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Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care

BACKGROUND: Whilst multidimensional assessment enables the detection of treatable traits in severe asthma and has the potential to improve patient outcomes, healthcare disparities exist, and little is known about the factors influencing optimal management in severe asthma. This study aimed to explor...

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Autores principales: Majellano, Eleanor C., Clark, Vanessa L., McLoughlin, Rebecca F., Gibson, Peter G., McDonald, Vanessa M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9173624/
https://www.ncbi.nlm.nih.gov/pubmed/35671262
http://dx.doi.org/10.1371/journal.pone.0269038
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author Majellano, Eleanor C.
Clark, Vanessa L.
McLoughlin, Rebecca F.
Gibson, Peter G.
McDonald, Vanessa M.
author_facet Majellano, Eleanor C.
Clark, Vanessa L.
McLoughlin, Rebecca F.
Gibson, Peter G.
McDonald, Vanessa M.
author_sort Majellano, Eleanor C.
collection PubMed
description BACKGROUND: Whilst multidimensional assessment enables the detection of treatable traits in severe asthma and has the potential to improve patient outcomes, healthcare disparities exist, and little is known about the factors influencing optimal management in severe asthma. This study aimed to explore perceived barriers, and enablers to implementing personalised care in severe asthma, from the healthcare professionals’ perspective. METHODS: A descriptive, qualitative study involving a single focus group (n = 7) and semi-structured interviews (n = 33) with multidisciplinary healthcare professionals involved in severe asthma care was conducted. A hybrid thematic and content analysis was undertaken to identify themes, which were then deductively mapped to the Theoretical Domains Framework (TDF). RESULTS: Overall, three emergent themes were identified: (1) Barriers- (2) Enablers- to optimal management; (3) Desired model of care. Across all TDF domains, 6 constructs influenced development and implementation of optimal care: (1) belief about consequences, (2) environmental context and resources, (3) belief about capabilities, (4) social/professional role and identity, (5) goals and (6) knowledge. CONCLUSION: Implementation of personalised care in severe asthma is complex and non-linear. The use of a theory-based approach effectively demonstrated how a variety of behaviours could be targeted to optimise and promote personalised care in different clinical setting.
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spelling pubmed-91736242022-06-08 Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care Majellano, Eleanor C. Clark, Vanessa L. McLoughlin, Rebecca F. Gibson, Peter G. McDonald, Vanessa M. PLoS One Research Article BACKGROUND: Whilst multidimensional assessment enables the detection of treatable traits in severe asthma and has the potential to improve patient outcomes, healthcare disparities exist, and little is known about the factors influencing optimal management in severe asthma. This study aimed to explore perceived barriers, and enablers to implementing personalised care in severe asthma, from the healthcare professionals’ perspective. METHODS: A descriptive, qualitative study involving a single focus group (n = 7) and semi-structured interviews (n = 33) with multidisciplinary healthcare professionals involved in severe asthma care was conducted. A hybrid thematic and content analysis was undertaken to identify themes, which were then deductively mapped to the Theoretical Domains Framework (TDF). RESULTS: Overall, three emergent themes were identified: (1) Barriers- (2) Enablers- to optimal management; (3) Desired model of care. Across all TDF domains, 6 constructs influenced development and implementation of optimal care: (1) belief about consequences, (2) environmental context and resources, (3) belief about capabilities, (4) social/professional role and identity, (5) goals and (6) knowledge. CONCLUSION: Implementation of personalised care in severe asthma is complex and non-linear. The use of a theory-based approach effectively demonstrated how a variety of behaviours could be targeted to optimise and promote personalised care in different clinical setting. Public Library of Science 2022-06-07 /pmc/articles/PMC9173624/ /pubmed/35671262 http://dx.doi.org/10.1371/journal.pone.0269038 Text en © 2022 Majellano et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Majellano, Eleanor C.
Clark, Vanessa L.
McLoughlin, Rebecca F.
Gibson, Peter G.
McDonald, Vanessa M.
Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
title Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
title_full Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
title_fullStr Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
title_full_unstemmed Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
title_short Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
title_sort using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9173624/
https://www.ncbi.nlm.nih.gov/pubmed/35671262
http://dx.doi.org/10.1371/journal.pone.0269038
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