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The Patient - Patient-Centered Outcomes Research
Published in: The Patient - Patient-Centered Outcomes Research 4/2010

Open Access 01-12-2010 | Review Article

Adaptive Choice-Based Conjoint Analysis

A New Patient-Centered Approach to the Assessment of Health Service Preferences

Authors: Dr Charles E. Cunningham, Ken Deal, Yvonne Chen

Published in: The Patient - Patient-Centered Outcomes Research | Issue 4/2010

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Abstract

Conjoint analysis (CA) has emerged as an important approach to the assessment of health service preferences. This article examines Adaptive Choice-Based Conjoint Analysis (ACBC) and reviews available evidence comparing ACBC with conventional approaches to CA. ACBC surveys more closely approximate the decision-making processes that influence real-world choices. Informants begin ACBC surveys by completing a build-your-own (BYO) task identifying the level of each attribute that they prefer. The ACBC software composes a series of attribute combinations clustering around each participant’s BYO choices. During the Screener section, informants decide whether each of these concepts is a possibility or not. Probe questions determine whether attribute levels consistently included in or excluded from each informant’s Screener section choices reflect ‘Unacceptable’ or ‘Must Have’ simplifying heuristics. Finally, concepts identified as possibilities during the Screener section are carried forward to a Choice Tournament. The winning concept in each Choice Tournament set advances to the next choice set until a winner is determined.
A review of randomized trials and cross-over studies suggests that, although ACBC surveys require more time than conventional approaches to CA, informants find ACBC surveys more engaging. In most studies, ACBC surveys yield lower standard errors, improved prediction of hold-out task choices, and better estimates of real-world product decisions than conventional choice-based CA surveys.
Footnotes
1
The term ‘concepts’ refers to the multi-attribute product or service options included in ACBC and choice-based conjoint surveys.
 
2
The ‘none threshold’ can be used to estimate the percentage of participants who would prefer none of the options presented in simulations.[14]
 
3
Investigators sometimes present one or more hold-out choice tasks to all participants. Hold-out tasks are not included in the design of the experiment or the estimation of utilities. The accuracy with which simulations using the utilities derived from the remaining choice tasks predict either individual hold-out task choices (hit rates), or the overall percentage of participants selecting each hold-out task option (share of preference), is thought to reflect the study’s internal validity.[14]
 
4
Although preferences for the levels of some attributes might have a natural order (e.g. treatment effect size or frequency of adverse events), respondent errors may lead to utility values violating these assumptions (e.g. reversals). Some statistical packages, therefore, allow analysts to impose constraints that require utilities to increase or decrease monotonically.[14]
 
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Metadata
Title
Adaptive Choice-Based Conjoint Analysis
A New Patient-Centered Approach to the Assessment of Health Service Preferences
Authors
Dr Charles E. Cunningham
Ken Deal
Yvonne Chen
Publication date
01-12-2010
Publisher
Springer International Publishing
Published in
The Patient - Patient-Centered Outcomes Research / Issue 4/2010
Print ISSN: 1178-1653
Electronic ISSN: 1178-1661
DOI
https://doi.org/10.2165/11537870-000000000-00000

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