses’ intention to use a decision aid for prenatal screening as well as their knowledge and overall appreciation of the training. METHODS This is a two-arm parallel randomized trial. Nurses working with pregnant women from the province of Quebec, and speaking in French, will be recruited online by a private survey firm. They will be randomly allocated (1:1 ratio) to either an experimental group, which will complete a web-based SDM training program for prenatal screening, or to a control group, which will complete a web-based training program focusing on prenatal screening alone. The experimental intervention consists of a three hour web-based and fully automated training activity hosted on the University Laval platform and has four modules: 1) SDM; 2) Down syndrome prenatal screening; 3) DA; and 4) Communication between healthcare professionals and the patient. For the control group, the topic of SDM in Module 1 has been replaced with “Context and history of prenatal screening” and the topic of DA in Module 3 has been replaced with “Consent in prenatal screening.” In addition to sociodemographic questions using a self-administered questionnaire with closed ended questions, we will assess 1) intention to use a DA in prenatal screening clinical practice; 2) knowledge; 3) satisfaction with the training; 4) acceptability; and 5) perceived usefulness. The randomization will be done by a predetermined sequence and include 36 nurses. Participants and researchers will be blinded. Intention to use DA will be assessed by a Student t test and bivariate and multivariate analysis will be performed to assess knowledge and overall appreciation of the training. RESULTS This study is ongoing and results will be available at the end of 2020 CONCLUSIONS This study results will inform on the impact of an SDM training program on nurses’ intention to use a decision aid for prenatal screening as well as their knowledge and overall appreciation of the training. It will also provide feedback on ways to upgrade the SDM training program, if needed. CLINICALTRIAL ClinicalTrials.gov ID NCT04162288
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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 | 0.039 | 0.039 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.074 | 0.011 |
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".