An examination of the efficacy of specific nursing interventions to the management of pain in cancer patients
Notice bibliographique
Résumé
Aim of the Study: The aim of this study was to determine if the nursing interventions of patient education and multidisciplinary coordination of care were able to improve pain control in the cancer patient in an acute hospital setting. Background of the Study: The role of the nurse in cancer pain management has been defined as being that of an educator, coordinator of care and advocate. A nurse with adequate knowledge of pain and its application to the cancer population and functioning in the role as defined is believed to be able to overcome many of the barriers that exist in implementing adequate analgesia and improve pain management in cancer patients. Design of the Study: A randomized experimental control group design was utilized. The study comprised 3 experimental groups and one control group incorporating pre and post testing. The Intervention of the Study: Experimental group one: subjects received education regarding their pain management which was tailored to meet their specific needs. Experimental group two: subjects underwent a pain assessment and construction of a care plan which was communicated verbally to the treating medical and nursing team and followed up with a written report which was documented in the history and sent to the treating medical physician. Experimental group three: subjects received the combined interventions administered to groups one and two. Control group four: subjects were assessed and all information was record in the same manner as for the experimental groups. The control group received their usual care during the study and their pain scores were measured at the same time intervals as the three experimental groups. Instrumentation: The Wisconsin Brief Pain Questionnaire was used for the assessment of all subjects. The McGill Pain Questionnaire was used as the outcome measure following intervention. Data Analysis: A one-way analysis of variance was used to detect the differences between the intervention groups and the control group. T-Tests were used to detect the differences between the groups incorporating a Bonferroni adjustment for frequent T tests. Results: The main effect demonstrated a significant difference between the treatment groups and control at a significance level of 0.002. T-Tests showed no significant difference between control and communication groups and no significant difference between education and combined groups. A significant difference was detected between education and control and between combined and control. Conclusions: Nursing interventions of patient education, coordination of care and advocacy can significantly improve cancer pain management. Intervention was tailored to meet the specific patient needs based on findings from the assessment and was dependent upon an adequate knowledge base. The nursing intervention of education was the most powerful of the three intervention types and its success was in tailoring to each individual. However, it is believed that with further recognition of the role of the nurse as coordinator of care will lead to greater improvements in cancer pain management.
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 | 0,002 | 0,015 |
| 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) | 0,002 | 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 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 ».