2024
Evaluating differences in receipt of survivorship care plan among cancer survivors with and without disabilities
Sarkar S, Zaidi M, Raziani Y, Poghosyan H. Evaluating differences in receipt of survivorship care plan among cancer survivors with and without disabilities. Supportive Care In Cancer 2024, 32: 637. PMID: 39235704, DOI: 10.1007/s00520-024-08796-6.Peer-Reviewed Original ResearchConceptsSurvivorship care plan receiptSurvivorship care plansDisability countCancer survivorsCare planningReceipt of survivorship care plansMethodsWe analyzed cross-sectional dataBehavioral Risk Factor Surveillance SystemFollow-up care instructionsRisk Factor Surveillance SystemSelf-reported cancer historyTreatment adherenceSelf-care difficultiesMultinomial multivariable logistic regressionIndependent living difficultiesPromote treatment adherenceMultivariate logistic regressionCancer survivorshipCross-sectional dataTreatment summarySelf-careCancer historyNo disabilityLiving difficultiesResultsThe sampleAssociation between adverse childhood experiences and self-reported health-risk behaviors among cancer survivors: A population-based study
Sarkar S, Jackson B, Manzo L, Jeon S, Poghosyan H. Association between adverse childhood experiences and self-reported health-risk behaviors among cancer survivors: A population-based study. PLOS ONE 2024, 19: e0299918. PMID: 38512934, PMCID: PMC10956880, DOI: 10.1371/journal.pone.0299918.Peer-Reviewed Original ResearchConceptsHealth risk behaviorsSelf-reported health risk behaviorsAdverse childhood experiencesHistory of adverse childhood experiencesOdds of reportingCancer survivorsE-cigarette useIncreased odds of reportingReport adverse childhood experiencesPrevalence of adverse childhood experiencesSelf-reportAlcohol drinkingHigher odds of reportingAdult cancer survivorsE-cigarettesSurvivor self-reportPrevent health risk behaviorsAdverse childhood experience historyChildhood experiencesAssociated with health risk behaviorsCigarette smokingHistory of cancerPopulation-based studyPrimary independent variableMultivariate logistic regression
2023
Investigating Racial and Ethnic Differences in Diabetes Self-Management Education Among Adults With Diabetes
Akyirem S, Choa E, Poghosyan H. Investigating Racial and Ethnic Differences in Diabetes Self-Management Education Among Adults With Diabetes. The Science Of Diabetes Self-Management And Care 2023, 49: 206-216. PMID: 37129292, DOI: 10.1177/26350106231169693.Peer-Reviewed Original ResearchConceptsDiabetes self-management educationDiabetes self-management education participantsSelf-management educationNon-Hispanic blacksNon-Hispanic whitesSocial determinants of health factorsEthnic differencesReduce health disparitiesImprove diabetes outcomesSelf-reported diabetesWeighted descriptive statisticsLower-level educationMultivariate logistic regressionCross-sectional dataHealth disparitiesDiabetes careDiabetes outcomesDiabetes ModuleHealth factorsPopulation-basedHispanic participantsReport participationDescriptive statisticsHispanic populationLogistic regressionThe role of financial security in loneliness or sadness among Medicare-enrolled cancer survivors during the COVID-19 pandemic
Sarkar S, Arakelyan S, Choa E, Poghosyan H. The role of financial security in loneliness or sadness among Medicare-enrolled cancer survivors during the COVID-19 pandemic. Journal Of Geriatric Oncology 2023, 14: 101507. PMID: 37216846, PMCID: PMC10123351, DOI: 10.1016/j.jgo.2023.101507.Peer-Reviewed Original ResearchMeSH KeywordsAgedCancer SurvivorsCOVID-19Cross-Sectional StudiesHumansLonelinessMedicareNeoplasmsPandemicsSadnessUnited StatesConceptsFeelings of lonelinessCancer survivorsSurge of COVID-19Increased feelings of lonelinessCancer historyMedicare beneficiariesSelf-reported cancer historyIncreasing rates of lonelinessWinter surgeIncreased feelingsRates of lonelinessCOVID-19 pandemicCross-sectional dataMultivariate logistic regression analysisLogistic regression analysisPopulation-basedFinancial securityCOVID-19MedicareSocioeconomic vulnerabilityLonelinessStudy cohortSurvivorsRegression analysisCross-tabulation analysis
2022
COVID-19 Vaccine Hesitancy Among Medicare Beneficiaries with and Without Cancer History: A US Population-based Study
Poghosyan H, Ni Z, Vlahov D, Nelson L, Nam S. COVID-19 Vaccine Hesitancy Among Medicare Beneficiaries with and Without Cancer History: A US Population-based Study. Journal Of Community Health 2022, 48: 315-324. PMID: 36427111, PMCID: PMC9702715, DOI: 10.1007/s10900-022-01174-5.Peer-Reviewed Original ResearchMeSH KeywordsAgedCOVID-19COVID-19 VaccinesCross-Sectional StudiesHumansMedicareNeoplasmsUnited StatesVaccinationConceptsCOVID-19 vaccineCOVID-19 vaccine hesitancyCancer historyVaccine hesitancyMedicare beneficiariesVaccine uptakeMultivariable logistic regression modelCOVID-19 vaccine uptakeVaccine hesitancy ratesOngoing health conditionsCOVID-19 vaccinationLogistic regression modelsComplex survey designLack of recommendationsHesitancy ratesVaccine benefitsCommon reasonHesitant individualsSide effectsUS populationVaccineHealth conditionsCross-sectional dataHesitancyRegression modelsAssociation between social connectedness and stress or anxiety among older cancer survivors during the 2020–2021 winter surge of the COVID-19 pandemic
Poghosyan H, Margaryan Y, Jeon S, Edelman EJ, Yu JB. Association between social connectedness and stress or anxiety among older cancer survivors during the 2020–2021 winter surge of the COVID-19 pandemic. Journal Of Geriatric Oncology 2022, 14: 101390. PMID: 36274031, PMCID: PMC9554341, DOI: 10.1016/j.jgo.2022.10.005.Peer-Reviewed Original ResearchRacial and Ethnic Variation in COVID-19 Vaccination Uptake Among Medicare Beneficiaries with Cancer History
Poghosyan H, Dinan MA, Tamamyan G, Nelson L, Jeon S. Racial and Ethnic Variation in COVID-19 Vaccination Uptake Among Medicare Beneficiaries with Cancer History. Journal Of Racial And Ethnic Health Disparities 2022, 10: 2354-2362. PMID: 36149576, PMCID: PMC9510246, DOI: 10.1007/s40615-022-01415-2.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedCOVID-19COVID-19 VaccinesCross-Sectional StudiesHumansMedicareNeoplasmsUnited StatesVaccinationConceptsNon-Hispanic white beneficiariesCancer historyVaccine doseMedicare beneficiariesWhite beneficiariesVaccine uptakeHispanic beneficiariesMultivariable logistic regression analysisCOVID-19 vaccination uptakeSelf-reported cancer historyCOVID-19 vaccine uptakeSelf-reported receiptCOVID-19 vaccination ratesLogistic regression analysisNon-Hispanic blacksSelf-reported raceUnvaccinated beneficiariesVaccination uptakeVaccine dosesVaccination ratesVaccine confidenceVaccine availabilitySupplement surveyCross-sectional dataEthnic variation
2021
Association between daily and non-daily cannabis use and depression among United States adult cancer survivors
Poghosyan H, Noonan E, Badri P, Braun I, Young G. Association between daily and non-daily cannabis use and depression among United States adult cancer survivors. Nursing Outlook 2021, 69: 672-685. PMID: 33581859, DOI: 10.1016/j.outlook.2021.01.012.Peer-Reviewed Original ResearchConceptsCancer survivorsBehavioral Risk Factor Surveillance System surveyIncreased odds of depressionAdult cancer survivorsOdds of depressionCannabis useWeighted descriptive statisticsEvidence-informed discussionsSelf-reported depressionNationally representative sampleMultivariate logistic regressionPopulation-basedSystem surveyIncreased oddsDescriptive statisticsRepresentative sampleOpen communicationLogistic regressionIncreased riskNone-usersSurvivorsDepressionPrevalenceCancerAssociationDifferences in Uptake of Low-Dose CT Scan for Lung Cancer among White and Black Adult Smokers in the United States-2017.
Poghosyan H, Fortin D, Moen E, Quigley K, Young G. Differences in Uptake of Low-Dose CT Scan for Lung Cancer among White and Black Adult Smokers in the United States-2017. Journal Of Health Care For The Poor And Underserved 2021, 32: 165-178. PMID: 33678689, DOI: 10.1353/hpu.2021.0016.Peer-Reviewed Original ResearchMeSH KeywordsAdultBlack or African AmericanCross-Sectional StudiesEarly Detection of CancerFemaleHumansLung NeoplasmsMaleSmokersTomography, X-Ray ComputedUnited StatesConceptsLow-dose computerized tomographyLDCT scansLung Cancer Screening ModuleBehavioral Risk Factor Surveillance SystemAdult smokersRisk Factor Surveillance SystemStudy racial/ethnic differencesPack-year smoking historyMultivariate logistic regressionCross-sectional dataHigh blood pressureLung cancerCancer historyRacial/ethnic differencesLow-dose CT scansPack-yearsHealth insuranceLogistic regressionRacial differencesSurveillance systemScreening moduleSmoking historyCT scanOddsLung disease
2020
Worry About the Future Health Issues of Smoking and Intention to Screen for Lung Cancer With Low-Dose Computed Tomography
Poghosyan H, Mello S, Robinson K, Tan A. Worry About the Future Health Issues of Smoking and Intention to Screen for Lung Cancer With Low-Dose Computed Tomography. Cancer Nursing 2020, 45: e146-e152. PMID: 34870941, PMCID: PMC8649175, DOI: 10.1097/ncc.0000000000000897.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedCross-Sectional StudiesEarly Detection of CancerFemaleHumansIntentionLung NeoplasmsMiddle AgedSmokingTomography, X-Ray ComputedConceptsIssue of smokingLung cancer screeningLow-dose computed tomographyRecommending lung cancer screeningHealth issuesBenefits of lung cancer screeningRates of lung cancer screeningCross-sectional online surveyFuture health issuesLung cancerMultivariate logistic regressionCancer screeningHealthcare providersSocioeconomic differencesEligible adultsComputed tomographyAdult smokersLogistic regressionExpressed worriesSmokingHealthLong-term prognosisSmoking historyDiagnosis of lung cancerModerately/veryMarijuana use among cancer survivors: Quantifying prevalence and identifying predictors
Poghosyan H, Poghosyan A. Marijuana use among cancer survivors: Quantifying prevalence and identifying predictors. Addictive Behaviors 2020, 112: 106634. PMID: 32920457, DOI: 10.1016/j.addbeh.2020.106634.Peer-Reviewed Original ResearchMeSH KeywordsAdultCancer SurvivorsCross-Sectional StudiesFemaleHumansMaleMarijuana SmokingMarijuana UseNeoplasmsPrevalenceUnited StatesConceptsBehavioral Risk Factor Surveillance System surveyPrevalence of current marijuana useCancer survivorsCurrent marijuana useAdult cancer survivorsNon-Hispanic blacksComplex survey designWeighted prevalence estimatesMarijuana useMultivariate logistic regressionFair/poor healthCross-sectional dataIndividual-level predictorsNon-HispanicPrevalence of marijuana useSystem surveyRacial/ethnic groupsQuantify prevalencePrevalence estimatesIndividual-levelLogistic regressionTobacco smokersSurvey designU.S. statesHighest prevalence
2019
Food insecure cancer survivors continue to smoke after their diagnosis despite not having enough to eat: implications for policy and clinical interventions
Poghosyan H, Scarpino S. Food insecure cancer survivors continue to smoke after their diagnosis despite not having enough to eat: implications for policy and clinical interventions. Cancer Causes & Control 2019, 30: 241-248. PMID: 30729359, DOI: 10.1007/s10552-019-01137-7.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedCancer SurvivorsCross-Sectional StudiesFemaleFood SupplyHumansLogistic ModelsMaleMiddle AgedOdds RatioSmokingSmoking CessationYoung AdultConceptsCancer survivorsAssociated with smoking statusSmoking statusFood insecurityBehavioral Risk Factor Surveillance SystemRisk Factor Surveillance SystemFood insecurity screeningAdult cancer survivorsWeighted multivariable logistic regression modelsSocial Context ModuleSmoking cessation interventionsConfidence intervalsMultivariate logistic regression modelCross-sectional studyProgression of careIndividual-level characteristicsLogistic regression modelsCessation interventionsConclusionsFood insecurityQuit smokingQuit attemptsOdds ratioSmoking behaviorIndividual-levelOutcome variables
2018
Social and Structural Determinants of Smoking Status and Quit Attempts Among Adults Living in 12 US States, 2015
Poghosyan H, Moen E, Kim D, Manjourides J, Cooley M. Social and Structural Determinants of Smoking Status and Quit Attempts Among Adults Living in 12 US States, 2015. American Journal Of Health Promotion 2018, 33: 498-506. PMID: 30071738, DOI: 10.1177/0890117118792827.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsAgedBehavioral Risk Factor Surveillance SystemCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedMultivariate AnalysisPsychologyRisk FactorsSex FactorsSmokingSmoking CessationSocial Determinants of HealthSocioeconomic FactorsUnited StatesYoung AdultConceptsBehavioral Risk Factor Surveillance SystemQuit attemptsSmoking statusIntermediary determinantsMental distressSecondary data analysis of cross-sectional dataHousing insecurityRisk Factor Surveillance SystemAnalysis of cross-sectional dataFrequent mental distressAdult smoking statusSmoking cessation interventionsSocial Context ModuleNon-Hispanic blacksRacially diverse adultsSmoking cessation ratesDetermination of smoking statusSecondary data analysisEnhance smoking cessation ratesHazardous alcohol useUS statesMultinomial logistic regressionCross-sectional dataCessation interventionsCurrent smoking
2016
The association between social support and smoking status in cancer survivors with frequent and infrequent mental distress: results from 10 US states, 2010
Poghosyan H, Darwish S, Kim S, Cooley M. The association between social support and smoking status in cancer survivors with frequent and infrequent mental distress: results from 10 US states, 2010. Journal Of Cancer Survivorship 2016, 10: 1078-1088. PMID: 27236586, DOI: 10.1007/s11764-016-0551-6.Peer-Reviewed Original ResearchMeSH KeywordsAgedCross-Sectional StudiesFemaleHistory, 21st CenturyHumansMaleMental HealthNeoplasmsSmokingSocial SupportSurvivorsConceptsFrequent mental distressLevels of social supportLow levels of social supportCancer survivorsMental distressSocial supportBehavioral Risk Factor Surveillance SystemSmoking statusIntensive smoking cessation interventionRisk Factor Surveillance SystemHigher levels of social supportCancer survivorship moduleAdult cancer survivorsSmoking cessation interventionsMethodsCross-sectional dataHealth care professionalsNon-Hispanic blacksNon-Hispanic whitesMental health differencesReceiving social supportUS statesCessation interventionsHealth differencesCare professionalsNever smokers
2015
Nurse practitioners as primary care providers
Poghosyan L, Shang J, Liu J, Poghosyan H, Liu N, Berkowitz B. Nurse practitioners as primary care providers. Health Care Management Review 2015, 40: 46-55. PMID: 24727678, DOI: 10.1097/hmr.0000000000000010.Peer-Reviewed Original ResearchMeSH KeywordsCross-Sectional StudiesData CollectionFemaleHumansMaleMassachusettsMiddle AgedNew YorkNurse PractitionersOrganizational CulturePrimary Health CareWorkforceConceptsNP practice environmentNurse practitionersPractice environmentNew York StateNurse Practitioner Primary Care Organizational Climate QuestionnaireHospital-affiliated practicesNP-administration relationsNP-physician relationsPoor practice environmentsPrimary care providersCommunity health centersPrimary care settingCross-sectional survey designHealth care organizationsCost-effective careOrganizational Climate QuestionnaireNP rolePrimary careCare providersCare settingsHealth professionalsCare organizationsHealth centersPhysician's officeNurses
2014
The association between having a first-degree family history of cancer and smoking status
Poghosyan H, Bell J, Joseph J, Cooley M. The association between having a first-degree family history of cancer and smoking status. Preventive Medicine 2014, 66: 12-16. PMID: 24875232, DOI: 10.1016/j.ypmed.2014.05.013.Peer-Reviewed Original ResearchConceptsFirst-degree family history of cancerFamily history of cancerFirst-degree family historyHistory of cancerCalifornia Health Interview SurveyHealth-promoting behaviorsHealth Interview SurveyPoor health outcomesSmoking cessation interventionsNon-institutionalized adultsPopulation-based dataDiagnosis of cancerCross-sectional dataCessation interventionsHealth outcomesInterview SurveyFormer smokersCurrent-smokersSmoking statusNever-smokersTarget populationSurvey designSmokingSample weightDiverse sample