Jennifer Schultz De La Rosa
- Assistant Professor, Family and Community Medicine - (Research Scholar Track)
- (520) 626-7864
- AHSC, Rm. 4320
- TUCSON, AZ 85724-5052
- jschult1@arizona.edu
Biography
Jennifer Schultz De La Rosa, PhD, is a medical sociologist and data scientist specializing in treatment quality and utilization, workforce development, stigma, and health equity in the interrelated areas of chronic pain, substance use, and mental health. Dr. De La Rosa is the Director of Strategy at the University of Arizona Health Sciences’ Comprehensive Center for Pain and Addiction and Assistant Research Professor at the Department of Family and Community Medicine, College of Medicine-Tucson. Dr. De La Rosa is serving a 3-year term on the Advocacy Committee of the United States Association for the Study of Pain and was selected to its 2024-2025 Leadership Academy as well. Her team’s most recent publication “The Unmet Mental Health Needs of U.S. Adults with Chronic Pain” was awarded Editor’s Choice by PAIN, the journal of the International Association for the Study of Pain. Dr. De La Rosa is principal investigator of PeerWORKS, a HRSA-funded program to train, certify, and place opioid-impacted individuals in community provider roles--providing behavioral health peer support to people with similar lived experiences. Dr. De La Rosa also directs evaluation of AzCANN, an Arizona Department of Health Services contracted program providing evidence-based education and training to health professionals concerning the adult use of cannabis.
Awards
- 2024-2025 Fellow, USASP Leadership Academy
- United States Association for the Study of Pain, Spring 2024
- University of Arizona's Team Award for Excellence
- University of Arizona, Spring 2024
- FY 2023 Fellow, University of Arizona Academic Leadership Institute
- University of Arizona Office of Learning and Organizational Development, Fall 2022
- Global Peer Support Celebration Day Certficate of Recognition
- Department of Family and Community Medicine, College of Medicine -- Tucson, Fall 2019
- Lead Tucson, Class of 2019
- Lead Tucson, formerly Greater Tucson Leadership, Fall 2019
Interests
Research
Chronic Pain, Anxiety/Depression, and Mental Health, Substance Use Disorder, Network Analysis, Health Service Quality, Patient Centered Care, Emotional and Attentional Regulation, Intertemporal Discounting and Delay Aversion, Impulsivity, Daily habits and rythms, Motivation, Goal Directed Persistence, Episodic Future Thinking, Integration of Self Across Past/Present Future, Reward Pathway Adaptation and Plasticity, Disentangling States and Traits, Situational and Contextual approaches, Lived Experience, Self-Determination and Empowerment, Learned Hopefulness.
Teaching
Co-Director of Pain and Society, FCM 304Bachelor's of Science in Medicine
Courses
2024-25 Courses
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Honors Directed Research
PSYS 392H (Fall 2024)
2023-24 Courses
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Independent Study
PSIO 399 (Spring 2024)
2021-22 Courses
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Indigenous Health
AIS 437 (Spring 2022) -
Indigenous Health
CHS 437 (Spring 2022) -
Indigenous Health
SOC 437 (Spring 2022)
2020-21 Courses
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Indigenous Health
AIS 437 (Spring 2021) -
Indigenous Health
CHS 437 (Spring 2021) -
Indigenous Health
SOC 437 (Spring 2021)
2019-20 Courses
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Indigenous Health
AIS 437 (Spring 2020) -
Indigenous Health
CHS 437 (Spring 2020) -
Indigenous Health
SOC 437 (Spring 2020)
2018-19 Courses
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Indigenous Health
AIS 437 (Fall 2018) -
Indigenous Health
CHS 437 (Fall 2018) -
Indigenous Health
SOC 437 (Fall 2018)
2017-18 Courses
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Health Disparities in Society
CHS 401 (Spring 2018) -
Health Disparities in Society
SOC 401 (Spring 2018)
Scholarly Contributions
Journals/Publications
- Schultz, J., & Schultz, J. (2017). Data as a Strategic Resource: Self-determination, Governance, and the Data Challenge for Indigenous Nations in the United States. International Indigenous Policy Journal.More infoData about Indigenous populations in the United States are inconsistent and irrelevant. Federal and state governments and researchers direct most collection, analysis, and use of data about U.S. Indigenous populations. Indigenous Peoples’ justified mistrust further complicates the collection and use of these data. Nonetheless, tribal leaders and communities depend on these data to inform decision making. Reliance on data that do not reflect tribal needs, priorities, and self-conceptions threatens tribal self-determination. Tribal data sovereignty through governance of data on Indigenous populations is long overdue. This article provides two case studies of the Ysleta del Sur Pueblo and Cheyenne River Sioux Tribe and their demographic and socioeconomic data initiatives to create locally and culturally relevant data for decision making.
