Adrian Aguilera

Bio/CV: 

Dr. Adrian Aguilera is an Associate Professor in the School of Social Welfare at UC Berkeley and the Department of Psychiatry and Behavioral Sciences at UC San Francisco (UCSF). Dr. Aguilera directs the Digital Health Equity and Access Lab (dHEAL) and the Latinx Center of Excellence in Behavioral Health. Dr. Aguilera's research is focused on developing and testing technology-based interventions to address health disparities in low-income and vulnerable populations, with an emphasis on Latinx populations. Dr. Aguilera's current work has focused on utilizing mobile phone technology to improve mental health interventions in primary care settings. He has developed and deployed HealthySMS, which is a platform for delivering text messaging health interventions and visualizing data received from patients. He has applied this approach in the MoodText project, using text messages as an adjunct to group cognitive behavioral treatment (CBT) for depression resulting in increased engagement in treatment. He is also co-PI of the DIAMANTE project, which adds machine learning to improve personalization of mobile phone based health interventions for individuals with diabetes and depression symptoms.

Dr. Aguilera's work has been funded by the National Institutes of Health, the Robert Wood Johnson Foundation, the Agency for Healthcare Research and Quality, and the Health Resources and Services Administration among others.

Dr. Aguilera earned his BA in Psychology and Comparative Studies in Race and Ethnicity from Stanford and his PhD in Clinical Psychology at UCLA. He also completed a psychology internship at the San Francisco VA and a postdoc in Clinical Services Research at UCSF. He is a licensed, practicing clinical psychologist at San Francisco General Hospital.

Google Scholar profile

Current Projects

MoodText: Automated Text Messaging to Improve Depression Treatment for Low-Income Populations

Adrian Aguilera, Principal Investigator

As an effort to develop innovative ways to engage patients with their health care providers, the study evaluates the development of an automated text-messaging adjunct to improve depression treatment among low-income, ethnic minority (including Spanish speakers) populations. Utilizing mobile phone based text messaging (or short messaging service: SMS) as a vehicle, the study expands upon previous work in various health applications of this technology across socioeconomic status.

Research questions address whether adding an automated SMS adjunct to group cognitive behavioral therapy (CBT) for depression can increase adherence (homework adherence, attendance, medication adherence) in order to improve the quality of care in public sector settings.

DIAMANTE

The DIAMANTE project investigates the effect of mobile text messages on engagement in physical activity in participants with diabetes and depression. The project involves participant interviews and user center design methodology in order to inform the development of a combined diabetes and depression text messaging intervention that will be embedded into existing primary care. By designing and testing an adaptive mobile health intervention within a safety net setting, we will increase the likelihood that the vulnerable populations most impacted by diabetes and depression will actually receive the support they need to make significant lifestyle changes, thereby improving their overall health. By targeting both diabetes and depression, our research will lead to services that are responsive to the realities of these comorbid disorders and will likely have greater impact than interventions that focus only on one disease or the other.

StayWell at Home/Bienestar en Casa

The StayWell project is a supportive text-message intervention in English and Spanish to help people cope with the stress and anxiety of COVID-19 social distancing. The purpose of this study is to examine if automated text-messages will improve depression and anxiety symptoms and enhance positive mood.

Expanded Publications

 Aguilera, A., Figueroa, C. A., Hernandez-Ramos, R., Sarkar, U., Cemballi, A., Gomez-Pathak, L., ... & Lyles, C. (2020). mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study. BMJ open, 10(8), e034723.

Figueroa C.A., Aguilera, A. (2020). The need for a mental health technology revolution in the COVID-19 pandemic. Frontiers in Psychiatry.

Aguilera, A., Bruehlman-Senecal, E., DeMasi, O., Avila-Garcia, P., (2017) Automated text messaging as an adjunct to CBT for depression: A clinical trial. Journal of Medical Internet Research.

Aguilera, A., & Lyles, C.R. (2017) The Case for Jointly Targeting Diabetes and Depression Among Vulnerable Patients Using Digital Technology. JMIR Diabetes

Bruehlman-Senecal, E., Aguilera, A., Schueller, S. M. (2017) Phone-based mood ratings prospectively predict psychotherapy attendance in a public hospital clinic. Behavior Therapy.

Suffoletto, B., & Aguilera, A. (2016). Expanding Adolescent Depression Prevention Through Simple Communication Technologies. Journal of Adolescent Health, 59(4), 373-374.

Vázquez, M. Y. G., Sexto, C. F., Rocha, Á., & Aguilera, A. (2016). Mobile Phones and Psychosocial Therapies with Vulnerable People: a First State of the Art. Journal of medical systems, 40(6), 1-12.

DeMasi, O., Aguilera, A., Recht, B. (2016) Detecting Change in Depressive Symptoms from Daily Wellbeing Questions, Personality, and Activity. Wireless Health 2016, Washington, D.C.

Aguilera, A., Schueller, S. M., & Leykin, Y. (2015). Daily mood ratings via text message as a proxy for clinic based depression assessmentJournal of affective disorders, 175, 471-474.

Aguilera, A. (2015). Digital Technology And Mental Health Interventions: Opportunities And Challenges. ARBOR Ciencia, Pensamiento y Cultura, 191(771), 10-3989.

Aguilera, A., & Berridge, C. (2014). Qualitative Feedback From a Text Messaging Intervention for Depression: Benefits, Drawbacks, and Cultural DifferencesJMIR mHealth and uHealth, 2(4).

Leykin, Y., Aguilera, A., Pérez-Stable, E. J., & Muñoz, R. F. (2013). Prompting Depression Treatment Seeking among Smokers: A Comparison of Participants from Six Countries in an Internet Stop Smoking RCT. Journal of Technology in Human Services, 31(3), 238-247.

Aguilera, A., & Muench, F. (2012). There’s an app for that: Information technology applications for cognitive behavioral practitionersThe Behavior Therapist. 35(4), 65-73.

Morris, M. E., & Aguilera, A. (2012). Mobile, Social, and Wearable Computing and the Evolution of Psychological PracticeProfessional Psychology: Research and Practice. 43(6), 622

Aguilera, A., Leykin, Y., Adler, N., Muñoz, R.F. (2012). Assessing the Impact of Relative Social Position and Absolute Community Resources on Depression and Obesity Among SmokersAmerican Journal of Community Psychology. 50(1-2), 211-6

Aguilera, A. & Muñoz, R.F.  (2011) Text messaging as an adjunct to cognitive behavioral therapy: A feasibility/usability pilot studyProfessional Psychology: Research and Practice. 42(6), 472-478

Aguilera, A., Lopez, S.R., Breitborde, N.J.K, Kopelowicz, A., Zarate, R. (2010). Expressed emotion, sociocultural context and the course of schizophreniaJournal of Abnormal Psychology119(4), 875-85.

Aguilera, A., Garza, M.J., Munoz, R.F. (2010). Group Cognitive-Behavioral Therapy for Depression in Spanish: Culture Sensitive Manualized Treatment in PracticeJournal of Clinical Psychology, 66(8), 857.

Research interests: 
  • Mobile Technology (mHealth) and Mental Health
  • Digital health
  • Machine Learning and Health
  • Latino Mental Health
  • Health Disparities
  • Cognitive-Behavioral Therapy for Depression
  • Primary Care Based Mental Health

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