Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review.

BACKGROUND: There are several mobile health (mHealth) apps in mobile app stores. These apps enter the business-to-customer market with limited controls. Both, apps that users use autonomously and those designed to be recommended by practitioners require an end-user validation to minimize the risk of using apps that are ineffective or harmful. Prior studies have reviewed the most relevant aspects in a tool designed for assessing mHealth app quality, and different options have been developed for this purpose. However, the psychometric properties of the mHealth quality measurement tools, that is, the validity and reliability of the tools for their purpose, also need to be studied. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) initiative has developed tools for selecting the most suitable measurement instrument for health outcomes, and one of the main fields of study was their psychometric properties. OBJECTIVE: This study aims to address and psychometrically analyze, following the COSMIN guideline, the quality of the tools that are used to measure the quality of mHealth apps. METHODS: From February 1, 2019, to December 31, 2019, 2 reviewers searched PubMed and Embase databases, identifying mHealth app quality measurement tools and all the validation studies associated with each of them. For inclusion, the studies had to be meant to validate a tool designed to assess mHealth apps. Studies that used these tools for the assessment of mHealth apps but did not include any psychometric validation were excluded. The measurement tools were analyzed according to the 10 psychometric properties described in the COSMIN guideline. The dimensions and items analyzed in each tool were also analyzed. RESULTS: The initial search showed 3372 articles. Only 10 finally met the inclusion criteria and were chosen for analysis in this review, analyzing 8 measurement tools. Of these tools, 4 validated ≥5 psychometric properties defined in the COSMIN guideline. Although some of the tools only measure the usability dimension, other tools provide information such as engagement, esthetics, or functionality. Furthermore, 2 measurement tools, Mobile App Rating Scale and mHealth Apps Usability Questionnaire, have a user version, as well as a professional version. CONCLUSIONS: The Health Information Technology Usability Evaluation Scale and the Measurement Scales for Perceived Usefulness and Perceived Ease of Use were the most validated tools, but they were very focused on usability. The Mobile App Rating Scale showed a moderate number of validated psychometric properties, measures a significant number of quality dimensions, and has been validated in a large number of mHealth apps, and its use is widespread. It is suggested that the continuation of the validation of this tool in other psychometric properties could provide an appropriate option for evaluating the quality of mHealth apps

Effectiveness of a gamified digital intervention based on lifestyle modification (iGAME) in secondary prevention: a protocol for a randomised controlled trial

Introduction Combating physical inactivity and reducing sitting time are one of the principal challenges proposed by public health systems. Gamification has been seen as an innovative, functional and motivating strategy to encourage patients to increase their physical activity (PA) and reduce sedentary lifestyles through behaviour change techniques (BCT). However, the effectiveness of these interventions is not usually studied before their use. The main objective of this study will be to analyse the effectiveness of a gamified mobile application (iGAME) developed in the context of promoting PA and reducing sitting time with the BCT approach, as an intervention of secondary prevention in sedentary patients.Methods and analysis A randomised clinical trial will be conducted among sedentary patients with one of these conditions: non-specific low back pain, cancer survivors and mild depression. The experimental group will receive a 12-week intervention based on a gamified mobile health application using BCT to promote PA and reduce sedentarism. Participants in the control group will be educated about the benefits of PA. The International Physical Activity Questionnaire will be considered the primary outcome. International Sedentary Assessment Tool, EuroQoL-5D, MEDRISK Instruments and consumption of Health System resources will be evaluated as secondary outcomes. Specific questionnaires will be administered depending on the clinical population. Outcomes will be assessed at baseline, at 6 weeks, at the end of the intervention (12 weeks), at 26 weeks and at 52 weeks.Ethics and dissemination The study has been approved by the Portal de Ética de la Investigación Biomédica de Andalucía Ethics Committee (RCT-iGAME 24092020). All participants will be informed about the purpose and content of the study and written informed consent will be completed. The results of this study will be published in a peer-reviewed journal and disseminated electronically and in print.Trial registration number NCT0401911

Assessment of the quality of mobile applications (Apps) for management of low back pain using the mobile app rating scale (mars)

Digital health interventions may improve different behaviours. However, the rapid proliferation of technological solutions often does not allow for a correct assessment of the quality of the tools. This study aims to review and assess the quality of the available mobile applications (apps) related to interventions for low back pain. Two reviewers search the official stores of Android (Play Store) and iOS (App Store) for localisation in Spain and the United Kingdom, in September 2019, searching for apps related to interventions for low back pain. Seventeen apps finally are included. The quality of the apps is measured using the Mobile App Rating Scale (MARS). The scores of each section and the final score of the apps are retrieved and the mean and standard deviation obtained. The average quality ranges between 2.83 and 4.57 (mean 3.82) on a scale from 1 (inadequate) to 5 (excellent). The best scores are found in functionality (4.7), followed by aesthetic content (mean 4.1). Information (2.93) and engagement (3.58) are the worst rated items. Apps generally have good overall quality, especially in terms of functionality and aesthetics. Engagement and information should be improved in most of the apps. Moreover, scientific evidence is necessary to support the use of applied health tools

Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code

The study’s purpose was to assess the reliability of the LIS2DH12 in two different positions, using the commercial sensor Actigraph GT9X as a reference instrument. Five participants completed two gait tests on a treadmill. Firstly, both sensors were worn on the wrist and around the thigh. Each test consisted of a 1 min walk for participants to become accustomed to the treadmill, followed by a 2 min trial at ten pre-set speeds. Data from both sensors were collected in real-time. Intraclass correlation coefficient (ICC) was used to evaluate the equality of characteristics obtained by both sensors: maximum peaks, minimum peaks, and the mean of the complete signal (sequence of acceleration values along the time) by each axis and speed were extracted to evaluate the equality of characteristics obtained with LIS2DH12 compared to Actigraph. Intraclass correlation coefficient (ICC) was extracted, and a standard deviation of the mean was obtained from the data. Our results show that LIS2DH12 measurements present more reliability than Actigraph GT9X, ICC > 0.8 at three axes. This study concludes that LIS2DH12 is as reliable and accurate as Actigraph GT9X Link and, therefore, would be a suitable tool for future kinematic studies

The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors

Through this study, we developed and validated a system for energy expenditure calcula-tion, which only requires low-cost inertial sensors and open source R software. Five healthy subjects ran at ten different speeds while their kinematic variables were recorded on the thigh and wrist. Two ActiGraph wireless inertial sensors and a low-cost Bluetooth-based inertial sensor (Lis2DH12), assembled by SensorID, were used. Ten energy expenditure equations were automatically calculated in a developed open source R software (our own creation). A correlation analysis was used to compare the results of the energy expenditure equations. A high interclass correlation coefficient of estimated energy expenditure on the thigh and wrist was observed with an Actigraph and Sensor ID accelerometer; the corrected Freedson equation showed the highest values, and the Santos-Lozano vector magnitude equation and Sasaki equation demonstrated the lowest one. Energy expenditure was compared between the wrist and thigh and showed low correlation values. Despite the positive results obtained, it was necessary to design specific equations for the estimation of energy expenditure measured with inertial sensors on the thigh. The use of the same formula equation in two different placements did not report a positive interclass correlation coefficient

Evaluation of Android and Apple Store Depression Applications Based on Mobile Application Rating Scale.

There are a large number of mobile applications that allow the monitoring of health status. The quality of the applications is only evaluated by users and not by standard criteria. This study aimed to examine depression-related applications in major mobile application stores and to analyze them using the rating scale tool Mobile Application Rating Scale (MARS). A search of digital applications for the control of symptoms and behavioral changes in depression was carried out in the two reference mobile operating systems, Apple (App Store) and Android (Play Store), by means of two reviewers with a blind methodology between September and October 2019 in stores from Spain and the United Kingdom. Eighteen applications from the Android Play Store and twelve from the App Store were included in this study. The quality of the applications was evaluated using the MARS scale from 1 (inadequate) to 5 (excellent). The average score of the applications based on the MARS was 3.67 ± 0.53. The sections with the highest scores were "Functionality" (4.51) and "Esthetics" (3.98) and the lowest "Application Subjective quality" (2.86) and "Information" (3.08). Mobile Health applications for the treatment of depression have great potential to influence the health status of users; however, applications come to the digital market without health control