Popular Smartphone Apps Research Articles

Can self-set goals encourage resource conservation? Field experimental evidence from a smartphone app

This study leverages a large RCT to examine the potential of goal-setting nudges to encourage resource conservation at scale. We randomize a feature that allows subjects to set themselves energy consumption targets in a popular smartphone app. We document negative effects of the nudge on app utilization and estimate null effects on energy consumption with confidence intervals that rule out estimates from observational studies. A complementary survey identifies the mechanisms underlying these behavioral responses. Using a structural model and random variation of the app’s price, we estimate that the average user is willing to pay 7.41 EUR to avoid the nudge.

CHAT SIMULATOR USING AES ENCRYPTION

Smartphones have become an integral part the lives of individuals and their priorities The present moment. The most visible uses are to chat and chat programs Most of these apps do does not provide the necessary protection and privacy information exchanged between users. Chat apps have become one of the most important and popular smartphone apps. It has the ability to exchange text messages, images and files that can freely communicate with each other. All messages must be protected and in this paper the encryption to used for secure all messages is by using AES encryption. AES (Advanced Encryption Standard) is a symmetric encryption algorithm widely used to keep data confidential in Internet networks. AES uses a block cipher with a block length of 128 bits and can encrypt data with keys consisting of 128, 192, or 256 bits. AES is one of the strongest encryption algorithms available today. It has been adopted by many organizations, including governments, banks, and technology companies. AES security is based on mathematical complexity and is difficult to crack even on ultra-fast computers. The AES encryption process involves multiple steps such as replace, move, and merge. The original data is split into smaller blocks and encrypted with the provided key. The blocks then change periodically, complicating the data patterns an attacker might find

Classification of Lapses in Smokers Attempting to Stop: A Supervised Machine Learning Approach Using Data From a Popular Smoking Cessation Smartphone App.

Smoking lapses after the quit date often lead to full relapse. To inform the development of real time, tailored lapse prevention support, we used observational data from a popular smoking cessation app to develop supervised machine learning algorithms to distinguish lapse from non-lapse reports. We used data from app users with ≥20 unprompted data entries, which included information about craving severity, mood, activity, social context, and lapse incidence. A series of group-level supervised machine learning algorithms (eg, Random Forest, XGBoost) were trained and tested. Their ability to classify lapses for out-of-sample (1) observations and (2) individuals were evaluated. Next, a series of individual-level and hybrid algorithms were trained and tested. Participants (N = 791) provided 37 002 data entries (7.6% lapses). The best-performing group-level algorithm had an area under the receiver operating characteristic curve (AUC) of 0.969 (95% confidence interval [CI] = 0.961 to 0.978). Its ability to classify lapses for out-of-sample individuals ranged from poor to excellent (AUC = 0.482-1.000). Individual-level algorithms could be constructed for 39/791 participants with sufficient data, with a median AUC of 0.938 (range: 0.518-1.000). Hybrid algorithms could be constructed for 184/791 participants and had a median AUC of 0.825 (range: 0.375-1.000). Using unprompted app data appeared feasible for constructing a high-performing group-level lapse classification algorithm but its performance was variable when applied to unseen individuals. Algorithms trained on each individual's dataset, in addition to hybrid algorithms trained on the group plus a proportion of each individual's data, had improved performance but could only be constructed for a minority of participants. This study used routinely collected data from a popular smartphone app to train and test a series of supervised machine learning algorithms to distinguish lapse from non-lapse events. Although a high-performing group-level algorithm was developed, it had variable performance when applied to new, unseen individuals. Individual-level and hybrid algorithms had somewhat greater performance but could not be constructed for all participants because of the lack of variability in the outcome measure. Triangulation of results with those from a prompted study design is recommended prior to intervention development, with real-world lapse prediction likely requiring a balance between unprompted and prompted app data.

Introducing Dietary Self-Monitoring to Undergraduate Women via a Calorie Counting App Has No Effect on Mental Health or Health Behaviors: Results From a Randomized Controlled Trial

BackgroundStrong positive relationships between dietary self-monitoring and eating disorder risk are seen in population-based, observational studies. However, current evidence cannot establish causality. Furthermore, little is known about other mental and behavioral health consequences of dietary self-monitoring among college women, a population vulnerable to eating disorders. ObjectiveTo determine if introducing dietary self-monitoring via a popular smartphone app to undergraduate women impacts eating disorder risk, other aspects of mental health, or health behaviors including dietary intake and physical activity. DesignRandomized controlled trial. Participants/settingUndergraduate women who had not engaged in dietary self-monitoring in the past year and who were at low-risk for an eating disorder participated between May and October 2019 (n = 200). InterventionParticipants were randomly assigned to engage in dietary self-monitoring via MyFitnessPal for approximately 1 month or to receive no intervention. Main outcome measuresSelf-report data on eating disorder risk, other mental health outcomes, and health behaviors were collected at baseline and post-intervention. Statistical analyses performedLinear and logistic regressions were utilized to test hypotheses. ResultsAdherence to the intervention was high, with participants recording their dietary intake via MyFitnessPal on average 89.1% of days between baseline and post-intervention. Assignment to the intervention was not associated with changes in eating disorder risk, anxiety, depressive symptoms, body satisfaction, quality of life, nutritional intake, physical activity, screen time, or other forms of weight-related self-monitoring (all P > .05). ConclusionsAmong dietary self-monitoring naive undergraduate women with low-risk of an eating disorder, dietary self-monitoring via MyFitnessPal for 1 month did not increase eating disorder risk, impact other aspects of mental health, or alter health behaviors including dietary intake. The null results in our study may be due to the selection of a low-risk sample; future research should explore whether there are populations for whom dietary self-monitoring is contraindicated.

Smartphone apps for eating disorders: A systematic review of evidence-based content and application of user-adjusted analyses.

To examine the frequency of evidence-based treatment elements in popular smartphone apps for eating disorders (EDs), and to characterize the extent to which real-world users encounter different elements. We searched the Apple App Store and Google Play Store for apps offering treatment or support to individuals with EDs. Then, we created a codebook of 47 elements found in evidence-based treatments for EDs. We examined the presence or absence of each element within each ED app. We also acquired estimates of the monthly active users (MAU) of each app. The ED apps (n = 28) included a median of nine elements of empirically supported treatments (mean = 9.46, SD = 6.28). Four apps accounted for 96% of all MAU. MAU-adjusted analyses revealed that several elements are reaching more users than raw frequency tallies would suggest. For example, assessments were included in 32% of apps, but 84% of users used an app with assessments. Similar trends were found for cognitive restructuring (21% of apps, 56% of MAU), activity scheduling (39%, 57%), and self-monitoring (14%, 46%). Problem solving, exposure, and relapse prevention strategies, elements that are prominent in face-to-face empirically supported treatments, were rarely included in the apps. Evidence-based content is commonly included in ED apps, with certain elements reaching more users than others. Additionally, the top four apps are responsible for nearly all active users. We recommend that ED clinicians and researchers familiarize themselves with these apps-those that patients are most likely to encounter.

Reassessing evidence-based content in popular smartphone apps for depression and anxiety: Developing and applying user-adjusted analyses.

To assess the dissemination of evidence-based content within smartphone apps for depression and anxiety by developing and applying user-adjusted analysis-a method for weighting app content based on each app's number of active users. We searched the Apple App Store and Google Play Store and identified 27 apps within the top search hits, which real-world users are most likely to encounter. We developed a codebook of evidence-based treatment elements by reviewing past research on empirically supported treatments. We coded the apps to develop an initial tally of the frequency of treatment elements within the mental health (MH) apps. We then developed and applied user-adjusted analysis to refine the tallies based on each app's number of monthly active users. The 2 most popular apps were responsible for 90% of monthly active users, and user-adjusted analysis markedly altered conclusions of prior reports based on tallies alone. For example, mindfulness was present in 37% of apps but reached 96% of monthly active users, cognitive restructuring was present in 22% but reached only 2%, and exposure was present in 7% but reached only 0.0004%. The potential impact of MH apps on mental health may be best evaluated via assessment that combines tallies of evidence-based content with data on the content users are actually accessing. Given wide variation in the popularity of MH apps, findings weighted by usage data may differ markedly from findings based on raw tallies alone. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Popular Smartphone Apps to Improve Wellness and Reduce Stress: Science or Snake Oil? (RP402)

Popular Smartphone Apps to Improve Wellness and Reduce Stress: Science or Snake Oil? (RP402)

Popular Smartphone Apps to Improve Wellness and Reduce Stress: Science or Snake Oil? (FR461C)

Popular Smartphone Apps to Improve Wellness and Reduce Stress: Science or Snake Oil? (FR461C)

Supplemental Material for Reassessing Evidence-Based Content in Popular Smartphone Apps for Depression and Anxiety: Developing and Applying User-Adjusted Analyses

Supplemental Material for Reassessing Evidence-Based Content in Popular Smartphone Apps for Depression and Anxiety: Developing and Applying User-Adjusted Analyses

A review of popular smartphone apps for depression and anxiety: Assessing the inclusion of evidence-based content

Smartphone applications for the treatment of depression and anxiety have acquired millions of users, yet little is known about whether they include evidence-based therapeutic content. We examined the extent to which popular mental health applications (MH apps) for depression and anxiety contain treatment elements found in empirically supported psychotherapy protocols (i.e., “common elements”). Of the 27 MH apps reviewed, 23 included at least one common element, with a median of three elements. Psychoeducation (in 52% of apps), relaxation (44%), meditation (41%), mindfulness (37%), and assessment (37%) were the most frequent elements, whereas several elements (e.g., problem solving) were not found in any apps. We also identified gaps between app content and empirically supported treatments. Cognitive restructuring was more common in depression protocols than in depression apps (75% of protocols vs. 31% of apps), as was problem solving (34% vs. 0%). For anxiety, exposure (85%, 12%), cognitive restructuring (60%, 12%), and problem solving (25%, 0%) were more common in protocols than apps. Overall, our findings highlight empirically supported treatment elements that are poorly represented in current MH apps. The absence of several core treatment elements underscores the need for future research, including randomized trials testing the effectiveness of popular MH apps.

Readability of Information on Smartphone Apps for Total Hip Replacement and Total Knee Replacement Surgery Patients.

Background:Readability is a vital component of health information and providing this material at an appropriate literacy level may positively influence patient experience.Objective:To assess the readability of the information provided within total hip replacement and total knee replacement apps to understand more about the impact this could have on patients.Method:A systematic search was conducted across the 5 most popular smartphone app stores: iTunes, Google Play, Windows Mobile, Blackberry App World, and Nokia Ovi. Apps were identified for screening if they: targeted total hip replacement or total knee replacement patients; were free of charge; and were in English. App readability assessment was conducted independently by 3 reviewers using the Gunning Fog Index, the Flesch Reading Ease Score, and the Flesch-Kincaid Grade Level.Results:Fifteen apps met the inclusion criteria. Only one app was found “easy to read” (My THR).Conclusion:Findings suggest that the overall readability of information provided is written at a level which is difficult for patients to comprehend. App developers should engage patients in the design process of their apps, in order to enhance patient experience and for the potential impact of these innovative health technologies to be truly realized.

Revealing the unrevealed: Mining smartphone users privacy perception on app markets

Popular smartphone apps may receive several thousands of user reviews containing statements about apps’ functionality, interface, user-friendliness, etc. They sometimes also comprise privacy relevant information that can be extremely helpful for app developers to better understand why users complain about certain privacy aspects of their apps. However, due to the complicated and sometimes vague nature of reviews, it is quite though and time consuming for developers to go through all these reviews to get information about privacy aspects of apps. Furthermore, previous studies confirmed that sometimes bad privacy practices happen due to the app developers’ lack of knowledge in API definition and usage. In addition, such information can be useful for mobile users as the lack of privacy indicators in smartphone ecosystems prevents them from being able to compare apps in terms of privacy and to perform informed privacy decision making when selecting apps. Therefore, in this paper we propose Mobile App Reviews Summarization (MARS) to overcome the aforementioned difficulties. We exploit user reviews on the Google Play Store as a relevant source in order to extract and quantify privacy relevant claims associated with apps. Based on Machine Learning (ML), Natural Language Processing (NLP) and sentiment analysis techniques, MARS detects privacy relevant reviews and categorizes them into a pre-identified list of privacy threats in the context of mobile apps. The combination of these concepts provides developers with specific knowledge about the privacy threats and behavior of apps based on user generated reports that are otherwise difficult to detect. Not only developers, but also users can benefit from such mechanism to compare apps in terms of privacy aspects. To this end, we complement MARS by a novel app behavior monitoring tool that further enhances the whole reliability of the results generated by MARS. Our results demonstrate the applicability of our approach which provides precision, recall and F-score as high as 94.84%, 91.30% and 92.79%, respectively. Also, we obtained interesting findings concerning the quantity and quality of privacy relevant information published in the user reviews and their relation to the apps’ behavior in reality indicating that user reviews are important and valuable source of information regarding the privacy behavior of mobile apps.

Smartphone apps for total hip replacement and total knee replacement surgery patients: a systematic review

Purpose: The aim of this study was to critically examine the content of smartphone apps produced for patients undergoing total hip replacement and total knee replacement surgery.Materials and methods: A systematic search was conducted across the five most popular smartphone app stores: iTunes; Google Play; Windows Mobile; Blackberry App World; and Nokia Ovi. Apps were identified for screening if they: targeted total hip replacement or total knee replacement patients; were free of charge; and were in English. App quality assessment was conducted independently by three reviewers using the Mobile App Rating Scale.Results: 15 apps met the inclusion criteria. On the 5-point Mobile App Rating Scale, the mean overall app quality score was 3.1. Within the Mobile App Rating Scale, the “Aesthetics” subscale had the most inconsistency across all apps, generating the highest and lowest mean scores (4.7 and 1, respectively). The “functionality” subscale had the highest mean score (3.8) among the four subscales, and the “information” subscale had the lowest mean score (2.7).Conclusion: This study highlights that despite a wide range of apps currently available to total hip replacement and total knee replacement patients, there is significant variability in their quality. Future efforts should be made to develop apps in partnership with patients, to improve the content, interactivity and relevance of apps.Implications for RehabilitationClinicians and rehabilitation professionals should consider that patients are using Smartphone apps to supplement their rehabilitation and be aware of currently available apps.Although some apps show promise, at present there is no one openly available app which is clinically recommended for rehabilitation use following total hip replacement and total knee replacement.Rehabilitation professionals tailor recovery programmes to individual patient needs following total hip replacement and total knee replacement, and future apps should also consider personal needs.We recommend that patients are involved in all stages of designing and testing future total hip replacement and total knee replacement rehabilitation apps.

Current Status of Cardiovascular Disease-Related Smartphone Apps Downloadable in China.

Smartphone apps present a great opportunity for the management of cardiovascular disease (CVD) as the adoption of apps becomes increasingly popular in China. Yet, little is known about the status of CVD-related Smartphone apps in the country. The aim of this study was to examine the current status of CVD-related smartphone apps available for download in China. Using CVD-related keywords written either in Chinese or English, the top 6 most popular smartphone app online stores in China were searched in September 2015. The information accountability of the selected apps was assessed with the Silberg scale. The key topic areas identified from the European Guidelines on cardiovascular disease prevention served to determine information coverage of the top 5 downloaded apps. The average Silberg score of 151 apps was 2.87 (out of 9) with most apps not revealing authors' qualifications and information references. There was also a lack of sponsorship disclosure and information update. Moreover, none of the top 5 downloaded apps covered all key areas of CVD management as recommended by the European Guidelines on cardiovascular disease prevention. There was little evidence of health professionals' involvement in the formation of the CVD-related apps. This study identified areas for improvement concerning information accountability and the scope of coverage of CVD-related apps downloadable in China. The findings may guide the future advancement of CVD-related apps and benefit CVD management in China.

Validity of Popular Smartphone Apps at Measuring Steps at Different Intensities

Validity of Popular Smartphone Apps at Measuring Steps at Different Intensities

The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment.

BackgroundAdvancements in mobile phone technology have led to the development of smartphones with the capability to run apps. The availability of a plethora of health- and fitness-related smartphone apps has the potential, both on a clinical and public health level, to facilitate healthy behavior change and weight management. However, current top-rated apps in this area have not been extensively evaluated in terms of scientific quality and behavioral theory evidence base.ObjectiveThe purpose of this study was to evaluate the quality of the most popular dietary weight-loss smartphone apps on the commercial market using comprehensive quality assessment criteria, and to quantify the behavior change techniques (BCTs) incorporated.MethodsThe top 200-rated Health & Fitness category apps from the free and paid sections of Google Play and iTunes App Store in Australia (n=800) were screened in August 2014. To be included in further analysis, an app had to focus on weight management, include a facility to record diet intake (self-monitoring), and be in English. One researcher downloaded and used the eligible apps thoroughly for 5 days and assessed the apps against quality assessment criteria which included the following domains: accountability, scientific coverage and content accuracy of information relevant to weight management, technology-enhanced features, usability, and incorporation of BCTs. For inter-rater reliability purposes, a second assessor provided ratings on 30% of the apps. The accuracy of app energy intake calculations was further investigated by comparison with results from a 3-day weighed food record (WFR).ResultsAcross the eligible apps reviewed (n=28), only 1 app (4%) received full marks for accountability. Overall, apps included an average of 5.1 (SD 2.3) out of 14 technology-enhanced features, and received a mean score of 13.5 (SD 3.7) out of 20 for usability. The majority of apps provided estimated energy requirements (24/28, 86%) and used a food database to calculate energy intake (21/28, 75%). When compared against the WFR, the mean absolute energy difference of apps which featured energy intake calculations (23/28, 82%) was 127 kJ (95% CI -45 to 299). An average of 6.3 (SD 3.7) of 26 BCTs were included.ConclusionsOverall, the most popular commercial apps for weight management are suboptimal in quality, given the inadequate scientific coverage and accuracy of weight-related information, and the relative absence of BCTs across the apps reviewed. With the limited regulatory oversight around the quality of these types of apps, this evaluation provides clinicians and consumers an informed view of the highest-quality apps in the current popular app pool appropriate for recommendation and uptake. Further research is necessary to assess the effectiveness of apps for weight management.

Are You Connected to the Best Apps?

While the vast majority of pharmacists use computers to access medical information, many prefer a mobile device to find information quickly. This review discusses pharmacists' use of mobile device applications (apps) and highlights an assortment of apps that are particularly helpful. Epocrates, which provides drug information and clinical content, was the first popular smartphone app developed in this area and was used to introduce the concept. Today, apps that provide a wide range of drug information can be supplemented with apps that fine-tune specific information about drug monitoring, disease states, and cost.

Smartphone apps for orthopaedic sports medicine - a smart move?

BackgroundWith the advent of smartphones together with their downloadable applications (apps), there is increasing opportunities for doctors, including orthopaedic sports surgeons, to integrate such technology into clinical practice. However, the clinical reliability of these medical apps remains questionable. We reviewed available apps themed specifically towards Orthopaedic Sports Medicine and related conditions and assessed the level of medical professional involvement in their design and content, along with a review of these apps.MethodThe most popular smartphone app stores (Android, Apple, Blackberry, Windows, Samsung, Nokia) were searched for Orthopaedic Sports medicine themed apps, using the search terms; Orthopaedic Sports Medicine, Orthopaedics, Sports medicine, Knee Injury, Shoulder Injury, Anterior Cruciate Ligament Tear, Medial Collateral Ligament Tear, Rotator Cuff Tear, Meniscal Tear, Tennis Elbow. All English language apps related to orthopaedic sports medicine were included.ResultsA total of 76 individual Orthopaedic Sports Medicine themed apps were identified. According to app store classifications, there were 45 (59 %) medical themed apps, 28 (37 %) health and fitness themed apps, 1 (1 %) business app, 1 (1 %) reference app and 1 (1 %) sports app. Forty-nine (64 %) apps were available for download free of charge. For those that charged access, the prices ranged from £0.69 to £69.99. Only 51 % of sports medicine apps had customer satisfaction ratings and 39 % had named medical professional involvement in their development or content.ConclusionsWe found the majority of Orthopaedic Sports Medicine apps had no named medical professional involvement, raising concerns over their content and evidence-base. We recommend increased regulation of such apps to improve the accountability of app content.

Smartphone apps for spinal surgery: is technology good or evil?

The increased utilization of smartphones together with their downloadable applications (apps) provides opportunity for doctors, including spinal surgeons, to integrate such technology into clinical practice. However, the clinical reliability of the medical app sector remains questionable. We reviewed available apps themed specifically towards spinal surgery and related conditions and assessed the level of medical professional involvement in their design and content. The most popular smartphone app stores (Android, Apple, Blackberry, Windows, Samsung, Nokia) were searched for spinal surgery-themed apps, using the disease terms Spinal Surgery, Back Surgery, Spine, Disc Prolapse, Sciatica, Radiculopathy, Spinal Stenosis, Scoliosis, Spinal Fracture and Spondylolisthesis. A total of 78 individual spinal surgery themed apps were identified, of which there were six duplicates (N=72). According to app store classifications, there were 57 (79%) medical themed apps, 11 (15%) health and fitness themed apps, 1 (1%) business and 3 (4%) education themed apps. Forty-five (63%) apps were available for download free of charge. For those that charged access, the prices ranged from £0.62 to £47.99. Only 44% of spinal surgery apps had customer satisfaction ratings and 56% had named medical professional involvement in their development or content. This is the first study to specifically address the characteristics of apps related to spinal surgery. We found that nearly half of spinal surgery apps had no named medical professional involvement, raising concerns over app content and evidence base for their use. We recommend increased regulation of spinal surgical apps to improve the accountability of app content.

Dietary self-monitoring, but not dietary quality, improves with use of smartphone app technology in an 8-week weight loss trial.

Dietary self-monitoring is linked to improved weight loss success. Mobile technologies, such as smartphone applications (apps), might allow for improved dietary tracking adherence. The authors assessed the use of a popular smartphone app for dietary self-monitoring and weight loss by comparing it with traditional diet counseling and entry methods. Diet tracking and weight loss were compared across participants during an 8-week weight loss trial. Participants tracked intake using 1 of 3 methods: the mobile app "Lose It!", the memo feature on a smartphone, or a traditional paper-and-pencil method. App users (n=19) recorded dietary data more consistently compared with the paper-and-pencil group (n = 15; P = .042) but not the memo group (n = 13). All groups lost weight over the course of the study (P = .001), and no difference in weight loss was noted between groups. Smartphone apps could represent a novel and feasible dietary self-monitoring method for individuals.