<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03786042</url>
  </required_header>
  <id_info>
    <org_study_id>D19034</org_study_id>
    <secondary_id>1R21CA232054-01</secondary_id>
    <nct_id>NCT03786042</nct_id>
  </id_info>
  <brief_title>Trial on the Effect of E-cigarette Advertising on Cigarette Perceptions in Adolescents</brief_title>
  <official_title>Does Exposure to Electronic Nicotine Delivery Systems Advertising Affect Positive Smoking Expectancies and Social Normative Beliefs About Smoking?</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Dartmouth-Hitchcock Medical Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Cancer Institute (NCI)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
    <collaborator>
      <agency>Dartmouth College</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Dartmouth-Hitchcock Medical Center</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This research aims to investigate how exposure to advertising for Electronic Nicotine&#xD;
      Delivery Systems (commonly called e-cigarettes) may lead to combustible smoking initiation in&#xD;
      adolescents.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      [3/14/2020]: Study recruitment temporarily halted due to the COVID-19 pandemic&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">February 4, 2019</start_date>
  <completion_date type="Actual">December 9, 2021</completion_date>
  <primary_completion_date type="Actual">December 9, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Factorial Assignment</intervention_model>
    <primary_purpose>Prevention</primary_purpose>
    <masking>Single (Participant)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>change in baseline in implicit positive smoking expectancies, measured by the implicit association test</measure>
    <time_frame>baseline, within 5 minutes post intervention</time_frame>
    <description>Scores are measured by recording the amount of time (reaction time) 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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Amount of time spent looking at static smoking cues in e-cigarette advertisements</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>Eye-tracking will be used to measure the amount of time 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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>7-item explicit positive smoking expectancies scale</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>Scores are measured on a 7-item scale. Positive smoking expectancies will be assessed using the following questions that follow the lead-in, &quot;Please tell me how you feel about the following statements.&quot; &quot;I think I would enjoy smoking&quot;; &quot;I think smoking would give me something to do when I'm bored&quot;; &quot;I think smoking would help me deal with problems or stress&quot;; &quot;I think smoking would help me stay thin&quot;; &quot;I think smoking would help me to feel more comfortable at parties&quot;; &quot;I think smoking would be relaxing&quot;; and &quot;I think smoking would make me look older.&quot; Responses are yes/no. Responses are coded as &quot;1&quot; for yes and &quot;0&quot; for no. Responses are then summed for a maximum positive smoking expectancy score out of 7. Higher scores mean higher positive smoking expectancies.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>11-item scale that measures social normative beliefs about smoking</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>This 11-item scale assess social normative beliefs about smoking related to 1) perceived disapproval from family/friends, 2) perceived popularity among successful/elite, and 3) perceived prevalence. Disapproval scale questions are answered using a 4-point Likert scale (1 = Strongly disagree; 4 = Strongly agree). A total disapproval score (ranging from 1 to 4) is calculated by averaging responses to each question. Higher values indicate a higher disapproval score. Popularity scale questions are answered using a 4-point Likert scale (1 = Strongly disagree; 4 = Strongly agree). A total popularity score (ranging from 1 to 4) is calculated by averaging responses to each question. Higher values indicate a higher popularity score. Prevalence scale questions are answered using a percent scale from 0 - 100% in 10% increments. A total prevalence scale (from 0 to 100) is calculated by averaging the responses to each question. Higher values indicate a higher prevalence score.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>A 3-item scale that measures adolescent smoking susceptibility</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>This 3-item instrument is used to predict which never smokers are likely to start smoking by measuring their curiosity to use tobacco products. Item responses are on a 4-point Likert scale (definitely yes, probably yes, probably not, definitely not). To classify a respondent as not susceptible to smoking, the respondent must indicate &quot;definitely not&quot; to all four items. Any other response to any item classifies a respondent as &quot;susceptible.&quot;</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Amount of time looking at dynamic smoking cues in e-cigarette advertisements</measure>
    <time_frame>During the intervention, approximately 15 minutes post baseline</time_frame>
    <description>Eye-tracking will be used to measure the total amount of time spent looking in realtime at smoking cues in TV commercials for e-cigarettes. The amount of time looking at smoking cues will be a measure of the amount of attention given to smoking cues. The longer the amount of time spent looking at smoking cues indicates that a greater amount of attention was given to the smoking cues.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>18-item scale that measures character attributes of actors that appeared in the commercials</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>Character Attributes will be collected using a scale that measures participants beliefs about character attributes using the lead in: &quot;I think [Character Name] is: &quot; using a 5-point Likert (1 = strongly disagree; 5 = strongly agree). There is a total of 6 attributes assessed: 1) smart (smart, intelligent, stupid), 2) successful (successful, achieves goals, gets what he/she wants), 3) attractive (physically attractive, ugly, good-looking), 4) funny (funny, humorous, makes me laugh), 5) respected (respected by others, receives approval, criticized by others), and 6) popular (has lots of friends, well liked, gets support from others). A total score (form 1 to 5) for each scale is calculated by averaging responses for each question within that scale. For each scale, a higher total score indicates higher beliefs about that attribute.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>5-item scale that measure how much participants wish to be like the actors appearing in the commercials.</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>This 5-item is scale is used to quantify how much a participant would like to be like an actor appearing in a commercial. Questions are rated on a 5-point Likert scale (1 = Strongly Disagree; 5 = Strongly agree). A total identification score (from 1 to 25) is calculated by summing the responses to each question. A higher total score indicates a higher level of wishful identification.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>13-item scale to measure risk perception about cigarette use</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>This 13-item scale measures risk perceptions associated with cigarette use. Questions are answered using a sliding percent scale from 0 - 100% in 10% increments. A risk perception scale is calculated (from 0 to 100) by averaging the responses to each question. Higher values indicate a higher risk perception.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>13-item scale to Measure risk perception about e-cigarette use</measure>
    <time_frame>approximately 30 minutes post intervention</time_frame>
    <description>This 13-item scale measures risk perceptions associated with e-cigarette use. Questions are answered using a sliding percent scale from 0 - 100% in 10% increments. A risk perception scale is calculated (from 0 to 100) by averaging the responses to each question. Higher values indicate a higher risk perception.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">132</enrollment>
  <condition>Attentional Bias</condition>
  <condition>Smoking Cues</condition>
  <condition>Positive Perceptions About Cigarette Smoking</condition>
  <condition>Social Norms</condition>
  <condition>Smoking Susceptibility</condition>
  <arm_group>
    <arm_group_label>E-cigarette ad exposure</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Participants in the e-cigarette ad exposure condition will view e-cigarette ads on the computer screen while having their eye movements tracked</description>
  </arm_group>
  <arm_group>
    <arm_group_label>non e-cigarette ad exposure</arm_group_label>
    <arm_group_type>Sham Comparator</arm_group_type>
    <description>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</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>E-cigarette ad exposure</intervention_name>
    <description>Participants view a series of e-cigarette TV commercials</description>
    <arm_group_label>E-cigarette ad exposure</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>non e-cigarette TV commercials</intervention_name>
    <description>Participants view a series of non e-cigarette TV commercials</description>
    <arm_group_label>non e-cigarette ad exposure</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        -&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Exclusion criteria will include inadequate English proficiency, and diagnosis of a&#xD;
             learning or vision disorder.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>14 Years</minimum_age>
    <maximum_age>17 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>James Sargent, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Geisel School of Medicine at Dartmouth College</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Diane Gilbert-Diamond, ScD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Geisel School of Medicine at Dartmouth College</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Dartmouth-Hithchock Medical Center</name>
      <address>
        <city>Lebanon</city>
        <state>New Hampshire</state>
        <zip>03756</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
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    <citation>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.</citation>
    <PMID>17845126</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>27654143</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>24686476</PMID>
  </reference>
  <reference>
    <citation>Gilbert, D. G. &amp; Rabinovich, N. E. International smoking series (with neural counterparts) verion 1.2. (1999).</citation>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>26442992</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>16085531</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>19122801</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>21098549</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>15458666</PMID>
  </reference>
  <reference>
    <citation>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.</citation>
    <PMID>10600426</PMID>
  </reference>
  <verification_date>May 2022</verification_date>
  <study_first_submitted>December 20, 2018</study_first_submitted>
  <study_first_submitted_qc>December 21, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 24, 2018</study_first_posted>
  <last_update_submitted>May 26, 2022</last_update_submitted>
  <last_update_submitted_qc>May 26, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">May 27, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Dartmouth-Hitchcock Medical Center</investigator_affiliation>
    <investigator_full_name>Diane Gilbert-Diamond</investigator_full_name>
    <investigator_title>Associate Professor</investigator_title>
  </responsible_party>
  <keyword>Positive Smoking expectancies</keyword>
  <keyword>e-cigarette advertising</keyword>
  <keyword>adolescents</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Disease Susceptibility</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03786042
org study id: D19034
secondary id: 1R21CA232054-01
nct id: NCT03786042
lead sponsor: 
collaborator: 
collaborator: 
is fda regulated drug: No
is fda regulated device: No
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
allocation: Randomized
intervention model: Factorial Assignment
primary purpose: Prevention
masking: Single (Participant)
measure: change in baseline in implicit positive smoking expectancies, measured by the implicit association test
time frame: baseline, within 5 minutes post intervention
description: Scores are measured by recording the amount of time (reaction time) 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.
measure: Amount of time spent looking at static smoking cues in e-cigarette advertisements
time frame: approximately 30 minutes post intervention
description: Eye-tracking will be used to measure the amount of time 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.
measure: 7-item explicit positive smoking expectancies scale
time frame: approximately 30 minutes post intervention
description: Scores are measured on a 7-item scale. Positive smoking expectancies will be assessed using the following questions that follow the lead-in, "Please tell me how you feel about the following statements." "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 yes/no. Responses are coded as "1" for yes and "0" for no. Responses are then summed for a maximum positive smoking expectancy score out of 7. Higher scores mean higher positive smoking expectancies.
measure: 11-item scale that measures social normative beliefs about smoking
time frame: approximately 30 minutes post intervention
description: This 11-item scale assess social normative beliefs about smoking related to 1) perceived disapproval from family/friends, 2) perceived popularity among successful/elite, and 3) perceived prevalence. Disapproval scale questions are answered using a 4-point Likert scale (1 = Strongly disagree; 4 = Strongly agree). A total disapproval score (ranging from 1 to 4) is calculated by averaging responses to each question. Higher values indicate a higher disapproval score. Popularity scale questions are answered using a 4-point Likert scale (1 = Strongly disagree; 4 = Strongly agree). A total popularity score (ranging from 1 to 4) is calculated by averaging responses to each question. Higher values indicate a higher popularity score. Prevalence scale questions are answered using a percent scale from 0 - 100% in 10% increments. A total prevalence scale (from 0 to 100) is calculated by averaging the responses to each question. Higher values indicate a higher prevalence score.
measure: A 3-item scale that measures adolescent smoking susceptibility
time frame: approximately 30 minutes post intervention
description: This 3-item instrument is used to predict which never smokers are likely to start smoking by measuring their curiosity to use tobacco products. Item responses are on a 4-point Likert scale (definitely yes, probably yes, probably not, definitely not). To classify a respondent as not susceptible to smoking, the respondent must indicate "definitely not" to all four items. Any other response to any item classifies a respondent as "susceptible."
measure: Amount of time looking at dynamic smoking cues in e-cigarette advertisements
time frame: During the intervention, approximately 15 minutes post baseline
description: Eye-tracking will be used to measure the total amount of time spent looking in realtime at smoking cues in TV commercials for e-cigarettes. The amount of time looking at smoking cues will be a measure of the amount of attention given to smoking cues. The longer the amount of time spent looking at smoking cues indicates that a greater amount of attention was given to the smoking cues.
measure: 18-item scale that measures character attributes of actors that appeared in the commercials
time frame: approximately 30 minutes post intervention
description: Character Attributes will be collected using a scale that measures participants beliefs about character attributes using the lead in: "I think [Character Name] is: " using a 5-point Likert (1 = strongly disagree; 5 = strongly agree). There is a total of 6 attributes assessed: 1) smart (smart, intelligent, stupid), 2) successful (successful, achieves goals, gets what he/she wants), 3) attractive (physically attractive, ugly, good-looking), 4) funny (funny, humorous, makes me laugh), 5) respected (respected by others, receives approval, criticized by others), and 6) popular (has lots of friends, well liked, gets support from others). A total score (form 1 to 5) for each scale is calculated by averaging responses for each question within that scale. For each scale, a higher total score indicates higher beliefs about that attribute.
measure: 5-item scale that measure how much participants wish to be like the actors appearing in the commercials.
time frame: approximately 30 minutes post intervention
description: This 5-item is scale is used to quantify how much a participant would like to be like an actor appearing in a commercial. Questions are rated on a 5-point Likert scale (1 = Strongly Disagree; 5 = Strongly agree). A total identification score (from 1 to 25) is calculated by summing the responses to each question. A higher total score indicates a higher level of wishful identification.
measure: 13-item scale to measure risk perception about cigarette use
time frame: approximately 30 minutes post intervention
description: This 13-item scale measures risk perceptions associated with cigarette use. Questions are answered using a sliding percent scale from 0 - 100% in 10% increments. A risk perception scale is calculated (from 0 to 100) by averaging the responses to each question. Higher values indicate a higher risk perception.
measure: 13-item scale to Measure risk perception about e-cigarette use
time frame: approximately 30 minutes post intervention
description: This 13-item scale measures risk perceptions associated with e-cigarette use. Questions are answered using a sliding percent scale from 0 - 100% in 10% increments. A risk perception scale is calculated (from 0 to 100) by averaging the responses to each question. Higher values indicate a higher risk perception.
arm group label: E-cigarette ad exposure
arm group type: Active Comparator
description: Participants in the e-cigarette ad exposure condition will view e-cigarette ads on the computer screen while having their eye movements tracked
arm group label: non e-cigarette ad exposure
arm group type: Sham Comparator
description: 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
intervention type: Behavioral
intervention name: E-cigarette ad exposure
description: Participants view a series of e-cigarette TV commercials
arm group label: E-cigarette ad exposure
intervention type: Other
intervention name: non e-cigarette TV commercials
description: Participants view a series of non e-cigarette TV commercials
arm group label: non e-cigarette ad exposure
criteria: 
gender: All
minimum age: 14 Years
maximum age: 17 Years
healthy volunteers: No
last name: James Sargent, MD
role: Principal Investigator
affiliation: Geisel School of Medicine at Dartmouth College
last name: Diane Gilbert-Diamond, ScD
role: Principal Investigator
affiliation: Geisel School of Medicine at Dartmouth College
facility: 
country: United States
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PMID: 27244815
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citation: 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.
PMID: 17845126
citation: 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.
PMID: 27654143
citation: 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.
PMID: 24686476
citation: Gilbert, D. G. & Rabinovich, N. E. International smoking series (with neural counterparts) verion 1.2. (1999).
citation: 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.
PMID: 26442992
citation: 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.
PMID: 16085531
citation: 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.
PMID: 19122801
citation: 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.
PMID: 21098549
citation: 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.
PMID: 15458666
citation: 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.
PMID: 10600426
responsible party type: Principal Investigator
investigator affiliation: Dartmouth-Hitchcock Medical Center
investigator full name: Diane Gilbert-Diamond
investigator title: Associate Professor
mesh term: Disease Susceptibility
sharing ipd: No