1. Applying Expectancy-value Model to understand Health Preference An Exploratory Study Xu-Hao Zhang Department of Pharmacy National University of Singapore

2. Outline of Presentation Introduction Health Preference & the Expectancy-value model Health Preference & the Expectancy-value modelMethods Study Design & Statistical Analysis Study Design & Statistical AnalysisResultsDiscussionConclusions

3. Health Preference Indicating people’s preference of a particular health state Measured by RS (Rating Scale) / TTO / SG Quantified as utility scores Confined to bed Some problems washing or dressing self Unable to perform usual activities No pain or discomfort Extremely anxious or discomfort 100 0 8

4. Why do we need to understand health preference? Health Preference UtilityScores Preference-based HRQoL instruments CUA for treatment comparisons Reported: Health preference to be associated with different demographic backgrounds Disease management

5. How can we understand health preference ? х Health Preference Health preference Attitude Expectancy - value model Subjective probability that the attitude has the attribute Attitudinal Attributes Evaluative value of the attribute ExternalVariables

6. Objectives of the study To generate factors of the health preference for the “Expectancy-value model” (“EVM”) To investigate the usefulness of EVM in explaining health preference

7. Study Design Focus group approach Attitudinal Attributes (AA) Questionnaire Development Pilot study   One-to-one interview  Eligible Chinese and Indian Singaporeans (aged above 20 and with over 6 yrs of education) across 5 age groups (20-29;30-39;40-49;50-59; 60+) 9

8. Questionnaire Development 1. Design: Measure of health preference of the health state by a 0-100 Visual Analogue Scale (VAS) Measure of health preference of the health state by a 0-100 Visual Analogue Scale (VAS)(VAS) Expectancy and value of each attribute, measured on a Expectancy and value of each attribute, measured on a 7-point Likert Scale 7-point Likert Scale External variables: age, gender, ethnicity, education, housing, marital status, and concurrent chronic diseases External variables: age, gender, ethnicity, education, housing, marital status, and concurrent chronic diseases 2. Face validity: Reviewed by 10 postgraduate students Reviewed by 10 postgraduate students 3. Finalization: Amended accordingly, if necessary Amended accordingly, if necessary

9. Statistical Analysis Univariate analysis: To identify external variable(s) to be included in EVM Multiple linear regression models (MLR): attitudinal attributes To investigate the explanative power of EVM by examining attitudinal attributes and significant external variables (if any) separately or in combination

10. Results Demographic information: Demographic information:  25 Chinese and 21 Indian Singaporeans  Age: 45.0 (SD: 15.55) years  55.6% female Four attitudinal attributes generated:  reduction in Health-related quality of life (RQoL)  adding a burden to family (BTF)  dependence on others ( DOO)  inability to work or study (ITW)

11. Ethnicity to be the only external variable identified to cause significant difference in VAS score (p<0.05) Results ChineseIndian Ethnicity 0 10 20 30 40 50 60 70 vas 34 36 4 20 13 16.9(11.8) 6.9 (16.7)

12. Results Power of EVM in explaining health preference: The combined sample (n=46) Chinese (n=25) Indians (n=21) EVM (sum of 4AA, ethnicity) 0.27 *0.130.24* Sum of 4 AA0.16 *// Ethnicity0.11 *// Table 1. Regression analysis on EVM, AAs and ethnicity Figures shown as adjusted R square: *p<0.05

13. Results Power of each AA in explaining health preference The combined sample (n=46) Chinese (n=25) Indians (n=21) RQol 0.14 * 0.16 * 0.16 * 0.12 * 0.12 * BTF 0.16 * 0.14 * 0.09 * 0.09 * DOO 0.10 * 0.04 0.23 * 0.23 * ITW 0.07 * 0.09* 0.003 0.003 Table 2. Regression analysis on each AA Figures shown as adjusted R square; The scores of 4 AAs are not statistically different for two ethnic groups; *: p<0.05 > > > <

14. Discussion Significance of the study the 1st ever to investigate factors influencing health preference the 1st ever to investigate factors influencing health preference from the psychological angle from the psychological angle demonstrating usefulness of EVM in explaining health preference demonstrating usefulness of EVM in explaining health preference providing justification of its application to other populations to providing justification of its application to other populations to enable comparisons enable comparisons Limitations Limitations Small sample size generalization of the result Small sample size generalization of the result х Studies with larger sample size are suggested to verify the results

15. The Expectancy-value model is helpful in explaining the variances in health preference. Future studies with larger sample sizes and among other populations are suggested for its further verifications. Conclusions

16. Thank You !