Unleashing the Potential of Primary Care Nurses in Chronic Pain Management: A Delphi Study on Priority Activities
Notice bibliographique
Résumé
<h3>Context:</h3> Chronic pain stands as a leading cause of disability globally, with patients often reporting inadequate access to primary care. Relevant primary care nursing activities for CP management remain poorly defined, limiting the full utilization of nurses9 competencies and expertise in chronic disease management. <h3>Objective:</h3> To identify and prioritize nursing activities for chronic pain management in primary care by adopting nurse and patient perspectives. <h3>Study Design, Setting, and Participants:</h3> We conducted a three-round Delphi study with nurses from primary care practices and patients living with pain for more than three months across Québec, Canada. This study was conducted in partnership with two patient partners living with chronic pain. <h3>Instrument and Outcome Measures:</h3> The research utilized web-based questionnaires within REDCap<sup>®</sup>. In the initial round, panellists identified nursing activities for chronic pain management they deemed most important through open-ended questions. In the two subsequent rounds, nursing activities were (items) were assessed for their importance using a 9-point Likert scale. Activities achieving agreement (≥75% of participants rating the importance at 7, 8, or 9, i.e., priority activities) composed the list from rounds 2 to 3 and the final list. Mean scores (and standard deviations) were also calculated for each activity to rank their importance. <h3>Results:</h3> 48 nurses and 122 patients participated (n=170) throughout the process. From 47 nursing activities derived from 1167 suggestions in the first round, 41 were prioritized by ≥75% of participants by the final round. These activities were grouped into four domains: global assessment (n = 15, 36.6% of all activities), care management (n = 10, 24.4%), health promotion (n = 7, 17.1%), and interprofessional collaboration (n = 9, 22.0%). The top three nursing activities based on the final mean score were: Assessing dimensions of pain experience, Screening signs and symptoms of mood disorders, and Establish a therapeutic alliance with empathic approach. <h3>Conclusions:</h3> Nurses and patients identified a shared set of nursing activities for primary chronic pain care that aligns with usual care already provided by nurses to patients living with chronic diseases. Our results will guide primary care practices and nurses’ activities to improve chronic pain management.
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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 | 0,008 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| 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 ».