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Towards the use of mixed methods inquiry as best practice in health outcomes research

Overview of attention for article published in Journal of Patient-Reported Outcomes, April 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#15 of 646)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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1 news outlet
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29 X users

Citations

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137 Dimensions

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458 Mendeley
Title
Towards the use of mixed methods inquiry as best practice in health outcomes research
Published in
Journal of Patient-Reported Outcomes, April 2018
DOI 10.1186/s41687-018-0043-8
Pubmed ID
Authors

Antoine Regnault, Tom Willgoss, Skye Barbic, On behalf of the International Society for Quality of Life Research (ISOQOL) Mixed Methods Special Interest Group (SIG)

Abstract

Mixed methods research (MMR) has found an increased interest in the field of health outcomes research. Consideration for both qualitative and quantitative perspectives has become key to contextualising patient experiences in a clinically meaningful measurement framework. The purpose of this paper is to outline a process for incorporating MMR in health outcomes research to guide stakeholders in their understanding of the essence of mixed methods inquiry. In addition, this paper will outline the benefits and challenges of MMR and describe the types of support needed for designing and conducting robust MMR measurement studies. MMR involves the application of a well-defined and pre-specified research design that articulates purposely and prospectively, qualitative and quantitative components to generate an integrated set of evidence addressing a single research question. Various methodological design options are possible depending on the research question. MMR designs allow a research question to be studied thoroughly from different perspectives. When applied, it allows the strengths of one approach to complement the restrictions of another. Among other applications, MMR can be used to enhance the creation of conceptual models and development of new instruments, to interpret the meaningfulness of outcomes in a clinical study from the patient perspective, and inform health care policy. Robust MMR requires research teams with experience in both qualitative and quantitative research. Moreover, a thorough understanding of the underlying principles of MMR is recommended at the point of study conception all the way through to implementation and knowledge dissemination. The framework outlined in this paper is designed to encourage health outcomes researchers to apply MMR to their research and to facilitate innovative, patient-centred methodological solutions to address the complex challenges of the field.

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 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 458 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 458 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 66 14%
Student > Ph. D. Student 62 14%
Student > Bachelor 44 10%
Researcher 32 7%
Student > Doctoral Student 26 6%
Other 66 14%
Unknown 162 35%
Readers by discipline Count As %
Nursing and Health Professions 70 15%
Social Sciences 42 9%
Medicine and Dentistry 41 9%
Psychology 29 6%
Business, Management and Accounting 17 4%
Other 89 19%
Unknown 170 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 2022.
All research outputs
#1,376,703
of 25,295,968 outputs
Outputs from Journal of Patient-Reported Outcomes
#15
of 646 outputs
Outputs of similar age
#29,672
of 335,438 outputs
Outputs of similar age from Journal of Patient-Reported Outcomes
#2
of 6 outputs
Altmetric has tracked 25,295,968 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 646 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 97% 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 335,438 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.