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Examples of sex/gender sensitivity in epidemiological research: results of an evaluation of original articles published in JECH 2006–2014

Overview of attention for article published in Health Research Policy and Systems, February 2017
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Title
Examples of sex/gender sensitivity in epidemiological research: results of an evaluation of original articles published in JECH 2006–2014
Published in
Health Research Policy and Systems, February 2017
DOI 10.1186/s12961-017-0174-z
Pubmed ID
Authors

Ingeborg Jahn, Claudia Börnhorst, Frauke Günther, Tilman Brand

Abstract

During the last decades, sex and gender biases have been identified in various areas of biomedical and public health research, leading to compromised validity of research findings. As a response, methodological requirements were developed but these are rarely translated into research practice. The aim of this study is to provide good practice examples of sex/gender sensitive health research. We conducted a systematic search of research articles published in JECH between 2006 and 2014. An instrument was constructed to evaluate sex/gender sensitivity in four stages of the research process (background, study design, statistical analysis, discussion). In total, 37 articles covering diverse topics were included. Thereof, 22 were evaluated as good practice example in at least one stage; two articles achieved highest ratings across all stages. Good examples of the background referred to available knowledge on sex/gender differences and sex/gender informed theoretical frameworks. Related to the study design, good examples calculated sample sizes to be able to detect sex/gender differences, selected sex/gender sensitive outcome/exposure indicators, or chose different cut-off values for male and female participants. Good examples of statistical analyses used interaction terms with sex/gender or different shapes of the estimated relationship for men and women. Examples of good discussions interpreted their findings related to social and biological explanatory models or questioned the statistical methods used to detect sex/gender differences. The identified good practice examples may inspire researchers to critically reflect on the relevance of sex/gender issues of their studies and help them to translate methodological recommendations of sex/gender sensitivity into research practice.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 2%
Unknown 64 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 15%
Researcher 10 15%
Student > Master 7 11%
Student > Bachelor 5 8%
Student > Postgraduate 5 8%
Other 10 15%
Unknown 18 28%
Readers by discipline Count As %
Medicine and Dentistry 14 22%
Social Sciences 8 12%
Psychology 5 8%
Business, Management and Accounting 4 6%
Nursing and Health Professions 3 5%
Other 8 12%
Unknown 23 35%

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 21 February 2017.
All research outputs
#4,670,364
of 9,093,370 outputs
Outputs from Health Research Policy and Systems
#460
of 536 outputs
Outputs of similar age
#136,018
of 253,044 outputs
Outputs of similar age from Health Research Policy and Systems
#28
of 30 outputs
Altmetric has tracked 9,093,370 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 536 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 9th percentile – i.e., 9% 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 253,044 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.