Challenges in recruiting frequent users of ambulance services for a community paramedic home visit program
Bibliographic record
Abstract
BACKGROUND: The Community Paramedicine at Home (CP@home) program is a health promotion program where community paramedics conduct risk assessments with frequent 9-1-1 callers in their homes, with a goal of reducing the frequency of 9-1-1 calls in this vulnerable population. The effectiveness of the CP@home program was investigated through a community-based RCT conducted in four regions in Ontario, Canada. The purpose of this current recruitment study is to examine the challenges met when recruiting for a community randomized control trial on high frequency 9-1-1 callers. METHODS: Eligible participants were recruited from one of four regions participating in the CP@home program and were randomly assigned to an intervention group (n = 1142) or control group (n = 1142). Data were collected during the recruitment process from the administrative database of the four paramedic services. Whether they live alone, their parental ethnicity, age, reason for calling 9-1-1, reason for not participating, contact method, and whether they were successfully contacted were recorded. Statistical significance was calculated using the Chi-Squared Test and Fisher's Exact Test to evaluate the effectiveness of the recruitment methods used to enroll eligible participants in the CP@home Program. RESULTS: Of the people who were contacted, 48.0% answered their phone when called and 53.9% answered their door when a home visit was attempted. In Total, 110 (33.1%) of people where a contact attempt was successful participated in the CP@home program. Most participants were over the age of 65, even though people as young as 18 were contacted. Older adults who called 9-1-1 for a lift assist were more likely to participate, compared to any other individual reason recorded, and were most often recruited through a home visit. CONCLUSIONS: This recruitment analysis successfully describes the challenges experienced by researchers when recruiting frequent 9-1-1 callers, which are considered a hard-to-reach population. The differences in age, contact method, and reason for calling 9-1-1 amongst people contacted and participants should be considered when recruiting this population for future research.
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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 | 0.160 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".