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Enregistrement W2080186864 · doi:10.1111/j.1365-2702.2010.03207.x

Commentary on Kocaman G, Seren S, Lash AA, Kurt S, Bengu N &amp; Yurumezoglu HA. Barriers to research usage by staff nurses in a university hospital. <i>Journal of Clinical Nursing</i> 19, 1908–1918

2010· letter· en· W2080186864 sur OpenAlexaboutno aff
Silvia Corchón

Notice bibliographique

RevueJournal of Clinical Nursing · 2010
Typeletter
Langueen
DomaineHealth Professions
ThématiqueHealth Sciences Research and Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)NursingNursing careNursing researchPsychologyMedicineHistory

Résumé

récupéré en direct d'OpenAlex

The paradigm of evidence-based practice (EBP) has been introduced internationally with the aim of applying research results in practice and deliver care based on sound evidence of what works (Rycroft-Malone et al. 2004, Pravikoff et al. 2005). In nursing, because of the focus of the discipline, evidence comes from an array of sources: an integration of research-based evidence with clinical experience, context characteristic and patients’ preferences (Reavy & Tavernier 2008). However, as many authors, including Kocaman et al. have stressed, decisions on nursing practice principally rely on the nurses’ personal experience and observations, not on research results. Considering its potential benefits for nursing care, there is a growing concern about the development of evidence-based nursing and nurses, at all levels, are increasingly expected to improve the quality of care through the incorporation of relevant research in decision-making (Roxburgh 2006, Hannes et al. 2007). In the literature, this has been called research utilisation, research use or research usage (RU) in Kocaman et al.’s (2010) article. Many authors have tried to clarify the reasons for the existing gap between research production and RU because, despite the increasing amount of research evidence, nursing practice remains reticent to apply its findings in practice (Profetto-McGrath et al. 2007, Reavy & Tavernier 2008). A good example can be found on Kocaman et al.’s article. This article offers interesting insights into the issue because it enlightens the situation in a specific context, the Turkish, which had not been studied before. This is necessary because most of the studies on RU have been conducted in countries with a research tradition such as the UK, the USA, Canada or Nordic countries, and results about the barriers to RU should not be directly translated to other contexts with different backgrounds and situations regarding nursing research, like Turkey (Corchon et al. 2010). In Kocaman et al.’s study, they used the most frequently used instrument in this kind of enquiry, the Barriers’ scale (Funk et al. 1991). Based on Roger’s model of Diffusion of Innovations, it is divided into four subscales to study barriers to RU: 1-Characteristics of the nurse; 2-Characteristics of the setting; 3-Characteristics of the innovation; and 4-Characteristics of the communication. Although this instrument has some limitations, the fact that it has been widely used in different contexts allows the comparison between the situations in different countries regarding the barriers to RU, as they have done in this article. Participants in Kocaman et al.’s study identified as the main barriers to RU the lack of time, lack of facilities and lack of support, together with the language barrier. In other words, in Turkey, they found that, although the characteristics of the nurse were important, the most significant barriers to RU were those related to the organisation, as it happens in the other compared countries, showing consistent results with previous studies (Retsas 2000, Parahoo & McCaughan 2001, Corchon 2009). Therefore, considering the important amount of literature focused on the barriers to RU and the congruent findings achieved along the years across different contexts, it seems that those have been over-studied and it is time to take a step forwards and start intervening on them. Many studies have looked at the barriers for EBP, but few have addressed innovative strategies to overcome them (Hundley et al. 2000, Clifford & Murray 2001) and these have mainly focused on the nurse, offering research training, without considering other contextual characteristics that, according to the literature, could be determinant. This study has shown once again that the development of nursing research and RU are complex issues and nurses, although interested and with positive attitudes towards RU, face important barriers that prevent them from participating in research activities and applying research evidence in practice (Pepler et al. 2006, Rycroft-Malone 2008). There are other factors, related to the organisation, that have a determinant influence. Some authors have explored the contextual factors and their influence on RU using the PARIHS framework, Promoting Action on Research Implementation in Health Services (Kitson et al. 1998). This framework argues that three major elements influence RU: the evidence, the context and the type of facilitation needed to ensure successful change. The context is composed of three dimensions: culture, leadership and evaluation. Positive characteristics of the context for RU, according to Cummings et al. (2007), are staff development, opportunity for nurse-to-nurse collaboration, and staffing and support services. Behind these factors, the organisational culture is a determining aspect (Scott-Findlay & Golden-Biddle 2005, Scott & Pollock 2008). The organisational culture shapes the research use by influencing the professionals’ attitudes and behaviours, ‘providing a context where particular ideas, activities or events are more highly valued than others’ (Scott & Pollock 2008, p. 299). To understand the organisational culture, Schein’s (1992) offers a hierarchical and iterative model of three levels: 1-Observable artefacts, the most observable elements of an organisation; 2-Values, articulated by norms, principles and ideologies; and 3-Basic underlying assumptions, the deepest level of culture. Scott-Findlay and Golden-Biddle (2005) applied this framework to explore the cultural reasons that prevented acute care nurses from RU, focusing on one aspect of the underlying assumptions of an organisational culture, the ‘nature of activity’. According to them, there are two extreme orientations regarding how work is valued: a doing orientation, focused on tasks and on efficiency, and a being orientation, focused on other values implying reflection. Generally, in health care organisations, the prevalent orientation is towards ‘doing’ more valued than reflection, and this guides how work is completed, the types of knowledge valued and used, and the provision of contexts for interaction (Scott-Findlay & Golden-Biddle 2005). For instance, nurses are expected to have things made rather than reflecting, which implies that research is not valued. Moreover, this orientation is more associated with practical knowledge than research knowledge, indicating the type of knowledge more valued in the organisation. This cultural orientation towards ‘doing’ clearly inhibits RU (Scott-Findlay & Golden-Biddle 2005). In conclusion, health professionals work in complex organisational structures and there are factors that do not depend on the individual but have an influence on RU. Thus, placing the responsibility of the failure to research utilisation on the individual is misguided (Rycroft-Malone 2008, Scott & Pollock 2008), and more effort should be focused on understanding how organisational culture might affect research development and RU (Fink et al. 2005, Scott-Findlay & Golden-Biddle 2005). ‘Developing a climate in which research is not only valued and seen for its intrinsic worth but is also considered an integral aspect of routine activity in an organisation’ (Thompson 2003, p. 143), an organisation in which ‘the nature of activity’ is more oriented towards ‘being’; are important organisational factors to bear in mind, and to act on, if there is an interest in developing nursing research and RU in practice.

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)0,048
score de la tête « metaresearch » (Gemma)0,029
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 consensuellesMétarecherche, Intégrité de la recherche
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,248
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0480,029
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0030,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0020,002
Communication savante0,0000,001
Science ouverte0,0030,000
Intégrité de la recherche0,0030,050
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,190
Tête enseignante GPT0,586
Écart entre enseignants0,396 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations12
Publié2010
Routes d'admission1
Résumé présentoui

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