Determinants of Influenza Vaccination among Healthcare Workers
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Bibliographic record
Abstract
OBJECTIVE: To identify the determinants of influenza vaccination and the moderators of the intention-behavior relationship among healthcare workers (HCWs). DESIGN: Prospective survey with 2-month follow-up. SETTING: Three university-affiliated public hospitals. PARTICIPANTS: Random sample of 424 HCWs. METHODS: The intention of an HCW to get vaccinated against influenza was measured by means of a self-administered questionnaire based on an extended version of the theory of planned behavior. An objective measure of behavior was extracted 2 months later from the vaccination database of the hospitals. RESULTS: Controlling for past behavior, we found that the determinants of influenza vaccination were intention (odds ratio [OR], 8.32 [95% confidence interval {CI}, 2.82-24.50]), moral norm (OR, 3.01 [95% CI, 1.17-7.76]), anticipated regret (OR, 2.33 [95% CI, 1.23-4.41]), and work status (ie, full time vs part time; OR, 1.99 [95% CI, 1.92-3.29]). Moral norm also interacted with intention as a significant moderator of the intention-behavior relationship (OR, 0.09 [95% CI, 0.03-0.30]). Again, apart from the influence of past behavior, intention to get vaccinated was predicted by use of the following variables: attitude (beta=.32; P<.001), professional norm (beta=.18; P<.001), moral norm (beta=.18; P<.001), subjective norm (beta=.09; P<.001), and self-efficacy (beta=.08; P<.001). This latter model explained 89% of the variance in HCWs' intentions to get vaccinated against influenza during the next vaccination campaign. CONCLUSIONS: Our study suggests that influenza vaccination among HCWs is mainly a motivational issue. In this regard, it can be suggested to reinforce the idea that getting vaccinated can reduce worry and protect family members.
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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 | 0.001 | 0.006 |
| 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 it