Self-medication among pregnant women in comparison to the general population: a scoping review of the main characteristics
Bibliographic record
Abstract
Objective: An in-depth evaluation of the published evidence is needed on self-medication, specifically the evidence focusing on vulnerable groups, such as pregnant women. This scoping review aims to provide an overview of the differences in self-medication prevalence and study characteristics among different groups, while identifying gaps in the literature. Methods: A literature search was performed in PubMed and Web of Science, including articles published in the last 10 years for the pregnant women group (PWG) and the general population group (GPG). Data on study design, self-medication prevalence, medications used, and other variables were collected, tabulated, and summarized. Results: From 2888 screened articles, 75 were considered including 108,559 individuals. The self-medication (SM) in the PWG ranged from 2.6 to 72.4% and most studies had an SM prevalence between 21 and 50% and in the GPG, 32 from 50 studies had a SM prevalence higher than 50%. The reviewed studies varied considerably in methodology, requiring careful interpretation. While most of the studies assessed self-medication during the entire pregnancy, self-medication definition was often inconsistent between studies. Acetaminophen was the most used medication and headache was the most frequent symptom leading to self-medication initiation in the PWG. Conclusions: Self-medication among pregnant women showed a lower prevalence when compared to the general population. The medications used and symptoms reported were similar between groups. However, methodological differences must be carefully considered. Pregnant women should carefully follow their physicians' advice before initiating self-medication to avoid preventable maternal and fetal adverse effects.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".