Traci Lemasters

West Virginia University, Morgantown, West Virginia, United States

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Publications (11)27.98 Total impact

  • T.J. LeMasters · S.S. Madhavan · U. Sambamoorthi · K. Kelly · H. Hazard · D. Long ·

    Value in Health 05/2015; 18(3):A216-A217. DOI:10.1016/j.jval.2015.03.1257 · 3.28 Impact Factor
  • T.J. LeMasters · S.S. Madhavan · U. Sambamoorthi · K. Kelly · H. Hazard · D. Long ·

    Value in Health 05/2015; 18(3):A216. DOI:10.1016/j.jval.2015.03.1256 · 3.28 Impact Factor
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    ABSTRACT: Risk perceptions are motivating factors for engaging in preventive health behaviors. Yet, almost one third of women attending a mobile mammography program targeted to rural and medically underserved Appalachian women respond "don't know" to their perceived 5-year risk of breast cancer. This study used cross-sectional data from women aged >40 years participating in Bonnie's Bus Mammography Screening and Preventive Care Survey from 2009 to 2011 to identify factors associated with "don't know" responses and accuracy of perceived risk according to constructs of the health belief model and sociodemographic characteristics. Women who responded "don't know" were more likely to be less educated, of lower income, insured by Medicaid, and less knowledgeable about breast cancer. Conversely, women who accurately perceived their risk were more likely to be of higher education, more knowledgeable about breast cancer, and have a family history of breast cancer. However, women with a high objective 5-year risk of breast cancer and older age at childbirth or were nulliparous were less likely to accurately perceive their risk. These findings suggest that women who indicate "don't know" responses and hold inaccurate risk perceptions are a population vulnerable to health disparities and may benefit from educational interventions focused on improving breast cancer knowledge and perceptions to empower them to take an active role in their preventive health and make informed decisions based on their individual level of risk.
    Journal of Cancer Education 02/2014; 29(4). DOI:10.1007/s13187-014-0621-2 · 1.23 Impact Factor
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    ABSTRACT: The aim of this study is to compare health behaviors between breast, prostate, female, and male colorectal cancer survivors to noncancer controls, stratified by short- and long-term survivors, and between cancer types and genders. A 3:1 population-based sample of breast (6,259), prostate (3,609), female colorectal (1,082), and male colorectal (816) cancer survivors from the 2009 Behavioral Risk Factor Surveillance System survey were matched to noncancer controls on age, gender, race/ethnicity, income, insurance, and region of the US. The likelihood of flu immunization, physical check-up, cholesterol check, body mass index (BMI), physical activity, diet (5-A-Day), smoking, and alcohol use were compared between groups using binomial logistic regression models. Short-term breast cancer survivors were significantly more likely to meet multiple behavioral recommendations, than controls, but the likelihood decreased in the long term. Breast and female colorectal cancer survivors were up to 2.27 (95 % CI 1.90, 2.71) and 1.89 times more likely (95 % CI 1.60, 2.24) to meet the 5-A-Day and BMI recommendations, up to 0.54 times less likely (95 % CI 0.46, 0.64) to drink any alcohol, but were 0.68 times less likely (95 % CI 0.49, 0.95) to meet the physical activity recommendation, compared to prostate and male colorectal cancer survivors. Some cancer survivors may engage in better health behaviors shortly after diagnosis, but the majority of cancer survivors do not have better health behaviors than individuals without a history of cancer. However, a consistent pattern of behavioral differences exist between male and female cancer survivors. Gender differences in health behaviors among cancer survivors may be influenced by perceptions of masculinity/femininity and disease risk. Ongoing health behavioral promotion and disease prevention efforts could be improved by addressing these perceptions.
    Journal of Cancer Survivorship 02/2014; 8(3). DOI:10.1007/s11764-014-0347-5 · 3.30 Impact Factor
  • Traci Lemasters · Suresh Madhavan · Usha Sambamoorthi · Sobha Kurian ·
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    ABSTRACT: Background Objectives were to compare health-related quality of life (HRQoL) between breast cancer survivors, prostate cancer survivors (PCS), and colorectal cancer survivors (CCS) to matched controls, stratified by short and long-term survivors, by cancer type, and gender. Methods By using the 2009 Behavioral Risk Factor Surveillance System, propensity scores matched three controls to adult survivors >1year past diagnosis (N=11,964) on age, gender, race/ethnicity, income, insurance status, and region of the USA Chi-square tests and logistic regression models compared HRQoL outcomes (life satisfaction, activity limitations, sleep quality, emotional support, general, physical, and mental health). ResultsAlthough all cancer survivors reported worse general health (p<0.000) and more activity limitations (p<0.004) than controls, these disparities decreased among long-term survivors. Short-term PCS and male CCS were more likely to report worse outcomes across additional domains of HRQoL than controls, but PCS were 0.61, 0.63, and 0.70 times less likely to report activity limitations, fair/poor general health, and 1-15 bad physical health days in the past month than male CCS. Breast cancer survivors and female CCS were 2.12 and 3.17, 1.58 and 1.86, and 1.49 and 153, respectively, times more likely to report rarely/never receiving needed emotional support, 1-15 bad mental health days in the past month, and not receiving enough sleep 1-15days in the past month than PCS and male CCS. Conclusions Cancer survivors experience worse HRQoL than similar individuals without a history of cancer and the severity of affected HRQoL domains differ by time since diagnosis, cancer type, and gender. Copyright (c) 2013 John Wiley & Sons, Ltd.
    Psycho-Oncology 04/2013; 22(10). DOI:10.1002/pon.3288 · 2.44 Impact Factor
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    ABSTRACT: Mobile mammography services are typically offered as a means to increase access and adherence to mammography screenings. As mobile mammography becomes a viable strategy to increase screening, a 3 year study of such a state-wide program in WV found surprisingly high rates of obesity within the study population. Thus, the objectives were to: (1) describe the demographic characteristics and comorbidities of women who utilized the WV program, and (2) determine the association between body mass index (BMI) and personal health and screening history, preventive care and wellness behaviors, nutrition and exercise behaviors, and demographics. Data collected from 1,099 women, age 40 and above, were analyzed using descriptive statistics, bivariate analyses, and a multivariate regression model. The majority (60.4 %) were married, had an income <$25,000 (59.2 %), and had health insurance (53.5 %). Major comorbidities were hypertension (49 %) and high cholesterol (43.9 %). Based on BMI scores, 884 participants were either overweight (26.6 %), mildly obese (27.7 %), moderately obese (15.1 %), or severely obese (11.1 %). Bivariate analyses indicated that increasing BMI was significantly associated with factors such as having hypertension or diabetes, limited daily activities, perceived health, and not smoking or drinking. The regression model was significant (p < 0.001; R2 = 0.425) indicating that women who engaged in preventive care behaviors were less likely to be obese than those who did not. The WV mobile mammography program appeared to attract women who were disproportionately obese and had multiple comorbidities, thus providing a great opportunity for targeted interventions related to improving preventive care and screening behaviors.
    Journal of Community Health 09/2012; 38(2). DOI:10.1007/s10900-012-9619-z · 1.28 Impact Factor
  • Source
    A. Vyas · S. Madhavan · T. LeMasters · E. Atkins · L. Vona-Davis · S. Remick · S. Kennedy ·

    Value in Health 06/2012; 15(4):A231. DOI:10.1016/j.jval.2012.03.1245 · 3.28 Impact Factor
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    E. Atkins · S. Madhavan · T. LeMasters · A. Vyas · L. Vona-Davis · S. Kennedy · S. Remick ·

    Value in Health 06/2012; 15(4):A231. DOI:10.1016/j.jval.2012.03.1246 · 3.28 Impact Factor
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    ABSTRACT: The objectives of this study were to evaluate the characteristics (demographic, access to care, health-related behavioral, self and family medical history, psychosocial) of women age 40 years and above who participated in a mobile mammography screening program conducted throughout West Virginia (WV) to determine the factors influencing their self-reported adherence to mammography screening guidelines. Data were analyzed using the Andersen Behavioral Model of Healthcare Utilization framework to determine the factors associated with adherence to mammography screening guidelines in these women. Of the 686 women included in the analysis, 46.2% reported having had a mammogram in the past 2 years. Bivariate analyses showed predisposing factors such as older age and unemployed status, visit to a obstetrician/gynecologist (OB/GYN) in the past year (an enabling factor) and need-related factors such as having a family history of breast cancer (BC), having had breast problems in the past, having had breast biopsy in the past, having had a Pap test in past 2 years, and having had all the screenings for cholesterol, blood glucose, bone mineral density and high blood pressure in past 2 years to be significant predictors of self-reported adherence to mammography guidelines. In the final model, being above 50 years (OR=2.132), being morbidly obese (OR=2.358), having BC-related events and low knowledge about mammography were significant predictors of self-reported adherence. Breast cancer related events seem to be associated with mammography screening adherence in this rural Appalachian population. Increasing adherence to mammography screening may require targeted, community-based educational interventions that precede and complement visits by the mobile mammography unit.
    Journal of Community Health 10/2011; 37(3):632-46. DOI:10.1007/s10900-011-9494-z · 1.28 Impact Factor
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    Traci LeMasters · Usha Sambamoorthi ·
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    ABSTRACT: To identify variations in screening mammography expenditures, primarily out-of-pocket and total expenditures, of women 40-64 years of age in the United States and factors associated with variations. Retrospective analysis of data collected from the 2007 and 2008 Medical Expenditure Panel Survey (MEPS). The sample included 2020 women 40-64 years of age who received one mammogram in 2007 or 2008. Ordinary least squares regression was used to describe relationships among out-of-pocket mammography expenditures, total mammography expenditures, and out-of-pocket mammography expenditures as a percentage of total mammography expenditures and such independent variables as insurance status and type, income, region of the United States, and type of facility where a mammogram was received. The average out-of-pocket expenditure for a mammogram in 2007 or 2008 was $33, representing 14.1% of the total mammogram expenditure ($266). After controlling for demographic and health factors, women who were uninsured, were from the Midwest, and had a mammogram at an office-based facility had greater out-of-pocket mammography expenditures. Women who were uninsured, lived in the South, and received their mammogram at an office-based facility had out-of-pocket mammography expenditures that represented a greater proportion of the total mammography expenditures. Large variations in out-of-pocket expenditures were observed among women with and without insurance and between insurance types, geographic regions of the United States, and types of facilities where mammograms were received. A higher financial burden of mammography screening among some subgroups of women may act as a barrier to future mammography screening.
    Journal of Women's Health 08/2011; 20(12):1775-83. DOI:10.1089/jwh.2010.2251 · 2.05 Impact Factor
  • Source
    T. LeMasters · U. Sambamoorthi ·

    Value in Health 05/2011; 14(3). DOI:10.1016/j.jval.2011.02.474 · 3.28 Impact Factor

Publication Stats

32 Citations
27.98 Total Impact Points


  • 2011-2014
    • West Virginia University
      • Department of Pharmaceutical Systems and Policy
      Morgantown, West Virginia, United States
  • 2012
    • Konan University
      Kōbe, Hyōgo, Japan