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Enregistrement W2573415733 · doi:10.1111/jan.13254

Bedside to bench: re‐thinking nursing research

2017· editorial· en· W2573415733 sur OpenAlexaboutno aff
Seamus Cowman

Notice bibliographique

RevueJournal of Advanced Nursing · 2017
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueHealth Sciences Research and Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBench to bedsideNursingMedicinePsychologyMedical physics

Résumé

récupéré en direct d'OpenAlex

There is very little clarity or agreement in the nursing profession on the best way to teach and examine students on research understanding, let alone develop and appraise nursing research application to patient care. Nursing research, in the curriculum, is a patchwork of interpretation, and in application it is delivered with varied levels of complexity across schools of Nursing and Midwifery, often with disregard to distinguishing undergraduate from postgraduate research teaching. This is not uncommon in health professions education, as this lack of clarity on teaching research also extends to medical schools. Throughout many years of external examining and institutional review, I have observed an indifference and uncertainty among academics towards research, which leads me to conclude that research all too often is viewed as an academic exercise. Such observations are supported through failings in research application to patient care activities. In nursing education, we need a fundamental review of nursing research from its conception to its application, incorporating how best to teach, examine and apply nursing research in undergraduate and post graduate education. Realistic learning outcomes with incremental building of research teaching content from research appreciation to advanced research methods is key to a successful approach. The determination of appropriate methods of student assessment will require profiling of content with progression from understanding nomenclature, to interpretation and systematic reviewing of literature (undergraduate), to critiquing and undertaking pilot study research work (post graduate), to the competencies of the commanding role of Principal Investigator. It should also be mandatory that all nursing research activity in whatever form should have meaningful links with clinical nursing and patient care. In health professions, the foundations for research were established during the formalization of structured education and professional regulation. The application of science into medical and nursing health services research is manifest in a model which aimed to improve the diffusion of knowledge from the basic sciences into patient care. Later, translational research was projected as a gateway which was supposed to fill a gap between knowledge produced at the university laboratory bench and its use at the bedside. The Canadian Institute for Health Research (2004) stated that translation research ‘encompasses all steps between the creation of new knowledge and its application to yield beneficial outcomes for society’ (p. 3). However, over a decade later, we have very little evidence to suggest that this model has been successful and there is little clarity on how such resource investment has been used for the benefit of patients. Contopoulos-loannidis et al. (2003) identified that less than 25% of highly promising biomedical discoveries resulted in a published randomized clinical trial and less than 10% were established in clinical practice within 20 years. The foundations of translational research, in principle, espoused a dual process: ‘Bench to Bedside’ and ‘Bedside to Bench’. The evidence suggests that the Bench to Bedside paradigm has dominated and Bedside to Bench efforts have been limited. One suggestion could be that the scientific aspects of research are poorly understood by clinicians and the difficulties of accessing and managing patients are poorly appreciated by academics. Therefore, the profession of nursing and indeed the medical profession are caught in a schism and are conflicted in trying to ensure the application of research to practice within the established biomedical research model of bench to bedside. The NIH funded nearly $15 billion of basic science research in 2009 and it may be argued that the level of investment in the Bench to Bedside model has not resulted in a commensurate level of sustained activity in evidence-based practice. Such concerns are expressed by Grol (2001) who suggests that in health care 30–40% of patients do not receive treatments based on proven effectiveness and up to 25% of patients receive unnecessary care or care that is potentially harmful. One of the many examples is, Hydrogen Peroxide (H2O2) which is still being used for wound cleaning, primarily as an antiseptic agent. However, it has no direct benefit as an antiseptic, but is associated with significant risk (Reid et al. 2011). It is now time for the health professions, including the nursing profession, to focus its efforts on developing the Bedside to Bench model. The interpretation and application of the Bedside to Bench model has limited discourse in the published literature. This may be related to Marincola's (2003) claim, that prestigious journals, appear more fascinated with the mythology of transgenic and knock-out mice than the humble reality of human disease. The advantages of the Bedside to Bench model are that the research is embedded in patient care and the process and outcomes have a direct bearing on improving care provided to patients. A methodological dominance of an interventional and outcomes research approach in the Bedside to Bench approach is consistent with models of nursing theory and the nursing process. In recent times, I have been focusing my research efforts on the application of the Bedside to Bench approach in my selection and supervision of post graduate students and also through the agreement of a nursing research strategy with one of our associated large teaching hospitals in Bahrain. Through the determination and adoption of a basic Bedside to Bench research model, post graduate students at MSc and PhD level have completed studies on topics which have resulted in change to patient care policy and clinical practice. Such topics include: patient compliance with Diskus inhalers, (Mac Hale et al. 2014); 30-degree tilt for pressure ulcer prevention (Moore et al. 2013); Changing analgesia and sedation management in the Paediatric Intensive Care Unit (Magner et al. 2016); and my most recent postgraduate student topic Improving Health Outcomes in Type 2 Diabetes (T2 DM), in Bahrain, through a Nurse-led patient and family intervention. Evidence-based practice sets out to addresses the growing body of healthcare knowledge supported by different levels of evidence for best practice; however, the fundamental challenge remains, of how to most effectively close the gap between what is known and what is practiced. One of the qualities of the Bedside to Bench research approach is that it is embedded in practice and, therefore, it places a clinical value on any proposed research and supports the process of finding solutions to problems in uncertain, complex healthcare environments.

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)0,019
score de la tête « metaresearch » (Gemma)0,039
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,100
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0190,039
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0060,000
Communication savante0,0000,001
Science ouverte0,0020,000
Intégrité de la recherche0,0010,011
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 Opus0,241
Tête enseignante GPT0,639
Écart entre enseignants0,398 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations4
Publié2017
Routes d'admission1
Résumé présentoui

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