The yield and usefulness of PAIN+ and PubMed databases for accessing research evidence on pain management: a randomized crossover trial
Notice bibliographique
Résumé
Abstract Introduction PAIN+and PubMed are two electronic databases with two different mechanisms of evidence retrieval. PubMed is used to “Pull” evidence where clinicians can enter search terms to find answers while PAIN+is a newly developed evidence repository where along with “Pull” service there is a “Push” service that alerts users about new research and the associated quality ratings, based on the individual preferences for content and altering criteria. Purpose The primary purpose of the study was to compare yield and usefulness of PubMed and PAIN+in retrieving evidence to address clinical research questions on pain management. The secondary purpose of the study was to identify what search terms and methods were used by clinicians to target pain research. Study design Two-phase double blinded randomized crossover trial. Methods Clinicians (n = 76) who were exposed to PAIN+for at least 1 year took part in this study. Participants were required to search for evidence 2 clinical question scenarios independently. The first clinical question was provided to all participants and thus, was multi-disciplinary. Participants were randomly assigned to search for evidence on their clinical question using either PAIN+or PubMed through the electronic interface. Upon completion of the search with one search engine, they were crossed over to the other search engine. A similar process was done for a second scenario that was discipline-specific. The yield was calculated using number of retrieved articles presented to participants and usefulness was evaluated using a series of Likert scale questions embedded in the testing. Results Multidisciplinary scenario:Overall, the participants had an overall one-page yield of 715 articles for PAIN+and 1135 articles for PubMed. The topmost article retrieved by PAIN+was rated as more useful (p = 0.001). While, the topmost article retrieved by PubMed was rated as consistent with current clinical practice (p = 0.02). PubMed (48%) was preferred over PAIN+(39%) to perform multidisciplinary search (p = 0.02). Discipline specific scenario:The participants had an overall one-page yield of 1046 articles for PAIN+and 1398 articles for PubMed. The topmost article retrieved by PAIN+was rated as more useful (p = 0.001) and consistent with current clinical practice (p = 0.02) than the articles retrieved by PubMed. PAIN+(52%) was preferred over PubMed (29%) to perform discipline specific search. Conclusion Clinicians from different disciplines find both PAIN+and PubMed useful for retrieving research studies to address clinical questions about pain management. Greater preferences and perceived usefulness of the top 3 retrieved papers was observed for PAIN+, but other dimensions of usefulness did not consistently favor either search engine. Trial registration Registered with ClinicalTrials.gov Identifier: NCT01348802 , Date: May 5, 2011.
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 | 0,038 | 0,058 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».