E-mailed Evidence Based Summaries Impact Physician Learning More than Practice
Notice bibliographique
Résumé
A Review of: Grad, Roland M., Pierre Pluye, Jay Mercer, Bernard Marlow, Marie Eve Beauchamp, Michael Shulha, Janique Johnson-Lafleur and Sharon Wood-Dauphinee. “Impact of Research-based Synopses Delivered as Daily E-mail: A Prospective Observational Study.” Journal of the American Medical Informatics Association (2008)15.2: 240-5. Objective – To determine the use and construct validity of a method to assess the cognitive impact of information derived from daily e-mail evidence based summaries (InfoPOEMs), and to describe the self-reported impact of these InfoPOEMs. Design – Prospective, observational study over a period of 150 days employing a questionnaire and rating scale. Setting – This study was conducted via the Internet between September 8, 2006 and February 4, 2007. Subjects – Canadian Medical Association (CMA) members who received InfoPOEMs via e-mail as of September 2006 were invited to participate. For inclusion in the analyses, a participant was defined as a practising family physician or general practitioner who submitted at least five ratings of InfoPOEMS during the study period (n=1,007). Methods – Volunteers completed a demographic questionnaire and provided informed consent online. Each subsequent InfoPOEM delivered included a link to a “ten-item impact assessment scale” (241). Participants checked “all that apply” of descriptive statements such as: My practice was (will be improved); I learned something new; I think this information is potentially harmful. Each combination of selections made was considered a pattern of cognitive impact. College of Family Physicians of Canada received continuing medical education (CME) credit for each InfoPOEM rated. Data were collected by the CMA and forwarded weekly to the investigators who used descriptive statistics, principal component analysis, and multilevel factor analysis to analyze the data. Main Results – 1,007 participants rated an average of 61 InfoPOEMs (ranging from five to 111). A total of 61,493 patterns of cognitive impact were submitted. Eighty-five different patterns were observed, i.e., there were 85 different combinations of the scale’s statements used. Ten patterns accounted for 89.4% of the reports. The top five patterns were: I learned something new (35.2%); No impact (17.1%); This information confirmed I did (will do) the right thing (9.6%); I learned something new AND My practice will be improved (9.4%); and, I was reassured (5.6%). I disagree with this information was checked at least once by 10.3% of the participants, and 8.0% checked I think this information is potentially harmful at least once. Conclusion – The authors applied a cognitive assessment instrument to determine the impact of InfoPOEMs e-mailed to primary care physicians in Canada and found that ten combinations of impact descriptors accounted for 89.4% of the total reports. Most suggested a positive impact on knowledge or practice. Of the total, 17.1% indicated No impact and 1.8% indicated the participant was frustrated as there was not enough information or nothing useful.
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 | 0,020 | 0,223 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».