Tim Patton, Project HealthDesign Ph.D. in Engineering Student, University of Wisconsin-Madison
Uba Backonja, Project HealthDesign Ph.D. in Nursing Student, University of Wisconsin-Madison
People might not be willing to share all of their observations of daily living (ODLs). This may be old news to health care providers, but it was a bit of a surprise to the engineers among us as we looked for information to help us design systems that support patients’ real needs in regard to personal health management, decision-making and monitoring behaviors.
Because they are indicators to which an individual pays attention and finds important to his or her health, ODLs are very specific to individual patients. To begin to obtain a systematic understanding of ODLs, we recently conducted a pilot in which we performed one-on-one interviews with 10 college students. The ODLs that emerged focused on health behaviors (e.g., exercise) and monitoring symptoms (e.g., pain). Because we framed the questions in terms of health, this is largely what we had expected. Throughout the pilot, we found that participants seemed willing to talk about very personal ODLs and discuss their personal habits’ and relationships’ impacts on their health.
Because of this apparent comfort with disclosing highly personal information, we assumed that participants would be comfortable disclosing all ODLs. However, we have some reservations regarding whether that assumption is true. During the interviews, not one student mentioned drinking alcohol, smoking, drug use, sex (unsafe or otherwise) or partying. In fact, none of the ODLs the students reported to us carried a negative social stigma, or could be seen as a “bad” ODL.
Were we simply lucky with our sample? The CDC estimates that 21.4% of adults ages 18–24 smoke and that young adults and adolescents under 21 drink 11% of all alcohol consumed in the United States. Furthermore, the CDC estimates that 43% of all students report drinking in a high-risk manner at some point during college. Statistically, it is unlikely that such behavior was truly absent in our sample population.
Thus, we are left to ponder why the “bad” ODLs were missing. We have considered the following:
- Our questions may have biased participants toward ODLs that improve or maintain health.
- Participants didn’t think to observe the effects of “bad” things as ODLs.
- Participants may deliberately avoid mentioning ODLs that might cast them in negative lights.
First, given that participants did mention things that detracted from health (e.g., lack of sleep, poor diet), we don’t think this can be explained by a positive bias in our interview questions. Second, other negative behaviors were noted (e.g., poor diet choices and exercise habits). Thus, we are left with a sense that people deliberately avoided telling us about “bad” ODLs.
Due to the anonymous nature of our interviews and the encouraging early results, we were hopeful we could avoid this potential issue and strive to account for it in future work. To properly design systems in support of ODLs, we must understand the full range of personal observations, including those that people prefer to keep to themselves. Thus, as we continue to push for systems that support personal health, we will likely need to find ways to safely and securely elicit all ODLs, whether good or “bad.”
