Content and Usability Evaluation of Medication Adherence Mobile Applications for Use in Pediatrics.
ABSTRACT: OBJECTIVE:The objective of this study was to systematically evaluate commercially available medication adherence apps for the inclusion of behavior change techniques (BCTs) and to conduct a usability analysis on a subset of apps with adolescents and young adults living with a chronic illness. METHODS:Medication adherence apps were identified via a search of iTunes app store in August 2016. Seventy-five apps meeting initial inclusion criteria were independently coded by two researchers for the presence/absence of 26 BCTs. Twenty adolescents and young adults (ages: 13-20 years) with inflammatory bowel disease conducted usability testing on a subset of apps (n?=?4). RESULTS:Across 75 apps coded for presence/absence of 26 BCTs, only 7 unique BCTs were identified. The number of BCTs per app ranged from 2 to 6, with an average of 3.3 BCTs. In usability testing, quality ratings varied across apps. Medisafe received the highest average scores on engagement, functionality, aesthetics, and information subscales. Medisafe and MyTherapy ranked first and second, respectively, on overall quality and perceived impact ratings. CONCLUSION:Content evaluation revealed only a limited number of BCTs that have been translated to medication adherence apps. Among apps with comparable content, clear user preferences emerged based on perceived quality and usability. Greater collaboration is needed between psychologists and health technologists to incorporate more evidence-based BCTs in apps. Findings also indicate a need for app developers to consider and incorporate the preferences of younger end users to improve app quality and engagement for pediatric populations.
Project description:<h4>Background</h4>The number of commercial apps to improve health behaviours in children is growing rapidly. While this provides opportunities for promoting health, the content and quality of apps targeting children and adolescents is largely unexplored. This review systematically evaluated the content and quality of apps to improve diet, physical activity and sedentary behaviour in children and adolescents, and examined relationships of app quality ratings with number of app features and behaviour change techniques (BCTs) used.<h4>Methods</h4>Systematic literature searches were conducted in iTunes and Google Play stores between May-November 2016. Apps were included if they targeted children or adolescents, focused on improving diet, physical activity and/or sedentary behaviour, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. App inclusion, downloading and user-testing for quality assessment and content analysis were conducted independently by two reviewers. Spearman correlations were used to examine relationships between app quality, and number of technical app features and BCTs included.<h4>Results</h4>Twenty-five apps were included targeting diet (n = 12), physical activity (n = 18) and sedentary behaviour (n = 7). On a 5-point Mobile App Rating Scale (MARS), overall app quality was moderate (total MARS score: 3.6). Functionality was the highest scoring domain (mean: 4.1, SD: 0.6), followed by aesthetics (mean: 3.8, SD: 0.8), and lower scoring for engagement (mean: 3.6, SD: 0.7) and information quality (mean: 2.8, SD: 0.8). On average, 6 BCTs were identified per app (range: 1-14); the most frequently used BCTs were providing 'instructions' (n = 19), 'general encouragement' (n = 18), 'contingent rewards' (n = 17), and 'feedback on performance' (n = 13). App quality ratings correlated positively with numbers of technical app features (rho = 0.42, p < 0.05) and BCTs included (rho = 0.54, p < 0.01).<h4>Conclusions</h4>Popular commercial apps to improve diet, physical activity and sedentary behaviour in children and adolescents had moderate quality overall, scored higher in terms of functionality. Most apps incorporated some BCTs and higher quality apps included more app features and BCTs. Future app development should identify factors that promote users' app engagement, be tailored to specific population groups, and be informed by health behaviour theories.
Project description:BACKGROUND: There has been a recent proliferation in the development of smartphone applications (apps) aimed at modifying various health behaviours. While interventions that incorporate behaviour change techniques (BCTs) have been associated with greater effectiveness, it is not clear to what extent smartphone apps incorporate such techniques. The purpose of this study was to investigate the presence of BCTs in physical activity and dietary apps and determine how reliably the taxonomy checklist can be used to identify BCTs in smartphone apps. METHODS: The top-20 paid and top-20 free physical activity and/or dietary behaviour apps from the New Zealand Apple App Store Health & Fitness category were downloaded to an iPhone. Four independent raters user-tested and coded each app for the presence/absence of BCTs using the taxonomy of behaviour change techniques (26 BCTs in total). The number of BCTs included in the 40 apps was calculated. Krippendorff's alpha was used to evaluate interrater reliability for each of the 26 BCTs. RESULTS: Apps included an average of 8.1 (range 2-18) techniques, the number being slightly higher for paid (M?=?9.7, range 2-18) than free apps (M?=?6.6, range 3-14). The most frequently included BCTs were "provide instruction" (83% of the apps), "set graded tasks" (70%), and "prompt self-monitoring" (60%). Techniques such as "teach to use prompts/cues", "agree on behavioural contract", "relapse prevention" and "time management" were not present in the apps reviewed. Interrater reliability coefficients ranged from 0.1 to 0.9 (Mean 0.6, SD?=?0.2). CONCLUSIONS: Presence of BCTs varied by app type and price; however, BCTs associated with increased intervention effectiveness were in general more common in paid apps. The taxonomy checklist can be used by independent raters to reliably identify BCTs in physical activity and dietary behaviour smartphone apps.
Project description:Objective:Mobile applications (apps) are increasingly being utilized in health behavior change interventions. To determine the presence of underlying behavior change mechanisms, apps for physical activity have been coded for behavior change techniques (BCTs). However, apps for sedentary behavior have yet to be assessed for BCTs. Thus, the purpose of the present study was to review apps designed to decrease sedentary time and determine the presence of BCTs. Methods:Systematic searches of the iTunes App and Google Play stores were completed using keyword searches. Two reviewers independently coded free (n = 36) and paid (n = 14) app descriptions using a taxonomy of 93 BCTs (December 2016-January 2017). A subsample (n = 4) of free apps were trialed for one week by the reviewers and coded for the presence of BCTs (February 2017). Results:In the free and paid app descriptions, only 10 of 93 BCTs were present with a mean of 2.42 BCTs (range 0-6) per app. The BCTs coded most frequently were "prompts/cues" (n = 43), "information about health consequences" (n = 31), and "self-monitoring of behavior" (n = 17). For the four free apps that were trialed, three additional BCTs were coded that were not coded in the descriptions: "graded tasks," "focus on past successes," and "behavior substitution." Conclusions:These sedentary behavior apps have fewer BCTs compared with physical activity apps and traditional (i.e., non-app) physical activity and healthy eating interventions. The present study sheds light on the behavior change potential of sedentary behavior apps and provides practical insight about coding for BCTs in apps.
Project description:<h4>Objectives</h4>To estimate the efficacy of app-based interventions designed to support medication adherence and investigate which behaviour change techniques (BCTs) used by the apps are associated with efficacy.<h4>Design</h4>Systematic review of randomised controlled trials (RCTs), with meta-analysis.<h4>Setting</h4>Medline/PubMed, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Embase and Web of Science were searched from 1990 to November 2018 for RCTs conducted in any healthcare setting.<h4>Participants</h4>Studies of participants of any age taking prescribed medication for any health condition and for any duration.<h4>Intervention</h4>An app-based intervention delivered through a smartphone, tablet computer or personal digital assistant to help, support or advise about medication adherence.<h4>Comparator</h4>One of (1) usual care, (2) a control app which did not use any BCTs to improve medication adherence or (3) a non-app-based comparator.<h4>Primary and secondary outcome measures</h4>The primary outcome was the pooled effect size of changes in medication adherence. The secondary outcome was the association between BCTs used by the apps and the effect size.<h4>Results</h4>The initial search identified 13 259 citations. After title and abstract screening, full-text articles of 83 studies were screened for eligibility. Nine RCTs with 1159 recruited participants were included. The mean age of participants was >50 years in all but one study. Health conditions of target populations included cardiovascular disease, depression, Parkinson's disease, psoriasis and multimorbidity. The meta-analysis indicated that patients who use mobile apps to support them in taking medications are more likely to self-report adherence to medications (OR 2.120, 95% CI 1.635 to 2.747, n=988) than those in the comparator groups. Meta-regression of the BCTs did not reveal any significant associations with effect size.<h4>Conclusions</h4>App-based medication adherence interventions may have a positive effect on patient adherence. Larger scale studies are required to further evaluate this effect, including long-term sustainability, and intervention and participant characteristics that are associated with efficacy and app usage.<h4>Prospero registration number</h4>PROSPERO Protocol Registration Number: CRD42017080150.
Project description:Nonadherence produces considerable health consequences and economic burden to patients and payers. One approach to improve medication nonadherence that has gained interest in recent years is the use of smartphone adherence apps. The development of smartphone adherence apps has increased rapidly since 2012; however, literature evaluating the clinical app and effectiveness of smartphone adherence apps to improve medication adherence is generally lacking.The aims of this study were to (1) provide an updated evaluation and comparison of medication adherence apps in the marketplace by assessing the features, functionality, and health literacy (HL) of the highest-ranking adherence apps and (2) indirectly measure the validity of our rating methodology by determining the relationship between our app evaluations and Web-based consumer ratings.Two independent reviewers assessed the features and functionality using a 4-domain rating tool of all adherence apps identified based on developer claims. The same reviewers downloaded and tested the 100 highest-ranking apps including an additional domain for assessment of HL. Pearson product correlations were estimated between the consumer ratings and our domain and total scores.A total of 824 adherence apps were identified; of these, 645 unique apps were evaluated after applying exclusion criteria. The median initial score based on descriptions was 14 (max of 68; range 0-60). As a result, 100 of the highest-scoring unique apps underwent user testing. The median overall user-tested score was 31.5 (max of 73; range 0-60). The majority of the user tested the adherence apps that underwent user testing reported a consumer rating score in their respective online marketplace. The mean consumer rating was 3.93 (SD 0.84). The total user-tested score was positively correlated with consumer ratings (r=.1969, P=.04).More adherence apps are available in the Web-based marketplace, and the quality of these apps varies considerably. Consumer ratings are positively but weakly correlated with user-testing scores suggesting that our rating tool has some validity but that consumers and clinicians may assess adherence app quality differently.
Project description:BACKGROUND:The quality of life of people living with chronic conditions is highly dependent on self-management behaviors. Mobile health (mHealth) apps could facilitate self-management and thus help improve population health. To achieve their potential, apps need to target specific behaviors with appropriate techniques that support change and do so in a way that allows users to understand and act upon the content with which they interact. OBJECTIVE:Our objective was to identify apps targeted toward the self-management of chronic conditions and that are available in France. We aimed to examine what target behaviors and behavior change techniques (BCTs) they include, their level of understandability and actionability, and the associations between these characteristics. METHODS:We extracted data from the Google Play store on apps labelled as Top in the Medicine category. We also extracted data on apps that were found through 12 popular terms (ie, keywords) for the four most common chronic condition groups-cardiovascular diseases, cancers, respiratory diseases, and diabetes-along with apps identified through a literature search. We selected and downloaded native Android apps available in French for the self-management of any chronic condition in one of the four groups and extracted background characteristics (eg, stars and number of ratings), coded the presence of target behaviors and BCTs using the BCT taxonomy, and coded the understandability and actionability of apps using the Patient Education Material Assessment Tool for audiovisual materials (PEMAT-A/V). We performed descriptive statistics and bivariate statistical tests. RESULTS:A total of 44 distinct native apps were available for download in France and in French: 39 (89%) were found via the Google Play store and 5 (11%) were found via literature search. A total of 19 (43%) apps were for diabetes, 10 for cardiovascular diseases (23%), 8 for more than one condition in the four groups (18%), 6 for respiratory diseases (14%), and 1 for cancer (2%). The median number of target behaviors per app was 2 (range 0-7) and of BCTs per app was 3 (range 0-12). The most common BCT was self-monitoring of outcome(s) of behavior (31 apps), while the most common target behavior was tracking symptoms (30 apps). The median level of understandability was 42% and of actionability was 0%. Apps with more target behaviors and more BCTs were also more understandable (ρ=.31, P=.04 and ρ=.35, P=.02, respectively), but were not significantly more actionable (ρ=.24, P=.12 and ρ=.29, P=.054, respectively). CONCLUSIONS:These apps target few behaviors and include few BCTs, limiting their potential for behavior change. While content is moderately understandable, clear instructions on when and how to act are uncommon. Developers need to work closely with health professionals, users, and behavior change experts to improve content and format so apps can better support patients in coping with chronic conditions. Developers may use these criteria for assessing content and format to guide app development and evaluation of app performance. TRIAL REGISTRATION:PROSPERO CRD42018094012; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=94012.
Project description:BACKGROUND:With the accessibility and widespread use of mobile phones, mobile phone apps targeting medication adherence may be useful tools to help patients take medications as prescribed. OBJECTIVE:Our objectives were to (1) characterize and assess mobile phone medication adherence apps guided by a conceptual framework on the focus of adherence interventions and (2) conduct a content analysis of Web-based reviews to explore users' perspectives and experiences with mobile phone medication adherence apps. METHODS:We searched for mobile phone medication adherence apps using keyword searches in Apple and Android operating systems. We characterized all apps in terms of number of downloads, ratings, languages, cost, and disease target. We categorized apps according to 4 key features of (1) alerting to take medication, (2) tracking medication taking, (3) reminding to refill or indicating amount of medication left, and (4) storing medication information. We then selected representative apps from each operating system for detailed quality assessment and user testing. We also downloaded Web-based reviews for these selected apps and conducted a qualitative content analysis using an inductive approach involving steps of initial open coding, construction of categories, and abstraction into themes. RESULTS:We identified 704 apps (443 from Apple and 261 from Android). The majority of apps across both operating systems had 1 or 2 features-specifically, 37.2% (165/443) and 38.1% (169/443) of Apple apps, respectively, and 41.4% (108/261) and 31.4% (108/261) of Android apps, respectively. Quality assessment and user testing of 20 selected apps revealed apps varied in quality and commonly focused on behavioral strategies to enhance medication adherence through alerts, reminders, and logs. A total of 1323 eligible Web-based reviews from these 20 selected apps were analyzed, and the following themes emerged: (1) features and functions appreciated by users, which included the ability to set up customized medication regimen details and reminders, monitor other health information (eg, vitals, supplements, and manage multiple people or pets), support health care visits (eg, having a list of medications and necessary health information in 1 app); (2) negative user experiences that captured technical difficulties (glitches, confusing app navigation, and poor interoperability), dosage schedule, and reminder setup inflexibility; and (3) desired functions and features related to optimization of information input, improvement of reminders, and upgrading app performance (better synchronization or backup of data and interoperability). CONCLUSIONS:A large number of mobile phone medication adherence apps are currently available. The majority of apps have features representing a behavioral approach to intervention. Findings of the content analysis offer mostly positive feedback as well as insights into current limitations and improvements that could be addressed in current and future medication adherence apps.
Project description:Smartphone applications (apps) offer a potentially cost-effective and a wide-reach aid to smoking cessation. In 2012, a content analysis of smoking cessation apps suggested that most apps did not adopt behaviour change techniques (BCTs), which according to previous research had suggested would promote higher success rates in quitting smoking. This study examined whether or not, this situation had changed by 2014 for free smoking cessation apps available in the Apple App Store. It also compared the use of engagement and ease-of-use features between the two time points.137 free apps available in the Apple App Sore in 2014 were coded using an established framework for the presence or absence of evidence-based BCTs, and engagement and ease-of-use features. The results from the 2014 data were compared with a similar exercise conducted on 83 free apps available in 2012.BCTs supporting identity change, rewarding abstinence and advising on changing routines were less prevalent in 2014 as compared with 2012 (14.6% vs. 42.2%, 18.2% vs. 48.2%, and 17.5% vs. 24.1%, respectively). Advice on coping with cravings and advice on the use of stop-smoking medication were more prevalent in 2014 as compared with 2012 (27.7% vs. 20.5% and 14.6% vs 3.6%, respectively). The use of recognised engagement features was less common in 2014 than in 2012 (45.3% vs. 69.6%) while ease-of-use features remained very high (94.5% vs. 82.6%).There was little evidence of improvement in the use of evidence-based BCTs in free smoking cessation iPhone-based apps between 2012 and 2014.
Project description:OBJECTIVES:To explore the relationship between popularity of mobile application (apps) for physical activity (PA) and their likely efficacy. The primary objective was to assess the association between app popularity (indicated by user ratings) and likely efficacy (indicated by the number of Behaviour Change Techniques (BCT) present). The secondary objective was to assess the relationship between user ratings and those BCTs that have been shown to be effective in increasing PA. DESIGN:Observational study. METHODS:400 top-ranked free and paid apps from iTunes and Google Play stores were screened, and were included if the primary behaviour targeted was PA and they had stand-alone functionality. The outcome variable of user rating was dichotomised into high (4, 5 stars) or low (1, 2, 3 stars) rating. SETTING:iTunes and Google Play app stores. PARTICIPANTS:No individual participants but the study used user-led rating system in the app store. PRIMARY AND SECONDARY OUTCOME MEASURES:BCTs and user rating. RESULTS:Of 400 apps, 156 were eligible and 65 were randomly selected, downloaded and assessed by two reviewers. There was no relationship overall between star ratings and the number of BCTs present, nor between star ratings and the presence of BCTs known to be effective in increasing PA. App store was strongly associated with star ratings, with lower likelihood of finding 4 or 5 stars in iTunes compared with Google Play (OR 0.74, 95%?CI 0.73 to 0.76, p<0.001). CONCLUSIONS:The findings of this study suggest that popularity does not necessarily imply the likelihood of effectiveness. Hence, public health impact is unlikely to be achieved by allowing market forces to 'prescribe' what is used by the public.