| Title |
Frequency of data extraction errors and methods to increase data extraction quality: a methodological review
|
|---|---|
| Published in |
BMC Medical Research Methodology, November 2017
|
| DOI | 10.1186/s12874-017-0431-4 |
| Pubmed ID | |
| Authors |
Tim Mathes, Pauline Klaßen, Dawid Pieper |
| Abstract |
Our objective was to assess the frequency of data extraction errors and its potential impact on results in systematic reviews. Furthermore, we evaluated the effect of different extraction methods, reviewer characteristics and reviewer training on error rates and results. We performed a systematic review of methodological literature in PubMed, Cochrane methodological registry, and by manual searches (12/2016). Studies were selected by two reviewers independently. Data were extracted in standardized tables by one reviewer and verified by a second. The analysis included six studies; four studies on extraction error frequency, one study comparing different reviewer extraction methods and two studies comparing different reviewer characteristics. We did not find a study on reviewer training. There was a high rate of extraction errors (up to 50%). Errors often had an influence on effect estimates. Different data extraction methods and reviewer characteristics had moderate effect on extraction error rates and effect estimates. The evidence base for established standards of data extraction seems weak despite the high prevalence of extraction errors. More comparative studies are needed to get deeper insights into the influence of different extraction methods. |
X Demographics
The data shown below were collected from the profiles of 86 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 21 | 24% |
| United States | 7 | 8% |
| Australia | 6 | 7% |
| Canada | 5 | 6% |
| Germany | 3 | 3% |
| Spain | 2 | 2% |
| Netherlands | 2 | 2% |
| Switzerland | 2 | 2% |
| South Africa | 2 | 2% |
| Other | 5 | 6% |
| Unknown | 31 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 46 | 53% |
| Scientists | 28 | 33% |
| Practitioners (doctors, other healthcare professionals) | 7 | 8% |
| Science communicators (journalists, bloggers, editors) | 4 | 5% |
| Unknown | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 194 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 44 | 23% |
| Student > Bachelor | 18 | 9% |
| Researcher | 17 | 9% |
| Student > Ph. D. Student | 13 | 7% |
| Student > Doctoral Student | 9 | 5% |
| Other | 24 | 12% |
| Unknown | 69 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 31 | 16% |
| Medicine and Dentistry | 31 | 16% |
| Psychology | 11 | 6% |
| Computer Science | 8 | 4% |
| Social Sciences | 6 | 3% |
| Other | 30 | 15% |
| Unknown | 77 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 56. 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 04 August 2021.
All research outputs
#771,866
of 25,595,500 outputs
Outputs from BMC Medical Research Methodology
#62
of 2,301 outputs
Outputs of similar age
#17,305
of 448,076 outputs
Outputs of similar age from BMC Medical Research Methodology
#6
of 42 outputs
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