↓ Skip to main content

An integrated digital/clinical approach to smoking cessation in lung cancer screening: study protocol for a randomized controlled trial

Overview of attention for article published in Trials, November 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
254 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
An integrated digital/clinical approach to smoking cessation in lung cancer screening: study protocol for a randomized controlled trial
Published in
Trials, November 2017
DOI 10.1186/s13063-017-2312-x
Pubmed ID
Authors

Amanda L. Graham, Michael V. Burke, Megan A. Jacobs, Sarah Cha, Ivana T. Croghan, Darrell R. Schroeder, James P. Moriarty, Bijan J. Borah, Donna F. Rasmussen, M. Jody Brookover, Dale B. Suesse, David E. Midthun, J. Taylor Hays

Abstract

Delivering effective tobacco dependence treatment that is feasible within lung cancer screening (LCS) programs is crucial for realizing the health benefits and cost savings of screening. Large-scale trials and systematic reviews have demonstrated that digital cessation interventions (i.e. web-based and text message) are effective, sustainable over the long-term, scalable, and cost-efficient. Use of digital technologies is commonplace among older adults, making this a feasible approach within LCS programs. Use of cessation treatment has been improved with models that proactively connect smokers to treatment rather than passive referrals. Proactive referral to cessation treatment has been advanced through healthcare systems changes such as modifying the electronic health record to automatically link smokers to treatment. This study evaluates the impact of a proactive enrollment strategy that links LCS-eligible smokers with an evidence-based intervention comprised of a web-based (WEB) program and integrated text messaging (TXT) in a three-arm randomized trial with repeated measures at one, three, six, and 12 months post randomization. The primary outcome is biochemically confirmed abstinence at 12 months post randomization. We will randomize 1650 smokers who present for a clinical LCS to: (1) a usual care control condition (UC) which consists of Ask-Advise-Refer; (2) a digital (WEB + TXT) cessation intervention; or (3) a digital cessation intervention combined with tobacco treatment specialist (TTS) counseling (WEB + TXT + TTS). The scalability and sustainability of a digital intervention may represent the most cost-effective and feasible approach for LCS programs to proactively engage large numbers of smokers in effective cessation treatment. We will also evaluate the impact and cost-effectiveness of adding proven clinical intervention provided by a TTS. We expect that a combined digital/clinical intervention will yield higher quit rates than digital alone, but that it may not be as cost-effective or feasible for LCS programs to implement. This study is innovative in its use of interoperable, digital technologies to deliver a sustainable, scalable, high-impact cessation intervention and to facilitate its integration within clinical practice. It will add to the growing knowledge base about the overall effectiveness of digital interventions and their role in the healthcare delivery system. ClinicalTrials.gov, NCT03084835 . Registered on 9 March 2017.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 254 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 254 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 32 13%
Researcher 28 11%
Student > Bachelor 27 11%
Student > Ph. D. Student 18 7%
Other 13 5%
Other 43 17%
Unknown 93 37%
Readers by discipline Count As %
Medicine and Dentistry 54 21%
Nursing and Health Professions 38 15%
Psychology 15 6%
Engineering 7 3%
Social Sciences 6 2%
Other 32 13%
Unknown 102 40%