Commentary on Brown <scp>CE</scp> , Ecoff L, Kim <scp>SC</scp> , Wickline <scp>MA</scp> , <scp>R</scp> ose <scp>B</scp> , <scp>K</scp> limpel <scp>K</scp> and <scp>G</scp> laser <scp>D</scp> (2010) Multi‐institutional study of barriers to research utilisation and evidence‐based practice among hospital nurses. <i> <scp>J</scp> ournal of Clinical Nursing </i> 19, 1944–1951
Notice bibliographique
Résumé
Twenty years ago, Funk et al. (1991) published the instrument Barriers to research utilisation scale, the BARRIERS scale. The numbers of researcher world-wide using the scale are impressive (Kajermo et al. 2010). The scale measures the nurse's perceptions of barriers to research utilisation. Because of different versions, the scale consists of 29 or 28 items that are divided in four subscales labelled Nurse – the characteristics of the adopter; Setting – the characteristics of the organisation; Research – the characteristics of the innovation; and Presentation – the characteristics of the communication. The factors are proposed to parallel major concepts in Rogers’ Diffusion of Innovation theory (Funk et al. 1991). In 2010, we published a systematic review of studies using the BARRIERS scale (Kajermo et al. 2010). We identified 63 studies in nursing populations of which the majority was conducted in English-speaking countries; however, the spread to non-English speaking countries had escalated during the last decade. One finding was that nurses perceived the setting/organisation and the presentation of research findings/communication as the main barriers to research utilisation. Somewhat surprisingly, the results in the studies remained the same over time, across countries and languages. Just six of the 63 included studies had examined associations between reported research use and perceptions of barriers to research utilisation, mostly using bivariate analyses. Few associations were identified and none of the studies reported statistically significant associations between nurses’ research use and barriers related to the setting/organisation. We therefore appreciate Baker et al. (2010) study as they examined the relationships between perceived barriers and adoption of evidence-based practice (EBP) among nurses in four hospitals using hierarchical multiple regression analyses. As in the majority of the studies using the BARRIERS scale, the nurses in the study by Brown et al. perceived the setting/organisation as the main barrier to research utilisation. Three of the four factors were significantly associated with EBP though explaining only 2·7% of the variance. The setting/organisation factor was not associated with EBP. The Baker et al. (2010) study supports our questioning of the validity of the BARRIERS scale. One problem with the scale is that the items represent general and non-specific barriers that represent information that is difficult to use for developing adequate interventions. Furthermore, as the scale was developed in the 1980s, there have been changes in healthcare. For example, remarkable development in information technology has increased the access to research findings and relevant evidence, an aspect that is not represented in the BARRIERS scale. As our review was published, we have identified at least ten additional publications using the BARRIERS scale in nursing populations, revealing the ongoing popularity and spread of the scale. On the basis of the study by Brown et al., the review by Carlson and Plonczynski (2008) and our review, our continued recommendation is that no more descriptive studies should be undertaken using the Barriers scale. Future research efforts should instead focus on addressing locally identified barriers as tailored interventions to overcome identified barriers appear to be an effective strategy to get evidence into practice (Baker et al. 2010). The authors declare they have no conflict of interest.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,087 | 0,558 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,006 |
| Méta-épidémiologie (sens large) | 0,011 | 0,004 |
| Bibliométrie | 0,008 | 0,011 |
| Études des sciences et des technologies | 0,012 | 0,012 |
| Communication savante | 0,003 | 0,015 |
| Science ouverte | 0,008 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,028 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».