Design for Digital Health Reading Course
Please join us for the Design for Digital Health Reading Course, starting Wednesday, January 11, 2023 at noon CST on Zoom. The course will run for 8 sessions, every other week.
To sign up, please fill out this form.
GENERAL INFORMATION
Description
This reading course will provide an introduction to designing digital health technologies. It is intended for clinical scientists who are developing and studying digital health technologies. The course will teach about the user-centered design process, focusing on methods and techniques that can be leveraged. We will use peer-reviewed journal articles and conference proceedings to provide instruction in these areas.
Objectives
By the end of the course, it is expected that participants will be able to leverage design theory and methods to improve engagement with and the clinical impact of digital health technologies.
Goals
The goals of this course are to provide clinical scientists with a foundational understanding of the user-centered design process and how it adds value to research on digital health technologies. By learning design methods and techniques that can be applied in their research, participants will be prepared to embark on this work in their clinical research. The course also aims to build collaborations around digital health research through a shared knowledge base and learning opportunity with other digital health researchers.
Expectations
Classes will occur every other week for 8 sessions. Sessions will be held virtually via Zoom. We expect participants to attend 75% of sessions. Prior to each session, participants will spend approximately 2 hours reading materials and formulating 1-2 discussion questions. Participants will submit questions before the session via Slack.
Participants will be asked to volunteer to co-lead one session. Session leaders will collate participants’ questions and facilitate a discussion of the research topic.
Instructors
Andrew Berry, Ph.D. and Kaylee Kruzan, Ph.D., Center for Behavioral Intervention Technologies (CBITs), Departments of Medical Social Sciences and Preventive Medicine, Northwestern University Feinberg School of Medicine.
CBITs is supported by a NIMH-funded ALACRITY grant (P50 MH119029) that focuses on designing digital mental health interventions for implementation.
Contact: andrew.berry@northwestern.edu and kaylee.kruzan@northwestern.edu
COURSE SCHEDULE (Zoom Link in Calendar Invite)
Date |
Topic |
1/11/23 |
The User-Centered Design Process |
1/25/23 |
Needs Assessment |
2/8/23 |
User Design Elicitation |
2/22/23 |
Prototypes |
3/8/23 |
Usability Testing |
3/22/23 |
Analyzing & Publishing Design Research |
4/5/23 |
Design in NIH Grants |
4/19/23 |
Other Topics in HCI & Wrap-Up |
COURSE TOPICS & READINGS
Session 1: Human-Computer Interaction and the User-Centered Design Process
Graham, A.K., Lattie, E.G., & Mohr, D.C. (2019). Experimental therapeutics for digital mental health. JAMA Psychiatry, 76(12), 1223–1224. doi: 10.1001/jamapsychiatry.2019.2075
PDF via NU File Link
Mohr, D.C., Lyon, A.R., Lattie, E.G., Reddy, M., & Schueller, S.M. (2017). Accelerating digital mental health research from early design and creation to successful implementation and sustainment. J Med Internet Res, 19(5), e153. doi: 10.2196/jmir.7725
PDF via NU File Link
Additional readings:
Lyon, A.R. & Koerner, K. (2016). User-centered design for psychosocial intervention development and implementation. Clin Psychol (New York), 23(2), 180-200. doi: 10.1111/cpsp.12154
PDF via NU File Link
Graham, A.K., Wildes, J.E., Reddy, M., Munson, S.A., Taylor, C.B., & Mohr, D.C. (2019). User‐centered design for technology‐enabled services for eating disorders. Int J Eat Disord, 52, 1095-1107. doi: 10.1002/eat.23130
PDF via NU File Link
Session 2: Needs Assessment
Kinzie, M.B., Cohn, W.F., Julian M.F., & Knaus, W.A. (2002). A user-centered model for web site design: Needs assessment, user interface design, and rapid prototyping. J Am Med Inform Assoc, 9(4), 320-330. doi: 10.1197/jamia.M0822
PDF via NU File Link
McCurdie T., Taneva, S., Casselman, M., Yeung, M., McDaniel, C., Ho, W., & Cafazzo, J. (2012). mHealth consumer apps: The case for user-centered design. Biomed Instrum Technol, 46(s2), 49-56. doi: 10.2345/0899-8205-46.s2.49
PDF via NU File Link
Session 3: User Design Elicitation
Ali, A.X. (2020). Understanding elicitation design studies: Why, when, and how. https://uxdesign.cc/have-you-heard-of-end-user-elicitation-design-studies-78ecfe68d6
PDF via NU File Link
Ali, A.X., Morris, M.R., & Wobbrock, J.O. (2019). Crowdlicit: A system for conducting distributed end-user elicitation and identification studies. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-12. doi: 10.1145/3290605.3300485
PDF via NU File Link
Harrington, C., Erete, S., & Piper, A.M. (2019). Deconstructing community-based collaborative design: Towards more equitable participatory design engagements. In Proceedings of the ACM on Human-Computer Interaction, 1-25. doi: 10.1145/3359318
PDF via NU File Link
Session 4: Creating and Soliciting User feedback on Prototypes
Houde, S. & Hill, C. (1997). What Do Prototypes Prototype? In M. Helander, T. Landauer & P. Prabhu (Eds), Handbook of Human-Computer Interaction (2nd ed., pp. 367-381). Amsterdam: Elsevier Science B.V. doi: 10.1016/B978-044481862-1.50082-0
PDF via NU File Link
Lenarduzzi, V. & Taibi, D. (2016). MVP explained: A systematic mapping study on the definitions of minimal viable product. 42th Euromicro Conference on Software Engineering and Advanced Applications, 112-119. doi: 10.1109/SEAA.2016.56
PDF via NU File Link
Session 5: Usability Testing
Zhang, D. & Adipat, B. (2005). Challenges, methodologies, and issues in the usability testing of mobile applications. International Journal of Human–Computer Interaction, 18(3), 293-308. doi: 10.1207/s15327590ijhc1803_3
PDF via NU File Link
Faulkner, L. (2003). Beyond the five-user assumption: Benefits of increased sample sizes in usability testing. Behavior Research Methods, Instruments, & Computers, 35, 379-383. doi: 10.3758/BF03195514
PDF via NU File Link
Session 6: Analyzing and Publishing Design Research
O'Leary, K., Schueller, S.M., Wobbrock, J.O., & Pratt, W. (2018). “Suddenly, we got to become therapists for each other”: Designing peer support chats for mental health. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1-14. doi: 10.1145/3173574.3173905
PDF via NU File Link
Morris, R.R., Kouddous, K., Kshirsagar, R., & Schueller, S.M. (2018). Towards an artificially empathic conversational agent for mental health applications: System design and user perceptions. J Med Internet Res, 20(6), e10148. doi: 10.2196/10148
PDF via NU File Link
Additional readings:
O'Brien, B.C., Harris, I.B., Beckman, T.J., Reed, D.A., & Cook, D.A. (2014). Standards for reporting qualitative research: A synthesis of recommendations. Acad Med, 89(9), 1245-51. doi: 10.1097/ACM.0000000000000388
PDF via NU File Link
Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care, 19(6), 349-357. doi: 10.1093/intqhc/mzm042
PDF via NU File Link
Lattie, E.G., Bass, M., Garcia, S.F., Phillips, S.M., Moreno, P.I., Flores, A.M., Smith, J.D., Scholtens, D., Barnard, C., Penedo, F.J., Cella, D., & Yanez, B. (2020). Optimizing health information technologies for symptom management in cancer patients and survivors: Usability evaluation. JMIR Form Res, 4(9), e18412. doi: 10.2196/18412
PDF via NU File Link
Session 7: Design in NIH Grants
Caine, K. (2016). Local standards for sample size at CHI. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 981-992. doi: 10.1145/2858036.2858498
PDF via NU File Link
Bastien, J.M. (2010). Usability testing: A review of some methodological and technical aspects of the method. Int J Med Inform, 79(4), e18-e23. doi: 10.1016/j.ijmedinf.2008.12.004
PDF via NU File Link
Additional readings:
Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82. doi: 10.1177/1525822X05279903
PDF via NU File Link
Fusch, P.I. & Ness, L.R. (2015). Are we there yet? Data saturation in qualitative research. Qualitative Report, 20(9), 1408-1416. Retrieved from https://nsuworks.nova.edu/tqr/vol20/iss9/3
PDF via NU File Link
Stavros, C. & Westberg, K. (2009). Using triangulation and multiple case studies to advance relationship marketing theory. Qualitative Market Research, 12(3), 307-320. doi: 10.1108/13522750910963827
PDF via NU File Link
Session 8: Other Topics in HCI & Wrap-Up
Topics and readings to be decided by participants
Additional Readings
Ogbonnaya-Ogburu, I.F., Smith, A.D.R., To, A., & Toyama, K. (2020). Critical race theory for HCI. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-16. doi: 10.1145/3313831.3376392
PDF via NU File Link
Additional Design Resources
https://www.interaction-design.org/literature