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Edwin D Boudreaux

Biographic Data

ID240259
NAMEEdwin D Boudreaux
GIVEN NAMESEdwin D
FAMILY NAMEBoudreaux
SIGNATUREBOUDREAUX E D
AFFILIATIONSUniversity of Massachusetts Chan Medical School
ORCID0000-0002-3223-6371
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS12
AUTHOR COUNT6
EDITOR COUNT0
FIRST PUBLICATION YEAR2003
LATEST PUBLICATION YEAR2021
H-INDEX3
  • Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data

    Open Access•Edwin D Boudreaux, Elke A Rundensteiner et al.•ARTICLE•Frontiers in Psychiatry•2021

    Objective: Early identification of individuals who are at risk for suicide is crucial in supporting suicide prevention. Machine learning is emerging as a promising approach to support this objective. Machine learning is broadly defined as a set of mathematical models and computational algorithms designed to automatically learn complex patterns between predictors and outcomes from example data, without being explicitly programmed to do so. The mod…

  • Ecological momentary assessment and first smoking cessation lapse after an acute cardiac event

    Open Access•Chelsea J Webber, Erin C O’hea et al.•ARTICLE•Journal of Health Psychology•2020•References: 13

    This 28-day pilot study assessed the feasibility of cell phone ecological momentary assessment in 40 smokers who received emergency department evaluations for acute coronary syndrome. Ecological momentary assessments used familiar touch tone response technology during a cell phone call to capture ratings of illness perceptions, emotion, behavioral intentions, and smoking. Ecological momentary assessments were conducted 1-8 times/day and took 1-2 …

  • Higher Educational Attainment is Associated with Lower Risk of a Future Suicide Attempt Among Non-Hispanic Whites but not Non-Hispanic Blacks

    Open Access•Assari, Heather T Schatten et al.•ARTICLE•Journal of Racial and Ethnic…•2019•Cited by: 3•References: 86

  • Predictors of psychological distress and interest in mental health services in individuals with cancer

    Open Access•Erin L O’hea, Erin O’hea et al.•ARTICLE•Journal of Health Psychology•2016•Cited by: 3•References: 21

    Identifying risk factors for psychological distress in patients with cancer may help providers more efficiently screen, identify, and manage distress. This article presents predictors of psychological distress in a large heterogeneous sample of cancer patients. In total, 836 patients were enrolled in a large randomized control trial and completed computerized psychosocial assessments Mental Health Assessment and Dynamic Referral for Oncology. Mul…

  • Predicting Medical Regimen Adherence

    Open Access•Erin L O’hea, Erin O’hea et al.•ARTICLE•Journal of Health Psychology•2005•Cited by: 6•References: 39

    The present study examined the interactions between five dimensions of health locus of control beliefs and their relationships with medical regimen adherence in low-income individuals diagnosed with type 2 diabetes. One hundred and nine patients were administered an expanded Multidimensional Health Locus of Control (MHLC) scale. HbA1c was used as a biological indicator of medical regimen adherence. Multivariate regression analyses demonstrated th…

  • Applying Exercise Stage of Change to a Low-income Underserved Population

    Cindy L Carmack Taylor, Edwin D Boudreaux et al.•ARTICLE•American Journal of Health Behavior•2003

    Further studies modifying the decisional balance measures are necessary before definitive statements regarding the applicability of these models to exercise within this specialized population can be made

  • Predicting Medical Regimen Adherence

    Open Access•Erin L O’hea, Erin O’hea et al.•ARTICLE•Journal of Health Psychology•2005•Cited by: 6•References: 39

    The present study examined the interactions between five dimensions of health locus of control beliefs and their relationships with medical regimen adherence in low-income individuals diagnosed with type 2 diabetes. One hundred and nine patients were administered an expanded Multidimensional Health Locus of Control (MHLC) scale. HbA1c was used as a biological indicator of medical regimen adherence. Multivariate regression analyses demonstrated th…

  • Higher Educational Attainment is Associated with Lower Risk of a Future Suicide Attempt Among Non-Hispanic Whites but not Non-Hispanic Blacks

    Open Access•Assari, Heather T Schatten et al.•ARTICLE•Journal of Racial and Ethnic…•2019•Cited by: 3•References: 86

  • Predictors of psychological distress and interest in mental health services in individuals with cancer

    Open Access•Erin L O’hea, Erin O’hea et al.•ARTICLE•Journal of Health Psychology•2016•Cited by: 3•References: 21

    Identifying risk factors for psychological distress in patients with cancer may help providers more efficiently screen, identify, and manage distress. This article presents predictors of psychological distress in a large heterogeneous sample of cancer patients. In total, 836 patients were enrolled in a large randomized control trial and completed computerized psychosocial assessments Mental Health Assessment and Dynamic Referral for Oncology. Mul…

  • Applying Exercise Stage of Change to a Low-income Underserved Population

    Cindy L Carmack Taylor, Edwin D Boudreaux et al.•ARTICLE•American Journal of Health Behavior•2003

    Further studies modifying the decisional balance measures are necessary before definitive statements regarding the applicability of these models to exercise within this specialized population can be made

  • Predicting Medical Regimen Adherence

    Open Access•Erin L O’hea, Erin O’hea et al.•ARTICLE•Journal of Health Psychology•2005•Cited by: 6•References: 39

    The present study examined the interactions between five dimensions of health locus of control beliefs and their relationships with medical regimen adherence in low-income individuals diagnosed with type 2 diabetes. One hundred and nine patients were administered an expanded Multidimensional Health Locus of Control (MHLC) scale. HbA1c was used as a biological indicator of medical regimen adherence. Multivariate regression analyses demonstrated th…

  • Predictors of psychological distress and interest in mental health services in individuals with cancer

    Open Access•Erin L O’hea, Erin O’hea et al.•ARTICLE•Journal of Health Psychology•2016•Cited by: 3•References: 21

    Identifying risk factors for psychological distress in patients with cancer may help providers more efficiently screen, identify, and manage distress. This article presents predictors of psychological distress in a large heterogeneous sample of cancer patients. In total, 836 patients were enrolled in a large randomized control trial and completed computerized psychosocial assessments Mental Health Assessment and Dynamic Referral for Oncology. Mul…

  • Higher Educational Attainment is Associated with Lower Risk of a Future Suicide Attempt Among Non-Hispanic Whites but not Non-Hispanic Blacks

    Open Access•Assari, Heather T Schatten et al.•ARTICLE•Journal of Racial and Ethnic…•2019•Cited by: 3•References: 86

  • Ecological momentary assessment and first smoking cessation lapse after an acute cardiac event

    Open Access•Chelsea J Webber, Erin C O’hea et al.•ARTICLE•Journal of Health Psychology•2020•References: 13

    This 28-day pilot study assessed the feasibility of cell phone ecological momentary assessment in 40 smokers who received emergency department evaluations for acute coronary syndrome. Ecological momentary assessments used familiar touch tone response technology during a cell phone call to capture ratings of illness perceptions, emotion, behavioral intentions, and smoking. Ecological momentary assessments were conducted 1-8 times/day and took 1-2 …

  • Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data

    Open Access•Edwin D Boudreaux, Elke A Rundensteiner et al.•ARTICLE•Frontiers in Psychiatry•2021

    Objective: Early identification of individuals who are at risk for suicide is crucial in supporting suicide prevention. Machine learning is emerging as a promising approach to support this objective. Machine learning is broadly defined as a set of mathematical models and computational algorithms designed to automatically learn complex patterns between predictors and outcomes from example data, without being explicitly programmed to do so. The mod…

Medicine (5 works) · Psychology (5 works) · Clinical Psychology (3 works) · Gerontology (3 works) · Internal Medicine (3 works) · Behavioral Health and Interventions (2 works) · Environmental health (2 works) · Ethnic group (2 works) · Family medicine (2 works) · Health disparities and outcomes (2 works)

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