A288 PHYSICIAN PERSPECTIVES OF MALNUTRITION CARE IN NOVA SCOTIA: A MORE-2-EAT (M2E) NOVA SCOTIA PHASE 2 QUALITATIVE SUBSTUDY
Notice bibliographique
Résumé
Abstract Background Malnutrition is a clinical entity that is often underdiagnosed due to a lack of standard nutrition status screening during patient encounters, a lack of malnutrition education throughout medical training, inadequate resources to provide proper nutritional care, and differing perceptions regarding the importance of this condition. Amongst patients whose malnutrition is left untreated, approximately two thirds of them will experience further decline in their nutritional status. It is therefore important that the nutritional status of each patient be evaluated with every healthcare encounter where malnutrition may be relevant. Purpose The purpose of this study is to assess generalist and specialist physician perspectives on patient malnutrition care at various Nova Scotia healthcare sites. The aim is to better understand physician viewpoints and attitudes towards malnutrition and nutrition care, its role in their patient care, and what factors might facilitate or impede its effective use in clinical practice. Method Using the Consolidated Framework of Implementation Research (CFIR) and Theoretical Domains Framework (TDF) approaches and ethics approval from the Nova Scotia Health Authority, individually recorded virtual interviews were conducted with physicians working in Nova Scotia. Standardized questions on malnutrition were asked to a target of 12-24 physicians Responses were transcribed and qualitatively analyzed using NVivo software by a professional data analyst. Result(s) To date, ten interviews have been completed. Preliminary qualitative analysis indicates that while all physicians agreed that malnutrition is an important aspect of a patient’s care, its consistent screening and ongoing management is variable. Key Theoretical Domains identified were Knowledge, Skills, Social/Professional Role and Identity, Beliefs about Capabilities, Memory Attention and Decisions Processes, and Social Influences. Overall, most physicians had a knowledge deficit related to nutrition care and malnutrition, which led to uncertainty on how to screen or manage it. Standardized malnutrition screening tools were infrequently used. This responsibility was often deferred to the dietitian, thereby minimizing the role that physicians play or believe they have in its management. A lack of time during clinical encounters was also a key contributing factor. Conclusion(s) Strategies to optimize physician involvement in and awareness of nutrition care include increased education to train physicians to recognize and manage malnutrition in patients. The use of health system resources such as standardized malnutrition screening tools when malnutrition may be an issue can help with earlier identification and subsequent management. In addition, a team-based approach consisting of healthcare professionals with knowledge of malnutrition that actively involves the physician may be the most appropriate way for patient malnutrition to be effectively managed and provide education to both the physician and the patient. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest D. Veldhuijzen van Zanten Shareholder of: N/A, Consultant of: N/A, Employee of: N/A, Paid Instructor of: N/A, Speakers bureau of: N/A, L. Gramlich Grant / Research support from: Baxter, research funds, principal investigator; Nestle, education funds, chair; and Fresenius Kabi, research funds, principal investigator., Consultant of: Abbott, honorarium for consultant/advisory board, L. Cahill Grant / Research support from: Canadian Institutes of Health Research (CIHR), Research Nova Scotia, Nova Scotia Health Research Fund, Dalhousie University’s Internal Medicine Research Fund (UIMRF), Nova Scotia Health Research Foundation, Queen Elizabeth II Foundation.
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 | 0,006 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».