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The use of purposeful sampling in a qualitative evidence synthesis: A worked example on sexual adjustment to a cancer trajectory

Overview of attention for article published in BMC Medical Research Methodology, February 2016
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  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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3 tweeters

Citations

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71 Dimensions

Readers on

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372 Mendeley
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3 CiteULike
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Title
The use of purposeful sampling in a qualitative evidence synthesis: A worked example on sexual adjustment to a cancer trajectory
Published in
BMC Medical Research Methodology, February 2016
DOI 10.1186/s12874-016-0114-6
Pubmed ID
Authors

Charlotte Benoot, Karin Hannes, Johan Bilsen

Abstract

An increasing number of qualitative evidence syntheses papers are found in health care literature. Many of these syntheses use a strictly exhaustive search strategy to collect articles, mirroring the standard template developed by major review organizations such as the Cochrane and Campbell Collaboration. The hegemonic idea behind it is that non-comprehensive samples in systematic reviews may introduce selection bias. However, exhaustive sampling in a qualitative evidence synthesis has been questioned, and a more purposeful way of sampling papers has been proposed as an alternative, although there is a lack of transparency on how these purposeful sampling strategies might be applied to a qualitative evidence synthesis. We discuss in our paper why and how we used purposeful sampling in a qualitative evidence synthesis about 'sexual adjustment to a cancer trajectory', by giving a worked example. We have chosen a mixed purposeful sampling, combining three different strategies that we considered the most consistent with our research purpose: intensity sampling, maximum variation sampling and confirming/disconfirming case sampling. The concept of purposeful sampling on the meta-level could not readily been borrowed from the logic applied in basic research projects. It also demands a considerable amount of flexibility, and is labour-intensive, which goes against the argument of many authors that using purposeful sampling provides a pragmatic solution or a short cut for researchers, compared with exhaustive sampling. Opportunities of purposeful sampling were the possible inclusion of new perspectives to the line-of-argument and the enhancement of the theoretical diversity of the papers being included, which could make the results more conceptually aligned with the synthesis purpose. This paper helps researchers to make decisions related to purposeful sampling in a more systematic and transparent way. Future research could confirm or disconfirm the hypothesis of conceptual enhancement by comparing the findings of a purposefully sampled qualitative evidence synthesis with those drawing on an exhaustive sample of the literature.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 372 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%
Netherlands 1 <1%
Unknown 369 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 76 20%
Student > Ph. D. Student 61 16%
Student > Bachelor 38 10%
Student > Doctoral Student 34 9%
Researcher 29 8%
Other 64 17%
Unknown 70 19%
Readers by discipline Count As %
Social Sciences 52 14%
Medicine and Dentistry 44 12%
Nursing and Health Professions 44 12%
Business, Management and Accounting 42 11%
Psychology 26 7%
Other 82 22%
Unknown 82 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 18 April 2016.
All research outputs
#3,155,027
of 7,565,447 outputs
Outputs from BMC Medical Research Methodology
#388
of 780 outputs
Outputs of similar age
#110,977
of 276,566 outputs
Outputs of similar age from BMC Medical Research Methodology
#17
of 33 outputs
Altmetric has tracked 7,565,447 research outputs across all sources so far. This one has received more attention than most of these and is in the 56th percentile.
So far Altmetric has tracked 780 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 276,566 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 58% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.