Evidence map›Paper›PMID 32238338›Full record

ArticleJournal of medical Internet research2020

Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment.

Amanda L Graham, George D Papandonatos, Megan A Jacobs, Michael S Amato, Sarah Cha, Amy M Cohn, Lorien C Abroms, Robyn Whittaker

Erratum issued Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT02585206 (Optimizing Text Messaging to Improve Adherence to Web-Based Cessation Treatment), which is not on this map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02585206 nacompletednot on this map

Optimizing Text Messaging to Improve Adherence to Web-Based Cessation Treatment

TypeinterventionalSponsorTruth InitiativeRan2018 to 2020Enrolled1,485ConditionsSmoking CessationArmsPersonalization, Integration, Dynamic Tailoring, Message Intensity, Optimal-Adherence Text
3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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  14. Barriers to Building More Effective Treatments: Negative Interactions Amongst Smoking Intervention Components.Clinical psychological science : a journal of the Association for Psychological Science · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Amanda L GrahamInnovations Center, Truth Initiative, Washington, DC, United States.ORCID 0000-0003-3036-9653
George D PapandonatosCenter for Statistical Sciences, Brown University, Providence, RI, United States.ORCID 0000-0001-6770-932X
Megan A JacobsInnovations Center, Truth Initiative, Washington, DC, United States.ORCID 0000-0001-6526-964X
Michael S AmatoInnovations Center, Truth Initiative, Washington, DC, United States.ORCID 0000-0002-9769-957X
Sarah ChaInnovations Center, Truth Initiative, Washington, DC, United States.ORCID 0000-0003-3505-3164
Amy M CohnOklahoma Tobacco Research Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.ORCID 0000-0001-9034-4293
Lorien C AbromsDepartment of Prevention and Community Health, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States.ORCID 0000-0001-6859-283X
Robyn WhittakerNational Institute for Health Innovation, University of Auckland, Auckland, New Zealand.ORCID 0000-0003-0901-9149
American Legacy Foundation · USBrown University · USMilken Institute · USUniversity of Auckland · NZUniversity of Oklahoma Health Sciences Center · US

Funding

Optimizing Text Messaging to Improve Adherence to Web-Based Cessation TreatmentR01DA038139 · NIDA · TRUTH INITIATIVE FOUNDATION · PI GRAHAM, AMANDA L · 2015 to 2019
$2.8M
NIDA NIH HHS R01 DA038139
6 · The paper itself

Abstract

backgroundSmoking remains a leading cause of preventable death and illness. Internet interventions for smoking cessation have the potential to significantly impact public health, given their broad reach and proven effectiveness. Given the dose-response association between engagement and behavior change, identifying strategies to promote engagement is a priority across digital health interventions. Text messaging is a proven smoking cessation treatment modality and a powerful strategy to increase intervention engagement in other areas of health, but it has not been tested as an engagement strategy for a digital cessation intervention.

objectiveThis study examined the impact of 4 experimental text message design factors on adult smokers' engagement with an internet smoking cessation program.

methodsWe conducted a 2×2×2×2 full factorial screening experiment wherein 864 participants were randomized to 1 of 16 experimental conditions after registering with a free internet smoking cessation program and enrolling in its automated text message program. Experimental factors were personalization (on/off), integration between the web and text message platforms (on/off), dynamic tailoring of intervention content based on user engagement (on/off), and message intensity (tapered vs abrupt drop-off). Primary outcomes were 3-month measures of engagement (ie, page views, time on site, and return visits to the website) as well as use of 6 interactive features of the internet program. All metrics were automatically tracked; there were no missing data.

resultsMain effects were detected for integration and dynamic tailoring. Integration significantly increased interactive feature use by participants, whereas dynamic tailoring increased the number of features used and page views. No main effects were found for message intensity or personalization alone, although several synergistic interactions with other experimental features were observed. Synergistic effects, when all experimental factors were active, resulted in the highest rates of interactive feature use and the greatest proportion of participants at high levels of engagement. Measured in terms of standardized mean differences (SMDs), effects on interactive feature use were highest for Build Support System (SMD 0.56; 95% CI 0.27 to 0.81), Choose Quit Smoking Aid (SMD 0.38; 95% CI 0.10 to 0.66), and Track Smoking Triggers (SMD 0.33; 95% CI 0.05 to 0.61). Among the engagement metrics, the largest effects were on overall feature utilization (SMD 0.33; 95% CI 0.06 to 0.59) and time on site (SMD 0.29; 95% CI 0.01 to 0.57). As no SMD >0.30 was observed for main effects on any outcome, results suggest that for some outcomes, the combined intervention was stronger than individual factors alone.

conclusionsThis factorial experiment demonstrates the effectiveness of text messaging as a strategy to increase engagement with an internet smoking cessation intervention, resulting in greater overall intervention dose and greater exposure to the core components of tobacco dependence treatment that can promote abstinence.

trial registrationClinicalTrials.gov NCT02585206; https://clinicaltrials.gov/ct2/show/NCT02585206. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2015-010687.

Indexed as

internetsmoking cessationtext messagingtobacco dependence

Identifiers

PMID32238338
PMCPMC7386536
OpenAlexW4210290286

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.