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Both mHealth and eHealth interventions for smoking cessation are rapidly being developed and tested. There are no data on use of mHealth and eHealth technologies by smokers in general or by smokers who are not motivated to quit smoking.
The aims of our study were to (1) assess technology use (eg, texting, social media, Internet) among smokers in the United States and United Kingdom, (2) examine whether technology use differs between smokers who are motivated to quit and smokers who are not motivated to quit, (3) examine previous use of technology to assist with smoking cessation, and (4) examine future intentions to use technology to assist with smoking cessation.
Participants were 1000 adult smokers (54.90%, 549/1000 female; mean age 43.9, SD 15.5 years; US: n=500, UK: n=500) who were recruited via online representative sampling strategies. Data were collected online and included demographics, smoking history, and frequency and patterns of technology use.
Among smokers in general, there was a high prevalence of mobile and smartphone ownership, sending and receiving texts, downloading and using apps, using Facebook, and visiting health-related websites. Smokers who were unmotivated to quit were significantly less likely to own a smartphone or handheld device that connects to the Internet than smokers motivated to quit. There was a significantly lower prevalence of sending text messages among US smokers unmotivated to quit (78.2%, 179/229) versus smokers motivated to quit (95.0%, 229/241), but no significant differences between the UK groups (motivated: 96.4%, 239/248; unmotivated: 94.9%, 223/235). Smokers unmotivated to quit in both countries were significantly less likely to use a handheld device to read email, play games, browse the Web, or visit health-related websites versus smokers motivated to quit. US smokers had a high prevalence of app downloads regardless of motivation to quit, but UK smokers who were motivated to quit had greater prevalence of app downloads than smokers unmotivated to quit. US smokers were significantly more likely to have a Facebook account (87.0%, 435/500) than UK smokers (76.4%, 382/500), but smokers unmotivated to quit in both countries used Facebook less frequently than smokers motivated to quit. Smokers who were unmotivated to quit were less likely to have used eHealth or mHealth platforms to help them quit smoking in the past and less likely to say that they would use them for smoking cessation in the future.
Although smokers unmotivated to quit make less use of technology than smokers motivated to quit, there is sufficient prevalence to make it worthwhile to develop eHealth and mHealth interventions to encourage cessation. Short and low-effort communications, such as text messaging, might be better for smokers who are less motivated to quit. Multiple channels may be required to reach unmotivated smokers.
The current prevalence of cigarette smoking is 18.1% in the United States [
The use of technology-based interventions, such as those delivered through Internet (eHealth) and mobile phones (mHealth), may enhance the reach of smoking cessation interventions given the lack of disparities by race, education, and income in use of these technologies [
Both mHealth and eHealth interventions have been shown to be effective for smoking cessation among those who are ready to quit [
We assessed smokers in the United States and United Kingdom because they are the 2 English-speaking markets with the most active users of iOS (iPhone/iPad) and Android devices [
Participants were 1000 current smokers: 500 in the United States and 500 in the United Kingdom. In each country, we recruited 250 smokers who did not want to quit smoking (defined as “does not plan to quit smoking cigarettes in the next 30 days”) and 250 smokers who were ready to quit smoking within 30 days and were either (1) currently investigating options for help with quitting smoking or (2) had set a quit date within 30 days. Participants were eligible if they were current, regular smokers (ie, smoke at least 3 tobacco cigarettes per day for the past year and smoked more than 100 cigarettes in their lifetime) and aged 18 years or older.
A total of 1767 people completed the initial screening questions; 572 were screened out because they did not meet eligibility criteria, 32 were removed due to random responding (see Data Analyses), and 89 were removed to ensure that the sample was representative of age and gender. Of those who were eligible to participate (n
Participants were recruited through online survey sampling conducted by Toluna, Inc. Toluna has processes in place to ensure that respondents do not misrepresent themselves to gain access to a study for which they are not eligible and that no participant takes part in any study more than once. Participants were recruited from Toluna’s panel, Toluna-affiliated partnerships, websites, and social media. All potential participants were extensively verified and underwent checks to ascertain their identity and location. Toluna also checked for duplication within the panel before permitting access to the survey. Participants received 4000 “panel points” for survey completion. These points could be redeemed for vouchers for shops and services, redeemed as cash, or used to enter prize drawings at the participant’s discretion.
All data were collected during one week in August 2014 and 21.90% (219/1000) of the sample completed the survey on their mobile phone. Toluna removed all identifiable information before transferring the dataset to investigators (ie, removal of IP addresses). Toluna adheres to and exceeds various data security protocols regarding personal identifiable information for its panelists and its research respondents and they meet all international data security protocols (eg, ISO27001). Ethical approval was obtained from The Miriam Hospital in the United States and the University of Manchester in the United Kingdom, and informed consent was obtained from participants before participation.
Demographics and smoking history were assessed with age, gender, marital status, ethnicity, employment, years of education, and number of cigarettes smoked per day. We assessed nicotine dependence with one item from the Fagerström Test for Nicotine Dependence (FTND) [
Data were cleaned before analyses. We eliminated (1) straight-liners (n=8), defined as respondents who selected the same answer option for all items within a scale so that they completed the survey as quick as possible with minimum effort and (2) speeders (n=24), who did not carefully read the questions and provided random responses as evidenced by completing the survey more quickly than the typical respondent (ie, completing the survey in less than half the median time). Toluna also checked for respondents who filled in random letters into open-ended question fields, those who inserted offensive words, and duplicate survey takers, but none were noted in our sample. The final sample size was 1000.
We analyzed the overall prevalence of technology use and frequency of use by smokers, as well as compared differences between smokers who were motivated to quit and smokers who were not motivated to quit. Independent group
Only 6.80% (73/1074) of the sample did not complete the survey. Noncompleters (n=73) were significantly more likely to be female (χ2
1=6.2,
The sample was comprised of 54.90% (549/1000) female smokers (
We assessed demographic differences between smokers who were motivated to quit and smokers who were not motivated to quit. Smokers who were not motivated to quit were significantly older (
Demographics of the total sample and by motivation to quit.
Variable | Total sample |
Smokers not motivated to quit |
Smokers motivated to quit |
χ2 1 |
|
|
Female, n (%) | 549 (54.90) | 286 (52.1) | 263(47.9) | 2.1 |
|
.14 |
Age (years), mean (SD) | 43.9 (15.4) | 50.3 (14.1) | 37.5 (14.1) |
|
14.31 | <.001 |
Ethnicity (white), n (%) | 826 (82.60) | 450 (54.5%) | 376 (45.5) | 36.6 |
|
<.001 |
<University education,a n (%) | 488 (49.10) | 253 (51.8) | 235 (48.2) | 1.10 |
|
.30 |
Employed full- or part-time, n (%) | 559 (55.90) | 245 (43.8) | 314 (56.2) | 19.3 |
|
<.001 |
Partnered/in relationship, n (%) | 613 (61.30) | 312 (50.9) | 301 (49.1) | 0.5 |
|
.48 |
Cigarettes smoked/day, mean (SD) | 16.6 (13.4) | 17.3 (12.6) | 15.8 (14.1) |
|
1.76 | .08 |
a Participants selecting “I don’t know” were counted as missing.
Of the US sample, 92.8% (464/500) reported owning a mobile phone and 75.9% (352/464) of these were smartphones (
Of those who had devices capable of text messaging, only 13.2% (62/470) reported that they never send text messages and 10.6% (50/470) reported that they never receive text messages. Of those who sent text messages, 32.8% (134/408) sent 2 to 9 texts per day and 34.1% (139/408) sent 10 or more texts per day (“supertexters”). Of those who received text messages, 33.5% (141/421) received 2 to 9 texts per day and 32.8% (138/421) received 10 or more texts per day.
Of those who reported having handheld devices (94.0% 470/500), the most common features regularly used (ie, several times per month or more) were reading email (68.3%, 321/470), browsing the Web (70%, 329/470), taking photos (66.0%, 310/470), using apps (66.6%, 313/470), and playing games (58.7%, 276/470). Additionally, 70% (350/500) of this sample had visited health-related websites on either a handheld device or computer; of these, only 34.0% (119/350) visited them regularly (twice per week or more). Of those who owned a handheld device capable of accessing the Internet, 91.4% (342/374) reported that they had previously downloaded an app; of those, 26.4% (n95/360) said that they used it for 1 month or more (but less than 1 year) and 34.4% (124/360) said that they used it for 1 year or more. Only 10.0% (36/360) reported that they downloaded an app, but used it for less than 1 day. For Facebook, 87% (435/500) reported having a Facebook account; 20.5% (89/435) checked it once per day and 49.7% (n216/435) checked it more than once per day.
There were differences in technology use and frequency of use between smokers who were motivated to quit and smokers who were not motivated to quit. Only 5.0% (12/241) of smokers who were motivated to quit reported never sending text messages versus 21.8% (50/229) of smokers who were not motivated to quit. Differences between motivation groups were maintained after demographics were controlled for in regression analysis (
Smokers who were motivated to quit were significantly more likely than smokers unmotivated to quit to regularly use their handheld devices to accomplish a variety of tasks (eg, email, browse the Web, use apps, play games;
The majority of smokers who were motivated to quit (93.8%, 195/208) reported that they previously downloaded an app and this prevalence was not significantly different from that of unmotivated smokers (88.6%, 147/166;
Prevalence of technology use among smokers in the United States and differences in technology use by motivation to quit.
Variable | Total US sample, n (%) |
Smokers not motivated to quit, n (%) |
Smokers motivated to quit, n (%) |
χ2 ( |
|
||
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|
|
|
|
|
||
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Own a mobile | 464 (92.8) | 225 (90.0) | 239 (95.6) | 5.9 (1) | .02 | |
|
Own a tablet | 249 (49.8) | 100 (40.0) | 149 (59.6) | 19.2 (1) | <.001 | |
|
Mobile is a smartphone | 352 (75.9) | 153 (68.0) | 199 (83.3) | 14.7 (1) | <.001 | |
|
Internet-enabled handheld device | 374 (79.6) | 166 (72.5) | 208 (86.3) | 13.8 (1) | <.001 | |
|
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|
|
|
||
|
Send text messages | 408 (86.8) | 179 (78.2) | 229 (95.0) | 29.1 (1) | <.001 | |
|
Receive text messages | 421 (89.6) | 190 (83.0) | 231 (95.9) | 20.9 (1) | <.001 | |
|
|
|
|
|
33.4 (5) | <.001 | |
|
|
≤1 texts per month | 31 (7.6) | 14 (7.8) | 17 (7.4) |
|
|
|
|
2-4 texts per monthb | 29 (7.1) | 22 (12.3) | 7 (3.1) |
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2-6 texts per weekc | 56 (13.7) | 35 (19.6) | 21 (9.2) |
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|
|
1 text per day | 19 (4.7) | 10 (5.6) | 9 (3.9) |
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|
2-9 texts per day | 134 (32.8) | 58 (32.4) | 76 (33.2) |
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|
|
≥10 texts per dayb | 139 (34.1) | 40 (22.3) | 99 (43.2) |
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|
32.4 (5) | <.001 | |
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|
≤1texts per month | 34 (8.1) | 17 (8.9) | 17 (7.4) |
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|
|
|
2-4 texts per monthc | 36 (8.6) | 26 (13.7) | 10 (4.3) |
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2-6 texts per weekc | 55 (13.1) | 36 (18.9) | 19 (8.2) |
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1 text per day | 17 (4.0) | 8 (4.2) | 9 (3.9) |
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|
2-9 texts per day | 141 (33.5) | 61 (32.1) | 80 (34.6) |
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|
≥10 texts per dayb | 138 (32.8) | 42 (22.1) | 96 (41.6) |
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||
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Read email | 321 (68.3) | 137 (59.8) | 184 (76.3) | 14.8 (1) | <.001 | |
|
Get directions or use navigation (eg, GPS) | 226 (48.1) | 83 (36.2) | 143 (59.3) | 25.1 (1) | <.001 | |
|
Browse the Web | 329 (70.0) | 136 (59.4) | 193 (80.1) | 24.0 (1) | <.001 | |
|
Listen to music | 276 (58.7) | 103 (45.0) | 173 (71.8) | 34.8 (1) | <.001 | |
|
Take photos | 310 (66.0) | 121 (52.8) | 189 (78.4) | 34.2 (1) | <.001 | |
|
Check the news | 270 (57.4) | 106 (46.3) | 164 (68.0) | 22.7 (1) | <.001 | |
|
Record video | 168 (35.7) | 57 (24.9) | 111 (46.1) | 22.9 (1) | <.001 | |
|
Use apps (for any purpose) | 313 (66.6) | 130 (56.8) | 183 (75.9) | 19.4 (1) | <.001 | |
|
Search for information | 315 (67.0) | 127 (55.5) | 188 (78.0) | 27.0 (1) | <.001 | |
|
Play games by yourself | 276 (58.7) | 114 (49.8) | 162 (67.2) | 14.7 (1) | <.001 | |
|
Play games with other people | 168 (35.7) | 46 (20.1) | 122 (50.6) | 47.7 (1) | <.001 | |
|
|
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|
||
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Previous app downloade | 342 (91.4) | 147 (88.6) | 195 (93.8) | 3.2 (1) | .07 | |
|
Longest used app fore |
|
|
|
7.1 (4) | .13 | |
|
|
<1 day | 36 (10.0) | 13 (8.6) | 23 (11.1) |
|
|
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|
≥1 day but <1 week | 56 (15.6) | 21 (13.8) | 35 (16.8) |
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≥1 week but <1 month | 49 (13.6) | 16 (10.5) | 33 (15.9) |
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|
≥1 month but <1 year | 95 (26.4) | 50 (32.9) | 45 (21.6) |
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≥1 year | 124 (34.4) | 52 (34.2) | 72 (34.6) |
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Facebook account | 435 (87.0) | 212 (84.8) | 223 (89.2) | 2.1 (1) | .14 | |
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15.7 (5) | .008 | |
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Never | 8 (1.8) | 3 (1.4) | 5 (2.2) |
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≤Once per month | 24 (5.5) | 17 (8.0) | 7 (3.1) |
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2-4 times per month | 26 (6.0) | 15 (7.1) | 11 (4.9) |
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2-6 times per week | 72 (16.6) | 42 (19.8) | 30 (13.5) |
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Once per day | 89 (20.5) | 48 (22.6) | 41 (18.4) |
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>Once per day | 216 (49.7) | 87 (41.0) | 129 (57.8) |
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350 (70.0) | 142 (56.8) | 208 (83.2) | 41.5 (1) | <.001 | ||
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38.5 (4) | <.001 | |
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≤Once per monthb | 125 (35.7) | 71 (50.0) | 54 (26.0) |
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2-4 times per month | 106 (30.3) | 45 (31.7) | 61 (29.3) |
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2-6 times per week | 54 (15.4) | 18 (12.7) | 36 (17.3) |
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Once per day | 34 (9.7) | 7 (4.9) | 27 (13.0) |
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>Once per dayb | 31 (8.9) | 1 (0.7) | 30 (14.4) |
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|
a Of those who sent text messages (n
b Standardized residual ≥2.58 or ≤–2.58.
c Standardized residual ≥1.96 or ≤–1.96
d Of those who receive text messages (n
e Of those who can access the Internet on their handheld device (n
f Of those who have a Facebook account (n
g Of those who visit websites related to health issues (n
Of the UK sample, 95.8% (479/500) reported owning a mobile phone and 82.9% (397/479) of these were smartphones (
The vast majority of UK smokers reported that they send (95.7%, 462/483) and receive (97.7%, 472/483) text messages. Of those who send text messages, 36.1% (167/462) send 2 to 9 texts per day and 21.4% (99/462) were supertexters. Of those who received text messages, 36.7% (173/472) received 2 to 9 texts per day and 21.2% (100/472) received 10 or more texts per day.
Of those who had handheld devices (96.6%, 483/500), the most common features regularly used (ie, several times per month or more) were browsing the Web (70.2%, 339/483), reading email (70.0%, 338/483), searching for information (68.9%, 333/483), using apps (66.5%, 321/483), and taking photos (62.1%, 300/483). Of those who ever visited health-related websites (61.0%, 305/500), 24.9% (76/305) visited them regularly (twice per week or more). Of those with Internet-enabled handheld devices (85.7%, 414/483), 86.2% (357/414) reported that they had previously downloaded an app; 26.6% (95/357) said that they used it for 1 month or more (but less than 1 year) and 34.2% (122/357) said that they used it for 1 year or more. Only 10.1% (36/357) said that they downloaded an app but used it less than 1 day; 29.1% (104/357) used it more than 1 day but less than 1 month. Of the UK sample, 76.4% (382/500) reported having a Facebook account; 20.7% (79/382) checked it once per day and 53.7% (205/382) checked it more than once per day.
There were no significant differences between smokers who were motivated to quit and smokers who were not motivated to quit in whether or not they texted; however, the prevalence of texting was very high among both groups: only 3.6% (9/248) of smokers who were motivated to quit reported never sending text messages versus 5.1% (12/235) of smokers who were not motivated to quit (
Among those who had Internet access on their handheld devices (85.7%, 414/483), smokers who were motivated to quit were significantly more likely to have previously downloaded an app (91.6%, 206/225) than smokers who were not motivated to quit (79.9%, 151/189). There were no significant group differences when demographic variables were controlled.
Smokers who were motivated to quit were significantly more likely to have a Facebook account (82.4%, 206/250) than smokers who were not motivated to quit (70.4%, 176/250). There were no significant differences between groups when demographic variables were controlled for in a logistic regression analysis. Of those who had a Facebook account, there was a significant relationship between motivation to quit and the frequency of checking Facebook. Although none of the standardized residuals were equal to or greater than 1.96 or equal to or less than –1.96, the largest difference in percentages showed that smokers who were motivated to quit were more likely to report checking their Facebook pages more than once per day than smokers who were not motivated to quit (58.3%, 120/206 vs 48.3%, 85/176).
Prevalence of technology use among smokers in the United Kingdom and differences in technology use by motivation to quit.
Variable | Total UK sample, |
Smokers not motivated to quit, |
Smokers motivated to quit, |
χ2 ( |
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Own a mobile | 479 (95.8) | 233 (93.2) | 246 (98.4) | 8.40 (1) | .004 | |
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Own a tablet | 281 (56.2) | 109 (43.6) | 172 (68.8) | 32.3 (1) | <.001 | |
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Mobile is a smartphone | 397 (82.9) | 173 (74.2) | 224 (91.1) | 23.8 (1) | <.001 | |
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Handheld device connects to the Internet | 414 (85.7) | 189 (80.4) | 225 (90.7) | 10.5 (1) | .001 | |
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Send text messages | 462 (95.7) | 223 (94.9) | 239 (96.4) | 0.6 (1) | .43 | |
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Receive text messages | 472 (97.7) | 232 (98.7) | 240 (96.8) | 2.1 (1) | .15 | |
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|
27.7 (5) | .001 | |
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|
≤1 texts per month | 41 (8.9) | 27 (12.1) | 14 (5.9) |
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|
2-4 texts per month | 38 (8.2) | 25 (11.2) | 13 (5.4) |
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2-6 texts per week | 87 (18.8) | 48 (21.5) | 39 (16.3) |
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1 text per day | 30 (6.5) | 17 (7.6) | 13 (5.4) |
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2-9 texts per day | 167 (36.1) | 72 (32.3) | 95 (39.7) |
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>10 texts per dayb | 99 (21.4) | 34 (15.2) | 65 (27.2) |
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26.3 (5) | <.001 | |
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≤1 texts per month | 32 (6.8) | 22 (9.5) | 10 (4.2) |
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2-4 texts per monthb | 48 (10.2) | 34 (14.7) | 14 (5.8) |
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2-6 texts per week | 84 (17.8) | 44 (19.0) | 40 (16.7) |
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1 text per day | 35 (7.4) | 16 (6.9) | 19 (7.9) |
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2-9 texts per day | 173 (36.7) | 84 (36.2) | 89 (37.1) |
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>10 texts per dayb | 100 (21.2) | 32 (13.8) | 68 (28.3) |
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Read email | 338 (70.0) | 139 (59.1) | 199 (80.2) | 25.6 (1) | <.001 | |
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Get directions or use navigation (eg, GPS) | 184 (38.1) | 60 (25.5) | 124 (50.0) | 30.6 (1) | <.001 | |
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Browse the Web | 339 (70.2) | 141 (60.0) | 198 (79.8) | 22.7 (1) | <.001 | |
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Listen to music | 257 (53.2) | 88 (37.4) | 169 (68.1) | 45.7 (1) | <.001 | |
|
Take photos | 300 (62.1) | 118 (50.2) | 182 (73.4) | 27.5 (1) | <.001 | |
|
Check the news | 286 (59.2) | 111 (47.2) | 175 (70.6) | 27.2 (1) | <.001 | |
|
Record video | 135 (28.0) | 35 (14.9) | 100 (40.3) | 38.8 (1) | <.001 | |
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Use apps (for any purpose) | 321 (66.5) | 129 (54.9) | 192 (77.4) | 27.5 (1) | <.001 | |
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Search for information | 333 (68.9) | 131 (55.7) | 202 (81.5) | 37.2 (1) | <.001 | |
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Play games by yourself | 254 (52.6) | 92 (39.1) | 162 (65.3) | 33.1 (1) | <.001 | |
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Play games with other people | 121 (25.1) | 34 (14.5) | 87 (35.1) | 27.3 (1) | <.001 | |
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Previous app downloadd | 357 (86.2) | 151 (79.9) | 206 (91.6) | 11.8 (1) | .001 | |
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6.8 (4) | .14 | |
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<1 day | 36 (10.1) | 13 (8.6) | 23 (11.2) |
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≥1day but <1 week | 56 (15.7) | 21 (13.9) | 35 (17.0) |
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≥1 week but <1 month | 48 (13.4) | 16 (10.6) | 32 (15.5) |
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≥1 month but <1 year | 95 (26.6) | 50 (33.1) | 45 (21.8) |
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≥1 year | 122 (34.2) | 51 (33.8) | 71 (34.5) |
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Facebook account | 382 (76.4) | 176 (70.4) | 206 (82.4) | 10.00 (1) | .002 | |
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13.0 (5) | .02 | |
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Never | 7 (1.8) | 5 (2.8) | 2 (1.0) |
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≤Once per month | 22 (5.8) | 16 (9.1) | 6 (2.9) |
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2-4 times per month | 26 (6.8) | 12 (6.8) | 14 (6.8) |
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2-6 times per week | 43 (11.3) | 25 (14.2) | 18 (8.7) |
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Once per day | 79 (20.7) | 33 (18.8) | 46 (22.3) |
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>Once per day | 205 (53.7) | 85 (48.3) | 120 (58.3) |
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305 (61.0) | 113 (45.2) | 192 (76.8) | 52.5 (1) | <.001 | ||
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15.7 (4) | .004 | |
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≤Once per month | 153 (50.2) | 69 (61.1) | 84 (43.8) |
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2-4 times per month | 76 (24.9) | 28 (24.8) | 48 (25.0) |
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2-6 times per week | 48 (15.7) | 10 (8.8) | 38 (19.8) |
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Once per day | 18 (5.9) | 6 (5.3) | 12 (6.3) |
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>Once per day | 10 (3.3) | 0 (0) | 10 (5.2) |
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a Of those who sent text messages (n
b Standardized residual ≥1.96 or ≤–1.96.
c Of those who receive text messages (n
d Of those who could access the Internet on their handheld devices (n
e Of those with a Facebook account (n
f Of those who visit websites related to health issues (n
Approximately one-quarter of smokers in the United States and United Kingdom reported that they previously used the Internet to quit smoking but the use of other technologies was low, ranging from 7.6% (38/500) for Twitter use in the United Kingdom to 15.2% (76/500) for smoking cessation app use in the United States (
There were significant differences in Internet-assisted cessation between smokers who were motivated to quit and smokers unmotivated to quit. Smokers who were motivated to quit were significantly more likely to have previously used each of the 5 assessed technologies to help them quit than smokers unmotivated to quit and these differences between groups were maintained when demographic covariates were controlled (Internet:
Across both countries, the platforms with the greatest percentage of people endorsing that they would use it to quit smoking in the future were the Internet (46.7%, 467/1000) and apps (42.7%, 427/1000) (
Previous use of technology-assisted smoking cessation among smokers in the United States and United Kingdom and differences by motivation to quit.
Previous use of technology to quit smoking | Total sample, n (%) | Unmotivated smokers, n (%) | Motivated smokers, n (%) | χ2 1 |
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Used the Internet (a website) | 131 (26.2) | 27 (10.8) | 104 (41.6) | 61.3 | <.001 |
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Joined a quit smoking program that involved text messaging | 66 (13.2) | 12 (4.8) | 54 (21.6) | 30.8 | <.001 |
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Used a quit smoking app on your phone | 76 (15.2) | 16 (6.4) | 60 (24.0) | 30.0 | <.001 |
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Used Twitter to connect with other smokers who are trying to quit | 61 (12.2) | 13 (5.2) | 48 (19.2) | 22.9 | <.001 |
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Used Facebook to connect with other smokers who are trying to quit | 74 (14.8) | 16 (6.4) | 58 (23.2) | 28.0 | <.001 |
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Used the Internet (a website) | 128 (25.6) | 23 (9.2) | 105 (42.0) | 70.6 | <.001 |
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Joined a quit smoking program that involved text messaging | 44 (8.8) | 6 (2.4) | 38 (15.2) | 25.5 | <.001 |
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Used a quit smoking app on your phone | 64 (12.8) | 7 (2.8) | 57 (22.8) | 44.8 | <.001 |
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Used Twitter to connect with other smokers who are trying to quit | 38 (7.6) | 3 (1.2) | 35 (14.0) | 29.2 | <.001 |
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Used Facebook to connect with other smokers who are trying to quit | 52 (10.4) | 8 (3.2) | 44 (17.6) | 27.8 | <.001 |
Future intentions to use technology-assisted smoking cessation among smokers in the United States and United Kingdom and differences by motivation to quit.
Future intentions to use technology to quit | Total sample, n (%) | Unmotivated smokers, n (%) | Motivated smokers, n (%) | χ2 1 |
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Use the Internet (a website) | 227 (45.4) | 87 (34.8) | 140 (56.0) | 22.7 | <.001 |
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Join a quit smoking program that involves text messaging | 157 (31.4) | 56 (22.4) | 101 (40.4) | 18.8 | <.001 |
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Use a quit smoking app on your phone | 217 (43.4) | 90 (36.0) | 127 (50.8) | 11.2 | <.001 |
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Use Twitter to connect with other smokers who are trying to quit | 113 (22.6) | 34 (13.6) | 79 (31.6) | 23.2 | <.001 |
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Use Facebook to connect with other smokers who are trying to quit | 152 (30.4) | 53 (21.2) | 99 (39.6) | 20.0 | <.001 |
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Use the Internet (a website) | 240 (48.0) | 89 (35.6) | 151 (60.4) | 30.8 | <.001 |
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Join a quit smoking program that involves text messaging | 128 (25.6) | 43 (17.2) | 85 (34.0) | 18.5 | <.001 |
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Use a quit smoking app on your phone | 210 (42.0) | 76 (30.4) | 134 (53.6) | 27.6 | <.001 |
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Use Twitter to connect with other smokers who are trying to quit | 82 (16.4) | 22 (8.8) | 60 (24.0) | 21.1 | <.001 |
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Use Facebook to connect with other smokers who are trying to quit | 129 (25.8) | 40 (16.0) | 89 (35.6) | 25.1 | <.001 |
Both mHealth and eHealth interventions for smoking cessation are rapidly being developed and tested, but to our knowledge, there are no data on use of these technologies by smokers in general or whether use differs by motivation to quit. Knowing the types of technologies that smokers engage with can help intervention planners design interventions that target smokers more effectively and efficiently. The aims of our study were to (1) assess technology use among smokers in the United States and United Kingdom, (2) examine whether technology use differs between smokers who are motivated to quit and smokers who are not motivated to quit, (3) examine previous use of technology-based assisted smoking cessation, and (4) examine future intentions to use technology-based assisted smoking cessation. The advantages of mobile platforms include the ability to implement interventions in real time and access them any time and from any place, ability to tailor to user needs (eg, content, timing, and intensity), few barriers to participation, decreased time gap between treatment and behavior, low participant burden (particularly important for smokers who are less motivated to quit), ability to provide instant support, ability to provide feedback on goal setting and achievement, capability for integration with social networking, and scalability to large populations.
Among smokers in general, we found a high prevalence of mobile and smartphone ownership, sending and receiving texts, downloading and using apps, using Facebook, and visiting websites related to health. The use of these platforms, however, has outpaced the ability to gather scientific evidence regarding their effectiveness for smoking cessation. Although more than 400 smoking cessation mobile apps were available in 2013 [
The second aim of our study was to evaluate whether use of these platforms differs between smokers who are motivated to quit and those who are not motivated to quit. Although the prevalence of texting was high in both countries, US smokers who were not motivated to quit were less likely to text than US smokers who were motivated to quit. In both countries, smokers who were motivated to quit were supertexters and unmotivated smokers tended to text less frequently. More than a quarter of our total sample and approximately one-fifth of unmotivated smokers said they would be willing to use a text message program to quit smoking in the future. The ubiquity and frequency of text messaging among smokers in general and among unmotivated smokers specifically lends support to the idea that text messaging could also be used to motivate smokers to quit, perhaps serving as a way to keep cessation “on the radar,” titrating the number of text messages upward when and if the smoker becomes motivated to quit. Creative ways to keep unmotivated smokers engaged with this process should be explored. To date, text message interventions for smoking cessation have targeted only smokers who are ready and willing to set a quit date within 30 days.
Compared with unmotivated smokers, smokers who were motivated to quit tended to use their handheld devices more often to read email, get directions, browse the Web, listen to music, take photos/video, check the news, search for information, and play games. Intervention planners could capitalize on this information by examining the most prevalent features used by smokers and how they might reach smokers through these features. For example, more than 65% smokers who were motivated to quit reported that they played games on their handheld device. Thus, gaming principles could be incorporated into mobile cessation, possibly curbing smoking urges, providing distraction during times of temptation, and promoting self-efficacy for quitting. One preliminary study has shown that a prototype of an interactive game was engaging to smokers [
App downloads and length of app use differed by motivation group and by country. In the United Kingdom, motivated smokers were more likely to have downloaded an app than unmotivated smokers, but there were no differences in the length of time that apps were used. In the United States, there were no differences between motivation groups in the prevalence of downloading apps (both >88%). Research is needed regarding what features make a smoking cessation app “sticky” (ie, has staying power with the user) and designing apps that adhere to the human-centered design principles, including health literacy [
Although the vast majority of smokers had a Facebook account (UK: 76.4%; US: 87.0%), there were significant differences by motivation to quit for UK smokers, such that motivated smokers were more likely to have an account than unmotivated smokers. Regardless of motivation to quit, more than 72% checked Facebook once per day or more. There may be several advantages to delivering health behavior interventions through Facebook [
One striking finding is that unmotivated smokers were less likely to visit health-related websites (on their computer or handheld device) than were motivated smokers. Thus, these smokers need to be reached proactively through other media channels. This parallels the recommendations that were put forth before the advent of technology, that public health impact for smoking cessation could be achieved through proactive reach through existing infrastructures where smokers are located, such as primary care [
We assessed previous use of technology-assisted smoking cessation and found that more than 25% of smokers in both countries used the Internet to quit smoking. Other technology platforms had very low prevalence (
One potential limitation of the current study is that participants were recruited online. There may be concern that this approach biases the sample to smokers who have Internet access. However, approximately 87% of the adult population of the United States and United Kingdom are Internet users [
Smoking cessation is an important public health goal, but the rate of cessation appears to have plateaued, meaning that new approaches are required. One possible approach is to devote greater efforts to understanding ways to target smokers who are not currently thinking of quitting smoking. This paper shows that although smokers who are not currently thinking of quitting make less use of technology than do smokers who are motivated to quit, sufficient numbers do use technology to make it worthwhile to develop these technologies designed to encourage unmotivated smokers to quit. Examining how health behavior change programs can capitalize on high rates of technology use is a public health priority, particularly because of the lack of disparities in the use of these technologies, relative low cost [
Fagerström Test for Nicotine Dependence
This work was funded by Cancer Research UK (Grant # C1005 A17906) and by internal funds from The Miriam Hospital while the first author was employed there. The sponsors did not have a role in the preparation or publication of this manuscript.
None declared.