MétaCan
Menu
← Retour à la cohorte
Enregistrement W4399298268

Applying the Narrow Forms of PubMed Methods-based and Topic-based Filters Increases Nephrologists’ Search Efficiency. A Review of: Shariff, S. Z., Sontrop, J. M., Haynes, R. B., Iansavichus, A. V., McKibbon, K. A., Wilczynski, N. L., Weir, M. A., Speechley, M. R., Thind, A. … Garg, A. X. (2012). Impact of PubMed search filters on the retrieval of evidence by physicians. CMAJ: Canadian Medical Association Journal, 184(3), E184-E190. doi: 10.1503/cmaj.101661

2012· review· en· W4399298268 sur OpenAlexaboutno aff
Kate Kelly

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typereview
Langueen
DomaineHealth Professions
ThématiqueHealth Sciences Research and Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer scienceMedicine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Objective – To determine whether the use ofPubMed methods-based filters and topic-basedfilters, alone or in combination, improvesphysician searching. Design – Mixed methods, surveyquestionnaire, comparative. Setting – Canada. Subjects – Random sample of Canadiannephrologists (n=153), responses (n=115),excluded (n=15), total (n=100). Methods – The methods are described in detailin a previously published study protocol by asubset of the authors (Shariff et al., 2010).One hundred systematic reviews on renaltherapy were identified using theEvidenceUpdates service(http://plus.mcmaster.ca/EvidenceUpdates)and a clinical question was derived from eachreview. Randomly-selected Canadiannephrologists were randomly assigned aunique clinical question derived from thereviews and asked, by survey, to provide thesearch query they would use to searchPubMed. The survey was administered untilone valid search query for each of the onehundred questions was received. The physician search was re-executed and compared to searches where either or both methods-based and topic-based filters were applied. Nine searches for each question were conducted: the original physician search, a broad and narrow form of the clinical queries therapy filter, a broad and narrow form of the nephrology topic filter and combinations of broad and narrow forms of both filters.Significance tests of comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to non-relevant articles) of the filtered and unfiltered searches were conducted. The primary studies included in the systematic reviews were set as the reference standard for relevant articles.As physicians indicated they did not scan beyond two pages of default PubMed results, primary analysis was also repeated on search results restricted to the first 40 records.The ability of the filters to retrieve highly-relevant or highly-cited articles was also tested, with an article being considered highly-relevant if referenced by UpToDate and highly-cited if its citation count was greater than the median citation count of all relevant articles for that question – there was an average of eight highly-cited articles per question.To reduce the risk of type I error, the conservative method of Bonferroni was applied so that tests with a p<0.003 were interpreted as statistically significant. Main Results – Response rate 75%. Physician-provided search terms retrieved 46% of relevant articles and a ratio of relevant to non-relevant articles of 1:16 (p<0.003). Applying the narrow forms of both the nephrology and clinical queries filters together produced the greatest overall improvement, with efficiency improving by 16% and comprehensiveness remaining unchanged. Applying a narrow form of the clinical queries filter increased efficiency by 17% (p<0.003) but decreased comprehensiveness by 8% (p<0.003). No combination of search filters produced improvements in both comprehensiveness and efficiency.When results were restricted to the first 40 citations, the use of the narrow form of the clinical queries filter alone improved overall search performance – comprehensiveness improved from 13% to 26 % and efficiency from 5.5% to 23%.For highly-cited or highly-relevant articles the combined use of the narrow forms of both filters produced the greatest overall improvement in efficiency but no significant change in comprehensiveness. Conclusion – The use of PubMed search filters improves the efficiency of physician searches and saves time and frustration. Applying clinical filters for quick clinical searches can significantly improve the efficiency of physician searching. Improved search performance has the potential to enhance the transfer of research into practice and improve patient care.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,148
score de la tête « metaresearch » (Gemma)0,402
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,852
Score d'incertitude au seuil0,783

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1480,402
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,006
Bibliométrie0,0180,015
Études des sciences et des technologies0,0020,001
Communication savante0,0060,009
Science ouverte0,0030,004
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0220,004

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.

Tête enseignante Opus0,516
Tête enseignante GPT0,628
Écart entre enseignants0,112 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineMéthodes
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueDOAJ (DOAJ: Directory of Open Access Journals)→Même sujetHealth Sciences Research and Education→Travaux en français237 207→