Published on in Vol 20, No 4 (2018): April

Preprints (earlier versions) of this paper are available at, first published .
Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial

Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial

Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial


  1. Bollyky J, Melton S, Xu T, Painter S, Knox B. The Effect of a Cellular-Enabled Glucose Meter on Glucose Control for Patients With Diabetes: Prospective Pre-Post Study. JMIR Diabetes 2019;4(4):e14799 View
  2. Rosenblat J, Kurdyak P, Cosci F, Berk M, Maes M, Brunoni A, Li M, Rodin G, McIntyre R, Carvalho A. Depression in the medically ill. Australian & New Zealand Journal of Psychiatry 2020;54(4):346 View
  3. Suh J, Williams S, Fann J, Fogarty J, Bauer A, Hsieh G. Parallel Journeys of Patients with Cancer and Depression: Challenges and Opportunities for Technology-Enabled Collaborative Care. Proceedings of the ACM on Human-Computer Interaction 2020;4(CSCW1):1 View
  4. Husdal R, Thors Adolfsson E, Leksell J, Eliasson B, Jansson S, Jerdén L, Stålhammar J, Steen L, Wallman T, Svensson A, Rosenblad A. Organisation of primary diabetes care in people with type 2 diabetes in relation to all-cause mortality: A nationwide register-based cohort study. Diabetes Research and Clinical Practice 2020;167:108352 View
  5. Jin H, Wu S. Text Messaging as a Screening Tool for Depression and Related Conditions in Underserved, Predominantly Minority Safety Net Primary Care Patients: Validity Study. Journal of Medical Internet Research 2020;22(3):e17282 View
  6. Jin H, Wu S. Screening Depression and Related Conditions via Text Messaging Versus Interview Assessment: Protocol for a Randomized Study. JMIR Research Protocols 2019;8(3):e12392 View
  7. Jin H, Wu S. Use of Patient-Reported Data to Match Depression Screening Intervals With Depression Risk Profiles in Primary Care Patients With Diabetes: Development and Validation of Prediction Models for Major Depression. JMIR Formative Research 2019;3(4):e13610 View
  8. Palakshappa D, Benefield A, Furgurson K, Harley M, Bundy R, Moses A, Taxter A, Bensinger A, Cao X, Denizard-Thompson N, Rosenthal G, Miller D. Feasibility of Mobile Technology to Identify and Address Patients' Unmet Social Needs in a Primary Care Clinic. Population Health Management 2021;24(3):385 View
  9. Evanson O, Wu S. Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes. Journal of Patient Experience 2020;7(5):734 View
  10. Hu J, Wu T, Damodaran S, Tabb K, Bauer A, Huang H. The Effectiveness of Collaborative Care on Depression Outcomes for Racial/Ethnic Minority Populations in Primary Care: A Systematic Review. Psychosomatics 2020;61(6):632 View
  11. Raya-Tena A, Fernández-San-Martin M, Martin-Royo J, Casañas R, Sauch-Valmaña G, Cols-Sagarra C, Navas-Mendez E, Masa-Font R, Casajuana-Closas M, Foguet-Boreu Q, Fernández-Linares E, Mendioroz-Peña J, González-Tejón S, Martín-López L, Jiménez-Herrera M. Effectiveness of a Psychoeducational Group Intervention Carried Out by Nurses for Patients with Depression and Physical Comorbidity in Primary Care: Randomized Clinical Trial. International Journal of Environmental Research and Public Health 2021;18(6):2948 View
  12. McMorrow R, Hunter B, Hendrieckx C, Kwasnicka D, Speight J, Cussen L, Ho F, Emery J, Manski-Nankervis J. Effect of routinely assessing and addressing depression and diabetes distress on clinical outcomes among adults with type 2 diabetes: a systematic review. BMJ Open 2022;12(5):e054650 View
  13. Moon K, Sobolev M, Kane J. Digital and Mobile Health Technology in Collaborative Behavioral Health Care: Scoping Review. JMIR Mental Health 2022;9(2):e30810 View
  14. Wang X, Liang J, Yang W, Bian Y. A Randomized, Controlled Trial Exploring Collaborative Nursing Intervention on Self-Care Ability and Blood Glucose of Patients with Type 2 Diabetes Mellitus. Disease Markers 2022;2022:1 View
  15. Suo X, Zhang Y, Liu Q, Zhao G, Zhu Y, Liu Y, Zhai J. A mental health survey among young front-line clinicians in high-risk areas during the COVID-19 sporadic epidemic in China. Frontiers in Psychiatry 2022;13 View
  16. Geerlings A, Janssen Daalen J, Ypinga J, Bloem B, Meinders M, Munneke M, Darweesh S, De Luca V. Case management interventions in chronic disease reduce anxiety and depressive symptoms: A systematic review and meta-analysis. PLOS ONE 2023;18(4):e0282590 View
  17. Racey M, Whitmore C, Alliston P, Cafazzo J, Crawford A, Castle D, Dragonetti R, Fitzpatrick-Lewis D, Jovkovic M, Melamed O, Naeem F, Senior P, Strudwick G, Ramdass S, Vien V, Selby P, Sherifali D. Technology-Supported Integrated Care Innovations to Support Diabetes and Mental Health Care: Scoping Review. JMIR Diabetes 2023;8:e44652 View
  18. Fernández-Rodríguez R, Zhao L, Bizzozero-Peroni B, Martínez-Vizcaíno V, Mesas A, Wittert G, Heilbronn L. Are e-Health Interventions Effective in Reducing Diabetes-Related Distress and Depression in Patients with Type 2 Diabetes? A Systematic Review with Meta-Analysis. Telemedicine and e-Health 2024;30(4):919 View

Books/Policy Documents

  1. Rosenfeld A, Benrimoh D, Armstrong C, Mirchi N, Langlois-Therrien T, Rollins C, Tanguay-Sela M, Mehltretter J, Fratila R, Israel S, Snook E, Perlman K, Kleinerman A, Saab B, Thoburn M, Gabbay C, Yaniv-Rosenfeld A. Applications of Big Data in Healthcare. View