TY - JOUR
T1 - Technology Use Patterns among Patients Enrolled in Inpatient Detoxification Treatment
AU - Tofighi, Babak
AU - Leonard, Noelle
AU - Greco, Peter
AU - Hadavand, Aboozar
AU - Acosta, Michelle C.
AU - Lee, Joshua D.
N1 - Funding Information:
From the NYU College of Nursing (NL); NYU Department of Population Health (JDL, BT, PG); Johns Hopkins School of Public Health (AH); National Development and Research Institutes, Inc, New York, NY (MCA). Received for publication May 9, 2018; accepted October 8, 2018. BT and JDL made substantial contributions to conception and design; BT and PG were involved with the acquisition of data; and BT, MA, NL, and JDL contributed to the analysis and interpretation of data, and drafting the manuscript. This study was supported by the National Institute on Drug Abuse (K23DA042140-01A1) and the NIH National Center for Advancing Translational Sciences (UL1 TR001445). The authors have no conflicts of interest to disclose. Send correspondence to Babak Tofighi, MD, MSc, 227 E. 30th St. 7th floor, 10016 New York, NY. E-mail: babak.tofighi@nyumc.org Copyright © 2019 American Society of Addiction Medicine ISSN: 1932-0620/19/1304-0279 DOI: 10.1097/ADM.0000000000000494
Publisher Copyright:
© 2019 American Society of Addiction Medicine. Unauthorized reproduction of this article is prohibited.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Technology-based interventions offer a practical, low-cost, and scalable approach to optimize the treatment of substance use disorders (SUDs) and related comorbidities (HIV, hepatitis C infection). This study assessed technology use patterns (mobile phones, desktop computers, internet, social media) among adults enrolled in inpatient detoxification treatment.Methods:A 49-item, quantitative and qualitative semi-structured survey assessed for demographic characteristics, technology use patterns (ie, mobile phone, text messaging [TM], smart phone applications, desktop computer, internet, and social media use), privacy concerns, and barriers to technology use. We used multivariate logistic regression models to assess the association between respondent demographic and clinical characteristics and their routine use of technologies.Results:Two hundred and six participants completed the survey. Nearly all participants reported mobile phone ownership (86%). Popular mobile phone features included TM (96%), web-browsers (81%), and accessing social media (61%). There was high mobile phone (3.3±2.98) and phone number (2.6±2.36) turnover in the preceding 12 months. Nearly half described daily or weekly access to desktop computers (48%) and most reported internet access (67%). Increased smartphone ownership was associated with higher education status (P=0.022) and homeless respondents were less likely to report mobile phone ownership (P=0.010) compared to participants with any housing status (ie, own apartment, residing with friends, family, or in a halfway house). Internet search engines were used by some participants (39.4%, 71/180) to locate 12 step support group meetings (37%), inpatient detoxification programs (35%), short- or long-term rehabilitation programs (32%), and outpatient treatment programs (4%).Conclusions:Technology use patterns among this hard-to-reach sample of inpatient detoxification respondents suggest high rates of mobile phone ownership, TM use, and moderate use of technology to facilitate linkage to addiction treatment services.
AB - Technology-based interventions offer a practical, low-cost, and scalable approach to optimize the treatment of substance use disorders (SUDs) and related comorbidities (HIV, hepatitis C infection). This study assessed technology use patterns (mobile phones, desktop computers, internet, social media) among adults enrolled in inpatient detoxification treatment.Methods:A 49-item, quantitative and qualitative semi-structured survey assessed for demographic characteristics, technology use patterns (ie, mobile phone, text messaging [TM], smart phone applications, desktop computer, internet, and social media use), privacy concerns, and barriers to technology use. We used multivariate logistic regression models to assess the association between respondent demographic and clinical characteristics and their routine use of technologies.Results:Two hundred and six participants completed the survey. Nearly all participants reported mobile phone ownership (86%). Popular mobile phone features included TM (96%), web-browsers (81%), and accessing social media (61%). There was high mobile phone (3.3±2.98) and phone number (2.6±2.36) turnover in the preceding 12 months. Nearly half described daily or weekly access to desktop computers (48%) and most reported internet access (67%). Increased smartphone ownership was associated with higher education status (P=0.022) and homeless respondents were less likely to report mobile phone ownership (P=0.010) compared to participants with any housing status (ie, own apartment, residing with friends, family, or in a halfway house). Internet search engines were used by some participants (39.4%, 71/180) to locate 12 step support group meetings (37%), inpatient detoxification programs (35%), short- or long-term rehabilitation programs (32%), and outpatient treatment programs (4%).Conclusions:Technology use patterns among this hard-to-reach sample of inpatient detoxification respondents suggest high rates of mobile phone ownership, TM use, and moderate use of technology to facilitate linkage to addiction treatment services.
KW - mobile health
KW - substance use disorders
KW - technology-based interventions
UR - http://www.scopus.com/inward/record.url?scp=85066479525&partnerID=8YFLogxK
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U2 - 10.1097/ADM.0000000000000494
DO - 10.1097/ADM.0000000000000494
M3 - Article
C2 - 30589653
AN - SCOPUS:85066479525
VL - 13
SP - 279
EP - 286
JO - Journal of Addiction Medicine
JF - Journal of Addiction Medicine
SN - 1932-0620
IS - 4
ER -