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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.




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.


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.


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. 


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.


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: and


COURSE SCHEDULE (Zoom Link in Calendar Invite)

A schedule of the 2023 course, with 8 sessions between January 11, 2023 to April 19, 2023.




The User-Centered Design Process


Needs Assessment


User Design Elicitation




Usability Testing


Analyzing & Publishing Design Research


Design in NIH Grants


Other Topics in HCI & Wrap-Up



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

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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

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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

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Session 3: User Design Elicitation

Ali, A.X. (2020). Understanding elicitation design studies: Why, when, and how.

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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Fusch, P.I. & Ness, L.R. (2015). Are we there yet? Data saturation in qualitative research. Qualitative Report, 20(9), 1408-1416. Retrieved from

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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

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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

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Additional Design Resources

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