2024
Stepped Care for Patients to Optimize Whole Recovery (SC-POWR): An Effectiveness Trial Evaluating a Stepped Care Model for Individuals With Opioid Use Disorder and Chronic Pain.
Rossi R, Cutter C, Beitel M, Covelli M, Fiellin D, Kerns R, Vassilieva S, Olabisi D, Barry D. Stepped Care for Patients to Optimize Whole Recovery (SC-POWR): An Effectiveness Trial Evaluating a Stepped Care Model for Individuals With Opioid Use Disorder and Chronic Pain. Substance Use & Addiction Journal 2024, 29767342241245095. PMID: 38606900, PMCID: PMC11470109, DOI: 10.1177/29767342241245095.Peer-Reviewed Original ResearchTreatment-as-usualOpioid use disorderChronic painCognitive behavioral therapyStepped careNonmedical opioid useEffectiveness trialOpioid useAlcohol useSession of exerciseStepped care modelWeekly group sessionsPain-related outcomesStress reductionDecreased pain intensityUse disorderNational Institutes of HealthOpioid use disorder treatmentCare modelInstitutes of HealthAssociated with higher levelsPain intensityPilot study of patientsPain improvementDurability of treatment response
2022
Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools
Piette JD, Newman S, Krein SL, Marinec N, Chen J, Williams DA, Edmond SN, Driscoll M, LaChappelle KM, Kerns RD, Maly M, Kim HM, Farris KB, Higgins DM, Buta E, Heapy AA. Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools. JAMA Internal Medicine 2022, 182: 975-983. PMID: 35939288, PMCID: PMC9361183, DOI: 10.1001/jamainternmed.2022.3178.Peer-Reviewed Original ResearchConceptsCBT-CPComparative effectiveness trialTherapist timeSecondary outcomesMore patientsEffectiveness trialInteractive voice responseCP groupMeaningful improvementsPatient-centered pain careRoland-Morris Disability QuestionnaireVeterans Affairs Health SystemMorris Disability QuestionnairePain intensity scoresChronic back painLess therapist timeMobile health toolsCognitive behavioral therapyRandomized noninferiorityDisability QuestionnaireNoninferiority criteriaOpioid analgesicsPain intensityPain therapyPrimary outcomeArtificial Intelligence (AI) to improve chronic pain care: Evidence of AI learning
Piette J, Newman S, Krein S, Marinec N, Chen J, Williams D, Edmond S, Driscoll M, LaChappelle K, Maly M, Kim H, Farris K, Higgins D, Kerns R, Heapy A. Artificial Intelligence (AI) to improve chronic pain care: Evidence of AI learning. Intelligence-Based Medicine 2022, 6: 100064. DOI: 10.1016/j.ibmed.2022.100064.Peer-Reviewed Original ResearchPatient interactionsPatient subgroupsInteractive voice response callsPain-related interferenceComparative effectiveness trialChronic pain careCourse of therapyPedometer step countsDisease management programsCognitive behavioral therapyCBT-CPChronic painMore patientsPain careTreatment modalitiesTreatment recommendationsEffectiveness trialPatientsStep countBehavioral therapyClinician timeWeeksTherapy sessionsMethods DataTherapist feedback
2021
Pain and smoking study (PASS): A comparative effectiveness trial of smoking cessation counseling for veterans with chronic pain
Bastian LA, Driscoll M, DeRycke E, Edmond S, Mattocks K, Goulet J, Kerns RD, Lawless M, Quon C, Selander K, Snow J, Casares J, Lee M, Brandt C, Ditre J, Becker W. Pain and smoking study (PASS): A comparative effectiveness trial of smoking cessation counseling for veterans with chronic pain. Contemporary Clinical Trials Communications 2021, 23: 100839. PMID: 34485755, PMCID: PMC8391053, DOI: 10.1016/j.conctc.2021.100839.Peer-Reviewed Original ResearchCognitive-behavioral interventionsBehavioral interventionsAdaptive coping strategiesPain-related anxietyChronic painSmoking studiesGreater pain intensityCoping strategiesMotivational interviewingSmoking cessationPain-related functional interferenceTelephone counseling interventionCounseling interventionNicotine replacement therapyMental health comorbiditiesComparative effectiveness trialRandomized clinical trialsParticipantsEffectiveness trialRelapse managementVeteransCessation counselingBaseline characteristicsHealth comorbiditiesMedian age