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Enregistrement W3217000792 · doi:10.1111/jan.15108

Is Action Research just about telling a good story?

2021· editorial· en· W3217000792 sur OpenAlexaff
Mary Casey, David Coghlan, Áine Carroll, Diarmuid Stokes

Notice bibliographique

RevueJournal of Advanced Nursing · 2021
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueMental Health and Patient Involvement
Établissements canadiensTrinity College
Organismes subventionnairesnon disponible
Mots-clésAction (physics)PsychologyMedicine

Résumé

récupéré en direct d'OpenAlex

Patient participation demands greater attention from healthcare providers and researchers to ensure that the voice of vulnerable people is heard in a system that was originally designed to accommodate the needs of healthcare professionals. Covid 19 has brought the realisation that nursing care is not provided in a vacuum, it is impacted by socioeconomic and political mores. There is an increased demand to demonstrate the impact and outcome from participation and co-design in research (Palmer, 2020). More critical action in our research and practice is needed to collectively find solutions to such current questions as global warming and the unequal global distribution of resources such as Covid 19 vaccine allocations. The real question for us as a global society is—how can our research be of value beyond the essential development of the vaccine(s)? The patients' voice and that of employees in healthcare have never been more crucial to ensuring future societies can get on with everyday living with Covid 19 in a meaningful way as we undergo transformative change and manage the impact of Covid 19 locally, nationally and globally. The utility and flexibility of action research have increased the interest and employability of this approach in a range of healthcare contexts, in the recent past, as healthcare systems continue to value the voice of staff and patients. Active participation of patients and staff is vital to ensure the provision of a responsive and meaningful health service. Traditional research approaches are somewhat limited in their ability to include the participants' voice in their research journey. It is without a doubt that public and patient involvement initiatives (PPI) have created a greater understanding of the different layers of participation from collaboration, to consultation to inform the wider community, and in this onion-like layered engagement concept, action research remains the leader in the field. In this context, action research is gaining interest and becoming more popular, essentially because of 'its participatory paradigm, which invites participants to be both embedded and reflexive in the creation of collaborative learning and of actionable knowledge where research is with, rather than on or for, people' (Casey et al., 2021: 3). Its dual focus on theory and action has brought an increased emphasis on the application of action research in healthcare. Therefore theory and practice are linked in action research as are, thinking and taking action to achieve both practical and research objectives which provide improvement by closing the gap between research and implementation. In the context of change, action research aims at taking action and at the same time creating knowledge or theory about that action or change. In this way, action research provides actionable knowledge for other health care contexts such as learning about the management of the longer-term impacts of Covid 19. Action research therefore brings a change, by not only raising awareness but also in garnering participative support for action mediated by concerns for social justice in a local and global healthcare context. The action research process involves cycles of action and reflection and always has two goals: to find a solution to a real-world issue and to contribute to science through the elaboration of extant theory or the creation of new thinking. These are the dual imperatives of action research. However, it is the creation of actionable knowledge that is the most rigorous test of knowledge creation. Asking such questions as:-does the particular solution work in practice? and if not -why not?– and then, asking what can we do to improve the situation further? To address such questions, action research employs strict criteria and describes definite steps on how to engage in the research process. These steps are cyclical and iterative and for some researchers, these are seen as two overlapping spirals of activity, where one spiral captures the research activity and the other refers to the work project. Action research focuses on creating solutions to practical issues (see Figure 1) and it simultaneously empowers practitioners by encouraging their participation in all aspects of the research process and in its implementation. Participation in healthcare is a complex issue as it is mediated by the different lenses through which different professional groups view and understand problems while patients must engage with these in an organisational hierarchical context. It is through the relational component of action research that the participative values are to be found as it embraces multiple ways of knowing-for-action (Bradbury et al., 2019). Hence, participation from participants and co-researchers increases the involvement and sustainability of outcomes; however, the measurement of participation and the relational components is loose and inconsistent (Casey et al., 2021). In some published reports, the mention of stakeholder consultation, participant interviews and involvement in focus groups, is proffered as meeting the entire gambit of rigour to demonstrate the quality of the co-researcher relationship. This level of involvement aligns more with the idea of a consultation process, where the voice of the participant may be heard but there is no definite agreement that it will impact the direction of the project or research. Morrison and Lilford (2001) attest that, like other traditional forms of research, action research is scientific and although it is context dependent, nevertheless it offers explanatory theories, and these theories can be falsified. This raises the question of rigour and the scientific basis of action research. Action research therefore not only needs to be undertaken rigorously but also needs to demonstrate the details of how rigour was executed. The judge for rigour in action research is on the basis that knowledge generation is reflected in the co-creation and cooperation between the researcher and co-researchers through praxis. More recently, Coghlan and Shani (2014) suggest that demonstrating the quality of action research studies can be achieved by: (a) providing knowledge of the practical and academic context of the project; (b) enabling participants to become co-researchers; (c) undertaking cycles of action and reflection as the project is being implemented and knowledge is being co-generated; and (d) creating outcomes that are both achievable and sufficiently strong for theory development about the topic itself, or the process of undertaking the change or the actual change. It is essential to demonstrate not only that the research is guided by a reflexive concern for practical outcomes but also the process of iterative reflection as part of the change process. In other words, is the view of the patient or participant clearly visible? Action research must therefore acknowledge a range of perspectives on reality embodied in the different ways of knowing evident in the inclusion of the voice of participants without attempting to find consensus. The importance of the project is also considered essential criteria of quality and whether the project creates longer-term sustainable change. It is imperative therefore that all action researchers provide a rationale for their research approach and provide the evidence to support the quality of their action research studies. Without a description of such quality criteria, there is a risk that action research becomes negated as a valuable research approach. We do not have any conflicts of interest to report.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,303
score de la tête « metaresearch » (Gemma)0,411
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesMétarecherche
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,697
Score d'incertitude au seuil0,860

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,3030,411
Méta-épidémiologie (sens strict)0,0030,002
Méta-épidémiologie (sens large)0,0080,004
Bibliométrie0,0070,006
Études des sciences et des technologies0,0210,139
Communication savante0,0560,096
Science ouverte0,0090,023
Intégrité de la recherche0,0380,063
Charge utile insuffisante (le modèle a refusé de juger)0,0120,007

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 Opus0,446
Tête enseignante GPT0,601
Écart entre enseignants0,155 · 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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
DomaineMéthodes
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

Citations8
Publié2021
Routes d'admission1
Résumé présentoui

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