Residents and Medical Students Correctly Answer Clinical Questions More Often with Google and UpToDate than With PubMed or Ovid MEDLINE
Notice bibliographique
Résumé
Objective – To determine which search tool (Google, UpToDate, PubMed or Ovid-MEDLINE) produces more accurate answers for residents, medical students, and attending physicians searching on clinical questions in anesthesiology and critical care. Searcher confidence in the answers and speed with which answers were found were also examined. Design – Randomized study without a control group. Setting – Large university medical center. Subjects –Subjects included 15 fourth year medical students (third and fourth year), 35 residents, and 4 attending physicians volunteered and completed the study. One additional attending withdrew halfway through the study. The authors were unsuccessful in recruiting an equal number of subjects from each group. Methods – A set of eight anesthesia and critical care questions was developed, based on their commonality and importance in clinical practice and their answerability. Four search tools were employed: Google, UpToDate, PubMed, and Ovid MEDLINE. In part I, subjects were given a random set of four of the questions to answer with the search tool(s) of their choice, but could use only one search tool per question. In part II, several weeks later, the same subjects were randomly assigned a search tool with which to answer all 8 questions. The authors state that “for data analysis, PubMed was arbitrarily chosen to be the “reference standard.”” Statistical analysis was used to identify significant differences between PubMed and the other search tools. Main Results – Part I: Subjects choosing a search tool were more likely to find a correct answer with Google or UpToDate. There were no statistically significant differences in confidence with answers between any of the search tools and PubMed. Part II: Though subjects were assigned a search tool, some questions were repeated from part I. For repeated questions, Ovid users (compared to PubMed users) were significantly less likely to find the correct answer for repeated questions. Otherwise, there was no statistically significant difference in questions answered correctly. Confidence did not differ. When asked to answer new questions, subjects using Google and UpToDate were significantly more likely to find a correct answer than PubMed users. UpToDate users were more confident. There was no statistical difference in primary outcome (correct answer with high confidence) between Google, Ovid, and PubMed. Pooled data from parts I and II, removing repeated questions: Subjects using Google and UpToDate were more likely to find correct answers. Confidence was highest among UpToDate users. Average search time per question (limited to 5 minutes per question) in ascending order of time spent was: UpToDate, Google, PubMed, and Ovid. Conclusion – While the number of participants is small, the results suggest that the popular search engine Google and the commercially produced secondary online source UpToDate are more useful and efficient for finding answers to questions arising in anesthesiology and critical care practice than tools focused exclusively on indexing the primary literature.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,104 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,003 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».