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Am J Prev Med. Author manuscript; available in PMC Jul 12, 2012.
Published in final edited form as:
PMCID: PMC3395318
NIHMSID: NIHMS266329

iPhone Apps for Smoking Cessation

A Content Analysis

Abstract

Background

With the proliferation of smartphones such as the iPhone, mobile phones are being used in novel ways to promote smoking cessation.

Purpose

This study set out to examine the content of the 47 iPhone applications (apps) for smoking cessation that were distributed through the online iTunes store, as of June 24, 2009.

Methods

Each app was independently coded by two reviewers for their (1) approach to smoking cessation and their (2) adherence to the U.S. Public Health Service’s 2008 Clinical Practice Guidelines for Treating Tobacco Use and Dependence. Apps were also coded for their (3) frequency of downloads.

Results

Apps identified for smoking cessation were found to have low levels of adherence to key guidelines in the index. Few, if any, apps recommended or linked the user to proven treatments such as pharmacotherapy, counseling, and/or a quitline.

Conclusions

iPhone apps for smoking cessation rarely adhere to established guidelines for smoking cessation. It is recommended that current apps be revised and future apps be developed around evidence-based practices for smoking cessation.

Introduction

Mobile phones have shown some promise in helping people quit smoking and modifying other health behaviors.1,2,3,4 Most of these phone-based interventions have relied on the text-messaging feature of mobile phones and consisted of a series of short, and sometimes interactive, set of text messages that guide a person through the process of behavior change.

However, with the proliferation of smartphones, there are new possibilities for using mobile phones as tools for health promotion. Smartphones have powerful operating systems that can run computer programs or applications (“apps”), in addition to the standard features of mobile phones.5,6 Among smartphones, the iPhone is notable because since its release in 2007, third parties have been able to create apps for the iPhone operating system and distribute them to the public through a common online website, the Apple iTunes store. To date, the Apple iTunes store has released over 100,000 iPhone apps, which have been downloaded by consumers over three billion times.7,8 Of the applications that have been released, 20 have previously been identified as smoking cessation apps.9

Few studies have examined the content quality of iPhone applications for a given health behavior or condition. This study examines the content of existing iPhone apps as they apply to smoking cessation. Of interest is the degree to which these apps adhere to established best practices in smoking cessation, their popularity among iPhone users, and the relationship between these variables.

Methods

A list of applications was collected on June 24, 2009, using the Power Search function of iTunes version 8.1, available for download at www.apple.com/itunes. The search was restricted to apps compatible with the iPhone. The phrases “quit smoking”, “stop smoking”, and “smoking cessation” were used as search queries.10 The search initially identified 62 unique apps. Apps that included a basic and deluxe version were counted as separate apps in the event that they might differ in their smoking cessation attributes. Of the 62 apps, 10 were excluded because their description in the iTunes store indicated that were irrelevant for reducing or quitting smoking (e.g., an app about preparing barbequed foods which was retrieved with “quit smoking”); Four were eventually removed from the sample because they were no longer in the iTunes store at the time of downloading; One app was removed because the basic and deluxe versions proved to be identical. The final sample consisted of 47 apps, which were downloaded to an iPhone and analyzed.

Each app was coded for its primary approach to smoking cessation, based on categories identified by the National Tobacco Cessation Collaborative.9 Apps were categorized into: (1) “calculators” that generally tracked dollars saved and health benefits accrued over time since quitting, (2) “calendars” that generally tracked days until and after the quit date, (3) “hypnosis” that used hypnosis techniques for smoking cessation, (4) “rationing” that limited the numbers of cigarettes and/or the time in which cigarettes could be smoked, or (5) “other” for apps that did not primarily fit into one of these categories or used multiple categories. Each app was independently categorized by two coders with no disagreement between coders.

Apps were also coded for their level of adherence to the U.S. Public Health Service’s 2008 Clinical Practice Guideline for Treating Tobacco Use and Dependence.11 To measure adherence to the Clinical Practice Guidelines, an index of 20 items was developed, which were adapted from an index created by Bock et al.12 While guidelines developed for a clinical setting may not be appropriate for a mobile-phone app, the Clinical Practice Guidelines were used because they are a leading set of guidelines, have been successfully applied in past to computer-mediated smoking cessation programs12, and given the newness of apps on mobile phones, no other mobile-specific set of guidelines exist.

The items included in the adherence index are shown on the left side of Table 2. Each app was independently coded by two reviewers on each of the 20 guidelines using a scale which ranged from 0 to 3. A 3 indicated that the feature was fully present, and a 0 indicated that it was not present at all. For example, for the guideline to “recommend the use of approved medications”, apps that did not mention any approved medications received a score of 0, while apps that made a weak recommendation for approved medications received a score of 1, a clear recommendation received a score of 2, and a clear and strong recommendation received a score of 3. The two coders were found to be in agreement 86.6% of the time. Where coding scores differed by 1 point (9.9 %), the two scores were averaged. Where coding scores differed by 2 or more points (3.5 %), a third reviewer (LA) was used to resolve differences. The maximum possible score on the index was 60 for each app.

Table 2
Percentage of Apps (and Numbers of Apps) Exhibiting Strong Adherence to Guidelines, Rank Ordered by Guideline

Popularity was measured by looking on July 23, 2009 at the frequency of downloads of each app. Information about downloads was obtained from the iTunes store using the iTunes basic search function. For a given search term, this search function lists apps by name and provides information about each app, including “Popularity”, a measure of downloads since the app was released, which is depicted with vertical bars. Because of the design of this search function, searches can be obtained for only one search term at a time (e.g., quit smoking) and information is provided on only the relative downloads of apps within a given search term, that is, on how much a given app is downloaded relative to the other apps retrieved by the same search term. (Information on the actual number of downloads for apps is not available). Levels of downloads are updated daily with information from the previous day’s downloads (iTunes Store Customer Support, Apple, personal communication to Dr. Abroms, 3/3/2010).

A search was conducted for the term, “quit smoking”, which had originally retrieved the highest number of apps. This search identified 52 total apps, of which 30 were part of the original sample. A count was made of the vertical bars under the “Popularity” header associated with each of the apps in the sample. These values, which ranged from 1 to 36, served as the measure of download frequency for the apps in the current sample.

Results

The characteristics of the 47 smoking cessation apps included in the analysis are presented in Table 1. The mean adherence index score for all apps in the sample was 7.8 and adherence scores ranged from 0 to 30 of a total of 60 points. The mean price for an app was $1.82 and prices ranged from free to $9.99. Most apps used a calculator approach (31.9 %), followed by a calendar (27.7 %), rationing (10.6 %), hypnosis (6.4%), and other (23.4 %) approach. Of the apps that were categorized as using an “other” approach (n=11), apps tracked the number of cigarettes smoked daily (n=3), provided virtual cigarettes on the iPhone as a substitute for real ones (n=2), used visualization techniques to remove the pleasant associations of smoking (n=2), provided a way to connect to support for quitting (n=1), and provided a mix of various approaches (n=3). All deluxe versions of apps were found to have the same total adherence score as the basic versions (n=8), in spite of the fact that the deluxe versions offered additional features and charged more.

Table 1
Characteristics of Smoking Cessation Apps, Rank Ordered by Adherence Index Score

To understand which guidelines were strongly followed across apps, an analysis was conducted where only apps that earned adherence scores of 2 or higher for a particular guideline—indicating the feature was “mostly” or “fully” present—were included (See Table 2). This analysis indicates that on average, only 11.3% (SD=13.6) of apps strongly followed a given guideline, and that of app types, calculator apps were most successful in adhering to the guidelines while calendar apps were least successful. None of the apps were found to have strongly followed the guidelines to: ask a user for their tobacco use status, assess their willingness to quit, arrange for a follow-up, recommend the use of approved medications, and recommend the use of counseling and medication to quit smoking. Also noteworthy was that only 4.3% of apps strongly followed the guideline to connect a user with a Quitline and only 8.5% of apps made use of intra-treatment social support. On the other end of the spectrum, one in four apps strongly followed the guideline to enhance motivation by discussing the rewards associated with quitting, often by presenting personalized information on the health benefits and money saved associated with quitting (See Figure 1 for an example).

Figure 1
iQuit – Stop Smoking Counter: Example of a calculator app that provided the user with a personalized readout on health and monetary savings based on an entered quit date and quantity of cigarettes smoked per day.

In addition to adherence to recommended practices, of interest was the popularity of smoking cessation apps, as measured by the relative frequency of app downloads associated with the search term “quit smoking” (n=30). Of apps in the current sample, the top 5 downloaded apps in rank order were: Electric Smoke, Custom Hypnosis PLUS, Days Until, Daily Tracker: Track Life, and Big Day Event Countdown. These 5 apps—which were largely calendar (60%) and hypnosis (20%) apps—accounted for 67.8 % of downloads in the sample. Overall, a slight negative correlation was observed whereby apps that were more frequently downloaded were less likely to be adherent (R=−0.20; p<0.05).

Since 4 of 5 of these apps were not designed specifically to help someone quit smoking, and therefore could have been downloaded by users for modifying behaviors or achieving goals other than smoking cessation (e.g., weight loss), the analysis was further restricted to apps which were specific to quitting smoking, as indicated by a score of 2 or higher on this item in the index. From this restricted analysis (n=20 apps), the top downloaded smoking cessation apps in rank order were: Custom Hypnosis PLUS, Quit Smoking Now with Max Kirsten, My Stop Smoking Coach with Allen Carr, and Quit Smoking—Cold Turkey (Lite Version). These apps accounted for three fourths of downloads of apps which were specific to quitting smoking in the current sample. The top 2 apps, which were both hypnosis apps—-Custom Hypnosis PLUS and Quit Smoking Now with Max Kirsten—accounted for over half (55.4%) of downloads. These apps consisted of audio recordings (20–45 minutes long) of a hypnotherapist talking about relaxing and quitting smoking, while soothing music was played in the background.

Discussion

iPhone apps for smoking cessation available in mid-2009 had low levels of adherence to proven strategies for smoking cessation. Hypnosis and calendar apps that tracked days until and after user’s quit date dominated what users chose to download and apps that were more frequently downloaded had the lowest adherence scores.

Few apps referred the user to a recommended treatment, and none strongly endorsed the use of approved medications or the combination of counseling and medication. Apps largely did not connect users to anything outside of the app, like a quitline or clinic, or provide opportunities to reach out to friends and family for social support. These omissions represent serious weaknesses of existing apps for smoking cessation. Given current consumer demand for apps for a wide range of purposes13, these weaknesses should be recognized as both a missed opportunity to provide iPhone users with evidence-based smoking cessation aids and as a setback for the promotion of evidence-based smoking cessation methods11,14,15.

The finding that apps that were more frequently downloaded had lower scores on the total adherence index, is disappointing but not surprising. Indeed, over half of downloads for the smoking-specific apps associated with the term “quit smoking” in the current sample were found to be for hypnosis apps, a finding that is consistent with other literature on what consumers seek out for smoking cessation.16,17

In considering the value of iPhone apps for smoking cessation, it is noteworthy that currently iPhones or more broadly speaking smartphones have limited reach, especially among smokers. Smartphones make up 25% of the U.S. mobile phone market, one quarter of which consists of iPhone users18. Furthermore, iPhone users are a privileged group with 49% having a college education and 67% earn more than $70,000 a year.19 Given the demographics of smokers,20 it can be presumed that among iPhone users, smoking prevalence is low. However, iPhone purchases are rising among those with lower SES where smoking prevalence is higher, as consumers opt for a single mobile device for communications, Internet access, and entertainment in lieu of multiple devices.21 As smartphones reach a broader segment of the U.S. population, the reach and utility of iPhone apps for smoking cessation will grow.

The strength of this study is that it represents the first to systematically examine the content of iPhone apps for improving health behaviors such as smoking cessation. In an era where the prevalence of smartphones and their associated apps have exploded,13,18 it is important to explore the applications of these devices in promoting the public’s health, which includes promoting health behaviors such as smoking cessation.5

The weaknesses of this study include that the analysis is limited to attributes of iPhone apps based on the adherence index. Not all claims made within the apps were analyzed for accuracy, and the apps were not analyzed for their usability (or ease of use) with consumers. Additionally, because of the nature of search options in the iTunes search, it was not possible to get the download frequency data for all apps which were part of the current sample. Because the current search was limited to apps which came up for the term, “quit smoking” and omitted search results for “stop smoking” and “smoking cessation”, the current frequency data may be biased toward populations who more commonly use this term.10 Also because of limitations in the iTunes search, it was not possible to get an absolute sense of the numbers of downloads for smoking cessation apps. Finally, the scope of the analysis was limited to iPhone apps in the iTunes Store at the time of the analysis, a limitation given that apps frequently are added to and removed from the iTunes Store.

Text-messaging on mobile phones has already shown some promise in helping people quit smoking and modify other health behaviors.1,2,3,4 The iPhone and other smartphones offer the possibility of supplementing text message–based interventions with computer programs which can weave together expert systems, games, multimedia (e.g., music, video), and the Internet (e.g., email, social networking sites). While the current content analysis reveals that apps available at the time of the current study have low levels of adherence to key guidelines from the U.S. Public Health Service’s 2008 Clinical Practice Guidelines, it is hoped that future apps which are built around evidence-based practices might serve as powerful tools in smoking cessation. Therefore, a recommendation is to develop new apps and revise existing apps based on evidence-based principles, as well as the evaluation of these apps, to build understanding of how smartphones can be effective in helping people quit smoking.

Acknowledgments

This research was supported by 5K07 CA124579-02 to Dr. Lorien Abroms, awarded by the National Cancer Institute of the NIH.

Footnotes

LCA is the developer of a free iPhone app, My Quitline, which has been included in this analysis.

No other authors reported financial disclosures.

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References

1. Rodgers A, Corbett T, Bramley D, et al. Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging. Tob Control. 2005;4:255–61. [PMC free article] [PubMed]
2. Free C, Whittaker R, Knight R, Abramsky T, Rodgers A, Roberts IG. Txt2stop: a pilot randomised controlled trial of mobile phone-based smoking cessation support. Tob Control. 2009;2:88–91. [PubMed]
3. Riley W, Obermayer J, Jean-Mary J. Internet and mobile phone text messaging intervention for college smokers. J Am Coll Health. 2008;57:245–8. [PubMed]
4. Fjeldsoe BS, Marshall AL, Miller YD. Behavior change interventions delivered by mobile telephone short-message service. Am J Prev Med. 2009;36:165–73. [PubMed]
5. Patrick K, Griswold WG, Raab F, Intille SS. Health and the mobile phone. Am J Prev Med. 2008;35:177–81. [PMC free article] [PubMed]
6. Beal V. [December 8, 2009];The difference between a cell phone, smart phone, and PDA. Available at: http://www.webopedia.com/didyouknow/Hardware_Software/2008/smartphone_cellphone_pda.asp.
7. Apple. [December 8 2009];Apple announces over 100,000 apps now available on the app store. Available at: http://www.apple.com/pr/library/2009/11/04appstore.html.
8. Apple. [January 20, 2010];Apple’s app store downloads top three billion, 2010. Available at: http://www.apple.com/pr/library/2010/01/05appstore.html.
9. National Tobacco Cessation Collaborative (NTCC) Quit Smoking Apps on the iPhone. [December 8, 2009];NTCC Newsletter. 2008 Dec; Available at: http://www.tobacco-cessation.org/news_dec08.htm#spotlight.
10. Cobb NK, Graham AL. Characterizing internet searchers of smoking cessation information. [January 20, 2010];J Med Internet Res [serial online] 2006 Jul-Sep;8:e17. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2018828/?log%24=activity. [PMC free article] [PubMed]
11. Clinical Practice Guideline Treating Tobacco Use and Dependence 2008 Update Panel, Liaisons, and Staff. A Clinical Practice Guideline for Treating Tobacco Use and Dependence: 2008 Update: A U.S. Public Health Service Report. Am J Prev Med. 2008;35:158–176. [PubMed]
12. Bock BC, Graham AL, Sciamanna CN, et al. Smoking cessation treatment on the Internet: Content, quality, and usability. Nicotine Tob Res. 2004;6:207–219. [PubMed]
13. Purcell K, Entner R, Henderson N. The rise of apps culture. [October 13, 2010];Pew Internet and American Life Project. 2010 Online at http://pewinternet.org/Reports/2010/The-Rise-of-Apps-Culture.aspx.
14. Orleans CT. Increasing the demand for and use of effective smoking-cessation treatments: reaping the full health benefits of tobacco-control science and policy gains—in our lifetime. Am J Prev Med. 2007;33(6S):S340–7. [PubMed]
15. Backinger CL, Thornton-Bullock A, Miner C, et al. Building consumer demand for tobacco-cessation products and services: The National Tobacco Cessation Collaborative’s Consumer Demand Roundtable. Am J Prev Med. 2010;38(3S):S307–11. [PubMed]
16. Sood A, Ebbert JO, Sood R, Stevens SR. Complementary treatments for tobacco cessation: A survey. Nicotine Tob Res. 2006;8:767–771. [PubMed]
17. Abbot NC, Stead LF, White AR, Barnes J. Hypnotherapy for smoking cessation (Review) Cochrane Database of Systematic Reviews. 1998;(2) doi: 10.1002/14651858.CD001008. Art. No.: CD001008. [PubMed] [Cross Ref]
18. Smith A. Mobile Access 2010. Pew Internet & American Life Project. 2010 Online at http://pewinternet.org/Reports/2010/Mobile-Access-2010/Summary-of-Findings.aspx.
19. Hughes N. [December 8, 2009];New study shows iPhone users to be in a class by themselves. Available at: http://www.appleinsider.com/articles/09/06/12/new_study_shows_iphone_users_to_be_in_a_class_by_themselves.html.
20. Cokkinides V, Bandi P, McMahon C, Jemal A, Glynn T, Ward E. Tobacco control in the U.S.– Recent progress and opportunities. CA Cancer J Clin. 2009;59:352–265. [PubMed]
21. comScore. [December 8, 2009];In tough economy, lower income mobile consumers turn to iPhone as internet & entertainment device. http://www.comscore.com/Press_Events/Press_Releases/2008/10/Lower_Income_Mobile_Consumers_use_Iphone/(language)/eng-US.
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