Missed appointments: More complicated than we think
Bibliographic record
Abstract
Access to health care is a fundamental value of our Canadian health care system. Yet, missed appointments are a daily reality across Canadian paediatric outpatient settings and can jeopardize care. Young children who miss appointments are reported as having more adverse outcomes (1). Missed appointments are viewed as inefficient and a waste of valuable health care resources. As a result, many outpatient services have adopted a policy regarding discharge from service after a specific number of missed appointments. Parents who miss appointments are labelled pejoratively with terms such as ‘no-shows’, ‘noncompliant’, ‘nonattenders’, ‘hard to reach’, ‘disinterested’ or ‘lacking motivation’—all terms blaming missed appointments on families. To date, researchers have focused primarily on the predictors of attendance and nonattendance and its impact on service delivery (2). Engaging parents as an approach to deepen our understanding of missed appointments is rarely reported in the literature. The aim of our study was to engage mothers to share their experiences in missing outpatient neonatal follow-up (NFU) programs.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".