This document discusses the use of technology for health education and smoking cessation in the 21st century. It covers current uses of text messaging programs, smartphone apps, social media, and electronic health records for smoking cessation. Text messaging programs have been shown to increase smoking cessation rates by 70% compared to control groups. Smartphone apps are popular but often lack elements shown to be effective like counseling and connecting to quitlines. Social media platforms are emerging areas of research with some studies showing potential. Electronic health records have increased documentation of smoking status but have not consistently shown effects on quit rates. Overall technology provides major opportunities but also challenges to integrate platforms and balance privacy with care.

1. Health
Education
Technology in
the 21st Century
Lorien Abroms, ScD.
Milken Institute School of Public Health
George Washington University

2. Dr. Lorien Abroms/GWU has licensed Text2Quit &
Quit4Baby to Voxiva Inc.
This research was supported by NIH grants to Dr.
Lorien Abroms, 5K07 CA124579-02 and
1R15CA167586
Funding Source:
Disclosure:

3. Topics I’ll cover
I. Use of technology
II. Current Uses & Evidence
• Text Messaging Programs
• Smartphone apps
• Social Media
• Electronic Health Records

4. Device Ownership 2002-2014

5. Reach of Mobile Phones
90% of US adults
88% text message, top activity
64%+ have smartphones, almost
90% among young adults
75% have used phone to look up
health information
(Pew 2014; CTIA 2014)

8. “We Marry Them!”
 82 % of mobile phone owners never leave
home without their phones
 68 % sleep with device by bedside
 Invite them to interrupt us (at family
gatherings, at restaurant, at meetings)
 Increasingly rate as something “not
willing to live without”

10. The bottom line:
 Communication technologies are
proliferating in our daily lives.
 They are with us throughout the day
 They’re here by invitation – we embrace new
ways of inviting them in

11. Topics I’ll cover
I. Use of technology
II. Current uses and Evidence
• Text Messaging Programs
• Smartphone apps
• Social Media
• Electronic Health Records

12. • Smoking is the leading preventable
cause of death in the US
• 18% of US adults smoke
• 13% among pregnant women
• Provides constant lens as we examine
various technologies
• Well studied
A Focus on Smoking
Cessation

13. Cessation programs should:
Ask for tobacco use status
Advise every user to quit
Assess willingness to quit
Assist with a quit plan
 Recommend approved meds
 Practical counseling
 Intra-treatment social support
Connect to a quitline
Arrange for follow-up

14. Text Messaging

15.  Countries: New Zealand (2008), UK,
Australia, Costa Rica, US
 U.S.
 Text2Quit (Text2quit.com)
 130,000+ users since April 2012
 Integrated with 1-800-QUITNOW in 10
States
 SmokefreeTXT (smokefree.gov)
 Text QUIT to 47848
 100,000+ users since Sept. 2012
 Teen, Mom & Vet versions
Some Cessation Text Messaging
Services

16. Text4Baby
 Core Partners:
 Outreach Partners:
 Telecoms industry
support:
16

17. Text Messaging
(SMS)Cessation Programs
• Automated text messages (SMS) for quitting smoking
• Sent by a computer based on a message library and algorithm
(rules)
• Messages are timed around quit date
• Proactive: Advice on quitting and manage cravings, medication
msgs, and relapse messages.
• On-Demand: need additional motivation, having a craving,
relapse.
• Interactive, personalized
• 2-3 messages/day following quitdate

18. Advice on
Quitting
Ex-smoker
encouragement
On
demand
games &
tips
Check-Ins

19. Attributes that may promote
Smoking Cessation (Efficacy)
1. Help anywhere and anytime
2. Proactive messages interrupt
you
3. Interactive help
4. Personalized help
5. Increase contact time
6. Unobtrusive and confidential
7. (Goes with smoking)
Source: Abroms, Padmanabhan, and Evans 2011

20. Whittaker et al. Meta-Analysis. Cochrane.
2012
RR 1.7; 70% increase over control

21. Free et al. (2011) Lancet
 Text2Stop (N=5800)
 5 msg/day first 5 weeks; then 3 msg/week for 26
weeks
 Biochemically verified continuous abstinence at 6
months:
10·7% txt2stop vs 4·9% control (p<0·0001)
 No evidence that effect b/c drove use of quitline or
NRT

22. Abroms et al. 2014 (N=503)
Abroms et al. Am J Prev Medicine. 2014
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
1 month 3 months 6 months
Text2Quit
Control
NoSmokinginthePast7days
30.5%
14.5%
33.2%
19.9%
31.7%
20.7%

23. US Preventive Services

24. 0 5 10 15 20 25 30
Other/Not clear
Self-efficacy
Quantity/Frequency
Social Control
Skills/Info
Encouragement
Social Support
Global Help
On Demand Tools
Constant/Reminder
9.9
3.3
5
5.5
7.7
14.9
15.5
20.4
21
26
Percent (%)
What Did You Like About Text2Quit? (1 Month)
(n=181)
“Made me feel accountable.”
“[An] electronic conscience”
Texts constantly reminded
me about my plan to quit.”“That you can [SMS] whenever you
are feeling the urge to smoke and in
that time frame you are actually not
smoking...”
“Someone kind of there with you…”
“Like a constantly concerned friend”
“Texts gave good
ideas on how to fight
cravings ….”
Abroms et al. 2013

25. 0 5 10 15 20 25 30 35 40 45 50
Other/Not clear
Message Tailoring
Text as a Trigger
Technical Issues
Message Timing
Content/Info
Lacked Personal Interaction
Message Frequency
Nothing
6.7
2.4
2.9
3.8
5.3
6.7
7.2
18.2
46.8
Percent (%)
What Did You Dislike About Text2Quit? (1 Month)
(n=173)
“OMG. TOO MANY
TEXTS PER DAY.”
“I would like it more
if there was an
actual coach ...”
“Sometimes I would be doing really
good…then I would get a text and it
would make me start craving and
thinking about smoking.”
Abroms et al. 2013

26. Design Considerations
+Spohr et al. 2015; ^Head et al. 2014
Effect
•Message tailoring and
personalization ^
•Decreasing vs. fixed
message frequency ^
No Effect
•Text plus other
modality. +^
•Extra protocols of
messages
•On Demand messages
•Social/peer to peer
messages

27. Smartphone Apps

28. Sampling Process
100,000+
Apps in
iTunes Store
71
Apps
52
Apps
47 Apps in
Sample
Power Search for “quit smoking”,
“stop smoking”, and “smoking
cessation”
Assess
relevance
from app
description
Download available apps

29. Google App Installs (2015)
 3,025,000-12,302,000 installs from top
50 “Quit Smoking” Apps since end
2012

30. Popular App Types:
iPhone and Android
N=98
Other = informational brochure, substitute cigarette,
game, lung health tester

31. Calculator: QuitNow!

32. Game: Cigarette Fighter

33. Evidence: Cessation programs
should:
Ask for tobacco use status
Advise every user to quit
Assess willingness to quit
Assist with a quit plan
 Recommend approved meds
 Practical counseling
 Intra-treatment social support
Connect to a quitline
Enhance motivation
Arrange for follow-up

34. Popular Smoking Cessation
Apps
Overall Low Adherence: 12/42
Present in Apps
(>50%)
 Interactive
 Personalized
Advice to Quit
 Ask for tobacco
status
Lacking in Apps (<20%)
 Practical counseling on how to
quit (19.4%)
 Recommend meds (4.1%)
 Connecting to a quitline (0.0
%)
 Social support (17.3%)
 Text alerts (12.2%)
Abroms et al. 2013
N=98

35. Emerging Evidence
CBT 28-day program:
Ubhi HK1, Michie S, Kotz D, Wong
WC, West R. 2015
Acceptance & Commitment Theory:
Bricker JB, Mull KE, Kientz JA,
Vilardaga R, Mercer LD, Akioka KJ,
Heffner JL 2014

36. Quit Ninja: Craving manager:
Personalized motivations that improve
over time
(Beckford et al.)

37. Social Media

38. Social Media: Fan Pages
 Pages
 Groups
 Apps

39. Twitter Groups
RANDOMIZED
CONTROLLED TRIAL OF
TWEET2QUIT FOR
SMOKING CESSATION
Private group with two daily
msg:
(1) a group discussion topic,
(2) feedback on prior day
tweeting
Outcome: 20% for control and
40% for Twitter participants
(Pechmann et al. 2015)

40. Facebook: Groups
Ramo et al. , 2013

41. Facebook app: Ubiquitous
Cobb et al. , unpublished
N=9000
• randomized to
12 conditions
Outcome:
diffusion through
social network

42. Content Analysis Facebook
Apps (Jacobs et al. 2014, JMIR)
 N=9
 apps fell into three broad categories: public pledge to quit (n=3),
quit-date-based calculator/tracker (n=4), or a multicomponent
quit smoking program (n=2).
 Allowed app-related posting within Facebook (ie, on self/other
Facebook profile), had a within-app "community" feature (n=4)
 Adherence index summary scores among Facebook apps were
low overall (mean 15.1, SD 7.8, range 7-30)
 Untapped opportunity

43. Electronic Health
Records (EHR)

44.  In the US, high adoption of electronic health records (EHR),
especially among large clinical practices.
 Meaningful use /ACA requires adoption of EHR and inclusion of
smoking status field
 For smoking cessation, could be used :
 During clinical visit, to remind clinicians to record tobacco use, to
give brief advice to quit, to prescribe medications and to refer to
cessation counseling.
 To create a registry of smokers for outreach
 Link to the provision of electronic cessation programs
 Do they actually help patients quit?
About EHR

45. Use of Alerts
Mathias et al., 2012

46. Registry model of
prevention and health
promotion.
 Identify patients from EHR
 Send invitation via SMS
 Patient opts-in
GW MFA: Get
SMS to
improve your
health. Reply
1 to opt into
SMS quit
smoking
program &
start your
journey to a
smokefree
you.

47. N=11, most observational
With introduction of EHR,
documentation of tobacco use and
referral to cessation counseling
increased
No effect on patient smoking
cessation
High variability in how tasks were
achieved
Cochrane Review EHR
and smoking cessation
(Boyle et al. 2011)

48. Summary of EHR attributes
All Studies (N=15)
Setting
Clinic
Dental Office
Hospital
Mixed
12 (80%)
1 (6.67%)
1 (6.67%)
1 (6.67%)
Type of EHR
EPIC
Logician
VistA
Practice Partner
Not specified
3 (20%)
2 (13.33%)
1 (6.67%)
1 (6.67%)
8 (53.33%)
Use of Alert 6 (40%)
Presence of Best Practice Advisory 2 (13.33%)
Clinical Decision Support Features
Ask for tobacco status
Assess willingness to quit
Advise every user to quit/Brief Treatment
Referral to Counseling
Assist with patient education (materials)
Assist via referral to quitline
Assist with medication ordering
Arrange follow-up
15 (100%)
8 (53.33%)
6 (40%)
7 (46.67%)
5 (33.33%)
7 (46.67%)
9 (60%)
3 (20%)
Presence of Order set 7 (46.67%)
Shindler-
Ruwisch,
Bernstein, &
Abroms ; in
progress

49. Apple HealthKit
 Personal health record
 EHR (Epic) can read data
points patient is willing
to share
 Trials underway

50. Conclusions

51. Summary
I. Use of technology: high &
growing
II. Current uses and Evidence
• Text Messaging Programs
(14)
• Smartphone apps (3)
• Social Media (3)
• Electronic Health Records
(11)

52. Challenges
 More research
 Do new programs/platforms work? How to optimize
them?
 Integration with each other and with health systems
 Not either or: Don’t forget that we have access to people
too
 Privacy & Security
 Balance patient privacy with care
 Phenomena of “On and Off the Grid”

53.  Reach. Opportunity to Reach people where they are
 Efficacy. Opportunity to supplement in-person
clinician, phone counseling and other traditional
models
 Efficacy. Opportunity to create new behavior change
models (and theories!)
 Tracking and feedback
 Timing as secondary to content
 Social support, influence, norms
 Gaming
Opportunity

54.  Integration with health systems
 EHR & health educators as designers
 Packs of cigarettes with mCessation on the
warning label
 Next Generation of Programs
 Smartphone apps integrated with texting
 Sensors—lighters to track opening a pack
of cigs; CO monitors for feedback on
phones
 Social Media
 Avatars/Games
 iWatch apps
The future…
To quit, text
“Quit” to 47848

55. BeFree Study Team:
Leah Leavitt, MPH(c), Jennifer
Schindler-Ruwisch, MPH, Laura
Macherelli, MPH(c)
Smartphone App Analysis
Team:
Lee Westmaas PhD (ACS),
Jeuneviette Bontemps-Jones
(ACS), Rathna Ramani MPH
New Mexico Quitline Team:
Phil Carrol, Kelly Carpenter
(Alere), Booke Magnussun
(Alere), Judy Mendel MPH
Thank-you !
Acknowledgements:

56. References & Selected Readings
 Abroms LC, Ahuja M, Kodl, Y, Thaweethai L, Sims J, Winickoff J, Windsor RA. (2012a)
 Text2Quit:results from a pilot test of a personalized, interactive mobile health smoking
 cessation program. Journal of Health Communication (2012).

 Abroms LC, Ahuja M, Windsor RA. (2012b). Text2Quit:results from a randomized trial of a personalized, interactive mobile health smoking cessation program. Presented at SRNT,
2013.

 Abroms LC, Padmanabhan N, Evans WD. (2011a). Mobile Phones for Health Communication to
 Promote Behavior Change. eHealth applications: Promising strategies for behavior change. Noar, S. M., & Harrington, N. G. (Eds.). New York: Routledge, (in-press).

 Abroms LC, Padmanabhan N, Thaweethai L, Phillips T. (2011b). A content analysis of iPhone
 apps for smoking cessation. American Journal of Preventive Medicine. 40(3):279-85.

 Brendryen H, Drozd F, Kraft P. A Digital Smoking Cessation Program Delivered Through
 Internet and Cell Phone Without Nicotine Replacement (Happy Ending): Randomized Controlled Trial. J Med Internet Res. 2008; 10(5):e51.

 Cole-Lewis H, Kershaw T. Text messaging as a tool for behavior change in
 disease prevention and management. Epidemiologic Rev. 2010; 32(1):56-69.

 Free C, Knight R, Robertson S, Whittaker R, Edwards P, Zhou W, Rodgers A, Cairns J, Kenward MG, Roberts I. (2011). Smoking cessation support delivered via mobile phone text
messaging (txt2stop): a single-blind, randomised trial. Lancet. 378(9785):49-55.

 Free et al. 2013.Review of mHealth. Plos One.

 Guide to Community Preventive Services. (2011). Increasing tobacco use cessation: mobile phone-based interventions. Accessed on 2/22/12 at :
http://www.thecommunityguide.org/tobacco/cessation/mobilephone.html

 Naughton F, Prevost AT, Gilbert H, Sutton S. (2012). Randomized Controlled Trial Evaluation of a Tailored Leaflet and SMS Text Message Self-help Intervention for Pregnant Smokers
(MiQuit). Nicotine Tob Res. Feb 6.

 Rodgers A, Corbett T, Bramley D. Do U Smoke after TXT? Results of a randomized trial of smoking cessation using mobile phone text messaging. Tobacco Control. 2005;14(4): 255-
261.

 The Quit Group. Evaluation of the first year of the Txt2Quit Services (Online) July 31,
 2009: [Cited: March 2011]Available at: http://www.quit.org.nz/file/research/FINAL%202008-09%20Txt2Quit%20evaluation%20report%2020090731.pdf

 Whittaker R, Borland R, Bullen C, Lin RB, McRobbie H, Rodgers A. Mobile
 phone-based interventions for smoking .The Cochrane Library, 2009;(4).

 Whittaker R, Maddison R, McRobbie H. A Multimedia Mobile Phone-Based Youth Smoking Cessation Intervention Findings From Content Development and Piloting Studies, Journal
of Medical Internet Research, 2008;10(5): e49.

 Whittaker R. et al. The Cochrance Library, 2012.

57. {
and non-conscious
processes
-Elephant and the
Rider-

58.  Five broad purposes for use of social media in public
 health/health promotion have been proposed: (a)
communicate
 with consumers for market insights (Centers
 for Disease Control and Prevention [CDC], 2010, Kruse,
 2010); (b) establish and promote a brand with
consumers
 (Kruse, 2010); (c) disseminate critical information
(CDC,
 2010); (d) expand reach to include broader, more
diverse
 audiences (CDC, 2010); and (e) foster public
engagement
 and partnerships with consumers (CDC, 2010).
Types of uses in health
promotion

59.  social media as evidenced by the finding that 60% of
 state health departments now use at least one
application
 (Thackeray, VanWagenen, Koch Smith, Neiger, &
Prier,
 2011). In addition, one third of adults use social
media to
 access health information, and nearly 80% of
physicians
 who consult with patients online use social media
channels
 to create or share medical content (Hughes, 2010).
Use of social media for
health (Neiger et al. 2013)

60. Games

61. Game
 A game is a rule-based activity that involves
challenge to reach a goal and that provides
feedback on progress made toward that goal
(Leiberman 2011)
 Rules
 Goals
 Feedback

62. What is Gamification?
 Game design principles applied to
non-games
 Goal: engage with the audience
 Goal: encourage desired behaviors
 Result: mastery and autonomy
 Result: transform routine into
excitement

63. Players told to crush as many virtual cigarettes as possible. Players encountered the
targets while wandering through a fictional medieval castle depicted on a computer
screen. By the end of the 12-week support program, 15% of the cigarette crushers said
they quit smoking, compared with just 2% of the ball-gripping group. (Girard 2009)