Applying Expectancy-value Model to understand Health Preference An Exploratory Study

1. Applying Expectancy-value Modelto understand Health PreferenceAn Exploratory Study Xu-Hao Zhang Department of Pharmacy National University of Singapore

2. Outline of Presentation • Introduction Health Preference & the Expectancy-value model • Methods Study Design & Statistical Analysis • Results • Discussion • Conclusions

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

4. Health Preference • Whydo we needto understand health preference? Preference-based HRQoL instruments Disease management Utility Scores CUA for treatment comparisons Reported: Health preference to be associated with different demographic backgrounds

5. Health Preference • Howcan weunderstand health preference ? х Attitude Health preference Attitudinal Attributes Expectancy - valuemodel External Variables Subjective probability that the attitude has the attribute Evaluative value of the attribute

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

9. Statistical Analysis • Univariate analysis: To identify external variable(s) to be included in EVM • Multiple linear regression models (MLR): 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: • 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. 13 70 60 36 50 34 40 vas 20 30 4 20 10 0 Chinese Indian Ethnicity Results • Ethnicity to be the only external variable identified to cause significant difference in VAS score(p<0.05) 6.9 (16.7) 16.9(11.8)

12. Results • Power of EVM in explaining health preference: 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 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 from the psychological angle • demonstrating usefulness of EVM in explaining health preference • providing justification of its application to other populations to enable comparisons • Limitations • Small sample sizegeneralization of the result х Studies with larger sample size are suggested to verify the results

15. Conclusions • 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.

16. Thank You !