Improving Response Rates: Introducing an Anonymous Longitudinal Survey Research Protocol for Veterinary Medical Students
Bibliographic record
Abstract
With the Journal of Veterinary Medical Education's recent summer 2005 theme issue on stress, the mental-health concerns of veterinary medical students has been brought to the forefront of the field. Since it is anticipated that research on this topic will continue and that educational institutions may implement changes based upon these results, it is of the utmost importance that this research be of the highest quality. Of particular concern with human-subject inquiries are response rates and confidentiality. In order to accommodate these concerns, an example of a survey research protocol that promotes high response rates and minimizes threats to internal validity influenced by student mistrust in assurances of confidentiality is presented. Specifically, the protocol is designed to ensure anonymity and to preserve the ability to track students longitudinally through the use of anonymous longitudinal identifiers. This protocol was tested with the first-year class of veterinary medical students at Kansas State University in October 2004 and March 2005. The two data collection periods yielded 90% and 76% response rates, respectively. The matching rate of participants, according to the anonymous longitudinal identifiers from Time 1 to Time 2, was 88%.
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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 | 0.099 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".