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How Older Adults Use the Internet to Look for Health Information Kathryn Flynn Duke University Maureen Smith University of Wisconsin Jeremy Freese University.

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Presentation on theme: "How Older Adults Use the Internet to Look for Health Information Kathryn Flynn Duke University Maureen Smith University of Wisconsin Jeremy Freese University."— Presentation transcript:

1 How Older Adults Use the Internet to Look for Health Information Kathryn Flynn Duke University Maureen Smith University of Wisconsin Jeremy Freese University of Wisconsin Harvard University

2 Introduction Many patients want more information than their physicians have time to provide Considerable enthusiasm for Internets potential to transform communication Concern about disparities in use Discussions of differential use have focused on social position Wide variation in use even among those of similar social position Far less attention to implications of psychological heterogeneity Unclear when patients are using the Internet to search for health information in relation to their outpatient doctor visits

3 Objective To determine how psychological differences are related to the use and timing of Internet health searches among older adults

4 Wisconsin Longitudinal Study (WLS) 1/3 random sample of Wisconsin high school graduates from spring 1957 (n=10,317) Surveys conducted in 1957 (in school), 1964 (mail to parents), 1975 (phone), (phone & mail), and (phone & mail) High response rates (>80%) WLS graduate sample is age homogeneous education truncated ethnically homogeneous

5 Sample characteristics Source: Wisconsin Longitudinal Study Graduate Survey 2004, N=6,125

6 Explanatory variables Personality Openness Conscientiousness Extraversion Agreeableness Neuroticism Cognitive ability High school IQ Self-reported effort to stay healthy Preferences Want to be told all treatment options Want MD to know entire medical history Want treatment choices Want to make treatment decisions

7 Control variables Gender Marital status # children Rural or farm origin Educational attainment Length of relationship with usual provider of care SF-12 Physical Mental Health insurance # prescription meds taken regularly Common conditions Asthma Cancer Diabetes IBS Heart disease Stroke Hypertension Joint problems

8 Analysis Multinomial logistic regression Regress searching behavior on explanatory variables Predict adjusted probability of each behavior by explanatory variable with all other variables held at population mean

9 State-of-the-art computing, 1957

10 Internet use in WLS sample, 2004 Source: 2004 WLS Graduate Survey, N=6125

11 Internet use in WLS sample, 2004 Source: 2004 WLS Graduate Survey, N=6125 2% have used net for health, but dont have home PC

12 Timing of last health-related search Source: 2004 WLS Graduate Survey, N=6125

13 Timing of last health-related search Graduate SchoolHigh School Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05 ***

14 Timing of last health-related search High cognitive abilityLow cognitive ability *** Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05

15 Timing of last health-related search Low OpennessHigh Openness *** Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05

16 Timing of last health-related search Low NeuroticismHigh Neuroticism * Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05

17 Timing of last health-related search Work hard stay healthyDont work hard to stay healthy ** Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05

18 Timing of last health-related search Want many treatment choicesDont want many choices ** Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05

19 Timing of last health-related search No CancerCancer * Source: 2004 WLS Graduate Survey, adjusted for all variables in the full model, *odds ratio significant at p<0.05

20 Conclusions Those with increased educational attainment, cognitive ability, and greater openness more likely to search for health information online Relatively few older patients are preparing for visits by seeking health information online Those that do tend to be more health-conscious or neurotic People diagnosed with cancer are more likely to search for health information online after a doctor visit Understanding how patients use non-physician sources of health information is important to facilitating shared decision making within doctor visits


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