Dataset Information

Game On? Smoking Cessation Through the Gamification of mHealth: A Longitudinal Qualitative Study.

ABSTRACT:

Background

Finding ways to increase and sustain engagement with mHealth interventions has become a challenge during application development. While gamification shows promise and has proven effective in many fields, critical questions remain concerning how to use gamification to modify health behavior.

Objective

The objective of this study is to investigate how the gamification of mHealth interventions leads to a change in health behavior, specifically with respect to smoking cessation.

Methods

We conducted a qualitative longitudinal study using a sample of 16 smokers divided into 2 cohorts (one used a gamified intervention and the other used a nongamified intervention). Each participant underwent 4 semistructured interviews over a period of 5 weeks. Semistructured interviews were also conducted with 4 experts in gamification, mHealth, and smoking cessation. Interviews were transcribed verbatim and thematic analysis undertaken.

Results

Results indicated perceived behavioral control and intrinsic motivation acted as positive drivers to game engagement and consequently positive health behavior. Importantly, external social influences exerted a negative effect. We identified 3 critical factors, whose presence was necessary for game engagement: purpose (explicit purpose known by the user), user alignment (congruency of game and user objectives), and functional utility (a well-designed game). We summarize these findings in a framework to guide the future development of gamified mHealth interventions.

Conclusions

Gamification holds the potential for a low-cost, highly effective mHealth solution that may replace or supplement the behavioral support component found in current smoking cessation programs. The framework reported here has been built on evidence specific to smoking cessation, however it can be adapted to health interventions in other disease categories. Future research is required to evaluate the generalizability and effectiveness of the framework, directly against current behavioral support therapy interventions in smoking cessation and beyond.

SUBMITTER: El-Hilly AA

PROVIDER: S-EPMC5099502 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Publications

Game On? Smoking Cessation Through the Gamification of mHealth: A Longitudinal Qualitative Study.

El-Hilly Abdulrahman Abdulla AA Iqbal Sheeraz Syed SS Ahmed Maroof M Sherwani Yusuf Y Muntasir Mohammed M Siddiqui Sarim S Al-Fagih Zaid Z Al-Fagih Zaid Z Usmani Omar O Eisingerich Andreas B AB

JMIR serious games 20161024 2

<h4>Background</h4>Finding ways to increase and sustain engagement with mHealth interventions has become a challenge during application development. While gamification shows promise and has proven effective in many fields, critical questions remain concerning how to use gamification to modify health behavior.<h4>Objective</h4>The objective of this study is to investigate how the gamification of mHealth interventions leads to a change in health behavior, specifically with respect to smoking cessa ...[more]

PMID: 27777216

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Project description:BackgroundGamification in smoking cessation apps has been found to improve cognitive outcomes associated with higher odds of quitting. Although some research has shown that gamification can also positively impact behavioral outcomes such as smoking cessation, studies have largely focused on physical activity and mental health. Only a few studies have explored the effects of gamification on smoking cessation outcomes, of which the majority have adopted qualitative methodologies and/or assessed engagement with apps using self-report.ObjectiveThis study aimed to explore levels of user engagement with gamification features in a smoking cessation app via in-app metrics. Specifically, the objective of this paper was to investigate whether higher engagement with gamification features is associated with the likelihood of quitting in the short term.MethodsData from a larger online study that recruited smokers seeking to quit were analyzed to address the objectives presented in this paper. The study took place between June 2019 and July 2020, and participants were primarily recruited via social media posts. Participants who met the eligibility criteria used 1 of 2 mobile apps for smoking cessation. In-app metrics shared by the developer of one of the smoking cessation apps, called Kwit, were used to assess engagement with gamification features. Out of 58 participants who used the Kwit app, 14 were excluded due to missing data or low engagement with the app (ie, not opening the app once a week). For the remaining 44 participants, mean (SD) values were calculated for engagement with the app using in-app metrics. A logistic regression model was used to investigate the association between engagement with gamification and 7-day smoking abstinence.ResultsIn total, data from 44 participants who used the Kwit app were analyzed. The majority of participants were male, married, and employed. Almost 30% (n=13) of participants self-reported successful 7-day abstinence at the end of the study. On average, the Kwit app was opened almost 31 (SD 39) times during the 4-week study period, with the diary feature used the most often (mean 22.8, SD 49.3). Moreover, it was found that each additional level unlocked was associated with approximately 22% higher odds of achieving 7-day abstinence after controlling for other factors such as age and gender (odds ratio 1.22, 95% CI 1.01-1.47).ConclusionsThis study highlights the likely positive effects of certain gamification elements such as levels and achievements on short-term smoking abstinence. Although more robust research with a larger sample size is needed, this research highlights the important role that gamification features integrated into mobile apps can play in facilitating and supporting health behavior change.

Project description:Many lifelong smokers establish smoking habits during young adulthood. A university can be an effective setting for early smoking cessation. We evaluated long-term predictors of smoking cessation among smokers in a university setting.We longitudinally followed a cohort of smokers enrolled in a university smoking cessation program in Seoul, South Korea. Sociodemographic factors, smoking-related variables, and changes in smoking habits were assessed during 6-week visit sessions and follow-up telephone interviews conducted 1 year or more later.A total of 205 participants were followed up (mean follow-up duration: 27.1 months). Cessation rates were 47.3% at the end of the visit sessions and 28.8% at follow-up. The long-term persistent smoking rate was significantly higher among individuals with peers who smoked (odds ratio [OR] = 8.64; 95% confidence interval [CI] = 1.75, 42.80), with family members who smoked (OR = 3.28; 95% CI = 1.20, 9.00), and who smoked 10 to 19 cigarettes/day (OR = 4.83; 95% CI = 1.49, 15.69). Conversely, persistent smoking was less likely among those who attended the program regularly (OR = 0.84 per visit; 95% CI = 0.72, 0.99) and attempted quitting more frequently (OR = 0.93 per attempt; 95% CI = 0.87, 0.99). Use of smoking cessation medications (varenicline or bupropion) was not significantly associated with long-term quitting (OR = 0.71; 95% CI = 0.26, 1.93).Peer influences were the strongest predictors of failure in long-term cessation among smokers who attempted to quit. Similarly, the existence of smokers in the family was negatively associated with successful quitting. Regular attendance at a smoking cessation program and a high number of attempts to quit were positively associated with successful quitting. Targeting peer and family smoking groups together rather than targeting individual smokers alone, implementing active cessation programs encouraging regular attendance, and providing comprehensive antismoking environments might be effective strategies in a university setting.

Project description:BackgroundNowadays, numerous health-related mobile apps implement gamification in an attempt to draw on the motivational potential of video games and thereby increase user engagement or foster certain health behaviors. However, research on effective gamification is still in its infancy and researchers increasingly recognize methodological shortcomings of existing studies. What we actually know about the phenomenon today stems from fragmented pieces of knowledge, and a variety of different perspectives. Existing research primarily draws on conceptual knowledge that is gained from research prototypes, and isolated from industry best practices. We still lack knowledge on how gamification has been successfully designed and implemented within the industry and whether certain gamification approaches have shown to be particularly suitable for certain health behaviors.ObjectiveWe address this lack of knowledge concerning best practices in the design and implementation of gamification for health-related mobile apps by identifying archetypes of gamification approaches that have emerged in pertinent health-related mobile apps and analyzing to what extent those gamification approaches are influenced by the underlying desired health-related outcomes.MethodsA 3-step research approach is employed. As a first step, a database of 143 pertinent gamified health-related mobile apps from the Apple App Store and Google Play Store is set up. Second, the gamification approach of each app within the database is classified based on an established taxonomy for gamification in health-related apps. Finally, a 2-step cluster analysis is conducted in order to identify archetypes of the most dominant gamification approaches in pertinent gamified health-related mobile apps.ResultsEight archetypes of gamification emerged from the analysis of health-related mobile apps: (1) competition and collaboration, (2) pursuing self-set goals without rewards, (3) episodical compliance tracking, (4) inherent gamification for external goals, (5) internal rewards for self-set goals, (6) continuous assistance through positive reinforcement, (7) positive and negative reinforcement without rewards, and (8) progressive gamification for health professionals. The results indicate a close relationship between the identified archetypes and the actual health behavior that is being targeted.ConclusionsBy unveiling salient best practices and discussing their relationship to targeted health behaviors, this study contributes to a more profound understanding of gamification in mobile health. The results can serve as a foundation for future research that advances the knowledge on how gamification may positively influence health behavior change and guide practitioners in the design and development of highly motivating and effective health-related mobile health apps.

Project description:IntroductionSmoking-related diseases are major contributors to disability and shorter life expectancy among opioid-dependent patients. Smoking prevalence is considerably higher for opioid-dependent persons than among the general population, and only a minority quit smoking in treatment settings. Studies show that pharmacological smoking cessation interventions have modest success rates. This study aimed to investigate patients' receiving opioid agonist therapy perspectives on factors affecting behavior and decisions related to smoking cessation, and their experiences with smoking cessation.MethodsThis is a qualitative study using semi-structured individual interviews. The participants were asked, among others, to elaborate on the participants' thoughts about smoking, previous attempts to quit tobacco use, and what could prompt a smoking cessation attempt. We analyzed the transcripts with systematic text condensation. The Standards for Reporting Qualitative Research and the Consolidated Criteria for Reporting Qualitative Research guidelines were followed. Opioid-dependent patients receiving opioid agonist therapy in outpatient clinics were invited to participate using a purposive sampling method. In total, fourteen individuals participated in this study.ResultsWe identified six themes which were: (1) reflections on how smoking affected decisions, (2) smoking and its impact on physical and mental health, (3) the economy as a motivator to stop smoking, (4) emotions, desires, and habits related to smoking, (5) knowledge of smoking, smoking cessation, and quit attempts, and (6) social factors influencing the participants' choices and activities. The participants were well informed about the consequences of smoking and had some knowledge and experience in quitting. The participants' pulmonary health was an important motivational factor for change. Withdrawal symptoms, anxiety, and fear of using other substances discouraged several from attempting to quit smoking. In contrast, social support from partners and access to meaningful activities were considered important factors for success. Few reported being offered help from health professionals to make a smoking cessation attempt.DiscussionExperiencing social support, being encouraged to quit smoking, and patients' concerns for their physical health were important reasons for wanting to quit smoking. Smoking cessation interventions based on patient preferences and on the behavior change wheel may enable a higher success rate among patients receiving opioid agonist therapy.

Project description:BACKGROUND:Smoking is still the number one preventable cause of death. Cravings-an intense desire or longing for a cigarette-are a major contributor to quit attempt failure. New tools to help smokers' manage their cravings are needed. OBJECTIVE:To present a case study of the development process and testing of a distraction/motivation game (Crave-Out) to help manage cravings. METHODS:We used a phased approach: in Phase 1 (alpha testing), we tested and refined the game concept, using a Web-based prototype. In Phase 2 (beta testing), we evaluated the distraction/motivation potential of the mobile game prototype, using a prepost design. After varying duration of abstinence, smokers completed the Questionnaire of Smoking Urge-Brief (QSU-Brief) measurement before and after playing Crave-Out. Paired t tests were used to compare pregame and postgame QSU-Brief levels. To test dissemination potential, we released the game on the Apple iTunes App Store and tracked downloads between December 22, 2011, and May 5, 2014. RESULTS:Our concept refinement resulted in a multilevel, pattern memory challenge game, with each level increasing in difficulty. Smokers could play the game as long as they wanted. At the end of each level, smokers were provided clear goals for the next level and rewards (positive reinforcement using motivational tokens that represented a benefit of quitting smoking). Negative reinforcement was removed in alpha testing as smokers felt it reminded them of smoking. Measurement of QSU-Brief (N=30) resulted in a pregame mean of 3.24 (SD 1.65) and postgame mean of 2.99 (SD 1.40) with an overall decrease of 0.25 in cravings (not statistically significant). In a subset analysis, the QSU-Brief decrease was significant for smokers abstinent for more than 48 hours (N=5) with a pregame mean of 2.84 (SD 1.16) and a postgame mean of 2.0 (SD 0.94; change=0.84; P =.03). Between December 22, 2011, and May 29, 2014, the game was downloaded 3372 times from the App-Store, with 1526 smokers visiting the online resource www.decide2quit.org linked to the game. CONCLUSIONS:Overall, playing the game resulted in small, but nonsignificant decreases in cravings, with changes greater for those had already quit for more than 48 hours. Lessons learned can inform further development. Future research could incorporate mHealth games in multicomponent cessation interventions. TRIAL REGISTRATION:Clinicaltrials.gov NCT00797628; https://clinicaltrials.gov/ct2/show/NCT00797628 (Archived by WebCite at http://www.webcitation.org/6hbJr6LWG).

Dataset Information

Game On? Smoking Cessation Through the Gamification of mHealth: A Longitudinal Qualitative Study.

Background

Objective

Methods

Results

Conclusions

Publications

Game On? Smoking Cessation Through the Gamification of mHealth: A Longitudinal Qualitative Study.

Similar Datasets

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