Science Briefs

Health Maintenance, Older Adults, and the Internet

Recently, we focused our research efforts on two separate, but complimentary projects: older adults' use of e-health information services and the factors that affect their adoption (or lack thereof) of advanced e-health maintenance services such as Personal Health Records (PHRs).

By Richard Pak, PhD, and Aideen Stronge, PhD

Richard Pak, PhDRichard Pak is an Assistant Professor in the Department of Psychology at Clemson University. He received his PhD in Psychology from the Georgia Institute of Technology in 2005. His research focuses on the psychological aspects of using new technologies for people of all ages. More information can be found on his Clemson faculty website. This research is supported by a Google Research Award.


Aideen Stronge, PhDAideen Stronge is a Senior User Experience Researcher at Google. She received her PhD in Psychology from the Georgia Institute of Technology in 2006. As a graduate student, Aideen's research focused on the design of technology for older adults from the Web to electronic medication reminders.




When you get a strange feeling in your stomach, funny looking blemish on your skin, or a new medication from the doctor what is the first thing you do? If you are like a lot of people, you go to the internet to search for health information (Pew Internet & American Life Project, 2005). As useful and immediate as this resource may be for the general public, it may be even more beneficial for older adults.

Technology, however, has advanced much faster than psychology, leading to unanswered questions about how to best design e-health systems for older adults. Access is made difficult due to a mismatch between older users’ cognitive capabilities and the demands placed upon them by the system. Recently, we focused our research efforts on two separate, but complimentary projects: older adults' use of e-health information services and the factors that affect their adoption (or lack thereof) of advanced e-health maintenance services such as Personal Health Records (PHRs).

Age-related change in Cognition

One way to describe age-related changes in cognition is in terms of how different skills and abilities change as we get older. For example, older adults may find it more difficult to learn new video games (compared to college students), but may still be able to beat college-aged players in games that rely heavily on knowledge such as Trivial Pursuit or Jeopardy. This distinction is reflected in the theory of fluid and crystallized intelligence (Horn & Cattell, 1967). Fluid intelligence refers to those abilities that allow individuals to think and act in novel situations (e.g., reasoning ability) and are thought to be unbiased by educational level or experience (Garfein, Schaie, & Willis, 1988). Specific indicators of fluid abilities are working memory and spatial abilities. Crystallized intelligence can be described as the products of experience or education. Indicators of crystallized intelligence are tests of general knowledge, or vocabulary. It has been well-established that fluid intelligence generally shows significant age-related declines whereas crystallized intelligence remains stable or increases with age (e.g., Horn, 1982; Kausler, 1991; Horn & Cattell, 1967; Schaie, 1996).

A high level of performance can be attained when crystallized intelligence is used to compensate for some aspects of declining fluid abilities (e.g., Salthouse, 1984). In a similar manner, older users may be able to compensate for declines in fluid ability when using the Internet, but can the design of a web interface specifically assist with this compensation strategy?

Unintentionally Designed for Older Adults?

Traditionally, websites have presented information in a categorical (or hierarchical) format (folders within folders). Using Amazon.com to browse for a book is a good illustration of how information can be hierarchically-organized. Figure 1 is a representation of the organization of a subset of Amazon’s book store. To find a specific children’s audio book you may first select the major top-level category of "Books," and then perhaps a sub-category ("Children's books"). From there, further categorical selections are made until a desired book is found (Figure 1):

Pak Figure 1

Navigation through hierarchical systems has been shown to be reliant on fluid abilities such as spatial ability and not surprisingly, older adults have exhibited age-related declines when using these systems (Laberge & Scialfa, 2005; Pak, Rogers, & Fisk, 2006; Seagull & Walker, 1992). For example, older adults were more likely than younger adults to rely on a search engine’s categorical structure when searching for information on the web (e.g., categories on the homepage) (Stronge, Rogers, & Fisk, 2006). This approach was found to be negatively correlated with success, ultimately contributing to the finding that older adults were less successful in finding information on the web than younger adults.

In recent years, there has been a major change in the focus, design, and delivery of web services (collectively termed "Web 2.0"). One example is in the way that informational databases can be organized and presented. Some websites are now providing "tag-based" interfaces in addition to offering search options and in place of the categorical organization of information. Tag-based interfaces present information clustered around keywords, similar concepts, or tags and rely on information-seeking behaviors that are more dependent on general/word knowledge.

In a tag-based system (for example on a website), each page is "tagged" with a specific keyword. For example, a children’s audio book might be assigned the tags "audio book, children, book". Instead of users navigating one category after another, they now just have to select any appropriate tag in the interface which then presents all of the documents that have been tagged with that word. Figure 2 represents this interaction. In Figure 2a, the user has clicked on the "Audio books" category and is then presented with all pages tagged with that term. In the second example, the user has selected the "Children’s" tag and is shown all pages with that term. Because pages are tagged with descriptive and redundant keywords, users may have a better chance of finding the desired pages. While on the surface, this type of presentation might seem overwhelming compared to the controlled presentation of folders and categories, we hypothesized that selection via a tag-based interface might place less demand on spatial abilities because there was less of a need to navigate the hierarchical structure of folders, and more demand on verbal knowledge or crystallized intelligence.

Pak Figure 2

In a recent experiment (Pak & Price, 2008) we found that performance in retrieving information with a computer was equivalent between younger and older adults when they used a tag-based system. Participants searched a fictional travel information website for answers to questions such as, "where do I mail my passport application?" We chose travel information under the assumption that neither age group would be especially familiar with the travel domain.

When participants navigated a hierarchically organized site, younger adults performed significantly better (faster and fewer errors) than older adults in the retrieval task. However, in the tag-based condition, performance was equivalent between younger and older adults (Figure 3). The lack of hierarchical organization or the relative flatness of the organization may ease spatial ability demands. In addition, the semantic organization around tags may increase demands on vocabulary and general knowledge. These results suggest that extant age differences in abilities may be overcome, to some extent, by relatively minor changes to the information access interface.

Pak Figure 3

With these results as a background, we are currently examining a topical domain where older adults are expected to have more knowledge than younger adults: health information. We expect that older adults’ higher level of health knowledge coupled with a tag-based interface, which takes advantage of knowledge, might further improve older adults’ information search performance. For example, in a previous study, age-related differences in prospective memory were reduced when a task was framed in terms of health behaviors (taking medications) as compared to when the exact same task was given a more neutral context such as remembering to schedule conference rooms at the right time (Stronge, 2006).

For most people, being able to access and use a database of accurate health information is convenient, but may be especially useful for older adults as they tend to be managing multiple conditions or take more medications than other age groups. Better understanding the relationship between age-related capabilities and limitations and the design of information systems can remove the usability barrier that might keep older adults from using e-health services.

Future E-health Technology and Older Adults

Imagine if you had your complete medical history, including doctor visits, diagnoses, medications, and medical images within easy access. This is the promise of Internet-based personal health records (PHR). PHRs are user-maintained, long-term records of a patient’s medical history. They are the consumer equivalent of what your doctor might use in his or her office. At a minimum level, PHRs serve as static repositories of information.

PHRs can be a useful and beneficial resource for older adults by giving them the ability to keep important health information in a single location, alleviating the need to keep and manage a myriad of paper records. PHRs may also act as decision support systems to help older adults make more informed health choices. For example, a diabetic patient may be able to track blood glucose levels over an extended period of time (months) and observe the effect of lifestyle or medication interventions by using a PHR that aggregates data from doctor visits and pharmacists, as well as data they may input on their own.

Older users may not adopt a new tool or technology merely because it is available. They must also perceive how the system is personally useful compared to existing methods (Davis, Bagozzi, & Warshaw, 1989) and that it is easy to use. As prior research has shown (Melenhorst, Rogers, & Bouwhuis, 2006), older adult’s adoption of new technologies may critically depend on whether they understand the costs and benefits of those technologies (perceived utility).

A two-pronged (at least) approach to older adult PHR adoption and usage should examine the ease of use component to better understand how to design the task and interface for older adults. This may require an understanding of how older adults currently manage their health records. In addition, it may require understanding, from the older users’ point of view, the potential costs and benefits of PHRs in relation to currently used tools and techniques.

References

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 982-1003.

Garfein, A. J., Schaie, K. W., & Willis, S. L. (1988). Microcomputer proficiency in later-middle-aged and older adults: Teaching old dogs new tricks. Social Behavior, 3 (2), 131-148.

Horn, J. L. (1982). The theory of fluid and crystallized intelligence in relation to concepts of cognitive psychology and aging in adulthood. In F. I. M. Craik & S. E. Trehub (Eds.), Aging and cognitive processes (pp. 847-870). New York: Plenum Press.

Horn, J. L., & Cattell, R. B. (1967). Age differences in fluid and crystallized intelligence. Acta Psychologica, 26, 107-129.

Kausler, D. H. (1991). Experimental psychology, cognition, and human aging (2nd ed.). New York: Springer-Verlag.

Laberge, J. C., & Scialfa, C. T. (2005). Predictors of web navigation performance in a life span sample of adults. Human Factors, 47, 289-302.

Melenhorst, A-S., Rogers, W. A., & Bouwhuis, D. G. (2006). Older adults’ motivated choice for technological innovation: Evidence for benefit-driven selectivity. Psychology and Aging, 21, 190-195.

Pak, R., & Price, M. M. (2008). Designing an information search interface for younger and older adults. Human Factors, 50, 614-628.

Pak, R., Rogers, W. A., & Fisk, A. D. (2006). Spatial ability sub-factors and their influence on an information search task. Human Factors, 48, 154-165.

Pew Internet & American Life Project. Online health search 2006; www.pewinternet.org/PPF/r/190/report_display.asp; retrieved October 6, 2008

Salthouse, T. A. (1984). Effects of age and skill on typing. Journal of Experimental Psychology: General, 3, 3-16.

Schaie, K. W. (1996). Intellectual development in adulthood. The Seattle longitudinal study. New York: Cambridge University Press.

Seagull, F. J. & Walker, N. (1992). The effects of hierarchical structure and visualization ability on computerized information retrieval. International Journal of Human-Computer Interaction, 4, 369-385.

Stronge, A. J. (2006). Understanding the role of planning in the performance of complex prospective memory tasks. Unpublished doctoral dissertation, Georgia Institute of Technology, Atlanta, GA.

Stronge, A. J., Rogers, W. A., Fisk, A. D. (2006). Web-based information search: effects of strategy use and age on search success. Human Factors, 48, 434-446.