What’s a Picture Worth

in text-message tobacco cessation interventions?

Shauna AyresUniversity of North Carolina at Chapel HillSeminar in Interdisciplinary Health CommunicationJOMC/HBEH 825, Fall 2016November 18, 2016

What We’ll Look At Today

• Brief background

• The good news

• Literature review highlights

• Research questions

• Study proposal

• Suggestions

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

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

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

Smartphones72%

"Dumb" phones

19%

No cell phone

9%

Cell Phone Use in the US3

1. CDC, 2016; 2. Keoleian, 2015; 3. Poushter, 2016

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

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

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?

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.

MeasuresPrimary 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

Baseline1 Month3 Months6 Months

12 Months

MeasuresPrimary 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

Baseline1 Month3 Months6 Months

12 Months

MeasuresPrimary 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

Baseline1 Month3 Months6 Months

12 Months

MeasuresPrimary 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

Baseline1 Month3 Months6 Months

12 Months

MeasuresPrimary 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

Baseline1 Month3 Months6 Months

12 Months

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

Open

Access

Dissemination

• Open access journals

• By request

• Conference presentations

Thank You

Questions

&

Feedback

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.

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.