Self-report of mental health distress among pregnant and parenting adolescents during the COVID-19 pandemic in Malawi
Bibliographic record
Abstract
Abstract Objective: Few studies have examined the effects of the COVID-19 pandemic on mental health among young people in sub-Saharan Africa and particularly pregnant and parenting adolescents exposed to multiple stressors. Our study addresses this gap by examining self-report of mental health challenges among pregnant and parenting adolescent girls during the pandemic. Methods: We undertook a cross-sectional survey involving 666 girls aged 13-19 in Blantyre district, southern Malawi, between March and May 2021. We recruited eligible respondents from households in 66 randomly selected rural (26) and urban (40) enumeration areas. Mental distress was assessed using nine symptoms including worry, restlessness, fear, anxiety, sadness, loneliness, frustration, fear, stress, and boredom. Girls were asked whether they experienced more of these symptoms after the start of the COVID-19 pandemic. Any girl experiencing one of these symptoms was considered to have experienced mental distress. Bivariate and multivariable regression models were used to examine correlates of mental distress. Findings: Girls’ median age was 18 years with a range of 13-19 years. Most girls (68.3%) reported having experienced somewhat more or much more mental distress, with 17.6% indicating all nine symptoms. In the adjusted model, pregnant and parenting girls aged 19 were more likely to report having experienced more mental distress (OR=1.79; 95% CI 1.15 – 2.77) during the pandemic compared to those aged 13-17 years. Similarly, girls who had ever worked had a higher likelihood of experiencing more mental distress (AOR:1.65; 95% CI 1.12 – 2.41) than before the pandemic. On the contrary, perceived neighborhood safety was protective against mental distress (OR=0.81 95% CI 0.69 – 0.95 p<0.01). Conclusion: Pregnant and parenting adolescent girls' mental health was adversely affected by the COVID-19 pandemic, thereby exacerbating their vulnerabilities and increasing risk of poor mental health. Our findings could inform interventions targeting adolescents’ mental health during pandemics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".