Social factors in frequent callers: a description of isolation, poverty and quality of life in those calling emergency medical services frequently
Bibliographic record
Abstract
BACKGROUND: Frequent users of emergency medical services (EMS) comprise a disproportionate percentage of emergency department (ED) visits. EDs are becoming increasingly overwhelmed and a portion of use by frequent callers of EMS is potentially avoidable. Social factors contribute to frequent use however few studies have examined their prevalence. This study aims to describe social isolation/loneliness, poverty, and quality of life in a sample of frequent callers of EMS in the Hamilton region, a southern Ontario mid-sized Canadian city. STUDY DESIGN: Cross-sectional quantitative study. METHODS: We surveyed people who called EMS five or more times within 12 months. A mailed self-administered survey with validated tools, and focused on four major measures: demographic information, social isolation, poverty, and quality of life. RESULTS: Sixty-seven frequent EMS callers revealed that 37-49% were lonely, 14% had gone hungry in the preceding month, and 43% had difficulties making ends meet at the end of the month. For quality of life, 78% had mobility problems, 55% had difficulty with self-care, 78% had difficulty with usual activities, 87% experienced pain/discomfort, and 67% had anxiety/depression. Overall quality adjusted life years value was 0.53 on a scale of 0 to 1. The response rate was 41.1%. CONCLUSIONS: Loneliness in our participants was more common than Hamilton and Canadian rates. Frequent EMS callers had higher rates of poverty and food insecurity than average Ontario citizens, which may also act as a barrier to accessing preventative health services. Lower quality of life may indicate chronic illness, and users who cannot access ambulatory care services consistently may call EMS more frequently. Frequent callers of EMS had high rates of social loneliness and poverty, and low quality of life, indicating a need for health service optimization for this vulnerable population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".