Le rôle de l'information sur Internet dans la consommation médicale : le cas des patients canadiens francophones et anglophones
Bibliographic record
Abstract
The aim of this research is to study the relationship between Internet information use and medical resources consumption by French-speaking and English-speaking Canadian patients. This relationship is assessed directly and indirectly through attitude variables. The choice to distinguish between French-speaking and English-speaking patients was justified by a mean comparison analysis. The analysis of the data obtained from the diffused quantitative questionnaire was performed using SPSS and PLS statistic tools. Results showed that the direct relationship between Internet information use and medical resources consumption is significant and positive for the two samples. However, it is stronger for the Frenchspeaking sample. This result probably reflects a greater concern regarding the offer of medical information on the Internet in the French language. Research contributions are theoretical and practical. On one hand, this research is the first to test the proposed model for two different populations in terms of used languages. On the other hand, the results of this study allow becoming aware of the existence of a possible problem regarding the offer of health information on the Web.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.005 | 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".