CClinicalTrials.gg
CompletedNCT03786042Updated Sep 26, 2025Results posted

Trial on the Effect of E-cigarette Advertising on Cigarette Perceptions in Adolescents

An interventional study of E-cigarette ad exposure and non e-cigarette TV commercials in Attentional Bias, Smoking Cues and Positive Perceptions About Cigarette Smoking, sponsored by Trustees of Dartmouth College. Completed at 1 site in United States. Open to participants aged 14 Years to 17 Years. Per ClinicalTrials.gov, last updated 2025-09-26.

Sponsored by Trustees of Dartmouth College · Not applicable, Interventional, and Prevention

Phase
Not applicable
Study type
Interventional
Enrollment
139
Allocation
Randomized
Ages
14 Years to 17 Years
Sex
All
01

Study summary

This research aims to investigate how exposure to advertising for Electronic Nicotine Delivery Systems (commonly called e-cigarettes) may lead to combustible smoking initiation in adolescents.

Read the detailed description

[3/14/2020]: Study recruitment temporarily halted due to the COVID-19 pandemic

02

Conditions studied

  • Attentional Bias
  • Smoking Cues
  • Positive Perceptions About Cigarette Smoking
  • Social Norms
  • Smoking Susceptibility

Keywords

  • Positive Smoking expectancies
  • e-cigarette advertising
  • adolescents
03

In context

Lead sponsor

Trustees of Dartmouth College is the lead sponsor of 38 studies on the registry; 18 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
14 Years to 17 Years
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

-

Exclusion criteria

Exclusion Criteria:

  • Exclusion criteria will include inadequate English proficiency, and diagnosis of a learning or vision disorder.
05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Factorial assignment
Masking
Single (Participant)
Enrollment
139 participants (actual)

Study arms

  • Active comparator
    E-cigarette ad exposure

    Participants in the e-cigarette ad exposure condition will view e-cigarette ads on the computer screen while having their eye movements tracked

    Behavioral: E-cigarette ad exposure

  • Sham comparator
    non e-cigarette ad exposure

    Participants in the non e-cigarette ad exposure condition will view non e-cigarette ads on the computer screen while having their eye movements tracked

    Other: non e-cigarette TV commercials

Interventions

  • BehavioralE-cigarette ad exposure

    Participants view a series of e-cigarette TV commercials

  • Othernon e-cigarette TV commercials

    Participants view a series of non e-cigarette TV commercials

06

What researchers measure

Primary outcomes

  1. Implicit Positive Smoking Expectancies, Measured by the Implicit Association Test

    Scores are measured by recording the amount of time (milliseconds) it takes to categorize smoking-related words with positive (e.g., cool) and negative (e.g., cancer) words. Faster reaction times when categorizing smoking-related words with positive words is evidence of higher positive smoking expectancies.

    Time frame: within 5 minutes post intervention

  2. Amount of Time Spent Looking at Static Smoking Cues in E-cigarette Advertisements

    Eye-tracking will be used to measure the amount of time (milliseconds) spent looking at static smoking cues in screen shots taken from e-cigarette advertisements. The amount time spent looking at a smoking cue is a measure how much attention was given to the smoking cue. The longer the looking time, the greater amount of attention.

    Time frame: approximately 30 minutes post intervention

  3. Implicit Positive Vaping Expectancies, Measured by the Implicit Association Test

    Scores are measured by recording the amount of time (milliseconds) it takes to categorize vaping-related words with positive (e.g., cool) and negative (e.g., cancer) words. Faster reaction times when categorizing smoking-related words with positive words is evidence of higher positive smoking expectancies.

    Time frame: within 5 minutes post intervention

07

Results

Posted Sep 26, 2025

Participant flow

Participant flow — Overall Study
MilestoneE-cigarette ad ExposureNon E-cigarette ad Exposure
Started8641
Completed8641
Not completed00

Outcome measures

PrimaryImplicit Positive Smoking Expectancies, Measured by the Implicit Association Test

Scores are measured by recording the amount of time (milliseconds) it takes to categorize smoking-related words with positive (e.g., cool) and negative (e.g., cancer) words. Faster reaction times when categorizing smoking-related words with positive words is evidence of higher positive smoking expectancies.

Time frame:
within 5 minutes post intervention
Reported as:
Mean · milliseconds
Implicit Positive Smoking Expectancies, Measured by the Implicit Association Test
millisecondsE-cigarette ad ExposureNon E-cigarette ad Exposure
Implicit Positive Smoking Expectancies, Measured by the Implicit Association Test1072.96 ± 171.911029.87 ± 108.60
PrimaryAmount of Time Spent Looking at Static Smoking Cues in E-cigarette Advertisements

Eye-tracking will be used to measure the amount of time (milliseconds) spent looking at static smoking cues in screen shots taken from e-cigarette advertisements. The amount time spent looking at a smoking cue is a measure how much attention was given to the smoking cue. The longer the looking time, the greater amount of attention.

Time frame:
approximately 30 minutes post intervention
Reported as:
Mean · milliseconds
Amount of Time Spent Looking at Static Smoking Cues in E-cigarette Advertisements
millisecondsE-cigarette ad Exposure
Amount of Time Spent Looking at Static Smoking Cues in E-cigarette Advertisements972.34 ± 581.76
PrimaryImplicit Positive Vaping Expectancies, Measured by the Implicit Association Test

Scores are measured by recording the amount of time (milliseconds) it takes to categorize vaping-related words with positive (e.g., cool) and negative (e.g., cancer) words. Faster reaction times when categorizing smoking-related words with positive words is evidence of higher positive smoking expectancies.

Time frame:
within 5 minutes post intervention
Reported as:
Mean · milliseconds
Implicit Positive Vaping Expectancies, Measured by the Implicit Association Test
millisecondsE-cigarette ad ExposureNon E-cigarette ad Exposure
Implicit Positive Vaping Expectancies, Measured by the Implicit Association Test1001.37 ± 114.741029.86 ± 108.60

Adverse events

Collected over Adverse event data was not collected for this study.. Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
E-cigarette ad Exposure———
Non E-cigarette ad Exposure———

Baseline characteristics

Age, Categorical
Age, Categorical(Participants)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
<=18 years8641127
Between 18 and 65 years000
>=65 years000
Age, Continuous
Age, Continuous(years)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
Mean15.04 ± 1.0115.36 ± 1.2015.15 ± 1.08
Sex: Female, Male
Sex: Female, Male(Participants)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
Female432467
Male421658
Ethnicity (NIH/OMB)
Ethnicity (NIH/OMB)(Participants)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
Hispanic or Latino101
Not Hispanic or Latino8541126
Unknown or Not Reported000
Race (NIH/OMB)
Race (NIH/OMB)(Participants)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
American Indian or Alaska Native000
Asian606
Native Hawaiian or Other Pacific Islander000
Black or African American202
White7441115
More than one race000
Unknown or Not Reported404
Region of Enrollment
Region of Enrollment(Participants)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
United States8641127
Positive smoking expectancies
Positive smoking expectancies(units on a scale)E-cigarette ad ExposureNon E-cigarette ad ExposureTotal
Mean0.88 ± 1.330.68 ± 1.130.83 ± 1.30
08

Study locations

1 site
  • Dartmouth-Hithchock Medical Center
    Lebanon, New Hampshire 03756, United States
09

References and documents

Publications

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  • Soneji S, Pierce JP, Choi K, Portnoy DB, Margolis KA, Stanton CA, Moore RJ, Bansal-Travers M, Carusi C, Hyland A, Sargent J. Engagement With Online Tobacco Marketing and Associations With Tobacco Product Use Among U.S. Youth. J Adolesc Health. 2017 Jul;61(1):61-69. doi: 10.1016/j.jadohealth.2017.01.023. Epub 2017 Mar 28. PubMed 28363720 ↗
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  • Pokhrel P, Fagan P, Herzog TA, Chen Q, Muranaka N, Kehl L, Unger JB. E-cigarette advertising exposure and implicit attitudes among young adult non-smokers. Drug Alcohol Depend. 2016 Jun 1;163:134-40. doi: 10.1016/j.drugalcdep.2016.04.008. Epub 2016 Apr 25. PubMed 27125661 ↗
  • Nosek BA. Moderators of the relationship between implicit and explicit evaluation. J Exp Psychol Gen. 2005 Nov;134(4):565-84. doi: 10.1037/0096-3445.134.4.565. PubMed 16316292 ↗
  • Field, M. & Wiers, R. in Drug Abuse and Addiction in Medical Illness: Causes, Consequences and Treatment (eds. Verster, J. C., Brady, K., Galanter, M. & Conrod, P.) 35-45 (Springer New York, 2012).
  • Hanewinkel R, Sargent JD. Exposure to smoking in internationally distributed American movies and youth smoking in Germany: a cross-cultural cohort study. Pediatrics. 2008 Jan;121(1):e108-17. doi: 10.1542/peds.2007-1201. PubMed 18166530 ↗
  • Sargent JD, Beach ML, Dalton MA, Mott LA, Tickle JJ, Ahrens MB, Heatherton TF. Effect of seeing tobacco use in films on trying smoking among adolescents: cross sectional study. BMJ. 2001 Dec 15;323(7326):1394-7. doi: 10.1136/bmj.323.7326.1394. PubMed 11744562 ↗
  • Dalton MA, Sargent JD, Beach ML, Titus-Ernstoff L, Gibson JJ, Ahrens MB, Tickle JJ, Heatherton TF. Effect of viewing smoking in movies on adolescent smoking initiation: a cohort study. Lancet. 2003 Jul 26;362(9380):281-5. doi: 10.1016/S0140-6736(03)13970-0. PubMed 12892958 ↗
  • Distefan JM, Pierce JP, Gilpin EA. Do favorite movie stars influence adolescent smoking initiation? Am J Public Health. 2004 Jul;94(7):1239-44. doi: 10.2105/ajph.94.7.1239. PubMed 15226149 ↗
  • Jackson C, Brown JD, L'Engle KL. R-rated movies, bedroom televisions, and initiation of smoking by white and black adolescents. Arch Pediatr Adolesc Med. 2007 Mar;161(3):260-8. doi: 10.1001/archpedi.161.3.260. PubMed 17339507 ↗
  • Barnett TE, Soule EK, Forrest JR, Porter L, Tomar SL. Adolescent Electronic Cigarette Use: Associations With Conventional Cigarette and Hookah Smoking. Am J Prev Med. 2015 Aug;49(2):199-206. doi: 10.1016/j.amepre.2015.02.013. Epub 2015 Mar 31. PubMed 25840880 ↗
  • Wills TA, Knight R, Williams RJ, Pagano I, Sargent JD. Risk factors for exclusive e-cigarette use and dual e-cigarette use and tobacco use in adolescents. Pediatrics. 2015 Jan;135(1):e43-51. doi: 10.1542/peds.2014-0760. Epub 2014 Dec 15. PubMed 25511118 ↗
  • Lochbuehler K, Otten R, Voogd H, Engels RC. Parental smoking and children's attention to smoking cues. J Psychopharmacol. 2012 Jul;26(7):1010-6. doi: 10.1177/0269881112439254. Epub 2012 Feb 27. PubMed 22371194 ↗
  • Kersbergen I, Field M. Visual attention to alcohol cues and responsible drinking statements within alcohol advertisements and public health campaigns: Relationships with drinking intentions and alcohol consumption in the laboratory. Psychol Addict Behav. 2017 Jun;31(4):435-446. doi: 10.1037/adb0000284. Epub 2017 May 11. PubMed 28493753 ↗
  • Yoshida, E., Peach, J. M., Zanna, M. P. & Spencer, S. J. Not all automatic associations are created equal: How implicit normative evaluations are distinct from implicit attitudes and uniquely predict meaningful behavior. J Exp Soc Psychol 48, 694-706 (2012).
  • Andrews JA, Hampson SE, Greenwald AG, Gordon J, Widdop C. Using the Implicit Association Test to Assess Children's Implicit Attitudes toward Smoking. J Appl Soc Psychol. 2010 Sep;40(9):2387-2406. doi: 10.1111/j.1559-1816.2010.00663.x. PubMed 21566676 ↗
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  • Gilbert-Diamond D, Emond JA, Lansigan RK, Rapuano KM, Kelley WM, Heatherton TF, Sargent JD. Television food advertisement exposure and FTO rs9939609 genotype in relation to excess consumption in children. Int J Obes (Lond). 2017 Jan;41(1):23-29. doi: 10.1038/ijo.2016.163. Epub 2016 Sep 22. PubMed 27654143 ↗
  • Bernhardt AM, Wilking C, Gottlieb M, Emond J, Sargent JD. Children's reaction to depictions of healthy foods in fast-food television advertisements. JAMA Pediatr. 2014 May;168(5):422-6. doi: 10.1001/jamapediatrics.2014.140. PubMed 24686476 ↗
  • Gilbert, D. G. & Rabinovich, N. E. International smoking series (with neural counterparts) verion 1.2. (1999).
  • Macy JT, Chassin L, Presson CC, Yeung E. Exposure to graphic warning labels on cigarette packages: Effects on implicit and explicit attitudes towards smoking among young adults. Psychol Health. 2016;31(3):349-63. doi: 10.1080/08870446.2015.1104309. Epub 2015 Nov 3. PubMed 26442992 ↗
  • Wahl SK, Turner LR, Mermelstein RJ, Flay BR. Adolescents' smoking expectancies: psychometric properties and prediction of behavior change. Nicotine Tob Res. 2005 Aug;7(4):613-23. doi: 10.1080/14622200500185579. PubMed 16085531 ↗
  • Sargent JD, Worth KA, Beach M, Gerrard M, Heatherton TF. Population-Based Assessment of Exposure to Risk Behaviors in Motion Pictures. Commun Methods Meas. 2008 Jan;2(1-2):134-151. doi: 10.1080/19312450802063404. PubMed 19122801 ↗
  • Lochbuehler K, Voogd H, Scholte RH, Engels RC. Attentional bias in smokers: exposure to dynamic smoking cues in contemporary movies. J Psychopharmacol. 2011 Apr;25(4):514-9. doi: 10.1177/0269881110388325. Epub 2010 Nov 23. PubMed 21098549 ↗
  • Connor CE, Egeth HE, Yantis S. Visual attention: bottom-up versus top-down. Curr Biol. 2004 Oct 5;14(19):R850-2. doi: 10.1016/j.cub.2004.09.041. PubMed 15458666 ↗
  • Dalton MA, Sargent JD, Beach ML, Bernhardt AM, Stevens M. Positive and negative outcome expectations of smoking: implications for prevention. Prev Med. 1999 Dec;29(6 Pt 1):460-5. doi: 10.1006/pmed.1999.0582. PubMed 10600426 ↗

Study documents

  • Protocol and statistical analysis plan · Dec 12, 2024

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

10

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 26, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
11

Registry details

Key details

Study ID
NCT03786042
Lead sponsor
Trustees of Dartmouth College
Collaborators
National Cancer Institute (NCI), Dartmouth College
Responsible party
Diane Gilbert-Diamond (Associate Professor, Trustees of Dartmouth College) — Principal investigator
First posted
Dec 24, 2018
Start date
Feb 4, 2019
Primary completion
Dec 9, 2021
Completion
Dec 9, 2021
Results posted
Sep 26, 2025
Last update
Sep 26, 2025

Study contacts

James Sargent, MD
principal investigator · Geisel School of Medicine at Dartmouth College
Diane Gilbert-Diamond, ScD
principal investigator · Geisel School of Medicine at Dartmouth College

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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