Smoking patterns and preferences for technology assisted smoking cessation interventions among adults with opioid and alcohol use disorders (Preprint)

Smoking patterns and preferences for technology assisted smoking cessation interventions among adults with opioid and alcohol use disorders

Journal of Substance Use ◽

10.1080/14659891.2019.1642407 ◽

2019 ◽

Vol 24 (6) ◽

pp. 660-665

Author(s):

Babak Tofighi ◽

Joshua D. Lee ◽

Scott Sherman ◽

Daniel Schatz ◽

Omar El-Shahawy

Keyword(s):

Smoking Cessation ◽

Alcohol Use ◽

Alcohol Use Disorders ◽

Smoking Patterns

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Smoking patterns and preferences for technology assisted smoking cessation interventions among adults with opioid and alcohol use disorders (Preprint)

10.2196/preprints.11422 ◽

2018 ◽

Author(s):

Babak Tofighi ◽

Joshua Lee ◽

Scott Sherman ◽

Daniel Schatz ◽

Omar El-Shahawy

Keyword(s):

Smoking Cessation ◽

Alcohol Use ◽

Mobile Phones ◽

Technology Use ◽

Clinical Characteristics ◽

Alcohol Use Disorder ◽

Text Message ◽

High Turnover ◽

Public Health Burden ◽

Smoking Patterns

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

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Smoking patterns and preferences for technology assisted smoking cessation interventions among adults with opioid and alcohol use disorders (Preprint)

10.2196/preprints.12903 ◽

2018 ◽

Author(s):

Babak Tofighi ◽

Joshua D. Lee ◽

Scott Sherman ◽

Daniel Schatz ◽

Omar El-Shahawy

Keyword(s):

Smoking Cessation ◽

Alcohol Use ◽

Mobile Phones ◽

Technology Use ◽

Clinical Characteristics ◽

Alcohol Use Disorder ◽

Text Message ◽

High Turnover ◽

Public Health Burden ◽

Smoking Patterns

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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