Understanding Why Frequent Users of EMS Call 9-1-1: A Grounded Theory Study
Bibliographic record
Abstract
INTRODUCTION: Frequent users of emergency medical services (EMS) have disproportionately high 9-1-1 call frequency. Evidence suggests that this small group burdens the health care system, leading to misallocation of already-limited health resources. AIM: To understand frequent users' perceptions and experiences regarding EMS, as well as the driving factors underlying their frequent use. METHOD: A grounded theory approach guided our qualitative research process. Participants older than 17 years who called EMS five or more times in the past year were consecutively sampled where each participant was contacted in the order they appeared on our list of potential participants for interviews until data saturation was achieved. Transcripts were analyzed to derive common themes among frequent EMS callers. RESULTS: Frequent EMS calls often resulted from chronic medical conditions creating recurrent crisis situations, mental health issues as well as mobility issues, frequent noninjurious falls, and social isolation. Combined with these factors, perceptions of the purpose of EMS and social circumstances also contributed to the creation of complex health issues that influenced frequent EMS use. These findings can advise the development of future paramedicine programs and health promotion interventions.
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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 | 0.028 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".