Obesity in Pregnancy Patient-Reported Outcomes: A Qualitative Meta-Synthesis [40N]
Bibliographic record
Abstract
INTRODUCTION: Patient-reported outcomes are infrequently reported in obesity (BMI>30 kg/m2) in pregnancy trials, compromising patient-centered care. Our primary objective was to meta-synthesize qualitative results, to determine outcomes reported by these women that may inform research and clinical practice. METHODS: MEDLINE, Embase, CINAHL, PubMed and grey literature were searched from inception to June 2018, identifying English-language qualitative studies of women with obesity in pregnancy. Results were screened and reference lists of included studies were searched. Study characteristics were extracted, followed by a thematic synthesis, in which patient-reported outcomes were identified according to the Core Outcome Measures in Effectiveness Trials' definition. Outcomes were categorized into the taxonomy of outcomes in medical research (Dodd et al.). RESULTS: Of 101 results, 27 studies were included. The following themes emerged: Perceived Barriers and Benefits of Interventions, Emotions, Fears or Concerns, Social Support, Healthcare Provider Support, Size-Related Experiences (Psychosocial and/or Obstetrical), and Concerns Regarding Medical Care, Equipment and/or Environment. No study specifically aimed to determine outcomes, thus only nine outcomes were explicitly identified and the rest were synthesized from findings. Emotional Functioning/Well-being and Delivery of Care were the most frequent categories in the outcome taxonomy, while outcomes in Mortality/Survival and Physiological/Clinical and Resource Use were least highlighted. CONCLUSION: Identified outcomes may inform future research and clinical practice, as they vary from outcomes currently reported in clinical trials. Furthermore, the limited number of measurable outcomes in qualitative studies highlights the need for future qualitative research that specifically aims to elicit patient-reported outcomes that can be measured in clinical trials.
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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 | 0.144 | 0.263 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".