Choice Of Apps Research Articles

Young Adults Journey with Digital Fitness Tools-A Qualitative Study on Use of Fitness Tracking Device.

Physical activity trackers possess the potential to encourage increased physical activity. However, users often exhibit poor long-term adherence to these devices, which may stem from a lack of understanding of the factors influencing their use, as well as changes in health behavior. This study aims to provide new insights into the types of health-related apps and devices that young people discover, select, and utilize, along with the underlying reasons for their choices. Young adults aged between 18-25 years reporting the use and nonuse of health apps and wearables were recruited and participated in focus group discussions about app choice, features, their perceptions towards the physical activity trackers, and reasons for continued use and for not using one. A total of Nine FGDS were conducted among users, nonusers, and former users of physical activity tracker usage. Data was recorded, transcribed, and analyzed for themes in an iterative approach. The physical activity tracker users group stated that they had a sense of achievement, validation, and other motivational feedback, which helped with adherence. All three groups (user, non-user, and former user) had similar concerns about cost, reliability, accuracy, and dependency. Former users also reported that the idea of accomplishing the goals would create anxiety and, in turn, harm the body. Former users and nonusers expressed their concerns regarding lack of time and loss of motivation to track their physical activity. Nonusers had issues with the functionality of the device (ease of use, battery, notifications, apps hang) and were also aware of all the health benefits of using wearables. Physical activity users group, former users group, and nonusers group shared concerns about accuracy, cost, and battery.

Two cities, two stages in transforming society-a mixed methods study comparing doctors' adoption of mobile apps for communication with patients in Hangzhou and Yancheng, China.

Mobile apps have become commonplace in doctor-patient communication over the last 20 years. Doctors mainly use two kinds of app, social networking apps (i.e., WeChat) and medical platform apps (i.e., Haodf). The purpose of this study was to investigate whether the attributes of social interaction in local society impact doctors' choice of mobile apps to communicate with patients. This article addresses two research questions: (a) To what degree do doctors' adoption patterns in different societies differ? (b) Why do doctors choose certain mobile apps to communicate with patients? This study employed a mixed methods research design to analyze doctor's adoption behavior patterns in two cities, Hangzhou (HZ) and Yancheng (YC), which represent two stages in transforming society. Various patterns, measured as the percentage of doctors who utilize the medical platform app of Haodf among all doctors and the average service counts per doctor, were compared in three groups of tertiary hospitals: the top ones in HZ, the average ones in HZ, and the average ones in YC. We also conducted thematic content analysis of qualitative data from semi-structured interviews with 20 purposely selected doctors in the two cities. The percentages of doctors who have adopted the app of Haodf from the three groups of tertiary hospitals were 49.97%, 41.00%, and 32.03%, with an average service counts per doctor of 261, 182 and 39, respectively. According to the interviewees, doctors from YC are more likely to use social networking apps to communicate with patients than their HZ counterparts to maintain social connections with their relatives, friends, colleagues, and others. This study demonstrates that doctors' choices of mobile apps are dependent upon social context. In traditional society, where people have close ties, the logic of using social networking apps lies in doctors' need to maximize the utility of their knowledge by maintaining social connections with others. In modern society, where the close ties between people have gradually weakened, the logic of using medical platform apps lies in doctors' needs for reputation marketing, either for themselves or for institutions, their affiliated departments or hospitals.

ИСПОЛЬЗОВАНИЕ ОБЛАЧНЫХ ТЕХНОЛОГИЙ В КОМБИНИРОВАННОМ ОБУЧЕНИИ ИНФОРМАТИКЕ СТУДЕНТОВ ИНЖЕНЕРНЫХ СПЕЦИАЛЬНОСТЕЙ

The purpose of this study is to analyze the model of using Google Apps in combined computer science education for engineering students. Research objectives: to determine the current requirements for teaching computer science to engineering students; to justify the expediency of using cloud technologies in teaching computer science to future engineers; and to select cloud tools that are most relevant for the computer science curriculum. As a result of the research, the choice of Google Apps as the leading and system-forming cloud-based computer science training tool for future engineers is justified, the model of using Google Apps in combined computer science teaching to engineering students is considered.

Nationwide research on the uses and motivations of dating apps by young adults in the cultural environment of Turkey

Since Tinder's worldwide popularity, location-based dating apps have become widespread. The existing literature mainly focuses on a single app in European and US contexts and pays little attention to other cultural contexts. This paper addresses this gap by examining dating app choices and motivations of young adults (18–29 years old) in Turkey. It examines the intersectionality of socio-demographic variables in a cultural setting that is quite different not only from European and US contexts but also from other Muslim-majority contexts. Deriving from the nationally representative survey ( n = 1,498), our research finds statistically significant differences in dating app preferences and adults’ motivations regarding location, sexual, gender, and religious identities. This study underlines the crucial role of cultural geography and its social fabric in mobile dating, even within the same national setting .

Framing Security Under Time Pressure: Brand Familiarity Matters for Mobile Application Choices

The current study examined the effects of security score framing, time pressure, and brand familiarity on mobile application choices. Past research has found the framing of safety versus risk scores affects how potential risks for mobile apps are communicated to users. Both time pressure and brand familiarity have been shown to affect consumers’ purchase behaviors but not yet for app-selection decisions. The current study examined the effects of time pressure and brand familiarity on the effectiveness of risk displays (framed as safety or risk) for mobile apps. Participants were shown screenshots of various apps with these factors manipulated, and they were to choose one out of six apps. Our findings indicate that users rely heavily on brand familiarity when choosing apps, which could lead to insecure decisions. Additionally, security scores guided app choices toward more secure apps when framed as safety than when framed as risk, although this advantage was only evident without time pressure and disappeared under time pressure. The design implications call for more careful screening and user education about the potential risks associated familiar apps, as well as the need of new security design solutions to help users under time pressure.

Evaluation of asemiautomated App Store analysis for the identification of health apps for cardiac arrhythmias.

Smartphone apps are increasingly utilised by patients and physicians for medical purposes. Thus, numerous applications are provided on the App Store platforms. The aim of the study was to establish anovel, expanded approach of asemiautomated retrospective App Store analysis (SARASA) to identify and characterise health apps in the context of cardiac arrhythmias. An automated total read-out of the "Medical" category of Apple's German App Store was performed in December 2022 by analysing the developer-provided descriptions and other metadata using asemiautomated multilevel approach. Search terms were defined, based on which the textual information of the total extraction results was automatically filtered. Atotal of 435 of 31,564 apps were identified in the context of cardiac arrhythmias. Of those, 81.4% were found to deal with education, decision support, or disease management, and 26.2% (additionally) provided the opportunity to derive information on heart rhythm. The apps were intended for healthcare professionals in 55.9%, students in 17.5%, and/or patients in 15.9%. In 31.5%, the target population was not specified in the description texts. In all, 108 apps (24.8%) provided atelemedicine treatment approach; 83.7% of the description texts did not reveal any information on medical product status; 8.3% of the apps indicated that they have and 8.0% that they do not have medical product status. Through the supplemented SARASA method, health apps in the context of cardiac arrhythmias could be identified and assigned to the target categories. Clinicians and patients have awide choice of apps, although the app description texts do not provide sufficient information about the intended use and quality.

Scoliosis Management through Apps and Software Tools.

Background: Scoliosis is curvature of the spine, often found in adolescents, which can impact on quality of life. Generally, scoliosis is diagnosed by measuring the Cobb angle, which represents the gold standard for scoliosis grade quantification. Commonly, scoliosis evaluation is conducted in person by medical professionals using traditional methods (i.e., involving a scoliometer and/or X-ray radiographs). In recent years, as has happened in various medicine disciplines, it is possible also in orthopedics to observe the spread of Information and Communications Technology (ICT) solutions (i.e., software-based approaches). As an example, smartphone applications (apps) and web-based applications may help the doctors in screening and monitoring scoliosis, thereby reducing the number of in-person visits. Objectives: This paper aims to provide an overview of the main features of the most popular scoliosis ICT tools, i.e., apps and web-based applications for scoliosis diagnosis, screening, and monitoring. Several apps are assessed and compared with the aim of providing a valid starting point for doctors and patients in their choice of software-based tools. Benefits for the patients may be: reducing the number of visits to the doctor, self-monitoring of scoliosis. Benefits for the doctors may be: monitoring the scoliosis progression over time, managing several patients in a remote way, mining the data of several patients for evaluating different therapeutic or exercise prescriptions. Materials and Methods: We first propose a methodology for the evaluation of scoliosis apps in which five macro-categories are considered: (i) technological aspects (e.g., available sensors, how angles are measured); (ii) the type of measurements (e.g., Cobb angle, angle of trunk rotation, axial vertebral rotation); (iii) availability (e.g., app store and eventual fee to pay); (iv) the functions offered to the user (e.g., posture monitoring, exercise prescription); (v) overall evaluation (e.g., pros and cons, usability). Then, six apps and one web-based application are described and evaluated using this methodology. Results: The results for assessment of scoliosis apps are shown in a tabular format for ease of understanding and intuitive comparison, which can help the doctors, specialists, and families in their choice of scoliosis apps. Conclusions: The use of ICT solutions for spinal curvature assessment and monitoring brings several advantages to both patients and orthopedics specialists. Six scoliosis apps and one web-based application are evaluated, and a guideline for their selection is provided.

A Multilateral Privacy Impact Analysis Method for Android Applications

Abstract Most people’s private lives can be monitored by smartphone applications (apps). Apps have the potential to invade private spaces, access and map social interactions, track users’ whereabouts, and track their online activities. Our interest is in the volume of data that a specific app can and seeks to retrieve on a smartphone. Smartphone app privacy friendliness is normally evaluated based on single-source analyses, which often do not offer a thorough assessment of the app’s actual privacy threats. In order to analyze Android apps’ privacy, this study proposes a multi-source methodology. Our data sets and methodology from app manifestos, privacy policies, vulnerability analysis and user reviews were described. Results from a case study on ten well-known finance applications operating in Nigeria were provided in order to assess our methodology. Our findings showed distinct patterns regarding the possible privacy implications of apps, with some of the apps in the data set infringing fundamental privacy principles. The case study’s findings reveal significant differences that can guide users in making relevant app choices.

Why people choose Apps: An evaluation of the ecology and user experience of mobile applications

PurposeTo investigate the reasons for users’ choice of mobile applications and how their choice relates to their experience of use. MethodA mixed methods study of the factors influencing users’ choice to adopt or abandon mobile applications. Seventy-nine respondents completed a questionnaire recording their top four favourite applications, the frequency of use and user experience measures: aesthetics, content, usability, pleasurable interaction, and overall experience. They also reported up to four abandoned Apps, with any alternatives considered and the reasons for use or abandoning. Follow-up interviews probed the reasons for users’ choice of specific applications. Results/ConclusionsSocial media was the most favoured category of App, followed by leisure, e-commerce, and communication. Quantitative data shows that content, usability and pleasure predict overall user experience and App acceptance. Interview data indicate that user's choice of downloading and abandoning applications is also influenced by usefulness, usability, content, reliability and contextual factors such as networking and recommendations. Most user App choices appear to be fast-path decisions made without systematic comparison of products.

PO42 Presentation Time: 4:45 PM: Gynecological Brachytherapy Pre-Planning Techniques: An Accurate Tool for Pre-Treatment Applicator Selection and Dose Prediction

<h3>Purpose</h3> To (1) develop a pre-planning technique to inform applicator (app) selection for brachytherapy (BT) treatments and (2) determine if this technique can accurately predict achievable HR-CTV and OAR dose metrics for an Advanced Gynecological Applicator (AGA) with needles. The accuracy of pre-plans generated on routine diagnostic scans and scans with an app present at the time of scan acquisition were evaluated and compared. <h3>Materials and Methods</h3> A retrospective study was performed on a patient who received treatment for Stage IVA cervical cancer. The treatment regimen included EBRT followed by 2 fractions (fxns) of pulsed-dose rate (PDR) BT. Four scans were acquired at different time points for BT planning: (Scan 1) a pre-BT MRI without app prior to PDR fxn 1; (Scan 2) CT with the AGA present at fxn 1; (Scan 3) post-BT1 / pre-BT2 MRI without app and acquired between fxns 1 and 2; and (Scan 4) CT with tandem and ovoids (TO). Solid applicator models (SAMs) of the AGA were rigidly registered (RR) in each of the four scans by a medical physicist. RR prioritized alignment of the SAMs with the HR-CTV and uterus, when possible. For the AGA, the paths of the straight needles were projected to cover the superior extent of the HR-CTV. Five plans were compared. Three plans were retrospectively generated pre-plans (Pre-Plan) using the AGA SAM, one plan was generated at the time of clinical treatment without a SAM (Clin-Plan), and one was a retrospectively re-optimized version of the clinical plan (Re-opt Plan) created using SAMs. Plans generated on Scans 1 and 3 were used to evaluate the accuracy of pre-planning with a SAM registered on a scan without an applicator present. The plan generated on Scan 4 was used to evaluate the accuracy of pre-planning with a SAM different than the app present in the scan. The plan generated on Scan 2 was used for clinical treatment and the dose metrics from the Re-Opt Plan generated on Scan 2 were used as a baseline for comparison with the Pre-Plans and the Clin Plan. All plans were optimized using uniform loading patterns. Contours were drawn by an attending radiation oncologist and plans were generated by a certified medical dosimetrist. An EBRT dose of 45 Gy to the target and OARs was assumed. The EBRT dose was subtracted from the total dose allowed by EMBRACE for each structure, and the remaining dose divided equally between the two PDR fxns. The Pre- and Re-Opt Plans were optimized to escalate dose to the HR-CTV while not exceeding any of the OAR objectives. The dose metrics of each Pre-Plan and Clin-Plan were compared with those of the Re-opt Plans. A clinically acceptable estimate was defined as +/- 6% of total OAR dose. <h3>Results</h3> All pre-plans accurately predicted the HR-CTV D90 to within 5% (Figure 1) regardless of app presence or absence during imaging. Pre-Plans generated with AGA SAMs registered on diagnostic scans without an app present did not accurately predict dose to the OARs (+/- 45% for bladder, +/- 16% for sigmoid). AGA Pre-Plans generated using scans with another app present (TO) accurately predicted the HR-CTV D90 within 5% and the bladder and sigmoid D2cc within 6% and 4%, respectively. The rectum D2cc was not accurately predicted by any of the Pre-Plans, likely due to physical deformations from the BT app placement. <h3>Conclusions</h3> The presence of an app in the scan, even if different from the SAM of interest, estimates the patient's anatomy at the time of implant and permits accurate prediction of dose to the bladder and sigmoid. MRI scans without a tandem in place are not of utility for pre-planning, regardless of timing. The developed pre-planning technique can be used to inform app choice using either pre-Brachy scans or scans acquired during a previous BT treatment fxn.

How Do Shared IT Applications Influence Agility? Theory and Evidence of a Convex Relationship

ABSTRACT Organizations increasingly depend on information technology (IT) applications (apps) for competitive positioning. Governance of IT apps presents a unique set of challenges, particularly as organizations turn to shared IT apps across business units (IT apps relatedness). Shared IT apps can foment IT misalignment within business units, while also creating opportunities for learning-related synergies. This study develops the idea that an organization’s efforts to increase IT apps relatedness influence business unit agility and that this relationship is U-shaped. Analysis of data from 120 organizations provides support for a convex, U‐shaped, relationship. Furthermore, the U-shaped curve flattens under conditions of increased market uncertainty. This relationship highlights the need for IT governance to balance tension between business unit interests that seek autonomy over certain IT app choices and corporate interests that push for synergies based on shared IT apps. Failure to create this balance could impede business unit agility and hurt the broader organization.

Research on parking app choice behavior based on MNL

As a kind of intelligent parking mode, shared parking mode has been widely promoted, and parking app, as a product of the development of sharing economy in the field of transportation, is also being vigorously advocated. However, there are not many people who use parking app to find and reserve parking space in practice, which is largely caused by insufficient information provided by the parking apps. In order to better explain, predict and improve drivers’ choice of parking apps, a multinomial logit model was established to analyze the relationship between drivers’ parking app choice behavior and the influential factors. The influential factors include drivers’ individual characteristics and parking app’s attributes, which were extracted from a questionnaire and typical parking apps currently in operation. The results show that the reservation and shared parking spaces, available parking spaces, parking charges and distance to the destination are the main factors that determine the drivers’ choice of parking app. This paper provides a reference for the development of Ningbo parking apps.

Hubungan Depresi dan Pilihan Aplikasi Smartphone dengan Kecanduan Smartphone Pada Siswa SMA

Advances in information and communication technology offer a sophisticated smartphone that has the potential to lead to addiction. Previous studies found smartphone addiction is motivated by the presence of psychological factors such as depression experienced by a person. In addition, previous studies also found a determining factor that is the magnitude of smartphone addiction different depends on the types of smartphone applications selected. Therefore, current research aims to identify the relationship between depression and the choice of smartphone apps with smartphone addiction in students. Current research is quantitative research methods. The participants of this study were 307 students. The instruments used in the study consisted of a depression scale, smartphone addiction scale, and smartphone app selection questionnaire. The data was analyzed using product-moment correlation. The data analysis revealed a positive correlation coefficient value of 0.468 with a significance of 0.000 (p&gt;0.05), meaning there was a positive association between depression and smartphone application choices with smartphone addiction in students. Thus, it can be concluded that the higher the level of depression experienced, the higher the level of smartphone addiction of students. Then, the choice of smartphone apps displayed a different impact on the level of smartphone addiction. Game applications have fewer percentages of voters compared to social media applications. However, game applications have a bigger influence on students' smartphone addiction.

Quality of condition suggestions and urgency advice provided by the Ada symptom assessment app evaluated with vignettes optimised for Australia.

When people face a health problem, they often first ask, 'Is there an app for that?'. We investigated the quality of advice provided by the Ada symptom assessment application to address the question, 'How do I know the app on my phone is safe and provides good advice?'. The app was tested with 48 independently created vignettes developed for a previous study, including 18 specifically developed for the Australian setting, using an independently developed methodology to evaluate the accuracy of condition suggestions and urgency advice. The correct condition was listed first in 65% of vignettes, and in the Top 3 results in 83% of vignettes. The urgency advice in the app exactly matched the gold standard 63% of vignettes. The app's accuracy of condition suggestion and urgency advice is higher than that of the best-performing symptom assessment app reported in a previous study (61%, 77% and 52% for conditions suggested in the Top 1, Top 3 and exactly matching urgency advice respectively). These results are relevant to the application of symptom assessment in primary and community health, where medical quality and safety should determine app choice.

A Novel Context-Aware Mobile Application Recommendation Approach Based on Users Behavior Trajectories

With the rapid development of mobile internet technology, mobile applications (apps) have been rapidly popularized. To facilitate users' choice of apps, app recommendation is becoming a research hotspot in academia and industry. Although traditional app recommendation approaches have achieved certain results, these methods only mechanically consider the user's current context information, ignoring the impact of the user's previous related context on the user's current selection of apps. We believe this has hindered the further improvement of the recommendation effect. Based on this fact, this paper proposes a novel context-aware mobile application recommendation approach based on user behavior trajectories. We named this approach CMARA, which is the initials acronym of the proposed approach. Specifically, 1) CMARA integrates the heterogeneous information of the target users such as the user's app, time, and location, into users behavior trajectories to model the users' app usage preferences; 2) CMARA constructs the context Voronoi diagram using the users' contextual point and leverages the context Voronoi diagram to build a novel user similarity model; 3) CMARA uses the target user's current contextual information to generate an app recommendation list that meets the user's preferences. Through experiments on large-scale real-world data, we verified the effectiveness of CMARA.

Self-Monitoring App Preferences for Sun Protection: Discrete Choice Experiment Survey Analysis.

BackgroundThe availability and use of health apps continues to increase, revolutionizing the way mobile health interventions are delivered. Apps are increasingly used to prevent disease, improve well-being, and promote healthy behavior. On a similar rise is the incidence of skin cancers. Much of the underlying risk can be prevented through behavior change and adequate sun protection. Self-monitoring apps have the potential to facilitate prevention by measuring risk (eg, sun intensity) and encouraging protective behavior (eg, seeking shade).ObjectiveOur aim was to assess health care consumer preferences for sun protection with a self-monitoring app that tracks the duration and intensity of sun exposure and provides feedback on when and how to protect the skin.MethodsWe conducted an unlabeled discrete choice experiment with 8 unique choice tasks, in which participants chose among 2 app alternatives, consisting of 5 preidentified 2-level attributes (self-monitoring method, privacy control, data sharing with health care provides, reminder customizability, and costs) that were the result of a multistep and multistakeholder qualitative approach. Participant preferences, and thus, the relative importance of attributes and their levels were estimated using conditional logit modeling. Analyses consisted of 200 usable surveys, yielding 3196 observations.ResultsOur respondents strongly preferred automatic over manually operated self-monitoring (odds ratio [OR] 2.37, 95% CI 2.06-2.72) and no cost over a single payment of 3 Swiss francs (OR 1.72, 95% CI 1.49-1.99). They also preferred having over not having the option of sharing their data with a health care provider of their choice (OR 1.66, 95% CI 1.40-1.97), repeated over single user consents, whenever app data are shared with commercial thirds (OR 1.57, 95% CI 1.31-1.88), and customizable over noncustomizable reminders (OR 1.30, 95% CI 1.09-1.54). While most participants favored thorough privacy infrastructures, the attribute of privacy control was a relatively weak driver of app choice. The attribute of self-monitoring method significantly interacted with gender and perceived personal usefulness of health apps, suggesting that female gender and lower perceived usefulness are associated with relatively weaker preferences for automatic self-monitoring.ConclusionsBased on the preferences of our respondents, we found that the utility of a self-monitoring sun protection app can be increased if the app is simple and adjustable; requires minimal effort, time, or expense; and has an interoperable design and thorough privacy infrastructure. Similar features might be desirable for preventive health apps in other areas, paving the way for future discrete choice experiments. Nonetheless, to fully understand these preference dynamics, further qualitative or mixed method research on mobile self-monitoring-based sun protection and broader preventive mobile self-monitoring is required.International Registered Report Identifier (IRRID)RR2-10.2196/16087

Can You Hear Me Now? Audio and Visual Interactions That Change App Choices.

Android and iOS mobile operating systems use permissions to enable phone owners to manage access to their device's resources. Both systems provide resource access dialogues at first use and per-resource controls. Android continues to offer permission manifests in the Android PlayStore for older apps but is transitioning away from this. Neither manifests nor first-use dialogues enable people to easily compare apps based on resource requests, and the corresponding privacy and security risks. Without the ability to compare resource requests when choosing an app, customers cannot select those apps that request fewer resources. Unnecessary and excessive permission requests, overuse of resources, information exfiltration, and risky apps are endemic. To address this issue we built upon past work in warning science and risk communication to design multimedia indicators to communicate the aggregate privacy and security risk associated with an app. Specifically, we provided participants with a privacy rating using the familiar padlock icon and used audio notifications to either warn or reinforce user choices. We empirically tested participants' app decisions with these padlock icons and audio notifications. The results showed that people with both visual cues and audio feedback are more likely to make app choices that are inversely correlated with the resources requested by the app. Those with neither indicators made decisions reflecting only app rating, while decisions made by those with either the audio or the visual indicators are sometimes inversely correlated with resource requests. This illustrates that simple clear communication about apps' aggregate risk, as opposed to atomic resource requests, changes participants' app selections potentially mitigating the state of information overuse and potential abuse. Additionally, neither the visual indicator nor the audio feedback affected the time required for participants to make a decision.

College student engagement with mental health apps: analysis of barriers to sustained use

Objective: College students’demand for mental health resources is straining the services offered by colleges. While mobile apps demonstrate potential to help, students’ engagement with these apps remains low. This study examines why college students show poor engagement with mental health apps and how apps may be adapted to suit this population. Participants: Participants were a convenience sample of 100 college students. Methods: Qualitative data was gathered through individual online interviews concerningattitudes toward mental health apps, and quantitative data was gathered through a survey about phone and app use. Results: Students were interested in mental health apps. 53% haddownloaded an app at one point, but only 19% currently used a mental health app. Stress and costdrove mental health app choices. Responses around engagement centered on: Data privacy, user interface, credibility, and customization. Conclusions: Students have specific wants for mental health apps including safety, simplicity, credibility, and customizability.

Rating of Pelvic Floor Muscle Training Mobile Applications for Treatment of Urinary Incontinence in Women

To identify pelvic floor muscle therapy mobile health applications (apps) targeting women with urinary incontinence (UI), and evaluate them in a standardized fashion. A systematic search of English language apps on the Canadian App Store (iOS) and Google Play (Android) Store was performed. Eligible apps were evaluated independently by 5 reviewers using the validated Mobile App Rating Scale (MARS) tool. Descriptive characteristics were summarized and MARS subscale and overall quality scores werereported. Of 139 mobile health apps identified, 20 unique apps were included for full review, of which there were 7 iOS only apps, 6 Android only apps, and 7 apps available in both stores. At the time of analysis, most apps had been updated within the last year (60%). Only 1 app had been trialed and verified by evidence in scientific literature. The majority of apps were free to download (80%). The median (interquartile range) MARS overall quality score was 3.7 (0.8) on a 0-5 scale, ranging from 2.7 to 4.1. The highest-rated subscale was "functionality" with a median score of 4.1 (0.6); the lowest-rated was "information" with a median score of 3.4 (0.6). The median MARS subjective quality score was 2.9 (1.0). There are both free and paid apps available on-line that deliver pelvic floor muscle therapy programs. Evaluation using the MARS tool identified that many apps are not of high quality, and only 1 was evidence-based and has been trialed clinically. This knowledge is relevant to the choice of apps by both patients and caregivers.

Analysis Of Physical Activity-Related Smartphone Apps For Behavior Change Potential

The majority of Americans do not meet physical activity (PA) guidelines. Adoption and adherence may be improved with personalized intervention. Smartphone app use has increased exponentially in the past decade, extending to many areas of life and crossing socioeconomic status, ethnicity, and gender. Free smartphone apps that address habitual PA may be a useful tool, but their potential to support PA behavior change is not well understood. PURPOSE: To evaluate top-ranked free health and fitness apps for PA behavior change potential and to determine the relationship between this evaluation and consumer perceptions of quality, such as app store ranking and consumer ratings. METHODS: The top 100 "free" health and fitness apps in the US iOS app store were screened for rinclusion. Apps were excluded if the descriptions did not address any aspects of PA or fitness; required an external device, purchase/subscription after a trial period, or a health club membership or specific health insurance. Apps were also excluded if their descriptions was not written in English. Two investigators downloaded and evaluated the remaining apps that met the inclusion criteria using the App Behavior Change Scale (ABACUS). Apps were scored on 21 strategies within 4 categories (knowledge/information, goals/planning, feedback/monitoring, and actions), and prevalence in the sample was calculated. Pearson correlations were estimated for the relationship between ABACUS total scores and relative app ranking, as well as consumer rating. Significance was set at p < 0.05. RESULTS: 23 apps met the inclusion criteria. 100% offered some form of personalization; 96% incorporated self-monitoring and/or rehearsal; and 70% included options for goal-setting. Only 13% recommended restructuring of the environment, and 4% provided advice on distraction or avoidance. There were no significant correlations between ABACUS score and store ranking (r2= -0.15, p = 0.49) or consumer rating (r2= -0.26, p = 0.91) . CONCLUSIONS: Free apps may have the potential to support PA behavior change, especially in the areas of planning and self-monitoring. There is no correlation between the total number of evidence-based behavior change strategies and app popularity, however, so it may be beneficial for wellness professionals to counsel patients and clients on app choice.