School-based caries prevention and the impact on acute and chronic student absenteeism
Bibliographic record
Abstract
Abstract Background Poor oral health is negatively associated with absenteeism, being attributed to millions of lost school days per year. The role of school-based dental programs that address oral health inequities on student attendance has not yet been explored. Methods Caried Away was a longitudinal, cluster-randomized, non-inferiority trial of preventive medicines for dental caries used in a school-based program. To explore the potential impact of caries prevention on attendance, we extracted data on average school absenteeism and the proportion of chronically absent students from publicly-available datasets maintained by the New York City Department of Education for years before, during, and after program onset. Data were obtained for all Caried Away schools as well as a group of untreated comparator schools. Total absences and the proportion of chronically absent students were modeled using multilevel mixed effects linear and two-limit tobit regression, respectively. Multiple model specifications were considered, including exposures to time-varying treatments across multiple years. Models also included a group of untreated comparator schools. Results In years in which treatment was provided through a school-based comprehensive caries prevention program, schools recorded approximately 944 fewer absences than in non-treatment years (95% CI = −1739, −149). Averaged across all study years, schools receiving either treatment had 1500 fewer absences than comparator schools, but this was not statistically significant. In contrast, chronic absenteeism was found to significantly decrease in later years of the program (B = -.037, 95% CI = -.062, -.011). Removing data for years affected by COVID-19 eliminated the significant reduction in total absences during treatment years, yet still showed a marginally significant interaction for chronic absenteeism. Discussion Though originally designed to mitigate access barriers to critical oral healthcare, early integration of school-based dental programs may positively impact school attendance. However, concerns over the reliability of attendance records due to the closing of school facilities resulting from COVID-19 may mask the true effect.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".