Assessing medical student learning in assessing the quality ofhealth information on the internet and communicating the skill topatients
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Notice bibliographique
Résumé
BACKGROUND: Patients increasingly turn to the internet for health information. However, seeking valid information can be difficult because of the speed of accumulation of information and lack of control. HealthInSite, the Canadian Health Network, the Health On the Net Foundation and the QUality Information ChecKlist have created criteria to assess internet health information. The fourth semester students at the Manipal College of Medical Sciences, Pokhara, Nepal, were taught to assess health information online and to communicate the same to simulated patients. Student feedback regarding the exercise was collected using a questionnaire. METHODS: The exercise was carried out during the pharmacology practical sessions in small groups of seven or eight students each. The students developed their own checklist using information from the organisation websites mentioned above. Each group analysed a particular health website. During the second session the groups communicated the critical appraisal criteria to a simulated patient. Then the patient chose websites for a particular disease condition. Formative assessment of the sessions was carried out. A questionnaire was used to collect student feedback about the sessions. Basic demographic information was collected. Student attitude was studied by noting their degree of agreement with a set of seven statements using a Likert-type scale. The median score was calculated. RESULTS: A total of 56 of the 73 fourth semester students participated. The gender ratio was equal. The common nationalities were Indians, Nepalese and Sri Lankans. The median score was 27 (maximum score 35) and the interquartile range was 4. There were no significant differences in the total scores among different subgroups of respondents. The students wanted similar sessions to be frequently incorporated during the course. Formative assessment revealed that the groups worked cohesively. They were able to analyse the given website appropriately and were successful in communicating the assessment criteria to the simulated patient. CONCLUSIONS: The sessions should be continued and strengthened and could be expanded to other semesters and especially to students during the clinical years of study. Preliminary feedback was positive but more detailed studies are required.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,062 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle