scholarly journals Differences in Sociodemographic and Alcohol‐Related Clinical Characteristics Between Treatment Seekers and Nontreatment Seekers and Their Role in Predicting Outcomes in the COMBINE Study for Alcohol Use Disorder

2020 ◽  
Vol 44 (10) ◽  
pp. 2097-2108
Author(s):  
Carolina L. Haass‐Koffler ◽  
Daria Piacentino ◽  
Xiaobai Li ◽  
Victoria M. Long ◽  
Mary R. Lee ◽  
...  
2018 ◽  
Author(s):  
Babak Tofighi ◽  
Joshua Lee ◽  
Scott Sherman ◽  
Daniel Schatz ◽  
Omar El-Shahawy

BACKGROUND Smoking remains a major public health burden among persons with opioid and/or alcohol use disorder yet preferences for technology assisted smoking cessation strategies remain largely unknown among this population. OBJECTIVE Assess smoking patterns and preferences for adopting technology-based interventions targeting smoking among individuals with opioid and/or alcohol use disorder. METHODS A 48-item semi-structured survey was conducted among inpatient detoxification program patients eliciting demographic and clinical characteristics, smoking profile, technology use patterns, and preferences for adopting technology-based smoking cessation interventions. Multivariate logistic regression models further evaluated the association between participant demographic and clinical characteristics and technology preferences. RESULTS Participants were mostly male (91%), unemployed or dependent on public assistance (68%), and admitted for detoxification for alcohol (47%), heroin (31%), or both alcohol and heroin (22%). Past 30-day smoking was reported by 78% of the sample, and 60% reported at least one quit attempt in the past year. Mobile phone ownership was common (89%); with an average past-year turnover of 4 mobile phones and 3 phone numbers. Computer ownership was low (28%) and one third reported daily internet use (34%). Telephone (41%) and text message-based interventions (40%) were the most popular technology-based intervention to facilitate smoking cessation. CONCLUSIONS Despite concurrent AUD-OUD, most had attempted to quit smoking in the last year and preferred telephone- and text message-based interventions to facilitate smoking cessation. However, high turnover of mobile phones, phone numbers, and limited access to computers pose barriers to dissemination of technology-based smoking cessation interventions in this vulnerable population. CLINICALTRIAL K23DA042140-01A1


2017 ◽  
Vol 53 (3) ◽  
pp. 235-240 ◽  
Author(s):  
Emily E Hartwell ◽  
Lara A Ray

2018 ◽  
Author(s):  
Babak Tofighi ◽  
Joshua D. Lee ◽  
Scott Sherman ◽  
Daniel Schatz ◽  
Omar El-Shahawy

BACKGROUND Smoking remains a major public health burden among persons with opioid and/or alcohol use disorder yet preferences for technology assisted smoking cessation strategies remain largely unknown among this population. OBJECTIVE Assess smoking patterns and preferences for adopting technology-based interventions targeting smoking among individuals with opioid and/or alcohol use disorder. METHODS A 49-item semi-structured survey was conducted in 2015 among urban, inpatient detoxification program patients eliciting demographic and clinical characteristics, smoking profile, technology use patterns, and preferences for adopting technology-based smoking cessation interventions. Multivariate logistic regression models further evaluated the association between participant demographic and clinical characteristics and technology preferences. RESULTS Participants were mostly male (91%), unemployed or dependent on public assistance (68%), and admitted for detoxification for alcohol (47%), heroin (31%), or both alcohol and heroin (22%). Past 30-day smoking was reported by 78% of the sample, and 60% reported at least one quit attempt in the past year. Mobile phone ownership was common (89%); with an average past-year turnover of 4 mobile phones and 3 phone numbers. Computer ownership was low (28%) and one third reported daily internet use (34%). Telephone (41%) and text message-based interventions (40%) were the most popular technology-based intervention to facilitate smoking cessation. CONCLUSIONS Despite concurrent AUD-OUD, most respondents had attempted to quit smoking in the last year and preferred telephone- and text message-based interventions to facilitate smoking cessation. However, high turnover of mobile phones, phone numbers, and limited access to computers pose barriers to dissemination of technology-based smoking cessation interventions in this vulnerable population.


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