The Exercise Oncology Knowledge Mobilization Initiative: An International Modified Delphi Study
Notice bibliographique
Résumé
Introduction Exercise is vital to health and well-being after a cancer diagnosis yet is poorly integrated in cancer care. Knowledge mobilization (KM) is essential to enhance exercise opportunities. We aimed to (1) develop and refine a list of highly important exercise oncology research and KM themes and (2) establish the relative importance of the themes for supporting the implementation of exercise as a standard of care for people living with and beyond cancer. Methods Informed by the Co-Produced Pathway to Impact KM framework, a modified Delphi study approach was used to develop, rate, and rank exercise oncology research and KM themes through an international stakeholder workshop and a three-round iterative online survey. Open-ended stakeholder feedback from cancer survivors, healthcare practitioners (HCPs), qualified exercise professionals (QEPs), policy makers, and researchers was used to update themes between survey rounds. Themes were ranked from highest to lowest importance and agreement was examined across all stakeholders and within stakeholder groups. Results A total of 269 exercise oncology stakeholders from 13 countries participated in the study. Twelve final exercise oncology research and KM themes were produced. The final top ranked research themes were related to: (1) QEP integration into primary cancer care teams, (2) Exercise oncology education for HCPs, and (3) Accessibility of cancer exercise programs & support services. There was statistically significant agreement between stakeholders ( p <0.001) and within stakeholder groups ( p ’s≤0.02) on the general rankings of themes (i.e., some themes generally ranked higher and lower compared to others). Low Kendall’s W statistics indicated variability related to the specific ranked order of the themes between stakeholders and within stakeholder groups. Moreover, there were key differences in the rankings for specific themes between policy makers and other stakeholder groups that highlight potentially important discordance in the research and KM priorities for policy makers that warrants further study. Conclusion These findings can be used to guide initiatives and align stakeholders on priorities to support exercise implementation as a standard of cancer care. Additional research is needed to better understand the differences in the proposed research and KM priorities across stakeholders.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».