Is social support related to better mental health, treatment continuation and success rates among individuals undergoing in-vitro fertilization? Systematic review and meta-analysis protocol
Bibliographic record
Abstract
Infertility and its treatment via in-vitro fertilization (IVF) represent a global health area of increasing importance. However, the physical and psychological burden of IVF can negatively impact psychological wellbeing, as well as treatment retention and success. Social support has been found to have positive health effects among populations facing health-related stressors worldwide, and its potential protective role for IVF patients merits further attention. We present a protocol for a systematic review of peer-reviewed published studies quantitatively investigating associations between social support and i) mental health; ii) the decision to (dis)continue with IVF treatment cycles and; iii) IVF success (pregnancy and birth rates); among individuals who are undertaking or have undertaken IVF cycles. Studies will be included if they work with human subjects, provide correlation coefficients between measures of social support and at least one of the outcomes of interest, and are in the English language. Social support may derive from both naturally occurring networks and more formalized sources or interventions. The protocol for this systematic review was developed according to the PRISMA-P guidelines. Ten health-, psychology- and sociology-related databases will be searched using composite search terms that include keywords for 'IVF' and 'social support'. To assess methodological quality, the authors will use a modified version of the Newcastle-Ottawa Scale. Should three or more moderate or good quality studies be identified for any one outcome of interest, correlation meta-analyses, using the Hedges-Olkin method, will be conducted to pool effect sizes and heterogeneity will be assessed. Should the number, quality and characteristics of eligible studies not allow for reliable quantitative synthesis, the authors will limit the analysis to qualitative synthesis, with a focus on implications of findings for future research and programming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".