An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study

<p>Abstract</p> <p>Background</p> <p>Despite the effectiveness of brief lifestyle intervention delivered in primary healthcare (PHC), implementation in routine practice remains suboptimal. Beliefs and attitudes have been shown to be associated with risk factor managemen...

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Main Authors: Williams Anna M, Davies Gawaine, Harris Mark F, Kemp Lynn A, Laws Rachel A, Eames-Brown Rosslyn
Format: Article
Language:English
Published: BMC 2009-10-01
Series:Implementation Science
Online Access:http://www.implementationscience.com/content/4/1/66
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spelling doaj-b4c4167ee97c4cd5a33a32cfca6686e92020-11-24T20:54:28ZengBMCImplementation Science1748-59082009-10-01416610.1186/1748-5908-4-66An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory studyWilliams Anna MDavies GawaineHarris Mark FKemp Lynn ALaws Rachel AEames-Brown Rosslyn<p>Abstract</p> <p>Background</p> <p>Despite the effectiveness of brief lifestyle intervention delivered in primary healthcare (PHC), implementation in routine practice remains suboptimal. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about the process by which clinicians' perceptions shape implementation. This study aims to describe a theoretical model to understand how clinicians' perceptions shape the implementation of lifestyle risk factor management in routine practice. The implications of the model for enhancing practices will also be discussed.</p> <p>Methods</p> <p>The study analysed data collected as part of a larger feasibility project of risk factor management in three community health teams in New South Wales (NSW), Australia. This included journal notes kept through the implementation of the project, and interviews with 48 participants comprising 23 clinicians (including community nurses, allied health practitioners and an Aboriginal health worker), five managers, and two project officers. Data were analysed using grounded theory principles of open, focused, and theoretical coding and constant comparative techniques to construct a model grounded in the data.</p> <p>Results</p> <p>The model suggests that implementation reflects both clinician beliefs about whether they should (commitment) and can (capacity) address lifestyle issues. Commitment represents the priority placed on risk factor management and reflects beliefs about role responsibility congruence, client receptiveness, and the likely impact of intervening. Clinician beliefs about their capacity for risk factor management reflect their views about self-efficacy, role support, and the fit between risk factor management ways of working. The model suggests that clinicians formulate different expectations and intentions about how they will intervene based on these beliefs about commitment and capacity and their philosophical views about appropriate ways to intervene. These expectations then provide a cognitive framework guiding their risk factor management practices. Finally, clinicians' appraisal of the overall benefits versus costs of addressing lifestyle issues acts to positively or negatively reinforce their commitment to implementing these practices.</p> <p>Conclusion</p> <p>The model extends previous research by outlining a process by which clinicians' perceptions shape implementation of lifestyle risk factor management in routine practice. This provides new insights to inform the development of effective strategies to improve such practices.</p> http://www.implementationscience.com/content/4/1/66
collection DOAJ
language English
format Article
sources DOAJ
author Williams Anna M
Davies Gawaine
Harris Mark F
Kemp Lynn A
Laws Rachel A
Eames-Brown Rosslyn
spellingShingle Williams Anna M
Davies Gawaine
Harris Mark F
Kemp Lynn A
Laws Rachel A
Eames-Brown Rosslyn
An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
Implementation Science
author_facet Williams Anna M
Davies Gawaine
Harris Mark F
Kemp Lynn A
Laws Rachel A
Eames-Brown Rosslyn
author_sort Williams Anna M
title An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
title_short An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
title_full An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
title_fullStr An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
title_full_unstemmed An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
title_sort exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study
publisher BMC
series Implementation Science
issn 1748-5908
publishDate 2009-10-01
description <p>Abstract</p> <p>Background</p> <p>Despite the effectiveness of brief lifestyle intervention delivered in primary healthcare (PHC), implementation in routine practice remains suboptimal. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about the process by which clinicians' perceptions shape implementation. This study aims to describe a theoretical model to understand how clinicians' perceptions shape the implementation of lifestyle risk factor management in routine practice. The implications of the model for enhancing practices will also be discussed.</p> <p>Methods</p> <p>The study analysed data collected as part of a larger feasibility project of risk factor management in three community health teams in New South Wales (NSW), Australia. This included journal notes kept through the implementation of the project, and interviews with 48 participants comprising 23 clinicians (including community nurses, allied health practitioners and an Aboriginal health worker), five managers, and two project officers. Data were analysed using grounded theory principles of open, focused, and theoretical coding and constant comparative techniques to construct a model grounded in the data.</p> <p>Results</p> <p>The model suggests that implementation reflects both clinician beliefs about whether they should (commitment) and can (capacity) address lifestyle issues. Commitment represents the priority placed on risk factor management and reflects beliefs about role responsibility congruence, client receptiveness, and the likely impact of intervening. Clinician beliefs about their capacity for risk factor management reflect their views about self-efficacy, role support, and the fit between risk factor management ways of working. The model suggests that clinicians formulate different expectations and intentions about how they will intervene based on these beliefs about commitment and capacity and their philosophical views about appropriate ways to intervene. These expectations then provide a cognitive framework guiding their risk factor management practices. Finally, clinicians' appraisal of the overall benefits versus costs of addressing lifestyle issues acts to positively or negatively reinforce their commitment to implementing these practices.</p> <p>Conclusion</p> <p>The model extends previous research by outlining a process by which clinicians' perceptions shape implementation of lifestyle risk factor management in routine practice. This provides new insights to inform the development of effective strategies to improve such practices.</p>
url http://www.implementationscience.com/content/4/1/66
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