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Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher

Overview of attention for article published in BMC Medical Research Methodology, October 2011
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Title
Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher
Published in
BMC Medical Research Methodology, October 2011
DOI 10.1186/1471-2288-11-145
Pubmed ID
Authors

MJ Park, Yoshihiko Yamazaki, Yuki Yonekura, Keiko Yukawa, Hirono Ishikawa, Takahiro Kiuchi, Joseph Green

Abstract

Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and complete loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
United States 1 2%
Unknown 42 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 18%
Student > Master 8 18%
Student > Ph. D. Student 6 14%
Student > Bachelor 3 7%
Student > Postgraduate 3 7%
Other 7 16%
Unknown 9 20%
Readers by discipline Count As %
Medicine and Dentistry 9 20%
Nursing and Health Professions 6 14%
Social Sciences 3 7%
Environmental Science 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Other 8 18%
Unknown 13 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 October 2011.
All research outputs
#15,237,301
of 22,655,397 outputs
Outputs from BMC Medical Research Methodology
#1,498
of 2,000 outputs
Outputs of similar age
#95,779
of 140,441 outputs
Outputs of similar age from BMC Medical Research Methodology
#13
of 23 outputs
Altmetric has tracked 22,655,397 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,000 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 16th percentile – i.e., 16% 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 140,441 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.