Geriatric Nursing In Primary Care: Addressing The Complex Needs Of An Aging Population
Notice bibliographique
Résumé
The management of patients in primary care settings is a complex and continuously changing task that's essential for meeting the diverse healthcare needs associated with aging. Based on research, the review emphasizes the prevalence of chronic conditions among older adults, highlighting the importance of proactive and systematic approaches to monitor and manage these conditions effectively. Educating patients plays a role in enabling individuals to engage in their healthcare journey actively. Collaboration with pharmacists is vital for optimizing medication plans and ensuring safety. Dealing with decline requires efforts across different disciplines, focusing on collaboration between primary care providers and specialists. Nondrug interventions like stimulation therapy and caregiver education make an impact on improving both patients' and families' quality of life. Addressing limitations, fall risks, and nutritional concerns underscores the need for an approach to clinical care. Physical therapists, occupational therapists, and geriatric nurses work together to develop strategies that address the challenges faced by elderly patients. Effective pain management, mental health support, and end-of-life care emphasize the importance of putting patients at the center of care through assessments and evidence-based treatments. With advancements in research, technology, and interventions in nursing within primary care settings, it's crucial for healthcare professionals to stay updated to provide optimal care. Keyword: Chronic Conditions, Cognitive Decline, End-of-life Care, Geriatric Nursing, Mental Health Abstract The management of patients in primary care settings is a complex and continuously changing task that's essential for meeting the diverse healthcare needs associated with aging. Based on research, the review emphasizes the prevalence of chronic conditions among older adults, highlighting the importance of proactive and systematic approaches to monitor and manage these conditions effectively. Educating patients plays a role in enabling individuals to engage in their healthcare journey actively. Collaboration with pharmacists is vital for optimizing medication plans and ensuring safety. Dealing with decline requires efforts across different disciplines, focusing on collaboration between primary care providers and specialists. Nondrug interventions like stimulation therapy and caregiver education make an impact on improving both patients' and families' quality of life. Addressing limitations, fall risks, and nutritional concerns underscores the need for an approach to clinical care. Physical therapists, occupational therapists, and geriatric nurses work together to develop strategies that address the challenges faced by elderly patients. Effective pain management, mental health support, and end-of-life care emphasize the importance of putting patients at the center of care through assessments and evidence-based treatments. With advancements in research, technology, and interventions in nursing within primary care settings, it's crucial for healthcare professionals to stay updated to provide optimal care.
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 | 0,004 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».