A study design proposal for incorporating photos into just-in-time interventions for smoking cessation. The presentation was given for a health communication seminar course in Fall 2016.

1. What’s a
Picture Worth
in text-message tobacco cessation interventions?
Shauna Ayres
University of North Carolina at Chapel Hill
Seminar in Interdisciplinary Health Communication
JOMC/HBEH 825, Fall 2016
November 18, 2016

3. What We’ll Look At Today
• Brief background
• The good news
• Literature review highlights
• Research questions
• Study proposal
• Suggestions

4. Smoker
Still A Threat
US adult smoking rates have decreased from
42.4% in 19652
to
15.1% in 20162
But North Carolina is still lagging behind at
19.1% in 20162
1. CDC, 2016; 2. Campaign for Tobacco-Free Kids, 2016
1

5. North Carolina
Smoking causes:
• 14,200 annual deaths1
• $3.81 billion in annual health costs1
• Higher rates of lung cancer at 49.1 per
100,000 people (national rate of 45.5 per 100,000)2
• Higher rates of COPD at 43.4-48.4 per
100,000 people (national rate 40.8 per 100,000)3
• 4 out of the 5 leading causes of death
in the state and account for about 2/3 of all
deaths or 50,000 deaths per year
(cancer, heart disease, stroke, & chronic lung disease)4
1. Campaign for Tobacco-Free Kids, 2016; 2. CDC, 2016; 3. CDC, 2014, 4. NCDHHS, 2016

6. The Good News
• Nearly half of all smokers try to
quit each year1
• mHealth has been successful in
addressing addictive behaviors, such
as smoking, alcohol, drugs, and eating
disorders2
Smartphones
72%
"Dumb"
phones
19%
No cell
phone
9%
Cell Phone Use in the US3
1. CDC, 2016; 2. Keoleian, 2015; 3. Poushter, 2016

7. Lit. Review Highlights
• Text messaging is an effective smoking cessation intervention for young adults1, 2,
3, 4, 5, 6, 7
• Text messaging is the preferred method for receiving smoking cessation support4
• Usability, readership, and satisfaction of text message interventions is high1, 4, 7
• Text messaging interventions are recommended as a supplemental cessation
support8
• There is extensive support for tailoring text messages1, 2, 3, 4, 5, 6, 7
• Quitting smoking is a process and measuring smoking abstinence should not be
an intervention’s only measure of success9
• Health communication and public health experts should identify and quickly
adapt to new technological trends to increase reach and interest in messaging6
1. Abroms, 2012; 2. Douglas & Free, 2013; 3. Free, 2011; 4. Buller, 2013;
2. 5. Skov-Ettrup, 2014; 6. Stanczyk, 2016; 7. Ybarra, 2013; 8. CDC, 2015; 9. Chaiton et al., 2016

8. Primary Gaps & Limitations
• Staying current on
technological advances and
trends
• Reaching populations with
limited cell phone use or
access
• Obtaining funding, of course
• Finding the optimal level of
tailoring

9. Research Questions
1. Are text messages that remind participants of their reasons for
quitting smoking more effective if pictures are included?
2. Are these text messages more effective if they included pictures
that are taken by the participants themselves?
3. What types of pictures or themes
emerge from participant’s photographs?

10. Study Proposal
• Based on Stop My Smoking USA RCT conducted by Ybarra et al. in 2011
in the U.S. among young adult smokers, 18-30 years old
• Participants must be between 18-30 years old, smoke 5+ cigarettes/day,
and provide consent. If eligible participants do not own a sufficient cell
phone, one will be provided at no cost.
Young Adult
Smokers
(n=1000)
Control/Waitlist
(n=250)
Text Only
(n=250)
Text +
Stock Photo
(n=250)
Text +
Personal Photo
(n=250)
Young Adult
Smokers
(n=1000)
C TO TS TP
Remember why it’s
so important to quit
smoking. It’s for Kylie
and Thomas.
Remember why it’s
so important to quit
smoking. It’s for Kylie
and Thomas.
Remember why it’s
so important to quit
smoking. It’s for Kylie
and Thomas.

11. Measures
Primary outcomes:
• Continuous smoking abstinence
• Avg. number of cigarettes smoked/day
• Blood test results
Secondary outcomes:
• Number of text message responses
• Intentions
• Attitudes
• Beliefs
• Readiness to change
• Self-efficacy for smoking behaviors
• Usability of intervention (TO, TS, TP only)
• Satisfaction with intervention (TO, TS, TP only)
• Picture themes (TP)
C TO, TS, TP
Baseline
12 Months
Baseline
1 Month
3 Months
6 Months
12 Months

12. Measures
Primary outcomes:
• Continuous smoking abstinence
• Avg. number of cigarettes smoked/day
• Blood test results
Secondary outcomes:
• Number of text message responses
• Intentions
• Attitudes
• Beliefs
• Readiness to change
• Self-efficacy for smoking behaviors
• Usability of intervention (TO, TS, TP only)
• Satisfaction with intervention (TO, TS, TP only)
• Picture themes (TP)
C TO, TS, TP
Baseline
12 Months
Baseline
1 Month
3 Months
6 Months
12 Months

13. Measures
Primary outcomes:
• Continuous smoking abstinence
• Avg. number of cigarettes smoked/day
• Blood test results
Secondary outcomes:
• Number of text message responses
• Intentions
• Attitudes
• Beliefs
• Readiness to change
• Self-efficacy for smoking behaviors
• Usability of intervention (TO, TS, TP only)
• Satisfaction with intervention (TO, TS, TP only)
• Picture themes (TP)
C TO, TS, TP
Baseline
12 Months
Baseline
1 Month
3 Months
6 Months
12 Months

14. Measures
Primary outcomes:
• Continuous smoking abstinence
• Avg. number of cigarettes smoked/day
• Blood test results
Secondary outcomes:
• Number of text message responses
• Intentions
• Attitudes
• Beliefs
• Readiness to change
• Self-efficacy for smoking behaviors
• Usability of intervention (TO, TS, TP only)
• Satisfaction with intervention (TO, TS, TP only)
• Picture themes (TP)
C TO, TS, TP
Baseline
12 Months
Baseline
1 Month
3 Months
6 Months
12 Months

15. Measures
Primary outcomes:
• Continuous smoking abstinence
• Avg. number of cigarettes smoked/day
• Blood test results
Secondary outcomes:
• Number of text message responses
• Intentions
• Attitudes
• Beliefs
• Readiness to change
• Self-efficacy for smoking behaviors
• Usability of intervention (TO, TS, TP only)
• Satisfaction with intervention (TO, TS, TP only)
• Picture themes (TP)
C TO, TS, TP
Baseline
12 Months
Baseline
1 Month
3 Months
6 Months
12 Months

16. Math
• Between group differences at each
assessment and over time
• Within group differences at each
assessment and over time.
• Effect sizes
• Chi square and logistic regression
tests will be conducted to determine
statistical significance among
demographic subgroups
• All statistical analyses will be
performed by a trained biostatistician

17. Open
Access
Dissemination
• Open access journals
• By request
• Conference presentations

19. Thank You
Questions
&
Feedback

20. References
Abroms, L.C., Ahuja, M., Kodl, Y., Thaweethai, L., Sims, J., Winickoff, J.P., & Windsor, R.A. (2012). Text2Quit: Results from a pilot test of a personalized, interactive mobile health
smoking cessation program. J Health Commun, 17 Suppl 1: 44-53.
Akter, S. & Ray, P. (2010). mHealth – an ultimate platform to serve the unserved. IMIA Yearbook of Medical Informatics, 94-100.
Buller, D.B., Borland, R., Bettinghaus, E.P., Shane, J.H., & Zimmerman, D.E. (2014). Randomized trial of a smartphone mobile application compared to text messaging to support
smoking cessation. Telemed J E Health. 20(3): 206-214.
Campaign for Tobacco-Free Kids (2016, Sept 13) Key state-specific tobacco-related data & rankings. https://www.tobaccofreekids.org/research/factsheets/pdf/0176.pdf
Campaign for Tobacco-Free Kids (2016, Sept 13). The path to tobacco addiction starts at very young ages. https://www.tobaccofreekids.org/research/factsheets/pdf/0127.pdf
Centers for Disease Control and Prevention (CDC) (2011, Nov 11). Quitting Smoking Among Adults --- United States, 2001—2010. Weekly MMWR report, 60(44); 1513-1519.
https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6044a2.htm
Centers for Disease Control and Prevention (CDC) (2014). Data and statistic. Chronic Obstructive Pulmonary Disease (COPD). http://www.cdc.gov/copd/data.htm
Centers for Disease Control and Prevention (CDC) (2015). Fast facts. Smoking & Tobacco Use. http://www.cdc.gov/tobacco/data_statistics/fact_sheets/fast_facts/
Centers for Disease Control and Prevention (CDC) (2015). Quitting smoking. Smoking & Tobacco Use. http://www.cdc.gov/tobacco/data_statistics/fact_sheets/cessation/quitting/
Centers for Disease Control and Prevention (CDC) (2016). Lung cancer rates by state. Lung Cancer. http://www.cdc.gov/cancer/lung/statistics/state.htm
Centers for Disease Control and Prevention (CDC) (2016). Trends in current cigarette smoking among high school students and adults, united states, 1965-2014. Smoking & Tobacco
Use. http://www.cdc.gov/tobacco/data_statistics/tables/trends/cig_smoking/
Chaiton, M., Diemert, L., Cohen, J.E., Bondy, S.J., Selby, P., Philipneri, A., & Schwartz, R. (2016) Estimating the number of quit attempts it takes to quit smoking successfully in a
longitudinal cohort of smokers. BMJ Open, 6:e011045. http://bmjopen.bmj.com/content/6/6/e011045.full
Douglas, N. & Free, C. (2013). 'Someone batting in my corner': Experiences of smoking-cessation support via text message. Br J Gen Pract. 63(616): e768-76.

21. References
(continued)
Free, C., Knight, R., Robertson, S., Whittaker, R., Edwards, P., Zhou, W., Rodgers, A., Cairns, J., Kenward, M.G., & Roberts, I. (2011). Smoking cessation support delivered via mobile
phone text messaging (txt2stop): A single-blind, randmised trial. Lancet, 378(9785): 49-55.
Keoleian, V., Polcin, D., & Galloway, G. P. (2015). Text Messaging for Addiction: A Review. Journal of Psychoactive Drugs, 47(2), 158–176.
Muench, F., Weiss, R.A., Kuerbis, A., & Morgenstern, J. (2013). Developing a theory driven test message intervention for addiction care with user driven content. Psychol Addict
Behav, 27(1): 315-321.
North Carolina Department of Health and Human Services (NCDHHS) (2016). Chronic disease and injury section. Department of Public Health.
http://publichealth.nc.gov/chronicdiseaseandinjury/
Poushter, J. (2016, Feb 22). Smartphone ownership rates skyrocket in many emerging economies, but digital divide remains. Pew Research Center.
http://www.pewglobal.org/2016/02/22/smartphone-ownership-rates-skyrocket-in-many-emerging-economies-but-digital-divide-remains/
Skov-Ettrup, L.S,. Ringgaard, L.W., Dalum, P., Flensborg-Madsen, T., Thygesen, L.C., & Tolstrup, J.S. (2014). Comparing tailored and untailored text messages for smoking cessation: A
randomized controlled trial among adolescent and young adult smokers. Health Educ Res, 29(2): 195-205.
Snider, C. (2016). Social media statistics. Chris Snider Design. http://chrissniderdesign.com/blog/resources/social-media-statistics/
Stanczyk, N.E., de Vries, H., Candel, M.J., Muris, J.W., & Bolman, C.A. (2016). Effectiveness of video- versus text-based computer-tailored smoking cessation interventions among
smokers after one year. Prev Med, 82: 42-50.
Statista (2016). Number of daily active Snapchat users from March 2014 to June 2016 (in millions). The Statistics Portal. https://www.statista.com/statistics/545967/snapchat-app-
dau/
U.S. Department of Health and Human Services (USDHHS) (2014). The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta, Georgia.
http://www.surgeongeneral.gov/library/reports/50-years-of-progress/sgr50-supplement-tables.pdf
Whittaker, R., Borland, R., Bullen, C., Lin, R.B., McRobbie, H., & Rodgers, A. (2009). Mobile phone-based interventions for smoking cessation (Review). Cochrane Database of
Systematic Reviews, 4; CD006611.
Ybarra, M.L., Holtrop, J.S., Prescott, T.L., Rahbar, M.H., & Strong, D. (2013). Pilot RCT results of stop my smoking USA: A text messaging-based smoking cessation program for young
adults. Nicotine Tob Res, 15(8): 1388-1399.