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Featured researches published by Ann Hryshko-Mullen.


Military Medicine | 2009

Preliminary Findings of a Randomized Controlled Trial of an Interdisciplinary Military Pain Program

Robert J. Gatchel; Donald D. McGeary; Alan L. Peterson; Mysti Moore; Karen Leroy; William C. Isler; Ann Hryshko-Mullen; Tom Edell

Chronic pain related to musculoskeletal conditions is the leading cause of medical discharge from active duty military service. The present study is the first randomized controlled trial of an interdisciplinary pain treatment program (functional restoration, FR) to decrease chronic musculoskeletal pain and increase functioning in an active duty military population. Sixty-six military participants were randomly assigned to either an FR treatment group or a standard anesthesia pain clinic treatment comparison group. A repeated measures design was employed and data were analyzed for pre- to post-treatment differences, as well as for 6-months and 1-year post-treatment outcomes. Findings revealed significantly greater improvements for the FR group on self-reported pain, disability, functional status, and fitness for military duty at the post-treatment and follow-up points, relative to the comparison group. These results clearly demonstrate the efficacy and military relevance of a FR program for active duty military personnel who have chronic musculoskeletal pain disorders.


Nicotine & Tobacco Research | 2016

Prevalence and Correlates of Tobacco and Nicotine Containing Product Use in a Sample of United States Air Force Trainees

Melissa A. Little; Karen J. Derefinko; Zoran Bursac; Jon O. Ebbert; Lauren Colvin; Gerald W. Talcott; Ann Hryshko-Mullen; Phyllis A. Richey; Robert C. Klesges

INTRODUCTION Although there is increasing attention to the prevalence of new and emerging tobacco products in the civilian population, remarkably little is known about the current prevalence of these products in a military population. METHODS The current investigation was designed to determine the prevalence of tobacco and nicotine containing products (TNCP) and correlates of use across multiple cohorts of trainees undergoing Technical Training in the US Air Force between April 2013 and December 2014. Chi-square test, Cochran-Armitage test for linear trend, and logistic regression models were applied to test differences and linear trends across time for TNCP use as well as correlates of use in a cross-sectional sample of 13 685 Airmen (final analytic sample). RESULTS Over a quarter (26.9%) of Airmen reported regular use of a TNCP. The two most prevalent products were cigarettes (11.2%) and hookah (10.5%). Among correlates of use, Airmen that regularly use TNCPs were more likely to be male, younger, non-Hispanic white, and single with a high school degree or General Education Development. Hookah was the most endorsed for intentions to use, and along with e-cigarettes, had the lowest perception of harm. While prevalence of most products remained constant across entering cohorts, the prevalence of e-cigarettes showed significant linear increase. CONCLUSIONS The prevalence of TNCP use is high across cohorts of Airmen. Remarkably high estimates of future intentions to use and low perceptions of harm for emerging products suggest that intervention efforts should be directed at multiple forms of TNCP use to address this important public health issue.


American Journal of Epidemiology | 2016

Types of Dual and Poly-Tobacco Users in the US Military

Melissa A. Little; Zoran Bursac; Karen J. Derefinko; Jon O. Ebbert; Gerald W. Talcott; Ann Hryshko-Mullen; Robert C. Klesges

The present investigation was designed to determine the prevalence and types of dual and poly-use of tobacco products in the US Air Force, as well as characteristics and factors associated with these types. We conducted a cross-sectional assessment of tobacco-product use among 13,873 Air Force trainees from 2013 to 2014. The assessment included prevalence of the use of 10 different tobacco products and demographic and environmental factors, such as risk perceptions of tobacco use, peer use, and tobacco-company influences. Latent class analysis was carried out to determine types of poly-tobacco users. Tobacco-product use was reported by 27.1% of participants, and of those, over half reported using more than 1 tobacco product. Latent class analysis indicated 5 classes of poly-tobacco use. Factors associated with poly-tobacco (vs. mono-tobacco) use included lower confidence to remain tobacco-free, low harm perceptions, and receiving tobacco products free at bars or social events. Rates of dual and poly-tobacco use are high among trainees, and while these groups are similar to mono users in some ways, there are a number of differences that need to be considered when developing targeted interventions to address use of multiple tobacco products.


Addictive Behaviors | 2016

Alcohol issues prior to training in the United States Air Force

Karen J. Derefinko; Robert C. Klesges; Zoran Bursac; Melissa A. Little; Ann Hryshko-Mullen; Gerald W. Talcott

The negative impact of alcohol is a significant concern to the US military given the costs associated with alcohol-related offenses. Despite considerable research in active duty personnel, relatively little is known about the current extent of alcohol use among incoming recruits. We examined the history of alcohol use and harmful patterns of alcohol consumption among recruits entering the United States Air Force (USAF; N=50,549) over the span of 4 years (2010-2014). Across all years, drinking rates reflected national average trends for those aged 18-24 (NIDA, 2014). However, when abstainers were excluded, those under 21 (n=10,568) reported an average of 18.4 drinks per week, whereas those age 21 and over (n=14,188) reported an average of 14.1 drinks per week, suggesting that for those who drink, those under 21 are exhibiting more risky drinking rates. Alcohol Use Disorders Identification Task (AUDIT) scores for drinkers reflected these same trends. For those under 21, 58% scored in risk categories of 2 or higher (risky drinking warranting attention), compared with 40% for those age 21 and over. These scores indicate that for recruits in the USAF, approximately half report alcohol use immediately prior to basic training, resulting in the inheritance of these potential alcohol related issues for those conducting training of these recruits. Based upon these numbers, brief alcohol interventions could have a potential positive impact on individuals in their initial training stages of the USAF to prevent these baseline issues from resulting in problems later in their military careers.


Military Medicine | 2015

Efficacy of a Tobacco Quitline in Active Duty Military and TRICARE Beneficiaries: A Randomized Trial

Robert C. Klesges; Jon O. Ebbert; G. Wayne Talcott; Fridtjof Thomas; Phyllis A. Richey; Catherine Womack; Ann Hryshko-Mullen; John S. Oh

A higher proportion of military personnel than civilians smoke cigarettes. Few randomized trials of tobacco use interventions have been conducted in the U.S. military. We evaluated the efficacy of a tobacco quitline (QL) in 1298 active duty military personnel, their dependents, reservists, and retirees who smoke cigarettes. Participants were randomized to either a proactive (counselor-initiated) or reactive (participant-initiated) QL intervention for 8 weeks. The proactive condition included up to an 8-week supply of free nicotine replacement therapy, and the reactive condition included a 2-week supply. The primary outcome was 12-month smoking abstinence. The enrolled population was predominantly affiliated with the Air Force and Army. At the end of treatment, proactive treatment was associated with a greater odds of both prolonged (44.22% vs. 24.96%; odds ratio [OR] = 2.4, P < 0.0001) and 7-day point prevalence (49.92% vs. 28.20%; OR = 2.5, P < 0.0001) smoking abstinence, a difference that was maintained for prolonged smoking abstinence at 12 months (22.03% vs. 13.41%; OR = 1.8, P < 0.0001). Our findings provide evidence that a proactive QL with nicotine replacement therapy is highly efficacious among Air Force and Army active duty and TRICARE beneficiaries and would provide an effective telephonic treatment option for this population of smokers.


Obesity | 2018

Dissemination of the Look AHEAD Intensive Lifestyle Intervention in the United States Military: A Randomized Controlled Trial: Weight Loss in the Military

Rebecca A. Krukowski; Marion E. Hare; Gerald W. Talcott; Leslie Gladney; Karen C. Johnson; Phyllis A. Richey; Mehmet Kocak; Patrick L. Keller; Ann Hryshko-Mullen; Robert C. Klesges

The purpose of this study, “Fit Blue,” was to compare a translation of the Look AHEAD (Action for Heath in Diabetes) intensive lifestyle intervention with a self‐paced version of the same intervention among active duty military personnel.


Military Medicine | 2018

Characteristics Associated With Participation in a Behavioral Weight Loss Randomized Control Trial in the U.S. Military

Margaret C. Fahey; Marion E. Hare; Gerald W. Talcott; Mehmet Kocak; Ann Hryshko-Mullen; Robert C. Klesges; Rebecca A. Krukowski

INTRODUCTION Effective recruitment and subsequent enrollment of diverse populations is often a challenge in randomized controlled trials, especially those focused on weight loss. In the civilian literature, individuals identified as racial and ethnic minorities, men, and younger and older adults are poorly represented in weight loss interventions. There are limited weight loss trials within military populations, and to our knowledge, none reported participant characteristics associated with enrollment. There may be unique motives and barriers for active duty personnel for enrollment in weight management trials. Given substantial costs and consequences of overweight and obesity in the U.S. military, identifying predictors and limitations to diverse enrollment can inform future interventions within this population. The study aims to describe the recruitment, screening, and enrollment process of a military weight loss intervention. Demographic and lifestyle characteristics of military personnel lost between screening and randomization are compared to characteristics of personnel randomized in the study and characteristics of the Air Force in general. MATERIALS AND METHODS The Fit Blue study, a randomized controlled behavioral weight loss trial for active duty personnel, was approved by the Institutional Review Board of the Wilford Hall Ambulatory Surgical Center in San Antonio, TX, USA and acknowledged by the Institutional Review Board at the University of Tennessee Health Science Center. Logistic regressions compared participant demographics, anthropometric data, and health behaviors between personnel that attended a screening visit but were not randomized and those randomized. Multivariable models were constructed for the likelihood of being randomized using a liberal entry and stay criteria of 0.10 for the p-values in a stepwise variable selection algorithm. Descriptive statistics compared the randomized Fit Blue cohort demographics to those of the U.S. Air Force. RESULTS In univariate analyses, older age (p < 0.02), having a college degree or higher (p < 0.007) and higher military rank (p < 0.02) were associated with completing the randomization process. The randomized cohort reported a lower percentage of total daily kilocalories for fat compared to the non-randomized cohort (p = 0.033). The non-randomized cohort reported more total minutes and intensity of physical activity (p = 0.073). In the multivariate model, only those with a college degree or higher were 3.2 times more likely to go onto randomization. (OR = 3.2, 95% CI = 2.0, 5.6, p < 0.0001). The Fit Blue study included a higher representation of personnel who identified as African American (19.4% versus 15.0%) and Hispanic/Latino (22.7% versus 14.3%) compared with the U.S. Air Force in general; however, men were underrepresented (49.4% versus 80.0%). TABLE I.Comparisons of Demographic Characteristics of Randomized Fit Blue Cohort to Screened Non-Randomized CohortFit Blue Randomized Participants (N = 248)Non-Randomized Cohort (N = 111)All Screened Participants (N = 359)p-ValueSex N (%)0.73 Male122 (49.2)52 (46.8)174 (48.5) Female126 (50.8)59 (53.2)183 (51.5)Age Mean (±SD) years34 (±7.5)32 (±6.7)33 (±7.3)0.02Race N (%)0.89 African American49 (19.8)22 (19.8)71 (19.8) Caucasian163 (65.7)75 (67.6)238 (66.3) Other36 (14.5)14 (12.2)50 (13.9)Ethnicity N (%)0.59 Hispanic/Latino56 (22.6)28 (25.2)84 (23.4) Non-Hispanic/Latino192 (77.4)83 (74.8)275 (76.6)Education N (%)<0.0001 Less than college degree123 (49.6)82 (73.9)205 (57.1) College degree or greater125 (50.4)29 (26.1)154 (42.9)Marital status N (%)0.83 Single/never married40 (16.1)20 (18)60 (16.7) Married/living as married169 (68.1)72 (64.9)241 (67.1) Separated/divorced39 (15.7)19 (17.1)58 (16.2)Number of additional adults in household N (%)0.82 046 (18.5)22 (19.8)68 (18.9) 1162 (65.3)73 (65.8)235 (65.5) 231 (12.5)14 (12.6)45 (12.5) 3 or more9 (3.6)2 (1.8)11 (3.1)Number of children in household N (%)0.56 091 (36.7)37 (33.3)128 (35.7) 159 (23.8)23 (20.7)82 (22.8) 257 (23)26 (23.4)83 (23.1) 3 or more41 (16.5)25 (22.5)66 (18.4)Years in service mean (± SD)12 (±6.6)11 (±6.1)12 (±6.4)0.20Military gradeaN (%)0.02 E1-E434 (13.7)19 (17.1)53 (14.8) E5-E6105 (42.3)58 (52.3)163 (45.4) E7-E952 (21)21 (18.9)73 (20.3) O1-O317 (6.9)9 (8.1)26 (7.2) O4-O639 (15.7)4 (3.6)43 (12)Branch0.68 Army4 (1.6)1 (0.9)5 (1.4) Air Force234 (94.4)105 (94.6)339 (94.4) Navy8 (3.2)5 (4.5)13 (3.6) Marine Corp2 (0.8)0 (0.0)2 (0.6)BMI (m2/kg) N (%)30.6 (±2.7)30.4 (±2.9)30.6 (±2.8)BMI category N (%)0.76 Overweight115 (46.4)52 (48.1)167 (46.9) Obese133 (53.6)56 (51.9)189 (53.1)aMilitary ranking; Enlisted (E) categories: E1-E4 (enlisted), E5-E6 (non-commissioned officers), E7-E9 (senior non-commissioned officers) and two Officer categories (O): O1-O3 (Company Grade Officer) and O4-O6 (Field Grade Officer); standard deviation (SD).Table II.Comparisons of Anthropometric Characteristics of Randomized Fit Blue Cohort to Screened Non-Randomized CohortFit Blue Randomized Participants (N = 248)Non-Randomized Cohort (N = 111)All Screened Participants (N = 359)p-ValuePhysical activity Total physical activity2525 (±3218)2840 (±2541)2621 (±3028)0.027 (mean (±SD) minutes per week) Total sedentary physical activity5046 (±239)472 (±221)494 (±234)0.35 (mean (±SD) minutes per week) Vigorous physical activity34 (±145)54 (±152)40 (±147)0.036 (mean (±SD) minutes per week)Dietary intake Total sweetened beverages (kcal per day)165 (±206)152.9 (±166)160.8 (±194)0.80 Fruit and vegetable consumption (cups per day)3 (±1)3 (±1)3 (±1)0.52 Dietary fat (% total kcal)35 (±4)34 (±4)35 (±4)0.033. CONCLUSIONS Accounting for all influencing characteristics, higher educational status was the only independent predictor of randomization. Perhaps, highly educated personnel are more invested in a military career, and thus, more concerned with consequences of failing required fitness tests. Thus, it may be important for future weight loss interventions to focus recruitment on less-educated personnel. Results suggest that weight loss interventions within a military population offer a unique opportunity to recruit a higher prevalence of males and individuals who identify as racial or ethnic minorities which are populations commonly underrepresented in weight loss research.


Contemporary Clinical Trials | 2012

Efficacy of a smoking quit line in the military: baseline design and analysis.

Phyllis A. Richey; Robert C. Klesges; Gerald W. Talcott; Margaret DeBon; Catherine Womack; Fridtjof Thomas; Ann Hryshko-Mullen


Contemporary Clinical Trials | 2018

Moms fit 2 fight: Rationale, design, and analysis plan of a behavioral weight management intervention for pregnant and postpartum women in the U.S. military

Margaret C. Fahey; G. Wayne Talcott; Callie M. Cox Bauer; Zoran Bursac; Leslie Gladney; Marion E. Hare; Jean Harvey; Melissa A. Little; Deirdre McCullough; Ann Hryshko-Mullen; Robert C. Klesges; Mehmet Kocak; Teresa M. Waters; Rebecca A. Krukowski


Archive | 2017

Tobacco Initiation and Re-Initiation Following a Period of Forced Abstinence: Brief Tobacco Interventions

Gerald W. Talcott; Melissa A. Little; Jon O. Ebbert; Zoran Bursac; Ann Hryshko-Mullen; Robert C. Klesges

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Robert C. Klesges

University of Tennessee Health Science Center

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Gerald W. Talcott

University of Tennessee Health Science Center

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Melissa A. Little

University of Tennessee Health Science Center

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Zoran Bursac

University of Tennessee Health Science Center

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Phyllis A. Richey

University of Tennessee Health Science Center

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Catherine Womack

University of Tennessee Health Science Center

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Karen J. Derefinko

University of Tennessee Health Science Center

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Marion E. Hare

University of Tennessee Health Science Center

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Mehmet Kocak

University of Tennessee Health Science Center

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