Bio


Tainayah Thomas, PhD, MPH is an Assistant Professor in the Department of Epidemiology and Population Health. Her research focuses on primary care improvement and diabetes prevention and management among racially and ethnically diverse populations. Dr. Thomas's research seeks to leverage delivery science research methodology to promote the integration of evidence-based research into clinical practice. Dr. Thomas is dedicated to transforming research into action by engaging community, health system, and policy stakeholders in adapting, implementing, and sustaining interventions that address health disparities and promote health equity.

Academic Appointments


Professional Education


  • PhD, University of North Carolina at Chapel Hill, Health Behavior (2019)
  • MPH, University of California, Los Angeles, Community Health Sciences (2010)
  • BA, University of Miami, Sociology and International Studies (2008)

2023-24 Courses


Stanford Advisees


All Publications


  • Principles for Stakeholder Engagement in Observational Health Research. JAMA health forum Thomas, T. W., Hooker, S. A., Schmittdiel, J. A. 2024; 5 (3): e240114

    View details for DOI 10.1001/jamahealthforum.2024.0114

    View details for PubMedID 38488777

  • Identifying Predictors of Homelessness Among Adults in a Large Integrated Health System in Northern California. The Permanente journal Rodriguez, L. A., Thomas, T. W., Finertie, H., Wiley, D., Dyer, W. T., Sanchez, P. E., Yassin, M., Banerjee, S., Adams, A., Schmittdiel, J. A. 2023: 1-16

    Abstract

    Introduction Homelessness contributes to worsening health and increased health care costs. There is little published research that leverages rich electronic health record (EHR) data to predict future homelessness risk and inform interventions to address it. The authors' objective was to develop a model for predicting future homelessness using individual EHR and geographic data covariates. Methods This retrospective cohort study included 2,543,504 adult members (≥ 18 years old) from Kaiser Permanente Northern California and evaluated which covariates predicted a composite outcome of homelessness status (hospital discharge documentation of a homeless patient, medical diagnosis of homelessness, approved medical financial assistance application for homelessness, and/or "homeless/shelter" in address name). The predictors were measured in 2018-2019 and included prior diagnoses and demographic and geographic data. The outcome was measured in 2020. The cohort was split (70:30) into a derivation and validation set, and logistic regression was used to model the outcome. Results Homelessness prevalence was 0.35% in the overall sample. The final logistic regression model included 26 prior diagnoses, demographic, and geographic-level predictors. The regression model using the validation set had moderate sensitivity (80.4%) and specificity (83.2%) for predicting future cases of homelessness and achieved excellent classification properties (area under the curve of 0.891 [95% confidence interval = 0.884-0.897]). Discussion This prediction model can be used as an initial triage step to enhance screening and referral tools for identifying and addressing homelessness, which can improve health and reduce health care costs. Conclusions EHR data can be used to predict chance of homelessness at a population health level.

    View details for DOI 10.7812/TPP/22.096

    View details for PubMedID 36911893

  • Effects of COVID-19 Shelter-in-Place Confinement on Diabetes Prevention Health Behaviors among US Adults with Prediabetes: A Cross-Sectional Survey. Preventive medicine reports Thomas, T., Lindsey, R., Yassin, M., Rodriguez, L. A., Heisler, M., Schmittdiel, J. 2023; 32: 102139

    Abstract

    The coronavirus disease 2019 (COVID-19) pandemic has resulted in significant lifestyle changes due to shelter-in-place confinement orders. The study's purpose was to assess if the COVID-19 pandemic affected self-reported diabetes prevention behaviors among American adults with prediabetes. As part of a randomized clinical trial among adults with prediabetes and overweight/obesity, questions were added to existing study surveys to assess the effect of the COVID-19 pandemic on diabetes prevention behaviors and stress. Survey responses were summarized using frequencies. 259 study participants completed seven COVID-19 survey questions from June 2020-June 2021. Participants were 62.9% female, 42.5% White, 31.3% Black, 11.6% Asian, 8.1% Hispanic, and 6.6% Other. Over 75% of participants reported that the COVID-19 pandemic affected physical activity levels, with 82.1% of those affected reporting decreased physical activity; 70.3% reported that the pandemic affected their eating habits, with 61.7% of those affected reporting their eating habits became less healthy; 73.7% reported that the pandemic affected their level of stress, with 97.4% of those affected reporting that their level of stress had increased; 60% reported that the pandemic affected their motivation to adopt/maintain healthy habits, with 72.9% of those affected reporting their motivation decreased. A high percentage of study participants with prediabetes reported decreases in health promotion behaviors and increases in stress due to the COVID-19 pandemic. Consequently, the pandemic could lead to increased diabetes incidence. Strategies to improve diabetes prevention behaviors and address mental health concerns among those at-risk for diabetes are critical during and after the COVID-19 pandemic.

    View details for DOI 10.1016/j.pmedr.2023.102139

    View details for PubMedID 36819668

    View details for PubMedCentralID PMC9922670

  • Address Changes Are Associated With Unmet Glycemic Targets: Opportunities to Improve Processes and Outcomes of Care Among People With Type 2 Diabetes. The Permanente journal Thomas, T., Dyer, W., Adams, A., Grant, R., Schmittdiel, J. 2022; 26 (2): 1-10

    Abstract

    Introduction The objective of this study was to identify and operationalize measures of potential housing insecurity within existing electronic health record data and to quantify the association between address changes and diabetes management goals among patients with type 2 diabetes. Methods We conducted a retrospective cohort study to measure potential housing insecurity in electronic health record data by quantifying the number of address changes in 2018. We considered at least one address change as a potential marker for housing insecurity. We used multivariable modified Poisson regressions to analyze the association between address change and clinical, utilization and preventive care outcomes while adjusting for patient and health system factors. Results We identified 274,123 adults with type 2 diabetes who were members of Kaiser Permanente Northern California in 2018 and 6% (N = 17,317) had at least one address change during 2018. In multivariate analyses, we found that one or more address changes was associated with greater chance of hemoglobin A1C < 9 (ARR: 1.12, 95% CI: 1.09, 1.15), lower chance of hemoglobin A1C < 8 (ARR: 0.95, 95% CI; 0.94, 0.96), lower chance of controlled blood pressure (ARR: 0.99, 95% CI: 0.98-0.99), greater chance of emergency department visits (ARR: 1.25, 95% CI: 1.23, 1.27), and lower chance of having a flu shot (ARR: 0.94, 95% CI: 0.93, 0.95) when compared to no address change. Discussion Changes in address are associated with worse diabetes management outcomes. Conclusion Identifying patients with potential housing insecurity and providing resources aimed at continuity of care and stable health care access could improve diabetes management for vulnerable populations.

    View details for DOI 10.7812/TPP/21.144

    View details for PubMedID 35933662

  • A Web-Based mHealth Intervention With Telephone Support to Increase Physical Activity Among Pregnant Patients With Overweight or Obesity: Feasibility Randomized Controlled Trial. JMIR formative research Thomas, T., Xu, F., Sridhar, S., Sedgwick, T., Nkemere, L., Badon, S. E., Quesenberry, C., Ferrara, A., Mandel, S., Brown, S. D., Hedderson, M. 2022; 6 (6): e33929

    Abstract

    BACKGROUND: Pregnant patients with overweight or obesity are at high risk for perinatal complications. Excess gestational weight gain (GWG) further exacerbates this risk. Mobile health (mHealth) lifestyle interventions that leverage technology to facilitate self-monitoring and provide just-in-time feedback may motivate behavior change to reduce excess GWG, reduce intervention costs, and increase scalability by improving access.OBJECTIVE: This study aimed to test the acceptability and feasibility of a pilot mHealth lifestyle intervention for pregnant patients with overweight or obesity to promote moderate intensity physical activity (PA), encourage guideline-concordant GWG, and inform the design of a larger pragmatic cluster randomized controlled trial.METHODS: We conducted a mixed methods acceptability and feasibility randomized controlled trial among pregnant patients with a prepregnancy BMI of 25 to 40 kg/m2. Patients with singletons at 8 to 15 weeks of gestation who were aged ≥21 years and had Wi-Fi access were recruited via email from 2 clinics within Kaiser Permanente Northern California and randomized to receive usual prenatal care or an mHealth lifestyle intervention. Participants in the intervention arm received wireless scales, access to an intervention website, activity trackers to receive automated feedback on weight gain and activity goals, and monthly calls from a lifestyle coach. Surveys and focus groups with intervention participants assessed intervention satisfaction and ways to improve the intervention. PA outcomes were self-assessed using the Pregnancy Physical Activity Questionnaire, and GWG was assessed using electronic health record data for both arms.RESULTS: Overall, 33 patients were randomly assigned to the intervention arm, and 35 patients were randomly assigned to the usual care arm. All participants in the intervention arm weighed themselves at least once a week, compared with 20% (7/35) of the participants in the usual care arm. Participants in the intervention arm wore the activity tracker 6.4 days per week and weighed themselves 5.3 times per week, and 88% (29/33) of them rated the program "good to excellent." Focus groups found that participants desired more nutrition-related support to help them manage GWG and would have preferred an app instead of a website. Participants in the intervention arm had a 23.46 metabolic equivalent of task hours greater change in total PA per week and a 247.2-minute greater change in moderate intensity PA per week in unadjusted models, but these effects were attenuated in adjusted models (change in total PA: 15.55 metabolic equivalent of task hours per week; change in moderate intensity PA: 199.6 minutes per week). We found no difference in total GWG (mean difference 1.14 kg) compared with usual care.CONCLUSIONS: The pilot mHealth lifestyle intervention was feasible, highly acceptable, and promoted self-monitoring. Refined interventions are needed to effectively affect PA and GWG among pregnant patients with overweight or obesity.TRIAL REGISTRATION: ClinicalTrials.gov NCT03936283; https://clinicaltrials.gov/ct2/show/NCT03936283.

    View details for DOI 10.2196/33929

    View details for PubMedID 35731565

  • ADDRESSING SOCIAL DETERMINANTS OF HEALTH IN BEHAVIORAL INTERVENTIONS TO IMPROVE HEALTH EQUITY Rosas, L., Espinosa, P., Thomas, T. W., Yaroch, A. OXFORD UNIV PRESS INC. 2022: S77
  • Is Shelter-in-Place Policy Related to Mail Order Pharmacy Use and Racial/Ethnic Disparities for Patients With Diabetes? DIABETES CARE Thomas, T. W., Dyer, W. T., Yassin, M., Neugebauer, R., Karter, A. J., Schmittdiel, J. A. 2021; 44 (6): E113-E114

    View details for DOI 10.2337/dc20-2686

    View details for Web of Science ID 000669490000001

    View details for PubMedID 33849937

    View details for PubMedCentralID PMC8247521