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Developing a contributing factor classification scheme for Rasmussen's AcciMap: Reliability and validity evaluation

Overview of attention for article published in Applied Ergonomics, May 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Article details
Title
Developing a contributing factor classification scheme for Rasmussen's AcciMap: Reliability and validity evaluation
Published in
Applied Ergonomics, May 2017
DOI 10.1016/j.apergo.2017.04.014
Pubmed ID
Authors
Abstract

One factor potentially limiting the uptake of Rasmussen's (1997) Accimap method by practitioners is the lack of a contributing factor classification scheme to guide accident analyses. This article evaluates the intra- and inter-rater reliability and criterion-referenced validity of a classification scheme developed to support the use of Accimap by led outdoor activity (LOA) practitioners. The classification scheme has two levels: the system level describes the actors, artefacts and activity context in terms of 14 codes; the descriptor level breaks the system level codes down into 107 specific contributing factors. The study involved 11 LOA practitioners using the scheme on two separate occasions to code a pre-determined list of contributing factors identified from four incident reports. Criterion-referenced validity was assessed by comparing the codes selected by LOA practitioners to those selected by the method creators. Mean intra-rater reliability scores at the system (M = 83.6%) and descriptor (M = 74%) levels were acceptable. Mean inter-rater reliability scores were not consistently acceptable for both coding attempts at the system level (MT1 = 68.8%; MT2 = 73.9%), and were poor at the descriptor level (MT1 = 58.5%; MT2 = 64.1%). Mean criterion referenced validity scores at the system level were acceptable (MT1 = 73.9%; MT2 = 75.3%). However, they were not consistently acceptable at the descriptor level (MT1 = 67.6%; MT2 = 70.8%). Overall, the results indicate that the classification scheme does not currently satisfy reliability and validity requirements, and that further work is required. The implications for the design and development of contributing factors classification schemes are discussed.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 86 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 %
Unknown 86 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 21 24%
Student > Master 11 13%
Researcher 6 7%
Student > Doctoral Student 5 6%
Student > Bachelor 4 5%
Other 12 14%
Unknown 27 31%
Readers by discipline
Readers by discipline Count As %
Engineering 23 27%
Social Sciences 10 12%
Business, Management and Accounting 5 6%
Nursing and Health Professions 4 5%
Medicine and Dentistry 4 5%
Other 9 10%
Unknown 31 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 2024.
All research outputs
#4,860,692
of 34,582,852 outputs
Outputs from Applied Ergonomics
#349
of 2,128 outputs
Outputs of similar age
#63,852
of 356,719 outputs
Outputs of similar age from Applied Ergonomics
#9
of 31 outputs
Altmetric has tracked 34,582,852 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,128 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 83% 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 356,719 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.