Stories are just powerful as data in personal health informatics
This article summarizes a CHI paper authored by Herman Saksono, Carmen Castaneda-Sceppa, Jessica A. Hoffman, Magy Seif El-Nasr, and Andrea G. Parker. At the end of the article, we shared the CHI 2021 video presentation.
After more than a decade after the launch of fitness trackers like Fitbit and Apple Watch, we need to rethink how these personal health informatics should be redesigned. Especially when there is a growing concern of fitness tracker abandonment (Clawson et al., 2015, Epstein et al., 2015). Here, we begin with two critical questions. First, is relying on the person to change their health behavior enough? Second, are these personal informatics tools can equitably beneficial for people of all socioeconomic statuses?
The answer is no and no.
First, we don’t develop health behavior in a vacuum. From the perspective of social psychology, our attitudes and behavior are influenced by our social environment. Second, fitness trackers also less beneficial for families of low-socioeconomic status neighborhoods (Saksono et al., 2018), because they deal with a greater barrier to be active, to begin with (Day, 2006). Burdening work and caregiving duties of single caregivers, compounded by unsafe neighborhoods, making it significantly harder for these families to be active. Furthermore, families in poverty are at the greatest risk of obesity (CDC, 2017), which also makes them at risk of getting diabetes and cardiovascular diseases (Reilly and Kelly, 2011, Umer et al., 2009).
Thus, in our CHI 2021 paper, we began taking the initial steps to understand how a social personal informatics tool can look like, and whether this redesign works for families of low socioeconomic status.
StoryMap and Social Cognitive Theory
We began by developing StoryMap on top of the Storywell app (read the Medium article here). In StoryMap, families can do two things. First, they can record their physical activity experiences as stories. This supports self-modeling. Second, they can share their fitness data and stories on a neighborhood map that other families can listen to and get some inspiration. This supports social modeling.
Self-modeling is learning by remembering your own experiences of being successful in the past (e.g., remembering how you managed to exercise).
Social modeling is learning by observing other people similar to you being successful in performing the task. These two modes of learning are the key process in Social Cognitive Theory, a well-established social psychology theory used in many fields (Bandura, 1986, 1999, 2001), including health and communication. During social modeling, you don’t have to observe the model directly. You can also observe the models’ pictures in action, read their experiences, or listen to their stories.
We then conducted in-depth qualitative fieldwork to understand whether StoryMap can fulfill its goal. We worked with 16 families of low socioeconomic status backgrounds for five weeks. We asked them to wear MiBand 2 fitness trackers and use the app regularly. And what we found was astounding.
The Personal and Social Power of Stories + Data
We found that both fitness data and stories are powerful means of health promotion, but they work in different ways. I will discuss the power of data and stories in self-modeling, followed by social modeling.
During self-modeling, storytelling of successful experiences in the past is a form of reflection that can be very motivating. Caregivers in the study described the power of remembering family exercises in the past. Remembering such experiences reminded them that they have the ability to exercise. Furthermore, remembering family exercises also brings good feelings from the past to the present. And because they felt good, they wanted to be active again at present. This shows that reflecting on past positive experiences is so powerful, and personal informatics should support reflections on past successes.
During social modeling, listening to peer stories and looking at their fitness data is also motivating. Here are four ways for data and stories from our peers are very valuable:
- Our peer’s data helps us to know our adequacy. That is, by seeing how other people similar to us perform, we get a sense of how much is an adequate goal for us. By setting a more reasonable goal and achieving those goals, our self-efficacy goes up.
- Stories from other people tell us the steps we need to take to achieve the task of being active. That’s very motivating because knowing how to do a task enhances our self-efficacy and motivation.
- Stories also communicate positive emotions after exercising. Such stories, enhance our outcome expectations. In other words, it solidifies your expectations that being active is emotionally satisfying.
- Stories also tell us that our behavior is aligned with our peers’ norms. Stories like that validate our actions. We feel confident about our behavior if the outcome expectations are validated by our peers’ norms.
We further expand our theoretical contribution by delineating data and stories. Data represents the outcomes of interest (e.g., using numbers, texts, visuals) that guide future actions and can be easily compared for informing assessments of adequacy. In contrast, stories represent memories that convey processes, progress, emotions, and values related to the actions. More importantly, while data sharing is valuable for social modeling, people also benefit from stories that elucidate the steps to be healthy and the good feelings of living a healthy life.
Conclusion
In conclusion, social personal informatics tools should incorporate both data and stories into their design because they are both important. People should be able to share stories + data in personal informatics tools so that their peers can learn and get inspired from their social environment.
Indeed, our peers can share misleading stories. For example, someone may share stories on how to get 20,000 steps — which is an unreasonably high goal. Thus, content moderation is still needed. This is because, after all, such tools are socio-technical systems. But let’s view this kind of tool as an opportunity to complement and equalize expert feedback with more relatable peer suggestions. That is, not as a tool to replace experts, but as a tool for people similar to us to exchange health strategies that work under the unique but shared constraints we lived.
Put more broadly, our social peers hold an untapped asset for motivating healthy lives. These assets are conveyed through relatable stories + data that convey strategies and joys in managing a healthy life. And, more importantly, stories can connect people and help develop relationships. This is very useful for marginalized communities to counter health disparities. Therefore, future work should focus more on how technologies can complement and amplify these social assets towards more grounded health technologies.
This article summarizes a CHI paper authored by Herman Saksono, Carmen Castaneda-Sceppa, Jessica A. Hoffman, Magy Seif El-Nasr, and Andrea G. Parker. At the end of the article, we shared the CHI 2021 video presentation.
Get the full paper at the ACM Digital Library. Storywell for Android is an open-source project, we invite you to contribute to the source code and the stories.
This material is based upon work supported by the National Science Foundation under Grant Number #1618406. This study was made possible through generous engagement from the participating families and community organizations, including Mattapan Food and Fitness Coalition, Smart from the Start, and Raising a Reader Massachusetts. We would like to thank Amanda Carreiro and Arushi Singh for contributing to the story and the illustration development as well as our colleagues at the Wellness Technology Lab for their tremendous support.
