Systematic review with meta-analysis on the quality of life of women undergoing IVF using Ferti-QOL questionnaire
Bibliographic record
Abstract
Abstract Background Infertility is a global health concern affecting millions of couples, with in vitro fertilization (IVF) emerging as a prominent solution. While IVF offers hope, it also presents significant physical, emotional, and financial challenges, profoundly impacting the quality of life (QOL) of women undergoing treatment. The Fertility Quality of Life (Ferti-QOL) questionnaire provides a comprehensive framework to assess the multifaceted effects of IVF on QOL. Objective This systematic review aims to synthesize evidence from cross-sectional studies that evaluated the QOL of women undergoing IVF using the Ferti-QOL questionnaire. Methods A comprehensive literature search was conducted across electronic databases, including PubMed, Embase, and the Cochrane Library, for studies published up to July 2024. Studies were included if they used the Ferti-QOL questionnaire to measure QOL in women undergoing IVF and adhered to predefined inclusion criteria. Methodological quality was assessed using the Newcastle–Ottawa Scale (NOS), and a meta-analysis was performed to estimate pooled mean QOL scores and explore subgroup variations. Results Eight cross-sectional studies were included, with a total sample size of 4,019 participants. The pooled mean Ferti-QOL score was 64.89 (95% CI: 61.15–68.63), indicating a moderate level of QOL. Subgroup analysis revealed that women under 35 years had lower QOL scores (61.94, 95% CI: 58.46–65.42) compared to women aged 35 years and above. Significant heterogeneity (I2 = 54%) was observed among studies, reflecting diverse cultural and demographic influences. Conclusion This review highlights the substantial impact of IVF on the QOL of women and underscores the need for individualized psychosocial support to address their unique challenges. Future research should focus on longitudinal studies and culturally specific interventions to enhance patient-centered care.
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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 | 0.013 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".