Notice bibliographique
Résumé
The gulf between what we know from research and what we do in practice is substantial. The existence of primary research, its synthesis and dissemination, although essential, are not sufficient for ensuring its enactment to improve health outcomes. The result is that our clients often may not receive optimal care. Knowledge translation seeks to address this problem. Knowledge translation has been described as a dynamic and iterative process that involves synthesis, dissemination, exchange and application of knowledge to improve health (Canadian Institutes for Health Research (CIHR) (2015). The field is characterised by conceptual challenges with for example, the terms knowledge translation, knowledge exchange, research utilisation and implementation variably being used to describe interrelated and overlapping perspectives, however each addresses the aim of closing the gap between research and practice. Despite this variation in terminology, the ‘knowledge’ to be translated ordinarily refers to recommendations from research, with many authors giving preference to high-quality, synthesised research such as systematic reviews or recommendations from clinical practice guidelines (Grimshaw, Eccles, Lavis, Hill & Squires, 2012). The rationale given for this is that individual studies may not be definitive enough on their own to warrant the efforts involved in changing practice. Even if this is the case, the pluralistic nature of knowledge should also be taken into account (Straus, Tetroe & Graham, 2013), as all forms of knowledge are needed to enact and advance our practice. It is also clear that the processes involved in knowledge translation could not take place without other forms of knowledge – experiential, tacit and strategic knowledge – all essential for negotiating the complexities of change within dynamic health-care environments. The targets of knowledge translation are many and varied. Within occupational therapy, the literature describes knowledge translation in the fields of stroke rehabilitation, vocational rehabilitation, mental health, falls prevention, assessments and interventions for children with cerebral palsy, and occupational therapy for people with dementia, to name a few. Much of this work has involved bringing about change in health professionals’ practice and/or the systems within which they work, neither of which is easy. A whole body of literature exists offering models and frameworks for guiding knowledge translation, many of which propose an analysis of the individual and contextual barriers to change, and application of tailored strategies to target known barriers. Also pivotal is the need for knowledge translation to be well-planned and to consider the perspectives of many different stakeholders. However, beyond understanding the methods for translating research findings into practice, it is also critical that research is developed with the end-use in mind. This requires not simply knowing who the end users may be, but extends to co-creation of knowledge. ‘Integrated knowledge translation’ where researchers and knowledge-users work together to shape the research process both prior to the commencement of research and beyond its completion (CIHR, 2015) is not a new idea; however, true involvement of consumers in co-creation of research and its translation is now increasingly valued. In short, knowledge translation is not straight forward, can be approached from many different perspectives, utilises multiple forms of knowledge, involves many different stakeholders and is a continuing process, but is an essential activity that we need all engage in. The Australian Occupational Therapy Journal will continue to support this effort.
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 | 0,007 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».