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Enregistrement W3026096580 · doi:10.1097/ncc.0000000000000855

Building Capacity in Cancer Nurses to Deliver Self-management Support: A Call for Action Paper

2020· article· en· W3026096580 sur OpenAlexaffabout
Raymond J. Chan, Deborah K. Mayer, Bogda Koczwara, Victoria Loerzel, Andreas Charalambous, Oluwaseyifunmi Andi Agbejule, Doris Howell

Notice bibliographique

RevueCancer Nursing · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueDiabetes Management and Education
Établissements canadiensPrincess Margaret Cancer CentreUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineWorkforcePsychosocialNursingCancerQuality of life (healthcare)Call to actionSocial supportFamily medicinePsychiatryPsychologyPsychotherapistBusiness

Résumé

récupéré en direct d'OpenAlex

With cancer being recognized as a chronic illness, self-management has been identified as integral to person-centered cancer care.1 Self-management is defined as “the individual’s ability to manage the symptoms, treatment, physical and psychosocial consequences, and lifestyle changes inherent in living with a chronic condition.”2 The ever-changing cancer care environment, with many aspects of the care being shifted to the home setting, has created and sustained a pressing need for patients and informal/family caregivers to self-monitor and self-manage impacts of their cancer, treatment-related adverse effects, and cancer-related symptoms. However, those tasks cannot occur without support. Cancer nurses play pivotal roles in providing self-management support (SMS) and improving patient outcomes throughout the cancer care trajectory.3–5 Systematic reviews have reported that self-management education and support, delivered by nurses educated and skilled in facilitating patient engagement, can result in positive behavioral change and better clinical outcomes in chronic conditions (eg, reduced blood pressure in hypertension, lower A1c in diabetes,6 cancer, reduced symptom severity, better quality of life).7–9 Better integration of SMS in cancer care requires effective implementation strategies at multiple levels including system-level policy change, strengthening of the evidence base through effectiveness and translational research, and workforce capacity building. This editorial argues the importance of capacity building in the cancer nursing workforce to provide high-quality SMS to cancer survivors. Several key international cancer nursing education frameworks10–12 acknowledge effective SMS provision as a core competency of cancer nurses. However, it was not the intent for these frameworks to detail specific SMS-related knowledge and skills in depth. Further, SMS-related knowledge and skills for nurses are seldom integrated into ongoing professional development pathways in cancer programs, or programs in undergraduate and graduate curricula.13 Building on existing frameworks applied to wider chronic disease and other disciplines,14,15 we have categorized the core competencies specific to SMS for cancer nurses into the following 3 domains: (1) General person-centered skills (ie, participatory communication skills that promote active patient/caregiver/survivor involvement in managing cancer and health; health promotion and prevention; assessment of health risk factors and self-management capacity including activation level and capability; tailoring patient education to health and cultural literacy; and developing shared agenda between the provider and the patient/survivor). (2) Behavior change skills (ie, application of health behavior change models and theory, mastery learning, motivational interviewing, health coaching, 5 A’s counseling techniques,16 goal setting and action planning, structured problem solving, behavior adjustment in response to self-monitoring, coaching for positive coping strategies, and enhancement of self-efficacy; facilitation of group self-management programs; and supporting patient decision-making, collaborative problem definition and care planning). (3) Organizational/system skills (ie, measurement-based practice and evaluation of health outcomes for “real-time” tailoring of care; navigational skills to facilitate transitions across phases in the cancer trajectory; facilitating patient navigation of peer and other resources; environmental modification to create a context for successful SMS; and remote monitoring and telephone triage for self-management). To further advance this area of practice, we call for 3 priority actions for the cancer nursing leadership community. First, we need to continue to advocate for the inclusion of SMS-related knowledge and skill development in the undergraduate and graduate curricula. The undergraduate educational efforts may be provided in a broader chronic disease management context. Core skills and knowledge should also be reflected in relevant specialty certification examinations where applicable. Second, research and education leaders should continue to strengthen the knowledge base and develop guidance through global consensus on the standards for knowledge and skill requirements specific to SMS at various levels of cancer nursing practice (ie, what should be the differences in standards for all nurses vs many nurses vs some nurses vs few nurses?).10 Last but not least, specific considerations regarding SMS in various social, economic, cultural, and geographical contexts should be taken into account in formulating future research and education strategies.1 As the largest cancer care workforce, nurses are well placed to systematize effective SMS, ultimately improving behavioral and health outcomes for all cancer survivors. Raymond Javan Chan, PhD, MAppSc (Research), BN, RN, GAICD Editorial Board Member, Cancer Nursing Princess Alexandra Hospital, Metro South Health, Queensland, Australia, and School of Nursing, Queensland University of Technology, Brisbane, AustraliaDeborah K. Mayer, PhD, RN, AOCN, FAAN School of Nursing, University of North Carolina, and UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NCBogda Koczwara, MBioethics, BM, BS, AM, FRACP, FAICD Flinders Medical Centre and Flinders University, Adelaide, AustraliaVictoria Loerzel, PhD, RN, OCN, FAAN College of Nursing, University of Central Florida, Orlando, FLAndreas Charalambous, PhD, MSc, BSc, RN, PGCert (Research) Department of Nursing, Cyprus University of Technology, and Department of Nursing, University of Turku, FinlandOluwaseyifunmi Andi Agbejule, BRadTherapy School of Nursing, Queensland University of Technology, Brisbane, AustraliaDoris Howell, PhD, RN Department of Supportive Care, Princess Margaret Cancer Research Center, and Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,836
Score d'incertitude au seuil0,520

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,083
Tête enseignante GPT0,373
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations19
Publié2020
Routes d'admission2
Résumé présentoui

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