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Proceedings of the AMIA Symposium logoLink to Proceedings of the AMIA Symposium
. 2001:364–368.

Acceptability of computerized visual analog scale, time trade-off and standard gamble rating methods in patients and the public.

L A Lenert 1, A E Sturley 1
PMCID: PMC2243469  PMID: 11825211

Abstract

One technique to enhance patient participation in clinical decision making is formal measurement of preferences and values. Three commonly applied methods are a visual analog scale(VAS), the standard gamble(SG), and the time trade-off(TTO). We studied participants subjective experience using computer implementations these methods using scale we call the VIBE (for Value Instrument Battery--Evaluation) that measures four aspects of user acceptance (clarity, difficulty, reasonableness, and comfort level) Studies were performed in two groups: patients with HIV infection (n=75) and a convenience sample of the general public(n=640). In the patient study, VIBE scores appeared reliable (Cronbach s alpha of 0.739, 0.826, and 0.716, for VAS, SG, and TTO ratings, respectively.) Patients acceptance of the VAS the highest, followed by the TTO and the SG method (p<0.05 for all comparisons). Despite significant enhancements in computer software for measuring SG preferences, observed differences in acceptance between SG and VAS methods were replicated in the general public study (p<0.0001 for differences). The results suggest developers of clinical decision support systems should use VAS and TTO rating methods where these methods are theoretically appropriate.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Lenert L., Kaplan R. M. Validity and interpretation of preference-based measures of health-related quality of life. Med Care. 2000 Sep;38(9 Suppl):II138–II150. doi: 10.1097/00005650-200009002-00021. [DOI] [PubMed] [Google Scholar]
  2. Protheroe J., Fahey T., Montgomery A. A., Peters T. J. The impact of patients' preferences on the treatment of atrial fibrillation: observational study of patient based decision analysis. BMJ. 2000 May 20;320(7246):1380–1384. doi: 10.1136/bmj.320.7246.1380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Robinson A., Loomes G., Jones-Lee M. Visual analog scales, standard gambles, and relative risk aversion. Med Decis Making. 2001 Jan-Feb;21(1):17–27. doi: 10.1177/0272989X0102100103. [DOI] [PubMed] [Google Scholar]
  4. Ruland C. M. Decision support for patient preference-based care planning: effects on nursing care and patient outcomes. J Am Med Inform Assoc. 1999 Jul-Aug;6(4):304–312. doi: 10.1136/jamia.1999.0060304. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Sanders G. D., Hagerty C. G., Sonnenberg F. A., Hlatky M. A., Owens D. K. Distributed decision support using a web-based interface: prevention of sudden cardiac death. Med Decis Making. 1999 Apr-Jun;19(2):157–166. doi: 10.1177/0272989X9901900206. [DOI] [PubMed] [Google Scholar]
  6. Scott G. C., Cher D. J., Lenert L. A. SecondOpinion: interactive Web-based access to a decision model. Proc AMIA Annu Fall Symp. 1997:769–773. [PMC free article] [PubMed] [Google Scholar]
  7. Soetikno R. M., Mrad R., Pao V., Lenert L. A. Quality-of-life research on the Internet: feasibility and potential biases in patients with ulcerative colitis. J Am Med Inform Assoc. 1997 Nov-Dec;4(6):426–435. doi: 10.1136/jamia.1997.0040426. [DOI] [PMC free article] [PubMed] [Google Scholar]

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