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Design for Digital Health Reading Course


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.


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. 


Andrea Graham, PhD and Emily Lattie, PhD, Center for Behavioral Intervention Technologies (CBITs), Department of Medical Social Sciences, 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)




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



COURSE TOPICS & READINGS (Box Folder of all 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

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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

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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

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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

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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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