About

Marcia Ory, PhD, MPH, is a Regents and Distinguished Professor in the School of Public Health at Texas A&M University, with affiliations in the Center for Community Health & Aging and the Department of Environmental & Occupational Health. Her educational background includes a BA in Sociology/Psychology from the University of Texas at Austin, an MA in Sociology/Human Development from Indiana University at Bloomington, a PhD in Family Studies (Sociology)/Human Development from Purdue University, and an MPH in Chronic Disease Epidemiology and Behavioral Sciences from Johns Hopkins Bloomberg School of Public Health. Her research interests encompass aging and health promotion, Alzheimer’s disease and related disorders, chronic disease management, evidence-based prevention, health technology and patient empowerment, implementation science, injury prevention and control, and opioid use disorder prevention, treatment, and recovery. Dr. Ory has received numerous awards and honors, including election as a fellow in several professional societies, distinguished alumna and scholar recognitions, and lifetime achievement awards. She has been recognized as one of the world's top scientists in social sciences and humanities by Research.com and ranked among the top 2% scientists by Stanford University in 2021, 2022, and 2023. Her contributions focus on advancing public health through research, mentorship, and leadership in aging and chronic disease prevention.

Research topics

• Medicine
• Sociology
• Computer Science
• Environmental health
• Internal medicine
• Nursing
• Demography
• Computer Security
• Social Science
• Information Retrieval
• Psychiatry
• Psychology
• Statistics
• Gerontology
• Process management
• Engineering
• Biology
• Mathematics
• Database
• Data science
• Social psychology
• Genetics
• Bioinformatics
• Engineering ethics

Selected publications

• Chronic Pain and Pain Management Experiences among Younger and Older Adults

  New Prairie Press (Kansas State University) · 2026-04-17

  articleOpen accessSenior author

  Chronic pain is pervasive among Americans. This study aims to understand how pain management experiences differ between younger and older adults. Online cross-sectional surveys (Nov 2017-Dec 2018) were collected from adults in the United States (U.S.) about their pain management experiences using Amazon Mechanical Turk. Data were collected from an online convenience sample of 202 adults (age 18 years and older) who were U.S. residents and had internet access. Multivariable logistic regression models were used to examine age differences in pain management experiences (i.e., referral to a pain specialist, receiving pain treatment information, being allowed to participate in decision-making). The multivariable logistic regression analyses excluded a participant who reported hardly ever experiencing pain over the past six months. Older adults were less likely to receive information about their pain treatment options (aOR = 0.40, 95% CI = [0.19, 0.82]). Still, they were more likely to perceive that they were sufficiently allowed to participate in their pain treatment decisions (aOR = 2.06, 95% CI = [1.07, 3.94]). No statistically significant differences were observed regarding pain specialist referrals or addiction concerns. Findings suggest differences in pain management experiences between younger and older adults. Further efforts are needed to examine the impact of differential patient involvement in pain treatment based on age. The study provides evidence of differential pain management experiences based on patients' age and offers potential explanations for these findings, along with implications for future research that can guide change in clinical practice.

  Publisher

• Guiding Approaches to Studying Alzheimer’s Disease: A Scoping Review of Community Engagement, Health Communication, and Implementation Science Research

  The Gerontologist · 2026-04-23

  article

  BACKGROUND AND OBJECTIVES: Alzheimer's disease and related dementias (ADRD) are a leading cause of death, affecting up to 57 million globally. Up to 45% of dementia cases could be prevented or delayed by addressing non-medical drivers of health (NMDoH). Community engagement, health communication, and implementation science are core areas of public health and important to consider when researching ADRD. However, these fields are often siloed, limiting efficacy of ADRD prevention and intervention. This scoping review maps how researchers have incorporated models and theoretical frameworks from these fields specific to ADRD outcomes and with attention to NMDoH. RESEARCH DESIGN AND METHODS: We searched five social science databases, and articles were included if they were empirical, written in English language, published 2010 forward, focused on ADRD or cognitive health, guided by or developed a framework, theory, or model, and addressed community engagement, health communication, or implementation science. RESULTS: We retrieved 2,428 articles which were reviewed in multiple stages by five co-authors, resulting in a final sample of 32 articles. Most articles utilized published frameworks, models, or theories, while five were guided by author-developed approaches. Nine articles integrated two core areas, and only one article integrated all three. DISCUSSION AND IMPLICATIONS: Increased integration of core areas and systematic application of theoretical frameworks are necessary to improve ADRD research with attention to NMDoH. Findings have the potential to inform training and mentorship opportunities for early-career researchers on best practices in interdisciplinary ADRD research, thereby improving community and population health outcomes.

  PublisherDOI

• A novel clinical trials search tool with iterative and geospatial capabilities

  Contemporary Clinical Trials · 2026-03-20

  articleSenior author
  PublisherDOI

• Generative AI-assisted Bayesian-frequentist Hybrid Inference in Single-cell RNA Sequencing Analysis for Genes Associated with Alzheimer’s Disease

  medRxiv · 2026-04-20

  articleOpen access

  Alzheimer's disease genomics and other high-dimensional omics studies demand powerful statistical methods, yet Bayesian inference remains underutilized despite its advantages in small-sample settings, owing to the prohibitive cost of eliciting reliable priors across thousands or millions of parameters. We propose an AI-assisted Bayesian-frequentist hybrid inference framework that couples large language model based prior elicitation with the hybrid inference theory of Yuan (2009). ChatGPT-4o is queried via a standardized prompt to assess the strength of evidence linking each gene to a disease of interest, and the response is mapped to an informative normal prior via a standardized effect-size calibration. Parameters for covariates of secondary interest are treated as frequentist parameters, preserving efficiency and avoiding sensitivity to mis-specified priors. We derive closed-form hybrid estimators under uniform and conjugate normal priors in linear models, establish their asymptotic equivalence to the frequentist and full Bayes estimators, and show in simulations that hybrid inference using unconditional variance estimation leads to high statistical power while accurately controlling the Type I error rate. Applied to single-cell RNA sequencing data from the ROSMAP cohort for Alzheimer's disease as an example, the framework identifies biologically coherent pathways (such as gamma-secretase pathways) previously undetected. The proposed framework offers a principled and computationally scalable approach to genome-wide Bayesian analysis, with potential for broad application across omics platforms and disease settings.

  PublisherOA PDFDOI

• Sapere Aude – Dare to Be Wise: Marcia G. Ory

  New Prairie Press (Kansas State University) · 2026-05-01

  articleOpen access1st authorCorresponding

  Sapere Aude – Dare to Be Wise is a unique editorial conversational interview-type feature. It is an attempt to deep dive into an Academy members’ background, formative experience, and education – specifically, to extract factors that contributed to their development and evolution as a professional, as well as their success as a prominent researcher in the health behavior arena. Every Academy member selected has a different story to tell and numerous models for success will emerge from this exploration of the membership.

  Publisher

• Comparative effectiveness of diabetes self-management education and support intervention strategies among adults with type 2 diabetes in Texas

  Frontiers in Public Health · 2025-03-18 · 4 citations

  articleOpen access1st authorCorresponding

  Background: With approximately 1-in-10 Texas estimated to be living with Type 2 Diabetes Mellitus (T2DM), and the steadily rising healthcare costs associated with non-managed T2DM, efforts are needed to help patients manage their diabetes and avoid costly health consequences. While many diabetes self-management interventions and solutions exist to improve health among people living with T2DM, less is known about the relative effectiveness of these interventions based on their delivery format and when used in combination. The purpose of this study was to identify the effectiveness of three intervention modalities to reduce hemoglobin A1c (A1c) among Texans with T2DM living in rural and urban settings. Methods: A three-arm randomized controlled trial (RCT) was conducted from November 2020 through March 2022. The three modalities included: (1) asynchronous virtual education and support program with one-on-one follow-up counseling [i.e., virtual Making Moves with Diabetes (vMMWD)]; (2) technology-based education and support (i.e., TBES); and (3) combined modality where participants sequentially received vMMWD and TBES (i.e., combined). Data were collected at baseline and again at 3- and 6-month follow-up. Using an intent-to-treat analysis, constrained longitudinal data analysis models were fitted to identify and compare changes in A1c over time. Results: Findings demonstrate the positive effects of all three intervention modalities (i.e., vMMWD, TBES, and combined) to significantly reduce A1c among participants. Longitudinal analyses identified that initial reductions in A1c at 3-month follow-up were sustained at 6-month follow-up. Findings were consistent among rural- and urban-residing participants. Conclusion: This RCT highlights the universal benefits of self-paced virtual diabetes self-management interventions to reduce A1c among Texans with unmanaged T2DM. Such low-cost interventions may be widely applicable for different settings and populations.

  PublisherOA PDFDOI

• Personalized Digital Health Solutions to Increasing Diabetes-Related Knowledge and Behavioral Outcomes: Results from an RCT  (Preprint)

  JMIR Diabetes · 2025-11-07

  articleOpen access1st authorCorresponding

  BACKGROUND: The prevalence of diabetes in the US necessitates investigations into how to better enable adults with type 2 diabetes to manage their health using easy to access and personally adaptable technologies. The ubiquity of digital content further justifies the need to consider the impact of different digital intervention modalities in diabetes self-care activities. OBJECTIVE: The purpose of this study is to compare the impact of two digital diabetes self-care education programs delivered separately, and in combination, to adults with type 2 diabetes across various settings in Texas. METHODS: We conducted a randomized control trial (RCT) in Texas with 188 adults with T2DM to assess whether two different interventions alone (vMMWD or TBES) or in combination (vMMWD followed by TBES) improved multiple outcomes associated with diabetes self-management. We employed several estimation techniques including generalized estimating equations (GEE), to account for multiple factors simultaneously. RESULTS: All three digital intervention modalities led to significant improvements (p<.05) in diabetes-related confidence, distress, and self-care behaviors, with significant effects from baseline through 6 months and supported by moderate to strong effect sizes for the total population (ranging from .446 to .827 at 3 months and .538 to .888 at 6 months). No statistically significant superiority was observed among the intervention modalities. Higher self-care behaviors were significantly associated with higher baseline confidence and lower distress. Those in the most disadvantaged positions (less education, less financial stability, and no health insurance) showed significantly larger improvement in selfcare behaviors. CONCLUSIONS: Given the benefits associated with the current study's interventions, we suggest future work to further develop digital content that can be tailored to individuals with T2DM to help them manage their chronic condition(s) in a cost-effective manner. CLINICALTRIAL: This trial was registered at ClinicalTrials.gov under ID number NCT06370494.

  PublisherDOI

• The application of the RE-AIM and PRISM framework to process evaluations of diabetes self-management programs: a systematic review and secondary analysis of literature

  Frontiers in Public Health · 2025-12-12

  articleOpen accessSenior author

  Background: Diabetes self-management programs, often known as DSMPs, are crucial interventions for enhancing clinical and behavioral outcomes in individuals with diabetes. Despite the well-established advantages of these programs, little is known about how they are carried out and maintained in real world environments. This systematic review builds upon a previously published prequel by applying the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) and PRISM (Practical, Robust Implementation and Sustainability Model) frameworks to examine the process evaluations of traditional, group-based DSMPs, with the goal of identifying implementation strengths, gaps, and contextual influences. Methods: = 78 articles) met inclusion criteria. Data were extracted and synthesized using RE-AIM and PRISM components, and study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). Results: = 78) satisfied the requirements for inclusion. Fewer research addressed Adoption (k = 5), Implementation (k = 24), and Maintenance (k = 26), whereas the majority focused on Reach (k = 66) and Effectiveness (k = 66). Only four studies found external contextual influences, compared to nineteen that found internal contextual elements. Process-level indicators-such as implementation fidelity, cost, sustainability, and provider engagement-were often underreported, despite consistent evidence of positive clinical and behavioral outcomes. Discussion: The review highlights a critical gap between outcome evaluation and implementation reporting in DSMP research. The organizational and contextual elements that affect program scalability and durability were overlooked in favor of patient-level outcomes in most of the studies. When the RE-AIM and PRISM frameworks were used systematically, it was discovered that several process components that are essential for long-term integration were underreported. Resolving these shortcomings can help direct the creation of scalable, context-aware DSMPs that are more adaptable to diverse populations and settings. Conclusion: Process evaluations should be thorough, context-sensitive, and theory-driven to improve the implementation, execution, and long-term effects of DSMPs. A more comprehensive analysis of program success is made possible by integrating the RE-AIM and PRISM frameworks, which closes the gap between research and real-world implementation. To educate healthcare policy and practice, future evaluations should use mixed method designs that evaluate implementation as well as results. Systematic review registration: This systematic review was registered in PROSPERO. The registration number is CRD42020177170.

  PublisherDOI

• Frameworks for process evaluations of diabetes self-management programs: a systematic review

  Health Promotion International · 2025-07-01

  reviewSenior author

  This systematic review investigates the utilization and reporting of frameworks to guide process evaluations (PE) of diabetes self-management programmes (DSMPs). Constituting a subset of articles from a previously published systematic review, seven studies, comprising nine articles, met the inclusion criteria. The different approaches to manage diabetes were reflected in the study's characteristics and types of interventions. The quality of reporting differed even with the inclusion of evaluation frameworks, which affected the evidence's transferability and comparability. All studies cited their frameworks; yet, only a few gave thorough explanations and used the frameworks consistently throughout their research. A critical appraisal for reporting quality revealed a need for standardized guidelines to assess the thoroughness of framework utilization. Implications for practice include adopting a checklist of indicators to enhance reporting quality and encouraging uniformity in PE methodologies.

  PublisherDOI

• Social disconnectedness and depressive symptoms across age groups: findings from a non-probability sample of employed U.S. adults

  Frontiers in Public Health · 2025-11-14

  articleOpen access

  Background Rates of social disconnectedness and depression have intensified in recent years. Yet, little is known about how they relate to one another across different age groups. This study assessed the relationship between social disconnectedness and depressive symptoms among U. S. adults of varying ages using an internet-delivered survey data collected between November 2021 and January 2022 from a non-probabilistic national sample of 2,496 employed adults aged 18–89 years. Methods Participants completed Upstream Social Interaction Risk Scale (U-SIRS-13) and the Patient Health Questionnaire short version (PHQ-2). Within each of five age groups (18–29, 30–39, 40–49, 50–59, 60+), descriptive statistics and Pearson’s r correlations were calculated for U-SIRS-13 and PHQ-2. Subsequently, logistic regression models were fitted to assess the relationship between the U-SIRS-13 and PHQ-2 (a score of 3 or greater indicated possible depression), controlling for sociodemographic covariates. Results The prevalence of possible depression among participants was 31.6%, which ranged from 46.8% (ages 18–29) to 10.5% (ages 60+). U-SIRS-13 and PHQ-2 had significant associations in all age groups (Pearson’s r range: 0.283–0.275, p &amp;lt; 0.001). Holding sociodemographic covariates constant, higher U-SIRS-13 scores were consistently associated with increased odds of possible depression across age groups (Odds Ratio range: 1.24–1.50, p &amp;lt; 0.001). While possible depression was more prevalent among younger age groups (18-29 and 30-39), the relationship between social disconnectedness and possible depression was stronger among older age groups (40–49, 50–59, and 60+). Conclusion This finding supports that regardless of age, individuals who experience higher levels of social disconnectedness are more likely to have possible depression Coordinated efforts are needed to address depressive symptomology and facilitate meaningful interactions with others in all age groups.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01HD047143

  NIH · $2.5M · 2011

• Fighting Obesity by Reinventing Public Transportation: A Natural Experiment

  NIH · $2.2M · 2018–2025

• Fighting Obesity by Reinventing Public Transportation: A Natural Experiment

  NIH · $583k · 2018–2023

Frequent coauthors

• Matthew Lee Smith

  Texas A&M University

  376 shared

• Russell E. Glasgow

  University of Colorado Anschutz Medical Campus

  178 shared

• Alex H. Krist

  169 shared

• Suzanne Heurtin‐Roberts

  168 shared

• Siobhan M. Phillips

  168 shared

• S. N. Sheinfeld-Gorin

  UCLA Health

  164 shared

• SangNam Ahn

  Texas A&M Health Science Center

  141 shared

• Samuel D. Towne

  University of Central Florida

  134 shared

Awards & honors

• Elected Member/Fellow: Academy for Behavioral Medicine Resea…
• Elected Member/Fellow: American Academy of Health Behavior
• Elected Member/Fellow: Gerontological Society of America
• Elected Member/Fellow: Society for Behavioral Medicine
• Distinguished Alumna, Distinguished Scholar, Purdue Universi…