Characterizing perceived usability and its correlation with smoking cessation: An analysis of user assessments of the smoking cessation app quitSTART
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ABSTRACT:
SUBMITTER: Chen Z
PROVIDER: S-EPMC10835281 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:The use of mobile health applications (apps) especially in the area of lifestyle behaviors has increased, thus providing unprecedented opportunities to develop health programs that can engage people in real-time and in the real-world. Yet, relatively little is known about which factors relate to the engagement of commercially available apps for health behaviors. This exploratory study examined behavioral engagement with a weight loss app, Lose It! and characterized higher versus lower engaged groups. Cross-sectional, anonymized data from Lose It! were analyzed (n = 12,427,196). This dataset was randomly split into 24 subsamples and three were used for this study (total n = 1,011,008). Classification and regression tree methods were used to identify subgroups of user engagement with one subsample, and descriptive analyses were conducted to examine other group characteristics associated with engagement. Data mining validation methods were conducted with two separate subsamples. On average, users engaged with the app for 29 days. Six unique subgroups were identified, and engagement for each subgroup varied, ranging from 3.5 to 172 days. Highly engaged subgroups were primarily distinguished by the customization of diet and exercise. Those less engaged were distinguished by weigh-ins and the customization of diet. Results were replicated in further analyses. Commercially-developed apps can reach large segments of the population, and data from these apps can provide insights into important app features that may aid in user engagement. Getting users to engage with a mobile health app is critical to the success of apps and interventions that are focused on health behavior change.
| S-EPMC5526821 | biostudies-other
Project description:BackgroundSmoking prevalence during and after pregnancy remains high among socioeconomically disadvantaged women. Mobile health (mHealth) apps with game and social support elements seem promising to support smoking cessation.ObjectiveThis study aims to describe the user-centered design and usability evaluation of Kindle, an mHealth app with game and social support elements, to support disadvantaged young women during and after pregnancy through the first stages of smoking cessation.MethodsDisadvantaged women (n=9), members of their social networks (n=4), and nurses supporting these women (n=51) were informants throughout the iterative prototype development of Kindle according to the International Organization for Standardization 9241-11:2018. Specific phases included understanding the context of use through secondary analysis of qualitative interview data (phase 1), establishing the user and organizational requirements (phase 2), production of design solutions (phase 3), and usability inspection of the prototype through a heuristic evaluation (3 experts) along with user testing by a think aloud method (5 disadvantaged women and 5 nurses; phase 4). Usability problems were categorized according to the principles of the Healthcare Information and Management Systems Society.ResultsPhase 1 resulted in an understanding of the VoorZorg program and the needs of VoorZorg nurses and clients (eg, focus on early stages of change and building new supportive networks to aid clients in smoking cessation). In phase 2, we established requirements (n=22; eg, mHealth app, secure communication between nurses and clients, easy-to-use interfaces, inclusion of game elements, and tailoring at early stages of change in smoking cessation). Phase 3 resulted in a prototype of Kindle, combining the interface for nurses and clients, including the following functionalities: personal goal setting with earning points; secured chat function between nurses and other clients; and tips, diary, and profile creation. The heuristic evaluation and thinking aloud method in phase 4 revealed 78 usability problems in the interfaces. Most usability problems concerned simplicity (eg, unclear clickable button) and naturalness (eg, unclear icon).ConclusionsThe user-centered design and usability testing of the mHealth app Kindle yielded useful insights. The involvement of end users, specifically socioeconomically disadvantaged women during and after their pregnancy, resulted in a prototype that met their needs and requirements (eg, mHealth app, secure communication between nurses and clients, easy-to-use interfaces, inclusion of game elements, and tailoring to the early stages of change in smoking cessation) to achieve readiness for smoking cessation. Moreover, the usability evaluation by end users and experts revealed unique usability problems for this population. These insights allow for further optimization of Kindle and encourage future studies to engage disadvantaged populations in all phases of mHealth intervention design and usability testing.
| S-EPMC8374659 | biostudies-literature
Project description:BackgroundSmoking rates in the United States have been reduced in the past decades to 15% of the general population. However, up to 88% of people with psychiatric symptoms still smoke, leading to high rates of disease and mortality. Therefore, there is a great need to develop smoking cessation interventions that have adequate levels of usability and can reach this population.ObjectiveThe objective of this study was to report the rationale, ideation, design, user research, and final specifications of a novel smoking cessation app for people with serious mental illness (SMI) that will be tested in a feasibility trial.MethodsWe used a variety of user-centered design methods and materials to develop the tailored smoking cessation app. This included expert panel guidance, a set of design principles and theory-based smoking cessation content, development of personas and paper prototyping, usability testing of the app prototype, establishment of app's core vision and design specification, and collaboration with a software development company.ResultsWe developed Learn to Quit, a smoking cessation app designed and tailored to individuals with SMI that incorporates the following: (1) evidence-based smoking cessation content from Acceptance and Commitment Therapy and US Clinical Practice Guidelines for smoking cessation aimed at providing skills for quitting while addressing mental health symptoms, (2) a set of behavioral principles to increase retention and comprehension of smoking cessation content, (3) a gamification component to encourage and sustain app engagement during a 14-day period, (4) an app structure and layout designed to minimize usability errors in people with SMI, and (5) a set of stories and visuals that communicate smoking cessation concepts and skills in simple terms.ConclusionsDespite its increasing importance, the design and development of mHealth technology is typically underreported, hampering scientific innovation. This report describes the systematic development of the first smoking cessation app tailored to people with SMI, a population with very high rates of nicotine addiction, and offers new design strategies to engage this population. mHealth developers in smoking cessation and related fields could benefit from a design strategy that capitalizes on the role visual engagement, storytelling, and the systematic application of behavior analytic principles to deliver evidence-based content.
| S-EPMC5790963 | biostudies-literature
Project description:ObjectiveThe objective of this study was to assess whether a version of the Smoke Free app with a supportive chatbot powered by artificial intelligence (versus a version without the chatbot) led to increased engagement and short-term quit success.MethodsDaily or non-daily smokers aged ≥18 years who purchased the 'pro' version of the app and set a quit date were randomly assigned (unequal allocation) to receive the app with or without the chatbot. The outcomes were engagement (i.e. total number of logins over the study period) and self-reported abstinence at a one-month follow-up. Unadjusted and adjusted negative binomial and logistic regression models were fitted to estimate incidence rate ratios (IRRs) and odds ratios (ORs) for the associations of interest.ResultsA total of 57,214 smokers were included (intervention: 9.3% (5339); control: 90.7% (51,875). The app with the chatbot compared with the standard version led to a 101% increase in engagement (IRRadj = 2.01, 95% confidence interval (CI) = 1.92-2.11, p < .001). The one-month follow-up rate was 10.6% (intervention: 19.9% (1,061/5,339); control: 9.7% (5,050/51,875). Smokers allocated to the intervention had greater odds of quit success (missing equals smoking: 844/5,339 vs. 3,704/51,875, ORadj = 2.38, 95% CI = 2.19-2.58, p < .001; follow-up only: 844/1,061 vs. 3,704/5,050, ORadj = 1.36, 95% CI = 1.16-1.61, p < .001).ConclusionThe addition of a supportive chatbot to a popular smoking cessation app more than doubled user engagement. In view of very low follow-up rates, there is low quality evidence that the addition also increased self-reported smoking cessation.
| S-EPMC6775545 | biostudies-literature
Project description:BackgroundThe recent widespread availability of augmented reality via smartphone offers an opportunity to translate cue exposure therapy for smoking cessation from the laboratory to the real world. Despite significant reductions in the smoking rates in the last decade, approximately 13.7% of the adults in the United States continue to smoke. Smoking-related cue exposure has demonstrated promise as an adjuvant therapy in the laboratory, but practical limitations have prevented its success in the real world. Augmented reality technology presents an innovative approach to overcome these limitations.ObjectiveThe aim of this study was to develop a smartphone app that presents smoking-related augmented reality images for cue exposure. Smokers provided feedback on the images and reported on the perceived urge to smoke, qualities of reality/coexistence, and general feedback about quality and functioning. The feedback was used to refine the augmented reality images within the app.MethodsIn collaboration with an augmented reality design company, we developed 6 smoking-related images (cigarette, lighter, ashtray, lit cigarette in ashtray, etc) and 6 neutral images similar in size or complexity for comparison (pen, eraser, notebook, soda bottle with droplets, etc). Ten smokers completed a survey of demographic characteristics, smoking history and behavior, dependence on nicotine, motivation to quit smoking, and familiarity with augmented reality technology. Then, participants viewed each augmented reality image and provided ratings on 10-point Likert scales for urge to smoke and reality/coexistence of the image into the scene. Participants were also queried with open-ended questions regarding the features of the images.ResultsOf the 10 participants, 5 (50%) had experienced augmented reality prior to the laboratory visit, but only 4 of those 5 participants used augmented reality at least weekly. Although the sample was small (N=10), smokers reported significantly higher urge to smoke after viewing the smoking-related augmented reality images (median 4.58, SD 3.49) versus the neutral images (median 1.42, SD 3.01) (Z=-2.14, P=.03; d=0.70). The average reality and coexistence ratings of the images did not differ between smoking-related and neutral images (all P>.29). Augmented reality images were found on average to be realistic (mean [SD] score 6.49 [3.11]) and have good environmental coexistence (mean [SD] score 6.93 [3.04]) and user coexistence (mean [SD] score 6.38 [3.27]) on the 10-point scale. Participant interviews revealed some areas of excellence (eg, details of the lit cigarette) and areas for improvement (eg, stability of images, lighting).ConclusionsAll images were generally perceived as being realistic and well-integrated into the environment. However, the smoking augmented reality images produced higher urge to smoke than the neutral augmented reality images. In total, our findings support the potential utility of augmented reality for cue exposure therapy. Future directions and next steps are discussed.
| S-EPMC7808889 | biostudies-literature
Project description:BackgroundCigarette smoking is a leading cause of preventable death, and identifying novel treatment approaches to promote smoking cessation is critical for improving public health. With the rise of digital health and mobile apps, these tools offer potential opportunities to address smoking cessation, yet the functionality of these apps and whether they offer scientifically based support for smoking cessation are unknown.ObjectiveThe goal of this research was to use the American Psychiatric Association app evaluation model to evaluate the top-returned apps from Android and Apple app store platforms related to smoking cessation and investigate the common app features available for end users.MethodsWe conducted a search of both Android and iOS app stores in July 2021 for apps related to the keywords "smoking," "tobacco," "smoke," and "cigarette" to evaluate apps for smoking cessation. Apps were screened for relevance, and trained raters identified and analyzed features, including accessibility (ie, cost), privacy, clinical foundation, and features of the apps, using a systematic framework of 105 objective questions from the American Psychiatric Association app evaluation model. All app rating data were deposited in mindapps, a publicly accessible database that is continuously updated every 6 months given the dynamic nature of apps available in the marketplace. We characterized apps available in July 2021 and November 2022.ResultsWe initially identified 389 apps, excluded 161 due to irrelevance and nonfunctioning, and rated 228, including 152 available for Android platforms and 120 available for iOS platforms. Some of the top-returned apps (71/228, 31%) in 2021 were no longer functioning in 2022. Our analysis of rated apps revealed limitations in accessibility and features. While most apps (179/228, 78%) were free to download, over half had costs associated with in-app purchases or full use. Less than 65% (149/228) had a privacy policy addressing the data collected in the app. In terms of intervention features, more than 56% (128/228) of apps allowed the user to set and check in on goals, and more than 46% (106/228) of them provided psychoeducation, although few apps provided evidence-based support for smoking cessation, such as peer support or skill training, including mindfulness and deep breathing, and even fewer provided evidence-based interventions, such as acceptance and commitment therapy or cognitive behavioral therapy. Only 12 apps in 2021 and 11 in 2022 had published studies supporting the feasibility or efficacy for smoking cessation.ConclusionsNumerous smoking cessation apps were identified, but analysis revealed limitations, including high rates of irrelevant and nonfunctioning apps, high rates of turnover, and few apps providing evidence-based support for smoking cessation. Thus, it may be challenging for consumers to identify relevant, evidence-based apps to support smoking cessation in the app store, and a comprehensive evaluation system of mental health apps is critically important.
| S-EPMC10375280 | biostudies-literature
Project description:OBJECTIVE:To assess the efficacy of an interactive smoking cessation decision-aid application (pp) compared with a smoking cessation static information app on continuous abstinence. DESIGN:Automated double-blind randomised controlled trial with 6 months follow-up (2014-2015). SETTING:Smartphone-based. PARTICIPANTS:684 participants (daily smokers of cigarettes, 18 years old or over) recruited passively from app stores in the USA, Australia, UK and Singapore, and randomised to one of two sub-apps. INTERVENTIONS:Behavioural, decision-aid, smartphone application. MAIN OUTCOMES:Continuous abstinence at 10 days, 1 month, 3 months and 6 months. RESULTS:Smokers who received the decision-aid app were more likely to be continuously abstinent at 1 month compared with the information-only app (28.5% vs 16.9%; relative risk (RR) 1.68; 95% CI 1.25 to 2.28). The effect was sustained at 3 months (23.8% vs 10.2%; RR 2.08; 95% CI 1.38 to 3.18) and 6 months (10.2% vs 4.8%; RR 2.02; 95% CI 1.08 to 3.81). Participants receiving the decision-aid app were also more likely to have made an informed choice (31.9% vs 19.6%) and have lower decisional conflict (19.5% vs 3.9%). CONCLUSION:A smartphone decision-aid app with support features significantly increased smoking cessation and informed choice. With an increasing number of smokers attempting to quit, unassisted evidence-based decision-aid apps can provide an effective and user-friendly option to many who are making quit decisions without healthcare professionals. TRIAL REGISTRATION NUMBER:ACTRN12613000833763.
| S-EPMC5780681 | biostudies-literature
Project description:BackgroundPeople with suicidal thoughts are more inclined to seek technology-delivered interventions than in-person forms of treatment, making mobile apps for suicide prevention an ideal platform for treatment delivery. This review examines apps designed for suicide prevention, with a specific focus on user engagement.ObjectiveThis study aims to update the literature and broadly evaluate the landscape of mobile health apps for suicide prevention; examine apps with key features and primary approaches to suicide prevention; and systematically evaluate the engagement, functionality, aesthetics, and information of the apps.MethodsAll apps related to suicidal thoughts and behaviors were identified in the Google Play and iOS app stores and were systematically reviewed for their content and quality. The mobile app rating scale (MARS) was used to evaluate app usability and engagement.ResultsOf the 66 apps identified, 42 (64%) were specifically designed for people with suicidal ideation, and 59 (89%) had at least one best practice feature for suicide risk reduction. The mean overall MARS score of all apps was 3.5 (range 2.1-4.5), with 83% (55/66) of apps having a minimum acceptability score of 3. The total MARS score was not associated with the user app rating (r=-0.001; P=.99) or the number of features (r=0.24; P=.09).ConclusionsThis study identified many usable and engaging apps in app stores designed for suicide prevention. However, there are only limited apps for clinicians. Thus, mobile apps for suicide prevention should be carefully developed and clinically evaluated.
| S-EPMC8319780 | biostudies-literature
Project description:To tailor and predict the outcomes of smoking cessation treatment, it is essential to identify the nature of motivation, as it is the basis for long-term change in healthy behaviors according to self-determination theory (SDT). The purpose of this study is to examine the psychometric properties of the French Smoking Cessation Motivation Scale (F-SCMS). The factorial structure and the psychometric properties were assessed with French-speaking users who had started a 9-step preparation program through a mobile app for smoking cessation (n = 13,044). The results of the present study confirmed content validity (CFI = 0.905, SRMR = 0.045, RMSEA = 0.087) and good internal consistency (α = 0.86, ωh = 0.7, ωt = 0.89) with CFA. The convergent validity was very small, but there were highly significant positive correlations between the willingness and readiness to quit with integrated and intrinsic subscales (rs = 0.25-0.37, p < 0.001). The amotivation subscale significantly had no correlation with any degree of willingness (r = 0.01, p < 0.001), ability (r = 0.01, p < 0.001), and readiness to quit (r = 0.02, p < 0.001). This scale facilitates future research regarding the nature of motivation to quit smoking in the French-speaking population.
| S-EPMC9407113 | biostudies-literature
Project description:BackgroundTobacco smoking is the leading cause of preventable death in the United States, and the annual economic burden attributable to smoking exceeds US $300 billion. Obstacles to smoking cessation include limited access and adherence to effective cessation interventions. Technology can help overcome these obstacles; many smartphone apps have been developed to aid smoking cessation, but few that conform to the US clinical practice guideline (USCPG) have been rigorously tested and reported in the literature. Clickotine is a novel smartphone app for smoking cessation, designed to deliver the essential features of the USCPG and engineered to engage smokers by personalizing intervention components.ObjectiveOur objective was to assess the engagement, efficacy, and safety of Clickotine in an initial, single-arm study. Outcomes measured were indicators of engagement with the smartphone app (number of app opens, number of interactions with the Clickotine program, and weeks active with Clickotine), cessation outcomes of 7- and 30-day self-reported abstinence from smoking, and negative health events.MethodsWe recruited US residents between 18 and 65 years of age who owned an iPhone and smoked 5 or more cigarettes daily for the study via online advertising. Respondents were prescreened for eligibility by telephone and, if appropriate, directed to a Web portal to provide informed consent, confirm eligibility, and download the Clickotine app. Participants completed study assessments via the online portal at baseline and after 8 weeks. Data were collected in Amazon S3 with no manual data entry, and access to all data was maximally restrictive, logged, and auditable.ResultsA total of 416 participants downloaded the app and constituted the intention-to-treat (ITT) sample. On average, participants opened the Clickotine app 100.6 times during the 8-week study (median 69), logged 214.4 interactions with the Clickotine program (median 178), and remained engaged with Clickotine for 5.3 weeks (median 5). Among the ITT sample, 45.2% (188/416) reported 7-day abstinence and 26.2% (109/416) reported 30-day abstinence from smoking after 8 weeks. Completer analysis focused on 365 (87.7%) of the 416 enrolled participants who completed the 8-week questionnaire revealed that 51.5% (188/365) of completers reported 7-day abstinence and 29.9% (109/365) reported 30-day abstinence. Few adverse events, mostly consistent with nicotine withdrawal symptoms, were reported and overall no safety signal was detected.ConclusionsIn this initial single-arm trial, Clickotine users appeared to demonstrate encouraging indicators of engagement in terms of the number of app opens, number of program interactions, and continued engagement over time. Clickotine users reported encouraging quit rates while reporting few adverse events. Future research is warranted to assess Clickotine's efficacy in a randomized controlled trial.Trial registrationClinicaltrials.gov NCT02656745; https://clinicaltrials.gov/ct2/show/NCT02656745 (Archived by WebCite at http://www.webcitation.org/6peTT4x60).
| S-EPMC5424127 | biostudies-literature