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Use of programme theory to understand the differential effects of interventions across socio-economic groups in systematic reviews—a systematic methodology review

Overview of attention for article published in Systematic Reviews, December 2017
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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 (89th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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1 blog
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Title
Use of programme theory to understand the differential effects of interventions across socio-economic groups in systematic reviews—a systematic methodology review
Published in
Systematic Reviews, December 2017
DOI 10.1186/s13643-017-0638-9
Pubmed ID
Authors

Michelle Maden, Alex Cunliffe, Naoimh McMahon, Andrew Booth, Gina Michelle Carey, Suzy Paisley, Rumona Dickson, Mark Gabbay

Abstract

Systematic review guidance recommends the use of programme theory to inform considerations of if and how healthcare interventions may work differently across socio-economic status (SES) groups. This study aimed to address the lack of detail on how reviewers operationalise this in practice. A methodological systematic review was undertaken to assess if, how and the extent to which systematic reviewers operationalise the guidance on the use of programme theory in considerations of socio-economic inequalities in health. Multiple databases were searched from January 2013 to May 2016. Studies were included if they were systematic reviews assessing the effectiveness of an intervention and included data on SES. Two reviewers independently screened all studies, undertook quality assessment and extracted data. A narrative approach to synthesis was adopted. A total of 37 systematic reviews were included, 10 of which were explicit in the use of terminology for 'programme theory'. Twenty-nine studies used programme theory to inform both their a priori assumptions and explain their review findings. Of these, 22 incorporated considerations of both what and how interventions do/do not work in SES groups to both predict and explain their review findings. Thirteen studies acknowledged 24 unique theoretical references to support their assumptions of what or how interventions may have different effects in SES groups. Most reviewers used supplementary evidence to support their considerations of differential effectiveness. The majority of authors outlined a programme theory in the "Introduction" and "Discussion" sections of the review to inform their assumptions or provide explanations of what or how interventions may result in differential effects within or across SES groups. About a third of reviews used programme theory to inform the review analysis and/or synthesis. Few authors used programme theory to inform their inclusion criteria, data extraction or quality assessment. Twenty-one studies tested their a priori programme theory. The use of programme theory to inform considerations of if, what and how interventions lead to differential effects on health in different SES groups in the systematic review process is not yet widely adopted, is used implicitly, is often fragmented and is not implemented in a systematic way.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 101 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 18%
Student > Master 9 9%
Student > Doctoral Student 8 8%
Student > Ph. D. Student 7 7%
Other 5 5%
Other 20 20%
Unknown 34 34%
Readers by discipline Count As %
Medicine and Dentistry 15 15%
Social Sciences 11 11%
Psychology 8 8%
Nursing and Health Professions 6 6%
Business, Management and Accounting 4 4%
Other 18 18%
Unknown 39 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 19 January 2018.
All research outputs
#2,180,176
of 25,032,929 outputs
Outputs from Systematic Reviews
#355
of 2,184 outputs
Outputs of similar age
#48,603
of 453,948 outputs
Outputs of similar age from Systematic Reviews
#17
of 56 outputs
Altmetric has tracked 25,032,929 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,184 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has done well, scoring higher than 83% 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 453,948 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 89% of its contemporaries.
We're also able to compare this research output to 56 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 71% of its contemporaries.