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Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening.

Publication ,  Journal Article
Pignone, MP; Brenner, AT; Hawley, S; Sheridan, SL; Lewis, CL; Jonas, DE; Howard, K
Published in: J Gen Intern Med
January 2012

PURPOSE: To compare two techniques for eliciting and clarifying patient values for decision making about colorectal cancer (CRC) screening: choice-based conjoint analysis and a rating and ranking task. METHODS: Using our decision lab registry and university e-mail lists, we recruited average risk adults ages 48-75 for a written, mailed survey. Eligible participants were given basic information about CRC screening and six attributes of CRC screening tests, then randomized to complete either a choice-based conjoint analysis with 16 discrete choice tasks or a rating and ranking task. The main outcome was the most important attribute, as determined from conjoint analysis or participant ranking. Conjoint analysis-based most important attribute was determined from individual patient-level utilities generated using multinomial logistic regression and hierarchical Bayesian modeling. RESULTS: Of the 114 eligible participants, 104 completed and returned questionnaires. Mean age was 57 (range 48-73), 70% were female, 88% were white, 71% were college graduates, and 62% were up to date with CRC screening. Ability to reduce CRC incidence and mortality was the most frequent most important attribute for both the conjoint analysis (56% of respondents) and rating/ranking (76% of respondents) groups, and these proportions differed significantly between groups (absolute difference 20%, 95% CI 3%, 37%, p =0.03). There were no significant differences between groups in proportion with clear values (p = 0.352), intent to be screened (p = 0.226) or unlabelled test preference (p = 0.521) CONCLUSIONS: Choice-based conjoint analysis produced somewhat different patterns of attribute importance than a rating and ranking task, but had little effect on other outcomes.

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Published In

J Gen Intern Med

DOI

EISSN

1525-1497

Publication Date

January 2012

Volume

27

Issue

1

Start / End Page

45 / 50

Location

United States

Related Subject Headings

  • Middle Aged
  • Male
  • Humans
  • General & Internal Medicine
  • Female
  • Early Detection of Cancer
  • Decision Making
  • Data Collection
  • Colorectal Neoplasms
  • Bayes Theorem
 

Citation

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ICMJE
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Pignone, M. P., Brenner, A. T., Hawley, S., Sheridan, S. L., Lewis, C. L., Jonas, D. E., & Howard, K. (2012). Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening. J Gen Intern Med, 27(1), 45–50. https://doi.org/10.1007/s11606-011-1837-z
Pignone, Michael P., Alison T. Brenner, Sarah Hawley, Stacey L. Sheridan, Carmen L. Lewis, Daniel E. Jonas, and Kirsten Howard. “Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening.J Gen Intern Med 27, no. 1 (January 2012): 45–50. https://doi.org/10.1007/s11606-011-1837-z.
Pignone MP, Brenner AT, Hawley S, Sheridan SL, Lewis CL, Jonas DE, et al. Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening. J Gen Intern Med. 2012 Jan;27(1):45–50.
Pignone, Michael P., et al. “Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening.J Gen Intern Med, vol. 27, no. 1, Jan. 2012, pp. 45–50. Pubmed, doi:10.1007/s11606-011-1837-z.
Pignone MP, Brenner AT, Hawley S, Sheridan SL, Lewis CL, Jonas DE, Howard K. Conjoint analysis versus rating and ranking for values elicitation and clarification in colorectal cancer screening. J Gen Intern Med. 2012 Jan;27(1):45–50.
Journal cover image

Published In

J Gen Intern Med

DOI

EISSN

1525-1497

Publication Date

January 2012

Volume

27

Issue

1

Start / End Page

45 / 50

Location

United States

Related Subject Headings

  • Middle Aged
  • Male
  • Humans
  • General & Internal Medicine
  • Female
  • Early Detection of Cancer
  • Decision Making
  • Data Collection
  • Colorectal Neoplasms
  • Bayes Theorem