Impact of COVID-19 on maternal health and child care behavior: Evidence from a quasi-experimental study of vulnerable communities in Boa Vista, Brazil
Bibliographic record
Abstract
BACKGROUND: COVID-19 related distress has been shown to have negative associations with family well-being. OBJECTIVES: To determine the immediate impact of acute COVID-19 infection on maternal well-being and parenting practices among Brazilian families. PARTICIPANTS AND SETTING: We studied 2'579 mothers (29'913 observations) of young children from vulnerable neighborhoods in Boa Vista, Brazil over 12 months. METHODS: We monitored family health and caregiving behavior including the incidence of COVID-19 infections in the surveyed households through bi-weekly phone interviews over 50 weeks, from June 2020 to May 2021. Primary outcomes were home-based child stimulation, positive parenting behavior, and parenting stress. We used fixed effects panel regressions to estimate the impact of household COVID-19 infections on parenting outcomes. RESULTS: Over the study period, 441 participants (17.1%; 831 (3.0%) observations) reported at least 1 positive COVID-19 infection in their household. Household COVID-19 infections significantly reduced home-based stimulation by 0.10 SDs (95%CI: -0.18, -0.01), positive parenting behaviors by 0.14 SDs (-0.21, -0.01), and increased parenting stress by 0.07 SDs (0.02, 0.12). The impact on home-based stimulation was most pronounced when the mother herself had a COVID-19 infection (-0.16; -0.29, -0.04). Parenting stress responded most strongly to mother or child COVID-19 infections. Effects were relatively short-lived, only children's infections' on parental stress was still detectable 2 weeks after initial infection. CONCLUSION: Our findings suggest that COVID-19 infections cause substantial disruptions in children's home environments - additional short-term support for families with acute infections could attenuate the negative impact on children's home environment during the pandemic.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".