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Despite promising data in Western countries, there is a dearth of research into the efficacy of text messaging-based smoking cessation programs in other settings, including the Middle East, where smoking prevalence rates are higher.
This paper reports cessation rates observed in SMS Turkey, a text messaging-based smoking cessation program for adult smokers in Ankara, Turkey.
This study was a small-scale, parallel-group randomized controlled trial (RCT) conducted in Ankara, Turkey. Participants were adult daily smokers who were seriously thinking about quitting in the next 15 days and living in Ankara, Turkey. The text messaging intervention, SMS Turkey, provided 6 weeks of daily messages aimed at giving participants skills to help them quit smoking. Messages were sent in an automated fashion, except 2 days and 7 days after the initial quit day. On days 2 and 7, the research assistant manually assigned participants to content “paths” based on whether they were still not smoking or had relapsed. The control arm received a brochure that provided similar information about smoking cessation. The main outcome measure was self-reported 3-month sustained abstinence, verified by carbon monoxide (CO) readings. Neither participants nor researchers were blinded to arm assignment.
The 151 participants were randomly assigned to 1 of 2 groups: 76 to the SMS Turkey intervention group and 75 to the brochure control group. Using intention to treat, all 151 participants were included in analyses. Three-month cessation trends were not significantly higher in the intervention group: 11% intervention vs 5% control had quit (χ2
1=1.4,
Although the study was not powered to detect statistically significant differences, as the primary aim was to provide estimates of effect size that could be used to better inform a power analysis for a larger trial, findings provide optimism that SMS Turkey may be able to affect quitting rates in environments with high smoking prevalence, such as Ankara, Turkey. The SMS Turkey software program did not work as well as it did 2 years previous. The system will need to be updated to maintain software compatibility with ongoing technology evolution.
Clinicaltrials.gov NCT00912795 http://clinicaltrials.gov/ct2/show/NCT00912795 (Archived by WebCite at http://www.webcitation.org/6Ch1cIA8l).
Cigarette smoking is a major contributor to morbidity and mortality in Turkey [
The smoking landscape changed dramatically in Turkey when it became the third country in Europe to go 100% smoke free in 2009 [
To increase cessation rates, smoking cessation programs need to be easily accessible and to reach a large number of people. An estimated 84% of adults in Turkey own a cell phone, 64% of whom use text messaging [
Preliminary data from Ankara, Turkey suggests that text messaging-based smoking cessation programs are feasible and acceptable [
This study was a parallel-group RCT conducted in Ankara, Turkey. Chesapeake IRB and Hacettepe University Ethical Committee reviewed and approved the research protocol. The clinical trial registration number is: NCT00912795.
Participants were daily smokers 18 years of age and older living in Ankara, Turkey. Additional eligibility criteria included: owning a mobile phone and having sent or received at least 1 text message in the past year; seriously thinking about quitting in the next 15 days; and not having a chronic or serious illness defined as emphysema, heart disease, or lung disease (because this population would likely require a different type of intervention).
As the capital of Turkey, Ankara is the second largest city in Turkey after Istanbul. The city is in the heart of the Anatolian peninsula and is part of a main trading route for tobacco [
As reported elsewhere [
Example of SMS Turkey content received by the intervention group (actual messages translated into Turkish).
Program arm | Example text message |
Pre-quit | When and why do you smoke? Start a smoking diary. Keep track of when you smoke, what you're doing (the activity), how you feel, and your craving (from 1-3). |
Quit day | Withdrawal symptoms are unique to everyone. Frustration, impatience, and depression are common but usually only last a week or two. |
Early quit | Treat every day like your quit day. Pretend as though it is the first day without cigarettes and be ready for temptation. |
Late quit | Call your “special supporter” and make plans for your 2-week anniversary—it's just 3 days away! |
Relapse | Becoming a non-smoker is like learning to ride a bike—it's hard at first and then you learn how to do it—and enjoy the ride! |
Encouragement | Whatever you decide about smoking, believe in yourself. You CAN quit smoking if you put your mind to it and have a plan for success. |
Previous research into the efficacy of telephone quit lines conducted in the United States suggests that most smoking relapse occurs within 2 days of quitting, and at 7 days, the relapse curve begins to flatten out [
Intervention participants began receiving program messages the day after enrollment and continued to receive messages daily through the end of the program. The frequency that participants received messages changed over the course of the program: participants generally received 5 messages per day in the pre-quit phase and then received more messages as the quit day approached. The highest number of messages was sent on the quit day and the day after; and then the number of messages began to taper down. In the last week of the program, participants were sent 1 message per day. Depending on the participant’s content path, the total number of messages received ranged from 91 (for those assigned to the encouragement arm) to 146 (for those who relapsed and then were assigned to the late quit messages).
Intervention messages were created in English, translated into Turkish, and then back-translated to ensure an accurate and appropriate translation. Messages were unidirectional: participants received but did not respond to messages. Research staff did not prompt or remind participants to engage with the intervention.
Previous text messaging-based smoking cessation trials have included a minimal contact control group that received 1 text message per week reminding them they were in the study [
The primary outcome measure was sustained abstinence 3 months after quit day, confirmed with a carbon monoxide (CO) reading of 8 ppm or less [
Secondary outcome measures included: 7-day and 28-day point prevalence of smoking behavior at 3 months; CO-verified 7-day point prevalence at 4 weeks; and reduction in cigarettes per day for those who are smoking at 3 months. Program acceptability measures included how well intervention participants liked the program and how likely they were to recommend it to others. Participants were also asked if they had suggestions to improve the program and, if so, what the improvement would be.
Covariates included smoking behavior, quitting characteristics, and psychosocial characteristics.
Participants provided information about their smoking history (eg, age at time of first cigarette) and smoking dependence [
At baseline, participants were asked how important quitting was and how confident they were that they would be able to quit smoking [
Social support is a significant factor in successful cessation efforts [
We targeted a sample size of 150 participants for feasibility reasons based on the project budget and timeline.
Participants chose 1 of 2 identical mailing envelopes. Inside, a slip of paper read either “SMS Turkey” (intervention group) or “brochure” (control group). Neither the participant nor the researcher knew which slip of paper was in each envelope.
An imbalance favoring the intervention arm was detected after approximately 100 participants were enrolled. The procedure was then modified so that the RA pulled a slip of paper from a hat that read either “SMS Turkey” or “brochure.” To ensure an equal number of participants in each arm, the number of slips of paper was equal to the number of places that remained in the intervention and control groups.
Participants were told that researchers had developed 2 different programs to help people quit smoking and that the aim of the study was to see if the programs help people quit. The intervention of interest was not specified. Once allocated to a particular arm, neither the RA nor the participant was blind to the participant’s arm assignment.
Participants were recruited and randomized between December 14, 2010, and June 16, 2011, through in-person outreach at local shopping malls and advertisements in local newspapers. Additionally, flyers were posted at Hacettepe University. Smokers indicated their interest by either calling the study office or speaking directly with the RA at the shopping mall. An in-person meeting was then scheduled, during which the RA explained the study, confirmed eligibility criteria, obtained informed written consent, and collected baseline data. The RA also set the participant’s quit day to be 15 days after enrollment. This time frame was chosen to align with the 14-day pre-quit phase for those assigned to the intervention group, although a quit day was set for all participants regardless of their arm assignment. Given that participants needed to be seriously thinking about quitting in the next 15 days to be eligible, this quit date seemed to be acceptable to all participants. The RA encouraged all participants who smoked 10 cigarettes or more per day to consider pharmacotherapy, regardless of their study arm.
Participants had contact with a human being during enrollment, at 2 and 7 days after their quit day (intervention participants only), at data collection follow-ups, and whenever there were technology problems (intervention participants only). Research incentives are not culturally normative in Turkey, so we did not use them in our study.
The RA collected self-reported survey data and CO readings, which detect cigarette smoking in the previous 24 hours, at the study office at baseline, at 4 weeks after quit day, and at the 3-months follow-up point. We measured program acceptability among intervention participants at 4 weeks. This time point was chosen over the 3-month follow-up point so that participants would have a stronger memory of the program experience.
Participants completed the survey online in a private room at the study office. The survey was pilot tested for validity when delivered online prior to the RCT: 75 adult smokers completed the survey online and 75 completed a paper-and-pencil version of the survey. Responses were similar across mode (unpublished data). If the participant could not come to the office at follow-up, the RA queried smoking status over the telephone by asking the same question included in the survey.
Analyses were presented in 2 ways. Intent-to-treat (ITT) analyses included all randomized individuals in the analysis (all participants lost to follow-up were assumed to still be smoking). Per-protocol analyses (PPA) included only participants who completed the follow-up measures. It should be noted that PPA is a self-selected sample. Therefore, results are no longer an unbiased sample from a randomized trial. Non-responsive (ie, decline to answer) replies to variables included in the analyses are imputed using best-set regression [
As shown in
As shown in
Sample characteristics by study arm (n=151).
Personal characteristics | Control |
Intervention |
Statistical comparison |
|
|
|
Mean (SD) |
Mean (SD) |
|
|
|
|
|
|
|
|
|
|
Age (range 19-62 years) | 35.6 (10.3) | 36.1 (9.5) |
|
0.76 |
|
Female | 32.0% (24) | 46.1% (35) | χ2 1=3.1 | 0.08 |
|
Low income |
49.3% (37) | 30.3% (23) | χ2 1=5.7 | 0.02 |
|
Married | 65.3% (49) | 55.3% (42) | χ2 1=1.6 | 0.21 |
|
Low educational attainment |
50.7% (38) | 36.8% (28) | χ2 1=2.9 | 0.09 |
|
|
|
|
|
|
|
Average number of cigarettes smoked per day |
20.4 (9.2) | 18.7 (7.2) |
|
0.21 |
|
Age at first cigarette |
17.1 (3.6) | 17.5 (3.7) |
|
0.48 |
|
Fagerström score |
4.9 (2.5) | 4.8 (2.3) |
|
0.79 |
|
Smoking triggers |
38.3 (9.2) | 41.9 (7.3) |
|
0.01 |
|
Difficulty not smoking when faced with stressors |
32.4 (7.8) | 34.8 (5.8) |
|
0.03 |
|
Good things about smoking |
5.8 (2.2) | 5.9 (2.7) |
|
0.66 |
|
Bad things about smoking |
33.1 (8.0) | 35.5 (6.2) |
|
0.04 |
|
Narghile smoking (ever in the past year) | 24.0% (18) | 25.0% (19) | χ2 1=0.02 | 0.89 |
|
Smoker living in the household | 48.0% (36) | 42.1% (32) | χ2 1=0.5 | 0.47 |
|
|
|
|
|
|
|
Importance of quitting to self (range 4-10) [ |
9.0 (1.4) | 8.9 (1.6) |
|
0.71 |
|
Confidence in one's ability to quit (range 0-10) [ |
6.0 (2.5) | 6.0 (2.4) |
|
0.99 |
|
Number of quit attempts in the past year (range 0-5+) | 2.4 (1.5) | 2.4 (1.5) |
|
0.93 |
|
Number of reasons to quit (range 1-8) | 2.7 (1.7) | 2.9 (1.6) |
|
0.42 |
|
Number of concerns about quitting (range 1-10) | 3.5 (2.0) | 3.9 (1.9) |
|
0.20 |
|
Good things about quitting (range 2-10) [ |
7.6 (1.9) | 8.2 (1.7) |
|
0.07 |
|
Bad things about quitting (range 6-29) [ |
18.3 (5.1) | 18.8 (4.8) |
|
0.52 |
|
Planning on using a evidence-based quitting aid | 34.7% (26) | 31.6% (24) | χ2 1=0.2 | 0.69 |
|
|
|
|
|
|
|
Social support from a “special person” |
14.9 (4.0) | 16.1 (3.6) |
|
0.05 |
|
Social support from family |
15.7 (3.5) | 16.8 (3.2) |
|
0.05 |
|
Social support from friends |
15.4 (3.1) | 16.3 (3.2) |
|
0.07 |
|
Problem drinking | 29.3% (22) | 40.8% (31) | χ2 1=2.2 | 0.14 |
SMS Turkey randomized controlled trial profile.
At 4 weeks, 78% (n=59) of intervention group and 80% (n=60) of control group participants provided cessation data. In addition, 54% (n=41) of intervention group and 55% (n=41) of control group participants provided CO data (χ2
1=0.008,
Three-month cessation rates, based upon ITT analyses, were statistically similar for the 2 arms: 11% intervention group versus 5% control group (χ2
1=1.4,
Primary and secondary outcomes of the SMS Turkey trial.
|
PPA | ITT analysis | |||||||
Control |
Intervention |
Relative risk |
Risk difference |
Control |
Intervention |
Relative risk |
Risk difference |
||
|
|
|
|
|
|
|
|
|
|
|
CO-verified sustained abstinence at 3 months | 15 (4) | 24 (8) | 1.6 (0.53-4.7) | 0.09 (-0.11-0.28) | 5 (4) | 11 (8) | 2.0 (0.62-6.3) | 0.05 (-0.03-0.14) |
|
|
|
|
|
|
|
|
|
|
|
CO-verified 7-day point prevalence abstinence at 4 weeksa | 12 (7) | 15 (9) | 1.3 (0.52-3.3) | 0.04 (-0.09-0.16) | 9 (7) | 12 (9) | 1.3 (0.50-3.2) | 0.03 (-0.07-0.12) |
|
Self-reported 7-day point prevalence abstinence at 3 months | 15 (4) | 29 (10) | 2.0 (0.70-5.6) | 0.15 (-0.06-0.35) | 5 (4) | 13 (10) | 2.5 (0.81-7.5) | 0.08 (-0.01-0.17) |
|
Self-reported 30-day point prevalence abstinence at 3 months | 15 (4) | 24 (8) | 1.6 (0.53-4.7) | 0.09 (-0.11-0.28) | 5 (4) | 11 (8) | 2.0 (0.62-6.3) | 0.05, (-0.03-0.14) |
a4-week PPA n=119 (ie, the 59 intervention and 60 control participants who provided cessation data at 4-weeks)
When the sample was stratified by biological sex (
Effect of SMS Turkey intervention on the primary outcome by subgroup.
|
PPA | ITT analysis | |||||
|
Control |
Intervention |
Statistical comparison | Control |
Intervention |
Statistical comparison | |
|
|||||||
|
|
|
|
|
|
|
|
|
Males (n=92) | 24 (4) | 17 (3) | χ2
1=0.26, |
8 (4) | 7 (3) | χ2
1=0.009, |
|
Females (n=59) | 0 (0) | 31 (5) | χ2
1= 3.9, |
0 (0) | 14 (5) | χ2
1=3.7, |
|
|
|
|
|
|
|
|
|
Light smokers |
0 (0) | 33 (5) | χ2
1=3.8, |
0 (0) | 17 (5) | χ2
1=5.3, |
|
Heavy smokers |
22 (4) | 16 (3) | χ2
1=0.25, |
9 (4) | 7 (3) | χ2
1=0.15, |
Among the 47 participants who provided data and were smoking at the 3-month follow-up, the average number of cigarettes smoked daily by intervention group participants (mean 11.9 cigarettes, SD 7.7) was lower, but not significantly so, compared to that reported by control group participants (mean 16.5, SD 9.9;
The intervention group had 2 people actively drop out: 1 no longer wanted to be in the program and 1 was unreachable because the phone number changed. The control group had 3 people drop out: 2 because they no longer wanted to be in the program and 1 was unreachable because the phone number changed.
Of the 59 intervention group participants who responded at the 4-week follow-up, 69% (n=41) said they somewhat or strongly liked the program and 78% (n=46) were somewhat or very likely to recommend the program to others. When asked what the ideal number of text messages per day would be, the average answer was 5.5 (SD 3.8, range 1-20). The most common suggestion to improve the program was to provide in-person contact, followed by the idea to provide psychological support. Other ideas included talking more about both the benefits of quitting and the dangers of smoking.
The software program used to deliver the SMS Turkey program was developed in 2009. Despite functioning well for the pilot feasibility study [
We encountered 2 serious issues with the software program during our study. First, the software program failed to send at least 1 program message to 58% (n=44) of intervention group participants. Most of the affected participants (64%) missed fewer than 5 intervention messages. Intervention participants who missed 5 or more program messages were somewhat less likely than those experiencing fewer interruptions to have a CO-verified smoking status at 3-months: 5% (n=1) vs 12% (n=7; χ2
1=0.75,
Second, 66% (n=50) of intervention participants were sent a duplicate text message at least once during the trial. Half (50%) of these participants received 22 or more duplicate messages (range 1-342 duplicate messages). Quitting rates were similar for intervention participants who received any number of duplicate text messages versus those who did not receive duplicate messages (11% versus 9%, respectively; χ2
1=0.12,
Despite the public health need to disseminate cost-effective, evidence-based smoking cessation programs, there is a paucity of research regarding the efficacy of these types of smoking cessation programs in Turkey and other countries with cultures that differ from the Western world. If we are to reduce smoking-related morbidity and mortality on a global level, this knowledge is critical in settings with high smoking prevalence rates, such as Turkey [
It is possible that other factors aside from the intervention content affected cessation rates. For example, although participants were told that 2 potentially equal programs were being tested, they may have been able to surmise that the text messaging-based program was the program of interest. If true, then perhaps participants in the text messaging-based program were more motivated and those in the brochure-based program were less motivated to quit. Because both groups received information about quitting, it seems equally possible that the participants believed the explanation that neither program was known to be better and therefore did not have expectations that the brochure should be inferior. Another potential influence on behavior may have been the interaction between the intervention participant and RA at 2 and 7 days after quit day. Even though the RA simply inquired about the participant’s smoking status, this check-in itself could have had some therapeutic effect. Indeed, it may be that text messaging programs that include brief human interaction have enhanced results. This should be studied further.
The SMS Turkey software program did not work as well as it did during the 1-arm feasibility pilot 2 years’ previous. However, it is interesting to note that indicators of program acceptability in this RCT are similar to those found in the previous study [
Of the eligible participants, 34% did not attend the initial enrollment meeting. Perhaps they did not show up because they were no longer interested in the program or reassessed their readiness to quit smoking. It is possible, however, that they were interested but could not attend because of other commitments. Subsequent trials should consider offering an online enrollment option to investigate whether this option increases the enrollment rate among eligible smokers. Also, the 40% response rate at the 3-month point is suboptimal. This response rate likely reflects the burden of needing to go to the study office to complete study measures. It may also represent the disengagement by intervention group participants who experienced significant technology problems and by control group participants who received minimal study contact. It is possible that this low overall follow-up rate introduced differential bias into the findings, but this seems less likely given that dropout rates were similar between the intervention and control groups. Future trials should consider using follow-up strategies that do not require participants to come to the office (eg, completion of the online survey at home or via text messaging; mail-in saliva
It should be noted that CO tests measure cigarette smoking in the past 24 hours. If participants reported at the 3-month follow-up that they had not had a cigarette since their quit day, but they had actually had a cigarette only a week previous, it would not be detected in the CO test. This limitation would apply equally to control group and intervention group participants, so it is unlikely that it affected the interpretation of the results. Moreover, a review of the literature suggests that biochemical verification is unlikely to change the interpretation of results in minimal contact interventions [
Another important limitation is the study’s small sample size and, therefore, limited power to statistically detect significant differences. As a preliminary RCT, the primary aim was to provide estimates of effect size that could be used to better inform a power analysis for a larger trial. As such, analyses–especially subanalyses–were underpowered. Also, the original randomization technique did not seem to be assigning participants to the study arms equally. Because the 2 arms are balanced on most factors, it appears that allocation concealment was achieved. However, without a visual recording of each enrollment meeting, there is no way to be absolutely certain.
Finally, compared to the national population of smokers in Turkey [
Data from this preliminary RCT provide reason for optimism that SMS Turkey has the potential to affect quitting rates–especially for women and light smokers. These findings provide further support for the hypothesis that, despite their brevity, smoking cessation information can be effectively communicated through a series of 160-character messages. Future research should focus on understanding mechanisms that affect the efficacy of the SMS Turkey program with the aim of eventually including it in the arsenal of evidence-based smoking cessation programs available to Turkish smokers who want to quit.
CONSORT-eHealth Checklist V1.6 [
adjusted Odds Ratio
cognitive behavorial therapy
carbon monoxide
generalized estimating equations
intent-to-treat
per-protocol analysis
research assistant
randomized controlled trial
short message service
World Health Organization
The project described was supported by Award Number R01TW007918 from the Fogarty International Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Fogarty International Center or the National Institutes of Health. The authors would like to thank the entire SMS Turkey research team, especially Dr. Jodi Holtrop for her contributions to the intervention content development, Ms. Tugba Beyazit for her rigorous implementation of the recruitment and data collection protocols, and Ms. Tonya Prescott for her data monitoring and data management contributions.
MY was the principal investigator of the project; she analyzed the data and wrote the first draft of the manuscript. TB trained the research staff and monitored data collection; she also contributed to the revision of the manuscript. JK provided consultation on methodology and contributed to the revision of the manuscript. SE was the principal investigator for the Turkey team and oversaw the implementation of the project; he also contributed to the revision of the manuscript.
None declared.