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Informing the implementation of evidence-informed decision making interventions using a social network analysis perspective; a mixed-methods study

Overview of attention for article published in BMC Health Services Research, February 2017
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

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1 policy source
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2 X users

Citations

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23 Dimensions

Readers on

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133 Mendeley
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Title
Informing the implementation of evidence-informed decision making interventions using a social network analysis perspective; a mixed-methods study
Published in
BMC Health Services Research, February 2017
DOI 10.1186/s12913-017-2067-9
Pubmed ID
Authors

Reza Yousefi Nooraie, Lynne Lohfeld, Alexandra Marin, Robert Hanneman, Maureen Dobbins

Abstract

Workforce development is an important aspect of evidence-informed decision making (EIDM) interventions. The structure of formal and informal social networks can influence, and be influenced, by the implementation of EIDM interventions. In a mixed methods study we assessed the outcomes of a targeted training intervention to promote EIDM among the staff in three public health units in Ontario, Canada. This report focuses on the qualitative phase of the study in which key staff were interviewed about the process of engagement in the intervention, communications during the intervention, and social consequences. Senior managers identified staff to take part in the intervention. Engagement was a top-down process determined by the way organizational leaders promoted EIDM and the relevance of staff's jobs to EIDM. Communication among staff participating in the workshops and ongoing progress meetings was influential in overcoming personal and normative barriers to implementing EIDM, and promoted the formation of long-lasting social connections among staff. Organization-wide presentations and meetings facilitated the recognition of expertise that the trained staff gained, including their reputation as experts according to their peers in different divisions. Selective training and capacity development interventions can result in forming an elite versus ordinary pattern that facilitates the recognition of in-house qualified experts while also strengthening social status inequality. The role of leadership in public health units is pivotal in championing and overseeing the implementation process. Network analysis can guide and inform the design, process, and evaluation of the EIDM training interventions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Unknown 131 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 17%
Student > Ph. D. Student 18 14%
Researcher 14 11%
Student > Doctoral Student 11 8%
Student > Bachelor 7 5%
Other 25 19%
Unknown 35 26%
Readers by discipline Count As %
Social Sciences 21 16%
Nursing and Health Professions 16 12%
Medicine and Dentistry 14 11%
Business, Management and Accounting 12 9%
Psychology 11 8%
Other 20 15%
Unknown 39 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 15 November 2017.
All research outputs
#6,648,653
of 24,217,496 outputs
Outputs from BMC Health Services Research
#3,150
of 8,145 outputs
Outputs of similar age
#121,116
of 427,868 outputs
Outputs of similar age from BMC Health Services Research
#61
of 165 outputs
Altmetric has tracked 24,217,496 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 8,145 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 60% 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 427,868 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.