Bibliographic record
Abstract
OBJECTIVES: Travel agents are in a key position to encourage travelers to seek consultation in travel clinics. Since the beginning of the year 2000, a newsletter specifically designed to sensitize travel agents to travel health has been published by the public health authorities and distributed to all travel agencies in Quebec. This study was undertaken to evaluate the utilization and appreciation of the newsletter by travel agents and its impact on preventive practices. METHODS: During the autumn of 2001, a cross-sectional descriptive survey was carried out among travel agencies in Quebec. Data were collected using a self-administered questionnaire sent by fax with a postal follow-up. RESULTS: A total of 252 of the 950 travel agencies contacted (27%) answered our questionnaire. In all, 78% of respondents said their agency receives the newsletter. Among these agencies, the majority of respondents considered that the subjects discussed in the newsletter are interesting (often or in general: 96%), that the subjects and preventive recommendations for travel destinations are useful in the travel agent's practice (often or in general: 89%), and generally presented in an adequate way (96%). According to the respondents, the newsletter encouraged them, often or very often, to inform travelers about travel-related health problems (70%) or to recommend a consultation in a travel clinic (63%). The impact of the newsletter on the recommendation to consult was greater among agents having more than 10 years' experience (odds ratio [OR] 3.2). When asked about the best way to send them the newsletter, only 31% identified bulk mailing, which was the current mode of distribution. CONCLUSION: Satisfaction rate with the newsletter appears to be high among respondents who receive it. However, the low response rate to the survey may indicate that as a whole, the travel agents' interest in the newsletter is mitigated. Despite the limitations of this study, the results will allow us to modify some aspects of the publication, especially regarding its distribution.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".