what sparked my curiosity?
However, there was a gap in research on how various factors influence this effect. I took an exploratory approach and looked into how differently framed graphs affected users' self-efficacy – their belief in their ability to perform certain actions – and their actual behaviors.
Positive framing
80% LEAN
meat
vs
Negative framing
20% FATTY
meat
Goal framing
=
vs
Loss framing
≠
Norm framing
vs
No norm framing
the question
the experiment
58 users tracked their mood and three health goals – eating breakfast, sleeping for at least 7 hours, and brisk walking for 30 minutes every day.
Depending on the group they were assigned to, users viewed a set of graph that gave an overview of their mood and activities.
results and impact
While there were no significant effects involving other behaviors, the influence of graph designs on users differed when it came to maintaining high mood levels and sleeping sufficiently.
Post-surveys showed that the graphs helped users become more aware of their daily behavior, serving as motivation to strive to perform healthier actions.
the longitudinal test
The mobile web app, developed using d3 and React.js, served as a wellness management platform. 58 students aged 18 and above were asked to use one version of the web app continuously for 4 weeks.
Questionnaire about self-efficacy to maintain mood and perform healthy activities
Daily use of the mobile web app for 4 weeks
The pre-tracking questionnaire with additional items involving user feedback
the results
what's a possible reason behind this?
Some people could have had exerted less effort achieving the health goals because of the belief that they were already doing well. This was the case for some participants, who mentioned that the graphs made them realize they had to work harder because they weren’t achieving their goals enough.
“I felt that seeing my stats helped me realize that I wasn't achieving my goals and that I should make an effort to achieve them.”
takeaways
With how mental health and wellness apps typically incorporate different activities together, there is still huge opportunity to dig deeper into the best combination of framing and graph designs.
Participant attrition is a significant risk in a longitudinal study. Understanding how to compensate for this by including qualitative methods can help maintain the quality of research insights.