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Cited by 356

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Analysis of subjective knee complaints using visual analog scales

Flandry, Fred, Hunt, Jon P., Terry, Glenn C., Hughston, Jack C.·1991·The American Journal of Sports Medicine

Abstract

A questionnaire using a system of visual analog scales was developed for analyzing subjective knee com plaints. This system was tested on 117 consecutive patients who had undergone knee surgery and 65 patients at their initial office evaluation of a knee disor der. The validity of and patient affinity for this type of questionnaire was compared with that of three other established subjective evaluation methods. The visual analog scale system was shown to be valid and comparable to other methods while offering several advantages. It brought greater sensitivity and greater statistical power to data collection and analysis by allowing a broader range of responses than did traditional categorical responses. It removed bias that was introduced by examiner questioning, and it allowed graphic temporal comparisons. Most importantly, pa tient affinity was higher for this type of subjective evaluation than for other methods.

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Crossref · 10.1177/036354659101900204

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Metadata

Authors
Flandry, F., Hunt, J. P., Terry, G. C., & Hughston, J. C.
Venue
The American Journal of Sports Medicine
Published
1991-03
Volume
19
Issue
2
Pages
112-118
ISSN
  • 0363-5465 (ISSN-L)
  • 1552-3365
OpenAlex
W2053432078
Cited by
356
References
22
FWCI
2.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Analysis of subjective knee complaints using visual analog scales. https://app.cochat.ai/papers/10.1177/036354659101900204
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Flandry, F., Hunt, J. P., Terry, G. C., & Hughston, J. C. (1991). Analysis of subjective knee complaints using visual analog scales. The American Journal of Sports Medicine. https://doi.org/10.1177/036354659101900204

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.