About

Martin David Cheatle, PhD, is an Associate Professor of Psychology in Psychiatry at the Hospital of the University of Pennsylvania and the Director of Behavioral Medicine at the PENN Pain Medicine Center. He also serves as the Director of Pain and Chemical Dependency Research at the Center for Studies of Addiction within the University of Pennsylvania Perelman School of Medicine. His research expertise focuses on chronic pain and substance use disorders, depression and suicidal ideation in patients with chronic pain, and chronic post-surgical pain. Dr. Cheatle's clinical expertise involves assessing and managing chronic pain from a biopsychosocial perspective. His work aims to improve understanding and treatment of pain and addiction, contributing significantly to the fields of pain medicine and behavioral health.

Research topics

• Medicine
• Psychiatry
• Physical therapy
• Psychology
• Internal medicine

Selected publications

• Correlates of mental defeat in individuals with chronic non-cancer pain on long-term opioid therapy

  Pain Medicine · 2025-05-08 · 1 citations

  articleOpen accessSenior author

  BACKGROUND: Individuals with chronic non-cancer pain (CNCP) often present with significant challenges that can impact physical, psychological, and social well-being. Mental defeat is a critical consequence of CNCP being a known predictor of suicidality. This study examines the relationships between specific psychological and coping factors and mental defeat among individuals with CNCP on long-term opioid therapy (LTOT). DESIGN: A cross-sectional study of secondary data. SETTING: Primary care, pain, and substance abuse clinics in Pennsylvania, Washington, and Utah. SUBJECTS: 744 adults with CNCP receiving LTOT (≥ 6 months). METHODS: Anxiety and depression symptoms and pain coping strategies were examined with hierarchical multiple linear regression analysis to describe their relationship to mental defeat. In an exploratory analysis, we also stratified the sample by the presence of opioid use disorder (OUD) to determine if the associations were differently represented. RESULTS: After controlling for covariates, anxiety (β = 7.07, P < .001) and depression symptoms (β = 14.17, P < .001) were statistically significant correlates of increased mental defeat. Diverting attention (β = 0.31, P < .05), coping self-statements (β = -0.30, P < .05), and catastrophizing (β = 1.47, P < .001) were significant correlates, explaining 51% of the variance in mental defeat (P < .001). Exploratory analysis revealed subgroup differences, such that while depression symptoms and catastrophizing were significant correlates of mental defeat in persons with and without OUD, anxiety and diverting attention were significant only in persons without OUD. CONCLUSIONS: These findings identify key psychological and coping correlates of mental defeat in persons with CNCP on LTOT, informing the development of interventions to mitigate it, and thereby reducing the risk of suicide in this vulnerable population.

  PublisherOA PDFDOI

• Cost Sharing for Acupuncture Therapy in Commercial Insurance Plans

  Global Advances in Integrative Medicine and Health · 2025-07-01

  articleOpen access

  Background: Cost sharing, or the extent to which patients contribute to health care spending, has been linked to various outcomes. The relationship between cost sharing and acupuncture utilization is unclear. Objectives: To measure the association between cost sharing (eg, copays, share of spending paid out of pocket, and consumer-driven health plans marked by high deductibles) and the use of in-network acupuncturists. Methods: Our team used commercial insurance claims. The study sample included 105 501 individuals who visited an in-network acupuncturist between 2012 and 2021. Results: In plans with less out-of-pocket spending overall, more members used an in-network acupuncturist. Plans with $0 copays and consumer-driven health plans had less acupuncture utilization compared to plans with higher copays and non-consumer driven health plans. Conclusion: Cost sharing had an inconsistent impact on acupuncture utilization. Our findings suggest that access to in-network acupuncturists is more important than cost sharing when it comes to increasing acupuncture utilization.

  PublisherDOI

• Machine Learning-Driven Predictive Modeling for Opioid Use Disorder in Chronic Pain Patients on Long-Term Opioid Use

  Journal of Pain · 2025-04-01

  articleSenior author
  PublisherDOI

• Mental Defeat Predicts Increased Suicide Risk in Chronic Pain: A 12‐Month Prospective Study

  European Journal of Pain · 2025-01-14 · 5 citations

  articleOpen access

  BACKGROUND: Mental defeat is considered a potential risk factor for suicidal thoughts and behaviours in chronic pain. This study evaluated the role of mental defeat in predicting future suicide risk and examined whether depression influences this relationship. METHODS: A total of 340 participants with chronic pain completed questionnaires at two time points, 12 months apart. Data collected included sociodemographic and pain characteristics, mental defeat, psychosocial risk factors including depression and health-related variables. Weighted univariate and multivariable analyses assessed the link between mental defeat and suicide risk, with a moderation analysis testing the role of depression. RESULTS: Higher levels of mental defeat and depression were linked to increased suicide risk at 12 months. Depression significantly amplified the effect of mental defeat on suicide risk, particularly in individuals with higher depression levels (B = 0.06, SE = 0.01, t = 6.21, p < 0.001) compared with moderate (B = 0.05, SE = 0.01, t = 5.20, p < 0.001) or low levels of depression (B = 0.04, SE = 0.01, t = 2.83, p = 0.004), indicating a dose-response relationship. CONCLUSIONS: Mental defeat is a significant risk factor for suicide in chronic pain, with depression intensifying this risk. Addressing both mental defeat and depression simultaneously in treatment may help reduce suicide risk in these patients. SIGNIFICANCE: This study strengthens the evidence linking mental defeat with heightened suicide risk in chronic pain. By providing prospective data, it clarifies the temporality of this relationship. Given that suicide risk doubles in chronic pain patients, whereby comorbid depression is common, these findings have crucial clinical implications. Both mental defeat and depression are modifiable. Addressing them together in treatment may help reduce suicide risk in this population.

  PublisherOA PDFDOI

• Patient Engagement in the Design and Conduct of the HOPE Trial

  Clinical Journal of the American Society of Nephrology · 2025-08-18 · 5 citations

  article

  The HOPE Consortium Trial to Reduce Pain and Opioid Use in Hemodialysis was a randomized, controlled trial funded by the National Institute of Diabetes and Digestive and Kidney Diseases. Patients on hemodialysis suffering from chronic pain were randomly assigned to receive usual care or a 12-week pain coping skills training program delivered remotely by trained coaches followed by 12 weeks of skills reinforcement via interactive voice response. Patient advisors participated in all stages of the study, including study design and development of recruitment materials. During the trial, patient advisors met monthly as an Advisory Board. In addition, patient advisors participated in all Steering Committee meetings, including in-person meetings and biweekly remote meetings. Patient advisors were represented on all study committees, with particularly extensive involvement in the Recruitment and Retention Committee. Patient advisors made important contributions to study design and conduct. Their involvement was critical to the study's successful enrollment and retention of study participants. Patient advisors characterized their involvement positively. They attributed their satisfaction with the experience to their full integration into in all aspects of the study and their treatment as equal partners. Several patient advisors have subsequently taken on other research, patient advocacy, or leadership roles, facilitated in part through their participation in the HOPE Trial. This study details the ways patient advisors were enlisted and decided to participate; outlines their many contributions; describes their experience; and provides guidance on how researchers can successfully incorporate patient advisors into future studies.

  PublisherDOI

• Prediction of opioid use disorder among patients with chronic non-cancer pain receiving long-term opioid therapy

  Pain Medicine · 2025-12-19

  articleOpen accessSenior author

  OBJECTIVE: Assessing opioid use disorder risk in patients prescribed long-term opioid therapy for management of chronic non-cancer pain is critical for prevention and early intervention. DESIGN: Case-control study. SETTING: Pain management and primary care clinics, and substance use treatment facilities. SUBJECTS: Participants are 1300 patients with chronic non-cancer pain (59.68% women; mean age = 49.03 years), 409 of whom developed opioid use disorder. METHODS: We compared the performance of 3 machine learning models that used the Opioid Risk Tool for Opioid Use Disorder alone with those that incorporated an expanded set of clinical predictors. RESULTS: The Opioid Risk Tool for Opioid Use Disorder showed strong performance (precision = 0.91; specificity = 0.96). Models that incorporated additional predictors showed improved performance on precision-recall area under the curve and F1 scores, particularly the random forest and eXtreme Gradient Boosting models. Aside from the Opioid Risk Tool for Opioid Use Disorder, the most important features in the expanded models were nicotine dependence, marital status, opioid misuse behaviors, and pain interference and catastrophizing. CONCLUSIONS: A stepwise approach that employs the Opioid Risk Tool for Opioid Use Disorder as a preliminary screener followed by a more in-depth assessment of clinical predictors among high-risk individuals may offer a feasible strategy to optimize efficiency and precision in risk stratification. Future work should refine and validate this framework in diverse population and care settings, as well as examine its integration into clinical workflow to enhance the identification of chronic non-cancer pain patients at risk for opioid use disorder.

  PublisherOA PDFDOI

• The Effect of Unmatched Cannula and Probes on Radiofrequency Ablation Lesion Size in Chicken Breast

  Interventional Pain Medicine · 2025-01-01

  articleOpen access
  PublisherDOI

• Trends in Pain Care for Patients with Chronic Low Back Pain Between 2012 and 2021

  Journal of General Internal Medicine · 2025-01-06

  letterSenior author
  PublisherDOI

• Patient-generated Values and Goals During a Remotely-delivered Pain Coping Skills Training for People with Chronic Pain Receiving Maintenance Hemodialysis

  Journal of Pain · 2025-04-01

  article
  PublisherDOI

• Pain and Suicide

  2024-05-30 · 1 citations

  book-chapter1st authorCorresponding

  Abstract Suicide has become a global epidemic. Suicide is the 12th leading cause of death in the United States. Certain populations are at high risk for suicide, including individuals who suffer from chronic pain. Many patients with chronic pain experience isolation, personal and vocational losses, and at times do not feel validated by family or their health care providers. Clinicians caring for patients with chronic pain should be cognizant of the risk factors for suicide. This chapter summarizes the current literature on pain and suicide, examines known risk factors and mediators, and discusses mitigation strategies to reduce the risk of suicidal ideation and suicidal behavior in patients with chronic pain.

  PublisherDOI

Recent grants

• Clinical and Genetic Characteristics of Opioid Addiction in Chronic Pain

  NIH · $2.3M · 2012–2019

• NIH Grant P60DA005186

  NIH · $60.9M · 2013

Frequent coauthors

• Amy C. Justice

  69 shared

• Stephen G. Waxman

  Yale University

  69 shared

• Mirko Pavicic

  Oak Ridge National Laboratory

  68 shared

• Emily E. Hartwell

  University of Pennsylvania

  67 shared

• Daniel Jacobson

  Oak Ridge National Laboratory

  67 shared

• Rachel L. Kember

  67 shared

• Kyle A. Sullivan

  Oak Ridge National Laboratory

  67 shared

• Ke Xu

  Yale University

  67 shared

Labs

• Martin David Cheatle LabPI

Education

• PhD, Psychology

  Princeton University