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The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care

Overview of attention for article published in Implementation Science, June 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

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16 X users
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1 Google+ user

Citations

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164 Dimensions

Readers on

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352 Mendeley
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1 CiteULike
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Title
The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care
Published in
Implementation Science, June 2014
DOI 10.1186/1748-5908-9-77
Pubmed ID
Authors

Monica Taljaard, Joanne E McKenzie, Craig R Ramsay, Jeremy M Grimshaw

Abstract

An interrupted time series design is a powerful quasi-experimental approach for evaluating effects of interventions introduced at a specific point in time. To utilize the strength of this design, a modification to standard regression analysis, such as segmented regression, is required. In segmented regression analysis, the change in intercept and/or slope from pre- to post-intervention is estimated and used to test causal hypotheses about the intervention. We illustrate segmented regression using data from a previously published study that evaluated the effectiveness of a collaborative intervention to improve quality in pre-hospital ambulance care for acute myocardial infarction (AMI) and stroke. In the original analysis, a standard regression model was used with time as a continuous variable. We contrast the results from this standard regression analysis with those from segmented regression analysis. We discuss the limitations of the former and advantages of the latter, as well as the challenges of using segmented regression in analysing complex quality improvement interventions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 352 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 <1%
Germany 1 <1%
Brazil 1 <1%
Australia 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Unknown 345 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 59 17%
Researcher 57 16%
Student > Ph. D. Student 54 15%
Student > Doctoral Student 25 7%
Other 19 5%
Other 68 19%
Unknown 70 20%
Readers by discipline Count As %
Medicine and Dentistry 89 25%
Nursing and Health Professions 35 10%
Social Sciences 28 8%
Agricultural and Biological Sciences 17 5%
Environmental Science 13 4%
Other 79 22%
Unknown 91 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 26 February 2023.
All research outputs
#3,393,498
of 25,368,786 outputs
Outputs from Implementation Science
#694
of 1,809 outputs
Outputs of similar age
#32,763
of 242,757 outputs
Outputs of similar age from Implementation Science
#9
of 36 outputs
Altmetric has tracked 25,368,786 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,809 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 61% 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 242,757 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 86% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.