The impact of a mindfulness-based stress reduction (MBSR) program on patients seeking infertility treatment: A feasibility study
Bibliographic record
Abstract
Objective: To investigate the effect of traditional Mindfulness-Based Stress Reduction (MBSR) program in infertility patients. Design, setting and population : A feasibility Randomized Controlled Trial (RCT) using an effectiveness-implementation type-II hybrid design was conducted with patients seeking infertility consultation in Canada. Methods: Participants were recruited at initial consultation and block randomized into standard treatment or a virtual Mindfulness Based Stress Reduction (MBSR) course. Main outcome measures: MBSR program completion rate and the effect of MBSR program on mental health and QOL measures Results: Of 155 patients that met inclusion criteria, 45 completed the intake survey, 34 met study criteria, 24 proceeded with randomization. Among those randomized to the MBSR group, 73% started the course and 64% completed >50% of the program. Of participants randomized into the MBSR arm, 82%, 45%, and 27% completed the first, second, and third survey, respectively. This compared to 77%, 69%, and 69% in the control group. Secondary outcomes, measuring mental health and QOL outcomes, pregnancy rates, and initiation of treatment, showed no significant differences. Conclusion: We identified challenges implementing intensive mindfulness interventions in this population and how these may be addressed in future studies. A large-scale RCT is required to evaluate the impact of MBSR on pursuing fertility treatment and mental health outcomes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".