Emotional distress in infertile women and failure of assisted reproductive technologies: meta-analysis of prospective psychosocial studies
Bibliographic record
Abstract
OBJECTIVE: To examine whether pretreatment emotional distress in women is associated with achievement of pregnancy after a cycle of assisted reproductive technology. DESIGN: Meta-analysis of prospective psychosocial studies. DATA SOURCES: PubMed, Medline, Embase, PsycINFO, PsychNET, ISI Web of Knowledge, and ISI Web of Science were searched for articles published from 1985 to March 2010 (inclusive). We also undertook a hand search of reference lists and contacted 29 authors. Eligible studies were prospective studies reporting a test of the association between pretreatment emotional distress (anxiety or depression) and pregnancy in women undergoing a single cycle of assisted reproductive technology. Review methods Two authors independently assessed the studies for eligibility and quality (using criteria adapted from the Newcastle-Ottawa quality scale) and extracted data. Authors contributed additional data not included in original publication. RESULTS: Fourteen studies with 3583 infertile women undergoing a cycle of fertility treatment were included in the meta-analysis. The effect size used was the standardised mean difference (adjusted for small sample size) in pretreatment anxiety or depression (priority on anxiety where both measured) between women who achieved a pregnancy (defined as a positive pregnancy test, positive fetal heart scan, or live birth) and those who did not. Pretreatment emotional distress was not associated with treatment outcome after a cycle of assisted reproductive technology (standardised mean difference -0.04, 95% confidence interval -0.11 to 0.03 (fixed effects model); heterogeneity I²=14%, P=0.30). Subgroup analyses according to previous experience of assisted reproductive technology, composition of the not pregnant group, and timing of the emotional assessment were not significant. The effect size did not vary according to study quality, but a significant subgroup analysis on timing of the pregnancy test, a contour enhanced funnel plot, and Egger's test indicated the presence of moderate publication bias. CONCLUSIONS: The findings of this meta-analysis should reassure women and doctors that emotional distress caused by fertility problems or other life events co-occurring with treatment will not compromise the chance of becoming pregnant.
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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 | 0.023 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.055 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".