Patient views on reminder letters for influenza vaccinations in an older primary care patient population:a mixed methods study
Bibliographic record
Abstract
OBJECTIVES: To explore the perspectives of older adults on the acceptability of reminder letters for influenza vaccinations. METHODS: We randomly selected 23 family physicians from each Family Health and Primary Care network participating in a demonstration project designed to increase the delivery of preventive services in Ontario. From the roster of each physician, we surveyed 35 randomly selected patients over 65 years of age who recently received a reminder letter regarding influenza vaccinations from their physician. The questionnaires sought patient perspectives on the acceptability and usefulness of the letter. We also conducted follow-up telephone interviews with a subgroup of respondents to explore some of the survey findings in greater depth. RESULTS: 85.3% (663/767) of patients completed the questionnaire. Sixty-five percent of respondents recalled receiving the reminder (n=431), and of those, 77.3% found it helpful. Of the respondents who recalled the letter and received a flu shot (n=348), 11.2% indicated they might not have done so without the letter. The majority of respondents reported that they would like to continue receiving reminder letters for influenza vaccinations (63.0%) and other preventive services (77.1%) from their family physician. The interview participants endorsed the use of reminder letters for improving vaccination coverage in older adults, but did not feel that the strategy was required for them personally. CONCLUSIONS: The general attitude of older adults towards reminder letters was favourable, and the reminders appear to have contributed to a modest increase in influenza vaccination rates.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".