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The physician’s experience of changing clinical practice: a struggle to unlearn

Overview of attention for article published in Implementation Science, February 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
1 news outlet
twitter
59 X users
facebook
1 Facebook page
video
1 YouTube creator

Citations

dimensions_citation
159 Dimensions

Readers on

mendeley
196 Mendeley
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Title
The physician’s experience of changing clinical practice: a struggle to unlearn
Published in
Implementation Science, February 2017
DOI 10.1186/s13012-017-0555-2
Pubmed ID
Authors

Divya M. Gupta, Richard J. Boland, David C. Aron

Abstract

Changing clinical practice is a difficult process, best illustrated by the time lag between evidence and use in practice and the extensive use of low-value care. Existing models mostly focus on the barriers to learning and implementing new knowledge. Changing clinical practice, however, includes not only the learning of new practices but also unlearning old and outmoded knowledge. There exists sparse literature regarding the unlearning that takes place at a physician level. Our research objective was to elucidate the experience of trying to abandon an outmoded clinical practice and its relation to learning a new one. We used a grounded theory-based qualitative approach to conduct our study. We conducted 30-min in-person interviews with 15 primary care physicians at the Cleveland VA Medical Center and its clinics. We used a semi-structured interview guide to standardize the interviews. Our two findings include (1) practice change disturbs the status quo equilibrium. Establishing a new equilibrium that incorporates the change may be a struggle; and (2) part of the struggle to establish a new equilibrium incorporating a practice change involves both the "evidence" itself and tensions between evidence and context. Our findings provide evidence-based support for many of the empirical unlearning models that have been adapted to healthcare. Our findings differ from these empirical models in that they refute the static and unidirectional nature of change that previous models imply. Rather, our findings suggest that clinical practice is in a constant flux of change; each instance of unlearning and learning is merely a punctuation mark in this spectrum of change. We suggest that physician unlearning models be modified to reflect the constantly changing nature of clinical practice and demonstrate that change is a multi-directional process.

X Demographics

X Demographics

The data shown below were collected from the profiles of 59 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 196 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 196 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 14%
Student > Master 25 13%
Researcher 23 12%
Student > Bachelor 16 8%
Other 14 7%
Other 39 20%
Unknown 51 26%
Readers by discipline Count As %
Medicine and Dentistry 46 23%
Nursing and Health Professions 35 18%
Social Sciences 10 5%
Psychology 8 4%
Agricultural and Biological Sciences 7 4%
Other 33 17%
Unknown 57 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 43. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 August 2022.
All research outputs
#896,508
of 24,274,366 outputs
Outputs from Implementation Science
#123
of 1,756 outputs
Outputs of similar age
#19,160
of 314,668 outputs
Outputs of similar age from Implementation Science
#7
of 41 outputs
Altmetric has tracked 24,274,366 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,756 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,668 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.