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Designing a Biomechanics Investigation

Overview of attention for article published in Journal of orthopaedic trauma, December 2012
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Article details
Title
Designing a Biomechanics Investigation
Published in
Journal of orthopaedic trauma, December 2012
DOI 10.1097/bot.0b013e3182724605
Pubmed ID
Authors
Abstract

Physical testing is commonly performed to answer important biomechanical questions in the treatment of patients with fractures and other orthopaedic conditions. However, a variety of mistakes that are made in performing such investigations can severely limit their impact. The goal of this article is to discuss important aspects of study design to consider when planning for biomechanical investigations so that the studies can provide maximal benefit to the field. The best mechanical investigations begin with a good research question, one that comes out of patient care experience, is clearly defined, and can be stated concisely. The first practical issue to be considered is often choosing the type of physical specimens to be tested to address the research question. A related issue involves determining how many specimens will be needed to answer the posed mechanical question. Cadavers are generally still the closest to the actual clinical situation, but they are limited by interspecimen variability, which often requires a matched pair design that can address only one question. Simulated bone specimens limit variability and can replicate normal and osteoporotic bone. In planning the physical testing, the critical mechanical variables involved in answering the research question must be identified and due consideration given to deciding how best to measure them. Another important issue that arises relates to whether or not single static loadings will suffice in the testing (eg, to study construct stiffness) or whether cyclic dynamic testing is necessary (eg, to study late failure likely attributable to fatigue). To summarize, experimental design should be carefully planned before initiating mechanical testing. Sample size calculations should be performed to ensure adequate power and that clinically relevant differences can be detected. This pregame analysis can save significant time and cost and greatly increase the likelihood that the results will advance knowledge.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Spain 1 2%
Chile 1 2%
Unknown 60 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 13 21%
Researcher 11 18%
Student > Ph. D. Student 9 15%
Student > Bachelor 4 6%
Other 3 5%
Other 10 16%
Unknown 12 19%
Readers by discipline
Readers by discipline Count As %
Engineering 17 27%
Medicine and Dentistry 16 26%
Agricultural and Biological Sciences 5 8%
Nursing and Health Professions 2 3%
Materials Science 2 3%
Other 4 6%
Unknown 16 26%
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 12 December 2012.
All research outputs
#28,603,920
of 34,363,559 outputs
Outputs from Journal of orthopaedic trauma
#2,506
of 3,262 outputs
Outputs of similar age
#287,794
of 344,205 outputs
Outputs of similar age from Journal of orthopaedic trauma
#32
of 50 outputs
Altmetric has tracked 34,363,559 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,262 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 5th percentile – i.e., 5% 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 344,205 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.