A qualitative descriptive study exploring perspectives on a school-based take-home COVID-19 saliva testing program
Bibliographic record
Abstract
Objectives: Saliva testing, a safe and comfortable screening modality, can effectively detect SARS-CoV-2 in children. Recognizing the need for accessible testing in schools, a COVID-19 School Testing Program was launched across 677 schools, providing take-home saliva kits, educational materials, and ongoing support to families and school leadership. This study aimed to explore participants' experiences with the program to inform future school-based public health initiatives. Methods: Using a prospective qualitative descriptive design, we conducted semi-structured interviews until thematic saturation was reached. Interviews were audio recorded, transcribed, and analyzed through inductive content analysis, with reflexivity, use of a critical friend, and thick description ensuring methodological rigor. Twenty-one participants were interviewed. Results: Six themes emerged: (1) improved access, (2) flexibility in testing environment, (3) less invasive option, (4) convenient drop-off, (5) prompt results, and (6) enhanced school safety. Conclusion: Findings emphasize accessibility, convenience, and flexibility as essential for effective school-based viral testing models.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".