Evaluating modified effects of family factors on intervention to protect primary school students from the impact of heatwave
Bibliographic record
Abstract
Identifying the factors that may impact intervention effectiveness of primary students is crucial for developing targeted intervention strategies on heatwave adaption. The purpose of the study was to assess how the family factors could affect the intervention effects of primary school students to adapt heatwave, using the data from a previously conducted primary school-based intervention study. The study recruited 648 students (9–13 years old) and their parents from two primary schools in Dongtai of Jiangsu province, China. From May to September 2017, a 5-mon intervention for enhancing knowledge, attitude and practice (KAP) was implemented at the intervention school. The students' KAP scores and the family-related information were measured by designed self-administered questionnaires at intervention school and control school separately before and after intervention. The effects of the intervention were explored through the propensity score matching and difference-in-difference method (PSM-DID), and stratified analysis were conducted by family factors. The overall KAP score increased by 2.391 (95% CI: 1.881, 2.902) after intervention, which shows that the intervention was effective. The students whose parents with higher school educational attainment, parents with employment, and household number ≤3 achieved significantly higher increment of KAP scores than their counterparts. Although students whose parents in marriage achieved higher score increasing than parents not in marriage, the difference was non-significant. Our findings indicated that parental education status, working status and the household size were the influence factors of heatwave adaption interventions for primary school students. Future interventions should take parental education status, working status and household size into account to improve the effectiveness of heatwave adaption intervention for primary school students.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".