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| ID | Type | Description | Link |
|---|---|---|---|
| 1R21CA232054-01 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Cancer Institute (NCI) | NIH |
| Dartmouth College | OTHER |
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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.
[3/14/2020]: Study recruitment temporarily halted due to the COVID-19 pandemic
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| E-cigarette ad exposure | Active Comparator | Participants in the e-cigarette ad exposure condition will view e-cigarette ads on the computer screen while having their eye movements tracked |
|
| non e-cigarette ad exposure | Sham Comparator | 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 |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| E-cigarette ad exposure | Behavioral | Participants view a series of e-cigarette TV commercials |
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| Measure | Description | Time Frame |
|---|---|---|
| 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. | within 5 minutes post intervention |
| 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. | approximately 30 minutes post intervention |
| 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. | within 5 minutes post intervention |
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Inclusion Criteria:
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Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| James Sargent, MD | Geisel School of Medicine at Dartmouth College | Principal Investigator |
| Diane Gilbert-Diamond, ScD | Geisel School of Medicine at Dartmouth College | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Dartmouth-Hithchock Medical Center | Lebanon | New Hampshire | 03756 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27244815 | Background | Singh T, Agaku IT, Arrazola RA, Marynak KL, Neff LJ, Rolle IT, King BA. Exposure to Advertisements and Electronic Cigarette Use Among US Middle and High School Students. Pediatrics. 2016 May;137(5):e20154155. doi: 10.1542/peds.2015-4155. | |
| 22876391 | Background | National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. Preventing Tobacco Use Among Youth and Young Adults: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2012. Available from http://www.ncbi.nlm.nih.gov/books/NBK99237/ |
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139 participants competed the consent process and agreed to participate in this study. However, only 127 completed any study visits because of the suspension of in-person lab visits caused by the COVID-19 pandemic between March 2020 and July 2021.
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| ID | Title | Description |
|---|---|---|
| FG000 | 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 E-cigarette ad exposure: Participants view a series of e-cigarette TV commercials |
| FG001 | Non E-cigarette ad Exposure |
| Title | Milestones | Reasons Not Completed | |||||
|---|---|---|---|---|---|---|---|
| Overall Study |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Dec 12, 2024 |
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| non e-cigarette TV commercials | Other | Participants view a series of non e-cigarette TV commercials |
|
| 28562266 | Background | Pierce JP, Sargent JD, White MM, Borek N, Portnoy DB, Green VR, Kaufman AR, Stanton CA, Bansal-Travers M, Strong DR, Pearson JL, Coleman BN, Leas E, Noble ML, Trinidad DR, Moran MB, Carusi C, Hyland A, Messer K. Receptivity to Tobacco Advertising and Susceptibility to Tobacco Products. Pediatrics. 2017 Jun;139(6):e20163353. doi: 10.1542/peds.2016-3353. |
| 26574551 | Background | Villanti AC, Rath JM, Williams VF, Pearson JL, Richardson A, Abrams DB, Niaura RS, Vallone DM. Impact of Exposure to Electronic Cigarette Advertising on Susceptibility and Trial of Electronic Cigarettes and Cigarettes in US Young Adults: A Randomized Controlled Trial. Nicotine Tob Res. 2016 May;18(5):1331-9. doi: 10.1093/ntr/ntv235. Epub 2015 Nov 16. |
| 20160916 | Background | Heatherton TF, Sargent JD. Does Watching Smoking in Movies Promote Teenage Smoking? Curr Dir Psychol Sci. 2009 Apr 15;18(2):63-67. doi: 10.1111/j.1467-8721.2009.01610.x. |
| 16264007 | Background | Sargent JD, Beach ML, Adachi-Mejia AM, Gibson JJ, Titus-Ernstoff LT, Carusi CP, Swain SD, Heatherton TF, Dalton MA. Exposure to movie smoking: its relation to smoking initiation among US adolescents. Pediatrics. 2005 Nov;116(5):1183-91. doi: 10.1542/peds.2005-0714. |
| 17614861 | Background | Dal Cin S, Gibson B, Zanna MP, Shumate R, Fong GT. Smoking in movies, implicit associations of smoking with the self, and intentions to smoke. Psychol Sci. 2007 Jul;18(7):559-63. doi: 10.1111/j.1467-9280.2007.01939.x. |
| Background | National Cancer Institute. The role of the media in promoting and reducing tobacco use. Tobacco control monograph No. 19. (2008). |
| Background | Centers for Disease Control and Prevention. Smoking in Movies. Available at: https://www.cdc.gov/tobacco/data_statistics/fact_sheets/youth_data/movies/index.htm. (Accessed: 5 November 2016) |
| 24918224 | Background | Duke JC, Lee YO, Kim AE, Watson KA, Arnold KY, Nonnemaker JM, Porter L. Exposure to electronic cigarette television advertisements among youth and young adults. Pediatrics. 2014 Jul;134(1):e29-36. doi: 10.1542/peds.2014-0269. Epub 2014 Jun 2. |
| Background | US Department of Health and Human Services. The health consequences of smoking - 50 years of progress. (2014). |
| 26618797 | Background | King AC, Smith LJ, Fridberg DJ, Matthews AK, McNamara PJ, Cao D. Exposure to electronic nicotine delivery systems (ENDS) visual imagery increases smoking urge and desire. Psychol Addict Behav. 2016 Feb;30(1):106-12. doi: 10.1037/adb0000123. Epub 2015 Nov 30. |
| Background | R, W. & A, S. Handbook of implicit cognition and addiction. (Sage, 2006). |
| 28645957 | Background | Booth P, Albery IP, Frings D. Effect of e-cigarette advertisements and antismoking messages on explicit and implicit attitudes towards tobacco and e-cigarette smoking in 18-65-year-olds: a randomised controlled study protocol. BMJ Open. 2017 Jun 23;7(6):e014361. doi: 10.1136/bmjopen-2016-014361. |
| 24018227 | Background | Baschnagel JS. Using mobile eye-tracking to assess attention to smoking cues in a naturalized environment. Addict Behav. 2013 Dec;38(12):2837-40. doi: 10.1016/j.addbeh.2013.08.005. Epub 2013 Aug 14. |
| 17485617 | Background | Primack BA, Switzer GE, Dalton MA. Improving measurement of normative beliefs involving smoking among adolescents. Arch Pediatr Adolesc Med. 2007 May;161(5):434-9. doi: 10.1001/archpedi.161.5.434. |
| 21242217 | Background | Hanewinkel R, Isensee B, Sargent JD, Morgenstern M. Cigarette advertising and teen smoking initiation. Pediatrics. 2011 Feb;127(2):e271-8. doi: 10.1542/peds.2010-2934. Epub 2011 Jan 17. |
| 27278656 | Background | Stautz K, Brown KG, King SE, Shemilt I, Marteau TM. Immediate effects of alcohol marketing communications and media portrayals on consumption and cognition: a systematic review and meta-analysis of experimental studies. BMC Public Health. 2016 Jun 9;16:465. doi: 10.1186/s12889-016-3116-8. |
| 26163170 | Background | Farrelly MC, Duke JC, Crankshaw EC, Eggers ME, Lee YO, Nonnemaker JM, Kim AE, Porter L. A Randomized Trial of the Effect of E-cigarette TV Advertisements on Intentions to Use E-cigarettes. Am J Prev Med. 2015 Nov;49(5):686-693. doi: 10.1016/j.amepre.2015.05.010. Epub 2015 Jul 7. |
| 28363720 | Background | 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. |
| 15804680 | Background | Lewis-Esquerre JM, Rodrigue JR, Kahler CW. Development and validation of an adolescent smoking consequences questionnaire. Nicotine Tob Res. 2005 Feb;7(1):81-90. doi: 10.1080/14622200412331328475. |
| 24650842 | Background | Grana RA, Ling PM. "Smoking revolution": a content analysis of electronic cigarette retail websites. Am J Prev Med. 2014 Apr;46(4):395-403. doi: 10.1016/j.amepre.2013.12.010. |
| 26270285 | Background | Voigt K. Smoking Norms and the Regulation of E-Cigarettes. Am J Public Health. 2015 Oct;105(10):1967-72. doi: 10.2105/AJPH.2015.302764. Epub 2015 Aug 13. |
| 24782418 | Background | Hunt K, Sweeting H. You have been QUALIFIED for a smokeless e-cig starter kit. J Epidemiol Community Health. 2014 Aug;68(8):786. doi: 10.1136/jech-2014-203879. Epub 2014 Apr 29. No abstract available. |
| 24821826 | Background | Grana R, Benowitz N, Glantz SA. E-cigarettes: a scientific review. Circulation. 2014 May 13;129(19):1972-86. doi: 10.1161/CIRCULATIONAHA.114.007667. No abstract available. |
| 24350902 | Background | Fairchild AL, Bayer R, Colgrove J. The renormalization of smoking? E-cigarettes and the tobacco "endgame". N Engl J Med. 2014 Jan 23;370(4):293-5. doi: 10.1056/NEJMp1313940. Epub 2013 Dec 18. No abstract available. |
| 10093176 | Background | Tyas SL, Pederson LL. Psychosocial factors related to adolescent smoking: a critical review of the literature. Tob Control. 1998 Winter;7(4):409-20. doi: 10.1136/tc.7.4.409. |
| Background | Gerrard, M., Gibbons, F. X., Houlihan, A. E., Stock, M. L. & Pomery, E. A. A dual-process approach to health risk decision making: The prototype willingness model. Dev Rev 28, 29-61 (2008). |
| 18995826 | Background | Frith CD, Frith U. Implicit and explicit processes in social cognition. Neuron. 2008 Nov 6;60(3):503-10. doi: 10.1016/j.neuron.2008.10.032. |
| 17146027 | Background | Wellman RJ, Sugarman DB, DiFranza JR, Winickoff JP. The extent to which tobacco marketing and tobacco use in films contribute to children's use of tobacco: a meta-analysis. Arch Pediatr Adolesc Med. 2006 Dec;160(12):1285-96. doi: 10.1001/archpedi.160.12.1285. |
| 27125661 | Background | 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. |
| 16316292 | Background | 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. |
| Background | 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). |
| 18166530 | Background | 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. |
| 11744562 | Background | 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. |
| 12892958 | Background | 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. |
| 15226149 | Background | 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. |
| 17339507 | Background | 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. |
| 25840880 | Background | 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. |
| 25511118 | Background | 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. |
| 22371194 | Background | 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. |
| 28493753 | Background | 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. |
| Background | 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). |
| 21566676 | Background | 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. |
| 17845126 | Background | Hine DW, Honan CA, Marks AD, Brettschneider K. Development and validation of the Smoking Expectancy Scale for Adolescents. Psychol Assess. 2007 Sep;19(3):347-55. doi: 10.1037/1040-3590.19.3.347. |
| 27654143 | Background | 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. |
| 24686476 | Background | 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. |
| Background | Gilbert, D. G. & Rabinovich, N. E. International smoking series (with neural counterparts) verion 1.2. (1999). |
| 26442992 | Background | 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. |
| 16085531 | Background | 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. |
| 19122801 | Background | 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. |
| 21098549 | Background | 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. |
| 15458666 | Background | 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. |
| 10600426 | Background | 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. |
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 non e-cigarette TV commercials: Participants view a series of non e-cigarette TV commercials |
| COMPLETED |
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| NOT COMPLETED |
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| ID | Title | Description |
|---|---|---|
| BG000 | 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 E-cigarette ad exposure: Participants view a series of e-cigarette TV commercials |
| BG001 | 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 non e-cigarette TV commercials: Participants view a series of non e-cigarette TV commercials |
| BG002 | Total | Total of all reporting groups |
| Units | Counts |
|---|---|
| Participants |
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| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Age, Categorical | Count of Participants | Participants |
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| Age, Continuous | Mean | Standard Deviation | years |
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| Sex: Female, Male | 1 participant in the e-cigarette condition did not indicate their sex 1 participant in the control condition did not indicate their sex | Count of Participants | Participants |
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| Ethnicity (NIH/OMB) | Count of Participants | Participants |
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| Race (NIH/OMB) | Count of Participants | Participants |
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| Region of Enrollment | Count of Participants | Participants |
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| Positive smoking expectancies | Positive smoking expectancies using a 7-item scale (1=not all; 2 7 = very much) "I think I would enjoy smoking"; "I think smoking would give me something to do when I'm bored"; "I think smoking would help me deal with problems or stress"; "I think smoking would help me stay thin"; "I think smoking would help me to feel more comfortable at parties"; "I think smoking would be relaxing"; and "I think smoking would make me look older. Responses are dichotomized and summed to create a score, ranging from 0 - 7. Higher scores meaning a higher positive smoking expectancy. | Mean | Standard Deviation | units on a scale |
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| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | 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. | Posted | Mean | Standard Deviation | milliseconds | within 5 minutes post intervention |
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| Primary | 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. | Data not collected for participants in Non E-cigarette ad Exposure Arm because they were not exposed to e-cigarette advertisements. | Posted | Mean | Standard Deviation | milliseconds | approximately 30 minutes post intervention |
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| Primary | 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. | Posted | Mean | Standard Deviation | milliseconds | within 5 minutes post intervention |
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Adverse event data was not collected for this study.
All-Cause Mortality, Serious, and Other (Not Including Serious) Adverse Events were not monitored/assessed because there were no anticipated serious adverse events is this study, defined as one that results in death, is life-threatening, requires hospitalization, or leads to a significant disability.
There were also no anticipated risks for all-cause mortality in this study, or other adverse events.
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | 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 E-cigarette ad exposure: Participants view a series of e-cigarette TV commercials | 0 | 0 | 0 | 0 | 0 | 0 |
| EG001 | 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 non e-cigarette TV commercials: Participants view a series of non e-cigarette TV commercials | 0 | 0 | 0 | 0 | 0 | 0 |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Research Scientist | Dartmouth college | 603-646-5408 | john.brand@dartmouth.edu |
| Dec 12, 2024 |
| Prot_SAP_000.pdf |
| Between 18 and 65 years |
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| >=65 years |
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