Impact of COVID-19 Lockdowns on Rates of Adolescent Pregnancies: A Systematic Review
Bibliographic record
Abstract
Abstract Background: Education is known to protect adolescent girls from unplanned pregnancy. School closures were component of COVID-19 "lockdown measures". The impact of these measures on adolescent pregnancy worldwideis unknown. Methods: We performed a systematic review to find evidence of the impact of "lockdowns" and school closures on adolescent pregnancy events during the COVID-19 pandemic. Databases including Pubmed, EMBASE, CINAHL, WHO Index Medicus, and Literatura Latinoamericana y Caribe en Ciencias de la Salud (LILACS) were searched. Studies that provided data on pregnancy rates in girls aged 10-19 before, during, and after the onset of the COVID-19 pandemic (defined as March 2020) were eligible for inclusion. Extracted data included study design, study location, age of participants, exposure period, and percentage or pregnancy rate data. Findings: On August 21 st , 2023, 3049 studies were screened, with 79 eligible for full-text review. Ten studies were included in the final review: Seven performed in Africa (Uganda, Kenya, South Africa, and Ethiopia), and three in the Americas (USA and Brazil). Adolescent pregnancy increased in six out of the seven African studies while a decrease or no change was noted in USA and Brazil.All studies were at a high risk of bias. Interpretation: Adolescent pregnancy rates during the COVID-19 pandemic may have substantially increased in sub-Saharan Africa. Data scarcity and low-quality evidence are significant limitations. The dynamic relationship between lockdown measures and adolescent pregnancies warrants ongoing multifaceted research and adaptive policies to safeguard adolescent sexual and reproductive health during health crisis. Systematic Review Registration: PROSPERO registration number CRD42022308354.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".