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Advancing implementation science through measure development and evaluation: a study protocol

Overview of attention for article published in Implementation Science, July 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

policy
1 policy source
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22 X users

Citations

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68 Dimensions

Readers on

mendeley
163 Mendeley
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1 CiteULike
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Title
Advancing implementation science through measure development and evaluation: a study protocol
Published in
Implementation Science, July 2015
DOI 10.1186/s13012-015-0287-0
Pubmed ID
Authors

Cara C. Lewis, Bryan J. Weiner, Cameo Stanick, Sarah M. Fischer

Abstract

Significant gaps related to measurement issues are among the most critical barriers to advancing implementation science. Three issues motivated the study aims: (a) the lack of stakeholder involvement in defining pragmatic measure qualities; (b) the dearth of measures, particularly for implementation outcomes; and (c) unknown psychometric and pragmatic strength of existing measures. Aim 1: Establish a stakeholder-driven operationalization of pragmatic measures and develop reliable, valid rating criteria for assessing the construct. Aim 2: Develop reliable, valid, and pragmatic measures of three critical implementation outcomes, acceptability, appropriateness, and feasibility. Aim 3: Identify Consolidated Framework for Implementation Research and Implementation Outcome Framework-linked measures that demonstrate both psychometric and pragmatic strength. For Aim 1, we will conduct (a) interviews with stakeholder panelists (N = 7) and complete a literature review to populate pragmatic measure construct criteria, (b) Q-sort activities (N = 20) to clarify the internal structure of the definition, (c) Delphi activities (N = 20) to achieve consensus on the dimension priorities, (d) test-retest and inter-rater reliability assessments of the emergent rating system, and (e) known-groups validity testing of the top three prioritized pragmatic criteria. For Aim 2, our systematic development process involves domain delineation, item generation, substantive validity assessment, structural validity assessment, reliability assessment, and predictive validity assessment. We will also assess discriminant validity, known-groups validity, structural invariance, sensitivity to change, and other pragmatic features. For Aim 3, we will refine our established evidence-based assessment (EBA) criteria, extract the relevant data from the literature, rate each measure using the EBA criteria, and summarize the data. The study outputs of each aim are expected to have a positive impact as they will establish and guide a comprehensive measurement-focused research agenda for implementation science and provide empirically supported measures, tools, and methods for accomplishing this work.

X Demographics

X Demographics

The data shown below were collected from the profiles of 22 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 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Malaysia 1 <1%
Spain 1 <1%
Unknown 160 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 18%
Student > Ph. D. Student 29 18%
Student > Doctoral Student 20 12%
Student > Master 19 12%
Other 9 6%
Other 31 19%
Unknown 25 15%
Readers by discipline Count As %
Social Sciences 33 20%
Medicine and Dentistry 29 18%
Psychology 21 13%
Nursing and Health Professions 20 12%
Business, Management and Accounting 4 2%
Other 22 13%
Unknown 34 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 09 December 2016.
All research outputs
#2,465,647
of 25,732,188 outputs
Outputs from Implementation Science
#482
of 1,820 outputs
Outputs of similar age
#30,251
of 275,964 outputs
Outputs of similar age from Implementation Science
#14
of 57 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,820 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has gotten more attention than average, scoring higher than 73% 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 275,964 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.