A Data-Free Digital Platform to Reach Families With Young Children During the COVID-19 Pandemic: Online Survey Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic and containment measures have severely affected families around the world. It is frequently assumed that digital technologies can supplement and perhaps even replace services for families. This is challenging in conditions of high device and data costs as well as poor internet provision and access, raising concerns about widening inequalities in availability of support and consequent effects on child and family outcomes. Very few studies have examined these issues, including in low- and middle-income countries. OBJECTIVE: The study objectives were two-fold. The first objective was to gather data on the impact of the COVID-19 pandemic on families of young children using an online survey. The second objective was to assess the feasibility of using a data-free online platform to conduct regular surveys and, potentially, to provide support for parents and families of young children in South Africa. METHODS: We used a data-free mobile messenger platform to conduct a short digital survey of the impact of the COVID-19 pandemic on caring for young children in South Africa. We report on the methodological processes and preliminary findings of the online survey. RESULTS: More than 44,000 individuals accessed the survey link and 16,217 consented to the short survey within 96 hours of its launch. Respondents were predominantly from lower classes and lower-middle classes, representing the majority of the population, with urban residential locations roughly proportionate to national patterns and some underrepresentation of rural households. Mothers comprised 70.2% (11,178/15,912) of respondents and fathers comprised 29.8% (4734/15,912), representing 18,672 children 5 years of age and younger. Response rates per survey item ranged from 74.8% (11,907/15,912) at the start of the survey to 50.3% (8007/15,912) at completion. A total of 82.0% (12,729/15,912) of parents experienced at least one challenge during the pandemic, and 32.4% (2737/8441) did not receive help when needed from listed sources. Aggregate and individual findings in the form of bar graphs were made available to participants to view and download once they had completed the survey. Participants were also able to download contact details for support and referral services at no data cost. CONCLUSIONS: Data-free survey methodology breaks new ground and demonstrates potential not previously considered. Reach is greater than achieved through phone surveys and some social media platforms, men are not usually included in parent surveys, costs are lower than phone surveys, and the technology allows for immediate feedback to respondents. These factors suggest that zero-rated, or no-cost, services could provide a feasible, sustainable, and equitable basis for ongoing interactions with families of young children.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".