2024
Gender Differences in “Making Weight” Behaviors Among U.S. Iraq and Afghan War Veterans: Implications for Future Health
Cary A, Neff K, Buta E, Fenn L, Ramsey C, Snow J, Haskell S, Masheb R. Gender Differences in “Making Weight” Behaviors Among U.S. Iraq and Afghan War Veterans: Implications for Future Health. Journal Of Women's Health 2024 PMID: 39510825, DOI: 10.1089/jwh.2024.0246.Peer-Reviewed Original ResearchFemale service membersEating pathologyMental healthAfghanistan war era veteransLevels of dietary restraintMeasures of eating behaviorPosttraumatic stress disorderService membersGender differencesWeight behaviorPotential gender differencesRates of obesityAssociated with female genderStress disorderFood addictionProportion of womenDietary restraintEmotional eatingEra veteransU.S.-IraqWar veteransExcessive exerciseFuture healthMilitary populationVeteransRecommendations for monitoring adherence and fidelity in pragmatic trials based on experience in the Pain Management Collaboratory
Dziura J, Gilstad-Hayden K, Coffman C, Long C, Yu Q, Buta E, Coggeshall S, Geda M, Peduzzi P, Kyriakides T. Recommendations for monitoring adherence and fidelity in pragmatic trials based on experience in the Pain Management Collaboratory. Pain Medicine 2024, 25: s41-s48. PMID: 39514878, PMCID: PMC11548857, DOI: 10.1093/pm/pnae080.Peer-Reviewed Original ResearchConceptsPain Management CollaboratoryPragmatic trialPragmatic Explanatory Continuum Indicator SummaryMonitor adherenceElectronic health recordsFidelity dataIntervention deliveryIntervention fidelityIndicator SummaryHealth recordsTrial interventionProtocol adherenceParticipant engagementStudy teamAdherence dataAdherenceTrial integrityInterventionParticipantsSafety monitoring boardFrequent sourcePainLevel of monitoringTrialsMonitoring boardReprint of: Sex differences in appeal, reward, and sensory experience of E-cigarette flavors among adults who smoke cigarettes
Davis D, Buta E, Green B, Krishnan-Sarin S. Reprint of: Sex differences in appeal, reward, and sensory experience of E-cigarette flavors among adults who smoke cigarettes. Preventive Medicine 2024, 188: 108114. PMID: 39232940, DOI: 10.1016/j.ypmed.2024.108114.Peer-Reviewed Original ResearchDrug Effects QuestionnaireE-cigarette appealLabeled Hedonic ScaleGeneral Labeled Magnitude ScaleSensory experienceEffects of sexSex differencesRewardEffective questionnairesExploratory analysisE-cigarette flavorsNicotine concentrationsE-cigarettesSmoking cigarettesE-cigarette experienceLinear mixed modelsEffects of e-cigarettesIntensity of flavorMenthol flavorsAdultsSexScaleCuesCigaretteHedonic scaleSex differences in appeal, reward, and sensory experience of E-cigarette flavors among adults who smoke cigarettes
Davis D, Buta E, Green B, Krishnan-Sarin S. Sex differences in appeal, reward, and sensory experience of E-cigarette flavors among adults who smoke cigarettes. Preventive Medicine 2024, 185: 108040. PMID: 38866212, PMCID: PMC11323236, DOI: 10.1016/j.ypmed.2024.108040.Peer-Reviewed Original ResearchDrug Effects QuestionnaireE-cigarette appealLabeled Hedonic ScaleGeneral Labeled Magnitude ScaleSensory experienceEffects of sexSex differencesRewardEffective questionnairesExploratory analysisE-cigarette flavorsNicotine concentrationsE-cigarettesSmoking cigarettesE-cigarette experienceIntensity of flavorLinear mixed modelsMenthol flavorsEffects of e-cigarettesAdultsSexScaleHedonic scaleCigaretteCuesBehavioral Precursors of Nicotine Product Use Trajectories Among Youth
Buta E, Gueorguieva R, Simon P, Garrison K. Behavioral Precursors of Nicotine Product Use Trajectories Among Youth. American Journal Of Preventive Medicine 2024, 67: 360-369. PMID: 38782105, DOI: 10.1016/j.amepre.2024.05.009.Peer-Reviewed Original ResearchNicotine useNicotine productsHarm perceptionsPopulation Assessment of Tobacco and Health StudyBehavioral precursorsPublic health priorityNon-user classPriority intervention targetsPredictors of trajectoriesNonuser classesHealth StudyHealth priorityNicotineHigher oddsCentral network nodesYouth agesNon-usersOddsIntervention targetsPopulation AssessmentYouthPositive expectationsSocioecological factors associated with multiple nicotine product use among U.S. youth: Findings from the population assessment of tobacco and health (PATH) study 2013–2018
Simon P, Stefanovics E, Ying S, Gueorguieva R, Krishnan-Sarin S, Buta E. Socioecological factors associated with multiple nicotine product use among U.S. youth: Findings from the population assessment of tobacco and health (PATH) study 2013–2018. Preventive Medicine 2024, 183: 107956. PMID: 38615947, DOI: 10.1016/j.ypmed.2024.107956.Peer-Reviewed Original ResearchPopulation Assessment of Tobacco and HealthNicotine product useU.S. youthAssociated with tobacco useEstimate adjusted associationsPopulation AssessmentPromote harm reductionTobacco product useMultinomial logistic regressionTobacco useAdjusted associationsSocioecological approachStudy Wave 1Harm reductionProduct useIntrapersonal factorsLogistic regressionWave 1Family factorsLifetime historyNicotine productsOlder ageLifetime usersYouthPrevent escalationA randomized controlled trial of potential tobacco policies prohibiting menthol flavor in cigarettes and e-cigarettes: a study protocol
Bold K, Sharma A, Haeny A, Gueorguieva R, Buta E, Baldassarri S, Lempert L, Krishnan-Sarin S, O’Malley S. A randomized controlled trial of potential tobacco policies prohibiting menthol flavor in cigarettes and e-cigarettes: a study protocol. BMC Psychiatry 2024, 24: 201. PMID: 38475757, PMCID: PMC10935798, DOI: 10.1186/s12888-024-05619-0.Peer-Reviewed Original ResearchConceptsSmoking menthol cigarettesE-cigarettesCigarette useReduce tobacco-related health disparitiesTobacco-related health disparitiesMenthol cigarettesRates of menthol cigarette useTobacco use statusMenthol cigarette useRandomized controlled trialsPublic health problemHealth disparitiesTobacco policiesFlavored e-cigarettesSmoke-freeMenthol flavorsMenthol policiesBlack adultsQuit smokingNon-Black participantsSmoking behaviorFollow-up visitHealth problemsSecondary outcomesE-cigarette productsCognitive behavioral therapy for chronic pain supported by digital patient feedback and artificial intelligence: Do patients with socioeconomic risk factors benefit?
Piette J, Driscoll M, Buta E, Kerns R, Heapy A. Cognitive behavioral therapy for chronic pain supported by digital patient feedback and artificial intelligence: Do patients with socioeconomic risk factors benefit? Intelligence-Based Medicine 2024, 10: 100164. DOI: 10.1016/j.ibmed.2024.100164.Peer-Reviewed Original ResearchSocial determinants of healthPain-related disabilityCBT-CPClinically meaningful improvementsCognitive behavioral therapyChronic painSocial determinants of health indicatorsTreatment engagementMeaningful improvementsDeterminants of healthSocially disadvantaged patientsSocioeconomic risk factorsComparative effectiveness trialPoor treatment engagementBehavioral therapySDoH indicatorsTreatment access barriersSocial determinantsDisadvantaged patientsSession completionExacerbate disparitiesDigital interventionsPatient feedbackGeographic accessAccess barriers
2023
Distinguishing probable atypical anorexia nervosa from weight loss alone in a national sample of U.S. Military Veterans: Disentangling the roles of weight suppression and cognitive concerns
Neff K, Buta E, Fenn L, Ramsey C, Snow J, Haskell S, Masheb R. Distinguishing probable atypical anorexia nervosa from weight loss alone in a national sample of U.S. Military Veterans: Disentangling the roles of weight suppression and cognitive concerns. International Journal Of Eating Disorders 2023, 57: 827-838. PMID: 38129986, DOI: 10.1002/eat.24116.Peer-Reviewed Original ResearchAtypical anorexia nervosaAtypical ANWeight suppressionAnorexia nervosaClinical entityWeight lossControl groupDietary restraintMental healthDistinct clinical entityPoor mental healthOnly groupU.S. military veteransClinical significanceHigh riskVeteran populationSecondary analysisWeight gainSpecialized interventionsMilitary veteransNervosaDisordersVeteransNational studyPathologyRelationship Between Pain and LGBT Status Among Veterans in Care in a Retrospective Cross-Sectional Cohort
Gordon K, Buta E, Pratt-Chapman M, Brandt C, Gueorguieva R, Warren A, Workman T, Zeng-Treitler Q, Goulet J. Relationship Between Pain and LGBT Status Among Veterans in Care in a Retrospective Cross-Sectional Cohort. Journal Of Pain Research 2023, 16: 4037-4047. PMID: 38054108, PMCID: PMC10695019, DOI: 10.2147/jpr.s432967.Peer-Reviewed Original ResearchRetrospective cross-sectional cohortCross-sectional cohortPersistent painSelf-reported pain scoresVeterans Health AdministrationRobust Poisson modelsCorporate Data WarehouseLGBT veteransPain screeningPain scoresClinic visitsPain assessmentPainAdjusted modelHealth AdministrationGreater painMental healthSubstance useCohortYear of entryBlack veteransHealthcare systemVeteransSignificant differencesAdministrative dataDevelopment and Psychometric Assessment of the Weight and Eating Quality of Life (WE-QOL) Scale in US Military Veterans
Masheb R, Snow J, Fenn L, Antoniadis N, Raffa S, Ruser C, Buta E. Development and Psychometric Assessment of the Weight and Eating Quality of Life (WE-QOL) Scale in US Military Veterans. Journal Of General Internal Medicine 2023, 38: 2076-2081. PMID: 36973571, PMCID: PMC10361921, DOI: 10.1007/s11606-023-08132-4.Peer-Reviewed Original ResearchConceptsVeterans Health AdministrationPopulation health metricsQOL measuresGeneric health-related QOL measuresHealth-related QOL measuresHealth metricsWeight management programPopulation health approachObesity-related diseasesQuality of careUS military veteransClinical remindersUS veteransPhysical activityHealth AdministrationPatient careEuropean QualityHealth approachWeight gainPhysical discomfortWeight stigmaMilitary veteransPsychometric assessmentEmotional distressLife ScaleThe first nicotine product tried is associated with current multiple nicotine product use and nicotine dependence among a nationally representative sample of U.S. youths
Simon P, Buta E, Jackson A, Camenga D, Kong G, Morean M, Bold K, Davis D, Krishnan-Sarin S, Gueorguieva R. The first nicotine product tried is associated with current multiple nicotine product use and nicotine dependence among a nationally representative sample of U.S. youths. Preventive Medicine 2023, 169: 107437. PMID: 36731754, PMCID: PMC10507373, DOI: 10.1016/j.ypmed.2023.107437.Peer-Reviewed Original ResearchConceptsNicotine product useSymptoms of dependenceNicotine dependenceMultiple product useSmokeless tobaccoNicotine productsProduct useSeparate multinomial logistic regression modelsHealth Study Waves 1Wave 1Smokeless tobacco usersHigher nicotine dependence scoresNicotine dependence scoresDemographic factorsLogistic regression modelsMultinomial logistic regression modelsMultivariable modelTobacco usersHigh riskDependence scoresSymptomsGreater likelihoodUse statusWave 4Regression models
2022
Using Daily Ratings to Examine Treatment Dose and Response in Cognitive Behavioral Therapy for Chronic Pain: A Secondary Analysis of the Co-Operative Pain Education and Self-Management Clinical Trial
MacLean R, Buta E, Higgins D, Driscoll M, Edmond S, LaChappelle K, Ankawi B, Krein S, Piette J, Heapy A. Using Daily Ratings to Examine Treatment Dose and Response in Cognitive Behavioral Therapy for Chronic Pain: A Secondary Analysis of the Co-Operative Pain Education and Self-Management Clinical Trial. Pain Medicine 2022, 24: 846-854. PMID: 36484691, PMCID: PMC10250557, DOI: 10.1093/pm/pnac192.Peer-Reviewed Original ResearchConceptsPain intensityCognitive behavioral therapyCBT-CPChronic painTreatment responseDaily stepsSecondary analysisBehavioral therapyMeaningful changeChronic back painStrong evidence baseBack painPain educationTreatment weekClinical trialsNoninferiority trialTreatment benefitOutcome measuresWeek 4Treatment doseWeek 2Baseline weekMost respondersSurvival analysisStep countModels for Zero-Inflated and Overdispersed Correlated Count Data: An Application to Cigarette Use
Pittman B, Buta E, Garrison K, Gueorguieva R. Models for Zero-Inflated and Overdispersed Correlated Count Data: An Application to Cigarette Use. Nicotine & Tobacco Research 2022, 25: 996-1003. PMID: 36318799, PMCID: PMC10077942, DOI: 10.1093/ntr/ntac253.Peer-Reviewed Original ResearchConceptsCorrelated count dataCount outcomesCount dataSubject-specific interpretationZero-InflatedIncorrect statistical inferenceStatistical inferenceCorrelated countsPoisson distributionOverdispersionModel assumptionsPoisson modelRandom effectsHurdle Poisson modelProper modelNegative binomial modelBinomial modelSuch dataAppropriate modelBest fitLarge varianceTobacco researchSuch outcomesModel fitTraining appAdherence to Daily Interactive Voice Response Calls for a Chronic Pain Intervention
Ankawi B, Piette J, Buta E, Edmond S, MacLean R, Higgins D, LaChappelle K, Krein S, Heapy A. Adherence to Daily Interactive Voice Response Calls for a Chronic Pain Intervention. Journal Of Technology In Behavioral Science 2022, 7: 343-350. DOI: 10.1007/s41347-022-00254-6.Peer-Reviewed Original ResearchChronic painCBT-CPIVR callsIntervention groupLong-term opioid treatmentChronic pain interventionsFirst-line treatmentNon-pharmacological managementNon-pharmacological interventionsCognitive behavioral therapyBaseline cognitive functioningOpioid treatmentBaseline characteristicsPain interventionsAdherence ratesPatient subgroupsTelehealth deliveryClinical trialsTreatment protocolPerson treatmentTreatment efficacyPainSecondary analysisDaily Interactive Voice ResponsePatients
2017
Interactive Voice Response–Based Self-management for Chronic Back Pain: The COPES Noninferiority Randomized Trial
Heapy AA, Higgins DM, Goulet JL, LaChappelle KM, Driscoll MA, Czlapinski RA, Buta E, Piette JD, Krein SL, Kerns RD. Interactive Voice Response–Based Self-management for Chronic Back Pain: The COPES Noninferiority Randomized Trial. JAMA Internal Medicine 2017, 177: 765-773. PMID: 28384682, PMCID: PMC5818820, DOI: 10.1001/jamainternmed.2017.0223.Peer-Reviewed Original ResearchConceptsPerson cognitive-behavioural therapyChronic back painNumeric rating scaleCognitive behavioral therapyBack painChronic painPrimary outcomeSleep qualityVeterans Affairs Health Care SystemPrespecified noninferiority marginAverage pain intensityNonpharmacologic treatment optionsPain-related interferenceChronic pain treatmentSelf-management trialCognitive behavioral therapy deliveryIndividual CBT sessionsEvidence-based treatmentsQuality of lifeSelf-help manualHealth care systemIVR monitoringNonpharmacologic interventionsSecondary outcomesStandard therapy(365) Longitudinal trajectories of pain intensity in veterans with low back pain
Buta E, Heapy A, Goulet J. (365) Longitudinal trajectories of pain intensity in veterans with low back pain. Journal Of Pain 2017, 18: s66. DOI: 10.1016/j.jpain.2017.02.339.Peer-Reviewed Original Research
2016
(208) The relationship among BMI, pain intensity, and musculoskeletal diagnoses
Higgins D, Buta E, Heapy A, Driscoll M, Kerns R, Masheb R, Becker W, Burgess D, Hausmann L, Bair M, Justice A, Wandner L, Krein S, Brandt C, Goulet J. (208) The relationship among BMI, pain intensity, and musculoskeletal diagnoses. Journal Of Pain 2016, 17: s28. DOI: 10.1016/j.jpain.2016.01.112.Peer-Reviewed Original Research(115) Demographic, psychological, and clinical predictors of Roland Morris Disability Questionnaire score among patients with chronic low back pain
Heapy A, LaChappelle K, Higgins D, Buta E, Driscoll M, Kerns R. (115) Demographic, psychological, and clinical predictors of Roland Morris Disability Questionnaire score among patients with chronic low back pain. Journal Of Pain 2016, 17: s4-s5. DOI: 10.1016/j.jpain.2016.01.018.Peer-Reviewed Original ResearchA modified classification tree method for personalized medicine decisions.
Tsai WM, Zhang H, Buta E, O'Malley S, Gueorguieva R. A modified classification tree method for personalized medicine decisions. Statistics And Its Interface 2016, 9: 239-253. PMID: 26770292, PMCID: PMC4707681, DOI: 10.4310/sii.2016.v9.n2.a11.Peer-Reviewed Original Research