Browsing by Author "Heapy, Alicia A."

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    Gender Differences in Demographic and Clinical Correlates among Veterans with Musculoskeletal Disorders
    (Elsevier, 2017-07) Higgins, Diana M.; Fenton, Brenda T.; Driscoll, Mary A.; Heapy, Alicia A.; Kerns, Robert D.; Bair, Matthew J.; Carroll, Constance; Brennan, Penny L.; Burgess, Diana J.; Piette, John D.; Haskell, Sally G.; Brandt, Cynthia A.; Goulet, Joseph L.; Medicine, School of Medicine
    Background Studies suggest that women may be at greater risk for developing chronic pain and pain-related disability. Methods Because musculoskeletal disorders (MSD) are the most frequently endorsed painful conditions among veterans, we sought to characterize gender differences in sociodemographic and clinical correlates among veterans upon entry into Veterans Health Administration's Musculoskeletal Disorders Cohort (n = 4,128,008). Results Women were more likely to be younger, Black, unmarried, and veterans of recent conflicts. In analyses adjusted for gender differences in sociodemographics, women were more likely to have diagnoses of fibromyalgia, temporomandibular disorders, and neck pain. Almost one in five women (19.4%) had more than one MSD diagnosis, compared with 15.7% of men; this higher risk of MSD multimorbidity remained in adjusted analyses. Adjusting for sociodemographics, women with MSD were more likely to have migraine headache and depressive, anxiety, and bipolar disorders. Women had lower odds of cardiovascular diseases, substance use disorders, and several MSDs, including back pain conditions. Men were more likely to report “no pain” on the pain intensity Numeric Rating Scale, whereas more women (41%) than men (34%) reported moderate to severe pain (Numeric Rating Scale 4+). Conclusions Because women veterans are more likely to have conditions such as fibromyalgia and mental health conditions, along with greater pain intensity in the setting of MSD, women-specific pain services may be needed.
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    If you personalize it, will they use it?: Self-reported and observed use of a tailored, internet-based pain self-management program
    (Oxford University Press, 2022) Reuman, Lillian; Solar, Chelsey; MacLean, R. Ross; Halat, Allison M.; Rajeevan, Haseena; Williams, David A.; Heapy, Alicia A.; Bair, Matthew J.; Krein, Sarah L.; Kerns, Robert D.; Higgins, Diana M.; Medicine, School of Medicine
    Little is known about how individuals with chronic pain use tailored internet-based interventions. This study is the first to compare self-reported skill module use to observed module access and to examine each of these in relationship to tailored recommendations to access specific content. Participants (N = 58) enrolled in a 10-week trial of the Pain EASE program, a tailored internet-based intervention that includes 10 pain self-management skill modules. Participants completed a “Self-Assessment,” which was used to provide a “Personalized Plan” that encouraged accessing specific modules. Participants self-reported module use during weekly data collection telephone calls. Program log data were extracted to capture “observed” module use during the trial period. Findings indicated significantly greater self-reported use of the Pain EASE modules compared to observed access with log data. Further, log data revealed that participants accessed less than half of the modules recommended to them via tailoring.
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    Predictors of engagement in an internet-based cognitive behavioral therapy program for veterans with chronic low back pain
    (Oxford University Press, 2021) Solar, Chelsey; Halat, Allison M.; MacLean, R. Ross; Rajeevan, Haseena; Williams, David A.; Krein, Sarah L.; Heapy, Alicia A.; Bair, Matthew J.; Kerns, Robert D.; Higgins, Diana M.; Medicine, School of Medicine
    Internet-based interventions for chronic pain have demonstrated efficacy and may address access barriers to care. Participant characteristics have been shown to affect engagement with these programs; however, limited information is available about the relationship between participant characteristics and engagement with internet-based programs for self-management of chronic pain. The current study examined relationships between demographic and clinical characteristics and engagement with the Pain EASE program, a self-directed, internet-based cognitive behavioral therapy intervention for veterans with chronic low back pain (cLBP). Veterans with cLBP were enrolled in a 10 week trial of the Pain EASE program. Engagement measures included the number of logins, access to coping skill modules, and completed study staff-initiated weekly check-in calls. Regression analyses were conducted to identify significant predictors of engagement from hypothesized predictors (e.g., race/ethnicity, age, depressive symptom severity, and pain interference). Participants (N = 58) were 93% male, 60.3% identified as White, and had a mean age of 54.5 years. Participants logged into the program a median of 3.5 times, accessed a median of 2 skill modules, and attended a median of 6 check-in calls. Quantile regression revealed that, at the 50th percentile, non-White-identified participants accessed fewer modules than White-identified participants (p = .019). Increased age was associated with increased module use (p = .001). No clinical characteristics were significantly associated with engagement measures. White-identified race/ethnicity and increased age were associated with greater engagement with the Pain EASE program. Results highlight the importance of defining and increasing engagement in internet-delivered pain care.
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    The Relationship Between Body Mass Index and Pain Intensity Among Veterans with Musculoskeletal Disorders: Findings from the MSD Cohort Study
    (Oxford University Press, 2020-10-01) Higgins, Diana M.; Buta, Eugenia; Heapy, Alicia A.; Driscoll, Mary A.; Kerns, Robert D.; Masheb, Robin; Becker, William C.; Hausmann, Leslie R.M.; Bair, Matthew J.; Wandner, Laura; Janke, E. Amy; Brandt, Cynthia A.; Goulet, Joseph L.; Medicine, School of Medicine
    Objective: To examine the relationship between body mass index (BMI) and pain intensity among veterans with musculoskeletal disorder diagnoses (MSDs; nontraumatic joint disorder; osteoarthritis; low back, back, and neck pain). Setting: Administrative and electronic health record data from the Veterans Health Administration (VHA). Subjects: A national cohort of US military veterans with MSDs in VHA care during 2001-2012 (N = 1,759,338). Methods: These cross-sectional data were analyzed using hurdle negative binomial models of pain intensity as a function of BMI, adjusted for comorbidities and demographics. Results: The sample had a mean age of 59.4, 95% were male, 77% were white/Non-Hispanic, 79% were overweight or obese, and 42% reported no pain at index MSD diagnosis. Overall, there was a J-shaped relationship between BMI and pain (nadir = 27 kg/m2), with the severely obese (BMI ≥ 40 kg/m2) being most likely to report any pain (OR vs normal weight = 1.23, 95% confidence interval = 1.21-1.26). The association between BMI and pain varied by MSD, with a stronger relationship in the osteoarthritis group and a less pronounced relationship in the back and low back pain groups. Conclusions: There was a high prevalence of overweight/obesity among veterans with MSD. High levels of BMI (>27 kg/m2) were associated with increased odds of pain, most markedly among veterans with osteoarthritis.