Initial perceptions of, and intention to use, an online guideline adaptation framework
Notice bibliographique
Résumé
AIM: The aim of this research was to evaluate CAN-Implement.Pro as a structured and systematic process for planning local evidence implementation, to develop a contextual and demographic profile of potential users and assess their initial perceptions and intention to use CAN-Implement.Pro. METHODS: Ethics approval was obtained from the University of Adelaide Human Research Ethics Committee (Approval number: H-2016-157). A descriptive cross-sectional study was undertaken to capture the demographic characteristics of participants, as well as their initial perceptions of, and intention to use, the software for guideline adaptation projects. RESULTS: A total of 21 individuals representing guideline groups completed the survey. Only 43% had taken part in at least one previous implementation project. Thirty-three percent reported embarking on their first implementation project; 24% had yet to participate in an evidence implementation project. Nursing was the most highly referenced profession at 75%, followed by medical specialties (40%); two respondents indicated allied health professions were included in their implementation group. Respondents represented countries or regions of high and upper middle income as classified by the WHO Regional Office for the Eastern Mediterranean. The majority (67%) found CAN-Implement.Pro to be well-organized, easy to navigate and reliable. Most (80%) also indicated they were more likely to return to the software than not; 20% were neutral. In terms of overall satisfaction, more than half (60%) were very satisfied or satisfied, a third (33%) was neutral and 7% were dissatisfied. Over 66% of the respondents considered their group to be familiar with the knowledge-to-action model. A slightly higher percentage (74%) reported software based upon the knowledge-to-action model had a strong conceptual framework. In terms of evidence informed functionality, 75% of the respondents concluded that the software could assist guideline groups to provide structure for their implementation planning; a similar proportion (75%) indicated that the software would also enhance or improve coordination, communication and logistics management in guideline-related implementation projects. Participants were familiar with a range of resources, models, theories and frameworks for implementation, implementation planning and guideline adaptation. The most common frameworks were related to behavioural theories or variations of the Promoting Action on Research Implementation in Health Services framework. CONCLUSION: Eighty percent of the respondents indicated that their group would be likely to use the software to guide implementation planning in future projects, whereas 20% were neutral. In terms of expectations for contemporary software, multimedia resources rated highly, as did interactive components within the knowledge-to-action model.
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 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».