Quality of Physical Activity Apps: Systematic Search in App Stores and Content Analysis

App-based telerehabilitation program for older adults on waiting list for physiotherapy after hospital discharge: a feasibility pragmatic randomized trial

BACKGROUND

Inactivity while waiting for outpatient physiotherapy worsens the physical deconditioning of older adults after hospital discharge. Exercise programs can minimize the progression of deconditioning. In developing countries, telerehabilitation for older adults on the waiting list is still in the early stages. This study aimed to evaluate the feasibility of the study procedures of a telerehabilitation program for older adults waiting for outpatient physiotherapy after hospital discharge.

METHODS

This pragmatic randomized controlled trial recruited older adults (≥ 60 years) with several clinical diagnoses on the waiting list for outpatient physiotherapy in the Brazilian public health system after hospital discharge. The telerehabilitation group (n = 17) received a personalized program of multicomponent remote exercises using a smartphone app. The control group (n = 17) followed the usual waiting list. We assessed recruitment and dropout rates, safety, adherence, and satisfaction. The preliminary effects were verified on clinical outcomes.

RESULTS

We recruited 5.6 older adults monthly; dropouts were 12%. No serious adverse events were associated with the telerehabilitation program. The weekly adherence was 2.85 (1.43) days, and in 63.3% of the weeks the participants were enrolled, they performed the exercise program at least twice a week. Participants rated the telerehabilitation program as 9.71 (0.21), and the safety of remote exercises without professional supervision as 8.6 (2.2) on a 0-10 scale.

CONCLUSIONS

The telerehabilitation program using a smartphone app was safe and presented high participants' satisfaction and adequate adherence, recruitment, and dropout rates. Therefore, the definitive study can be conducted with few modifications.

TRIAL REGISTRATION

Brazilian Registry of Clinical Trials (ReBEC), RBR-9243v7. Registered on 24 August 2020. https://ensaiosclinicos.gov.br/rg/RBR-9243v7 .

Quality Assessment of Smartphone Medication Management Apps in France: Systematic Search

BACKGROUND

Adherence to medication is estimated to be around 50% for chronically ill patients in high-income countries. Improving the effectiveness of adherence interventions could have a far greater impact on population health than any improvement in specific medical treatments. Mobile health (mHealth) is one of the most effective solutions for helping patients improve their medication intake, notably through the use of mobile apps with reminder systems. With more than 327,000 apps available in the mHealth field, it is difficult for health care professionals and patients alike to choose which apps to recommend and use.

OBJECTIVE

We aim to carry out a systematic search of medication management smartphone apps available in France that send reminders to patients and assess their quality using a validated scale.

METHODS

Mobile apps were identified in October and November 2022 after a systematic keyword search on the 2 main app download platforms: App Store (Apple Inc) and Google Play Store. Inclusion criteria were free availability, date of last update, and availability in French. Next, 2 health care professionals independently evaluated the included apps using the French version of the Mobile App Rating Scale (MARS-F), an objective scoring system validated for assessing the overall quality of apps in the mHealth field. An intraclass correlation coefficient was calculated to determine interrater reliability.

RESULTS

In total, 960 apps were identified and 49 were selected (25 from the App Store and 24 from the Google Play Store). Interrater reliability was excellent (intraclass correlation coefficient 0.92; 95% CI 0.87-0.95; P<.001). The average MARS-F score was 3.56 (SD 0.49) for apps on the App Store and 3.51 (SD 0.46) for those on the Google Play Store, with 10 apps scoring above 4 out of 5. Further, 2 apps were tested in at least one randomized controlled trial and showed positive results. The 2 apps with the highest ratings were Mediteo rappel de médicaments (Mediteo GmbH) and TOM rappel medicaments, pilule (Innovation6 GmbH), available on both platforms. Each app's MARS-F score was weakly correlated with user ratings on the App Store and moderately correlated on the Google Play Store.

CONCLUSIONS

To our knowledge, this is the first study that used a validated scoring system to evaluate medication management apps that send medication reminders. The quality of the apps was heterogeneous, with only 2 having been studied in a randomized controlled trial with positive results. The evaluation of apps in real-life conditions by patients is necessary to determine their acceptability and effectiveness. Certification of apps is also essential to help health care professionals and patients identify validated apps.

The acceptability, usability, engagement and optimisation of a mHealth service promoting healthy lifestyle behaviours: A mixed method feasibility study

Objective

Mobile health (mHealth) services suffer from high attrition rates yet represent a viable strategy for adults to improve their health. There is a need to develop evidence-based mHealth services and to constantly evaluate their feasibility. This study explored the acceptability, usability, engagement and optimisation of a co-developed mHealth service, aiming to promote healthy lifestyle behaviours.

Methods

The service LongLife Active® (LLA) is a mobile app with coaching. Adults were recruited from the general population. Quantitative results and qualitative findings guided the reasoning for the acceptability, usability, engagement and optimisation of LLA. Data from: questionnaires, log data, eight semi-structured interviews with users, feedback comments from users and two focus groups with product developers and coaches were collected. Inductive content analysis was used to analyse the qualitative data. A mixed method approach was used to interpret the findings.

Results

The final sample was 55 users (82% female), who signed up to use the service for 12 weeks. Engagement data was available for 43 (78%). The action plan was the most popular function engaged with by users. The mean scores for acceptability and usability were 3.3/5.0 and 50/100, respectively, rated by 15 users. Users expressed that the service's health focus was unique, and the service gave them a 'kickstart' in their behaviour change. Many ways to optimise the service were identified, including to increase personalisation, promote motivation and improve usability.

Conclusion

By incorporating suggestions for optimisation, this service has the potential to support peoples' healthy lifestyle behaviours.

The Most Popular Commercial Weight Management Apps in the Chinese App Store: Analysis of Quality, Features, and Behavior Change Techniques

BACKGROUND

Many smartphone apps designed to assist individuals in managing their weight are accessible, but the assessment of app quality and features has predominantly taken place in Western countries. Nevertheless, there is a scarcity of research evaluating weight management apps in China, which highlights the need for further investigation in this area.

OBJECTIVE

This study aims to conduct a comprehensive search for the most popular commercial Chinese smartphone apps focused on weight management and assess their quality, behavior change techniques (BCTs), and content-related features using appropriate evaluation scales. Additionally, the study sought to investigate the associations between the quality of various domains within weight management apps and the number of incorporated BCTs and app features.

METHODS

In April 2023, data on weight management apps from the iOS and Android app stores were downloaded from the Qimai Data platform. Subsequently, a total of 35 weight management apps were subjected to screening and analysis by 2 researchers. The features and quality of the apps were independently assessed by 6 professionals specializing in nutrition management and health behavioral change using the Mobile Application Rating Scale (MARS). Two registered dietitians, who had experience in app development and coding BCTs, applied the established 26-item BCT taxonomy to verify the presence of BCTs. Mean (SD) scores and their distributions were calculated for each section and item. Spearman correlations were used to assess the relationship between an app's quality and its technical features, as well as the number of incorporated BCTs.

RESULTS

The data set included a total of 35 apps, with 8 available in the Android Store, 10 in the Apple Store, and 17 in both. The overall quality, with a mean MARS score of 3.44 (SD 0.44), showed that functionality was the highest scoring domain (mean 4.18, SD 0.37), followed by aesthetics (mean 3.43, SD 0.42), engagement (mean 3.26, SD 0.64), and information (mean 2.91, SD 0.52), which had the lowest score. The mean number of BCTs in the analyzed apps was 9.17 (range 2-18 BCTs/app). The most common BCTs were "prompt review of behavioral goals" and "provide instruction," present in 31 apps (89%). This was followed by "prompt self-monitoring of behavior" in 30 apps (86%), "prompt specific goal setting" in 29 apps (83%), and "provide feedback on performance" in 27 apps (77%). The most prevalent features in the analyzed apps were the need for web access (35/35, 100%), monitoring/tracking (30/35, 86%), goal setting (29/35, 83%), and sending alerts (28/35, 80%). The study also revealed strong positive correlations among the number of BCTs incorporated, app quality, and app features. This suggests that apps with a higher number of BCTs tend to have better overall quality and more features.

CONCLUSIONS

The study found that the overall quality of weight management apps in China is moderate, with a particular weakness in the quality of information provided. The most prevalent BCTs in these apps were reviewing behavioral goals, providing guidance, self-monitoring of behavior, goal setting, and offering performance feedback. The most common features were the need for web access, monitoring and tracking, goal setting, and sending alerts. Notably, higher-quality weight management apps in China tended to incorporate more BCTs and features. These findings can be valuable for developers looking to improve weight management apps and enhance their potential to drive behavioral change in weight management.

Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey

Background

Physical inactivity is a global health issue, and mobile health (mHealth) apps are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity.

Objective

This study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample.

Methods

We recruited 20,573 web-based panelists who completed questionnaires concerning demographics, regular physical activity levels, and use of apps and wearables supporting physical activity. Participants who indicated that they were using a physical activity app or wearable were presented with a list of app functions (eg, sensor information, goal setting, journaling, and reward), among which they selected any functions they used.

Results

Approximately one-quarter (n=4465) of the sample was identified as app users and showed similar demographic characteristics to samples documented in the literature; that is, compared with app nonusers, app users were younger (odds ratio [OR] 0.57, 95% CI 0.50-0.65), were more likely to be men (OR 0.83, 95% CI 0.77-0.90), had higher BMI scores (OR 1.02, 95% CI 1.01-1.03), had higher levels of education (university or above; OR 1.528, 95% CI 1.19-1.99), were more likely to have a child (OR 1.16, 95% CI 1.05-1.28) and job (OR 1.28, 95% CI 1.17-1.40), and had a higher household income (OR 1.40, 95% CI 1.21-1.62). Our results revealed unique associations between demographic variables and specific app functions. For example, sensor information, journaling, and GPS were more frequently used by men than women (ORs <0.84). Another important finding is that people used a median of 2 (IQR 1-4) different functions within an app, and the most common pattern was to use sensor information (ie, self-monitoring) and one other function such as goal setting or reminders.

Conclusions

Regardless of the current trend in app development toward multifunctionality, our findings highlight the importance of app simplicity. A set of two functions (more precisely, self-monitoring and one other function) might be the minimum that can be accepted by most users. In addition, the identified individual differences will help developers and stakeholders pave the way for the personalization of app functions.

Exploring views and experiences of the general public's adoption of digital technologies for healthy lifestyle in Singapore: a qualitative study

Objective

Little is known about the general adult population's adoption of digital technology to support healthy lifestyle, especially when they are expected to take greater personal responsibility for managing their health and well-being today. The current qualitative study intended to gain an in-depth understanding of determinants of digital technology adoption for healthy lifestyle among community-dwelling adults in Singapore.

Design

A qualitative study design, with thematic framework analysis was applied to develop themes from the data.

Setting

Semi-structured individual interviews were conducted with participants either face-to-face or online through a videoconferencing platform.

Participants

14 women and 16 men from the general population who were between the ages of 22 and 71 years.

Results

Three major themes were developed: (1) digitally disempowered (2) safety and perceived risks and harm; (3) cultural values and drives. Adoption of technology among the general population is needs-driven, and contingent on individual, technological and other cross-cultural contextual factors.

Conclusion

Our findings highlight there is no one solution which fits all individuals, emphasizing the challenges of catering to diverse groups to reduce barriers to adoption of digital technologies for healthy lifestyle. Digital guidance and training, as well as social influences, can motivate technological adoption in the population. However, technical problems as well as data security and privacy concerns should first be adequately addressed. This study provides rich cross-cultural insights and informs policy-making due to its alignment with government public health initiatives to promote healthy lifestyle.

Stress Management Apps: Systematic Search and Multidimensional Assessment of Quality and Characteristics

BACKGROUND

Chronic stress poses risks for physical and mental well-being. Stress management interventions have been shown to be effective, and stress management apps (SMAs) might help to transfer strategies into everyday life.

OBJECTIVE

This review aims to provide a comprehensive overview of the quality and characteristics of SMAs to give potential users or health professionals a guideline when searching for SMAs in common app stores.

METHODS

SMAs were identified with a systematic search in the European Google Play Store and Apple App Store. SMAs were screened and checked according to the inclusion criteria. General characteristics and quality were assessed by 2 independent raters using the German Mobile Application Rating Scale (MARS-G). The MARS-G assesses quality (range 1 to 5) on the following four dimensions: (1) engagement, (2) functionality, (3) esthetics, and (4) information. In addition, the theory-based stress management strategies, evidence base, long-term availability, and common characteristics of the 5 top-rated SMAs were assessed and derived.

RESULTS

Of 2044 identified apps, 121 SMAs were included. Frequently implemented strategies (also in the 5 top-rated SMAs) were psychoeducation, breathing, and mindfulness, as well as the use of monitoring and reminder functions. Of the 121 SMAs, 111 (91.7%) provided a privacy policy, but only 44 (36.4%) required an active confirmation of informed consent. Data sharing with third parties was disclosed in only 14.0% (17/121) of the SMAs. The average quality of the included apps was above the cutoff score of 3.5 (mean 3.59, SD 0.50). The MARS-G dimensions yielded values above this cutoff score (functionality: mean 4.14, SD 0.47; esthetics: mean 3.76, SD 0.73) and below this score (information: mean 3.42, SD 0.46; engagement: mean 3.05, SD 0.78). Most theory-based stress management strategies were regenerative stress management strategies. The evidence base for 9.1% (11/121) of the SMAs could be identified, indicating significant group differences in several variables (eg, stress or depressive symptoms) in favor of SMAs. Moreover, 38.0% (46/121) of the SMAs were no longer available after a 2-year period.

CONCLUSIONS

The moderate information quality, scarce evidence base, constraints in data privacy and security features, and high volatility of SMAs pose challenges for users, health professionals, and researchers. However, owing to the scalability of SMAs and the few but promising results regarding their effectiveness, they have a high potential to reach and help a broad audience. For a holistic stress management approach, SMAs could benefit from a broader repertoire of strategies, such as more instrumental and mental stress management strategies. The common characteristics of SMAs with top-rated quality can be used as guidance for potential users and health professionals, but owing to the high volatility of SMAs, enhanced evaluation frameworks are needed.

Importance-performance analysis in fitness apps. A study from the viewpoint of gender and age

Background

We are currently undergoing a profound process of digital transformation that has favoured the development and use of apps in multiple facets of people's daily lives. In the fitness industry, this situation has facilitated the control of exercise and the maintenance of healthier lifestyles. However, it is not known how the perceived quality and importance of fitness apps vary for users based on gender and age, which is the objective of this study conducted among users of fitness centres.

Methods

By means of a convenience sample, 321 users from different centres of the boutique fitness chain Sano Centre (238 females and 83 males) took part in the study. They answered the 16 items of the MARS scale, distributed in four dimensions, in terms of importance and perceived quality. The existence of significant differences was analysed using non-parametrical statistics such as the U-Mann-Whitney (gender) and the H-Kruskal-Wallis (age). In addition, a cluster analysis, combining hierarchical and non-hierarchical methods, was analysed considering as a dependent variable the level of recommendation of fitness apps.

Results

Considering gender, in importance-performance analysis (IPA), credibility was the most important attribute for females and quality of information for males. In the case of age, credibility was the most important attribute in all the ranges. The cluster analysis established two groups (high and low recommendations of the fitness app). In importance, the first group scored better on all factors except entertainment and interest. In valuation, the scores were lower than on importance, especially in the low recommendation group.

Conclusion

Regarding usage behaviour, credibility is the factor to which users attach the highest importance and rating, regardless of gender and age. The main demand focuses on improving the gestural design and visual appeal, which will facilitate a better user experience.

Mobile applications in the Philippines during the COVID-19 pandemic: systematic search, use case mapping, and quality assessment using the Mobile App Rating Scale (MARS)

Background

In the Philippines, various mobile health apps were implemented during the COVID-19 pandemic with very little knowledge in terms of their quality. The aims of this paper were 1) to systemically search for mobile apps with COVID-19 pandemic use case that are implemented in the Philippines; 2) to assess the apps using Mobile App Rating Scale (MARS); and 3) to identify the critical points for future improvements of these apps.

Methods

To identify existing mobile applications with COVID-19 pandemic use case employed in the Philippines, Google Play and Apple App Stores were systematically searched. Further search was conducted using the Google Search. Data were extracted from the app web store profile and apps were categorized according to use cases. Mobile apps that met the inclusion criteria were independently assessed and scored by two researchers using the MARS-a 23-item, expert-based rating scale for assessing the quality of mHealth applications.

Results

A total of 27 apps were identified and assessed using MARS. The majority of the apps are designed for managing exposure to COVID-19 and for promoting health monitoring. The overall MARS score of all the apps is 3.62 points (SD 0.7), with a maximum score of 4.7 for an app used for telehealth and a minimum of 2.3 for a COVID-19 health declaration app. The majority (n = 19, 70%) of the apps are equal to or exceeded the minimum "acceptable" MARS score of 3.0. Looking at the categories, the apps for raising awareness received the highest MARS score of 4.58 (SD 0.03) while those designed for managing exposure to COVID-19 received the lowest mean score of 3.06 (SD 0.6).

Conclusions

There is a heterogenous quality of mHealth apps implemented during the COVID-19 pandemic in the Philippines. The study also identified areas to better improve the tools. Considering that mHealth is expected to be an integral part of the healthcare system post-pandemic, the results warrant better policies and guidance in the development and implementation to ensure quality across the board and as a result, positively impact health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44247-023-00007-2.

Development and Validation of Multivariable Prediction Algorithms to Estimate Future Walking Behavior in Adults: Retrospective Cohort Study

BACKGROUND

Physical inactivity is associated with numerous health risks, including cancer, cardiovascular disease, type 2 diabetes, increased health care expenditure, and preventable, premature deaths. The majority of Americans fall short of clinical guideline goals (ie, 8000-10,000 steps per day). Behavior prediction algorithms could enable efficacious interventions to promote physical activity by facilitating delivery of nudges at appropriate times.

OBJECTIVE

The aim of this paper is to develop and validate algorithms that predict walking (ie, >5 min) within the next 3 hours, predicted from the participants' previous 5 weeks' steps-per-minute data.

METHODS

We conducted a retrospective, closed cohort, secondary analysis of a 6-week microrandomized trial of the HeartSteps mobile health physical-activity intervention conducted in 2015. The prediction performance of 6 algorithms was evaluated, as follows: logistic regression, radial-basis function support vector machine, eXtreme Gradient Boosting (XGBoost), multilayered perceptron (MLP), decision tree, and random forest. For the MLP, 90 random layer architectures were tested for optimization. Prior 5-week hourly walking data, including missingness, were used for predictors. Whether the participant walked during the next 3 hours was used as the outcome. K-fold cross-validation (K=10) was used for the internal validation. The primary outcome measures are classification accuracy, the Mathew correlation coefficient, sensitivity, and specificity.

RESULTS

The total sample size included 6 weeks of data among 44 participants. Of the 44 participants, 31 (71%) were female, 26 (59%) were White, 36 (82%) had a college degree or more, and 15 (34%) were married. The mean age was 35.9 (SD 14.7) years. Participants (n=3, 7%) who did not have enough data (number of days <10) were excluded, resulting in 41 (93%) participants. MLP with optimized layer architecture showed the best performance in accuracy (82.0%, SD 1.1), whereas XGBoost (76.3%, SD 1.5), random forest (69.5%, SD 1.0), support vector machine (69.3%, SD 1.0), and decision tree (63.6%, SD 1.5) algorithms showed lower performance than logistic regression (77.2%, SD 1.2). MLP also showed superior overall performance to all other tried algorithms in Mathew correlation coefficient (0.643, SD 0.021), sensitivity (86.1%, SD 3.0), and specificity (77.8%, SD 3.3).

CONCLUSIONS

Walking behavior prediction models were developed and validated. MLP showed the highest overall performance of all attempted algorithms. A random search for optimal layer structure is a promising approach for prediction engine development. Future studies can test the real-world application of this algorithm in a "smart" intervention for promoting physical activity.

Blended Care Interventions to Promote Physical Activity: A Systematic Review of Randomized Controlled Trials

Background

Blended care interventions combine therapeutic guidance with digital care. Current research results show the promising role of the blended care approach in clinical care. This new way of delivering health care could have the potential to effectively promote physical activity in different public health settings.

Objective

The aim of the systematic review is to investigate the varieties of intervention characteristics of blended care interventions to promote physical activity in terms of structure, behavior change goals, behavior change techniques, and effectiveness of blended care interventions compared to a control group.

Methods

We searched for randomized controlled trials published from 2000 to March 2021 in MEDLINE, CINAHL, Cochrane Central Register of Controlled Trials, SPORTDiscus, PsycINFO, and Web of Science according to the PRISMA guidelines. Risk of bias was assessed using the Cochrane Collaboration tool. Study characteristics, intervention characteristics, and outcome data were extracted. Furthermore, the effect size on the outcome of physical activity was examined or calculated.

Results

In total, the number of reports identified from the database searches was 4828. Of these, 25 studies were included in the review, with a total of 5923 study participants. Results indicated that the characteristics of blended care interventions showed a high heterogeneity. The combinations of therapist-guided interventions and digital interventions allowed the identification of specific subgroups, but they varied in length (range 8–52 weeks, SD 16.6), intensity, and the combination of the components. The most used combination of blended care interventions to promote physical activity was the combination of one-on-one meetings via telephone and Web-based interventions. Motivational models of behavior change were used most frequently as underlying theoretical foundations. Certain behavior change techniques were used consistently across the individual components, e.g., “problem solving” in the therapist-guided component and “feedback on behavior” in the digital component. Considering the effect size of blended care interventions compared with control groups, most studies showed a small effect.

Conclusions

It can be concluded that blended care interventions have potential to promote physical activity. In the future, further high-quality studies should investigate which type of blended care intervention is effective for which target group. Additionally, insights are required on which intervention characteristics are most effective, taking into account new evidence on behavior change.

Registration This systematic literature review was registered in PROSPERO (CRD42020188556).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-022-00489-w.

Development and validation of the Turkish version of the Mobile App Rating Scale - MARS-TR

BACKGROUND

The number of mobile health apps (MHAs) is growing rapidly. MHAs have great potential to improve health and health care. However, the quality of available MHAs remains unknown due to the lack of quality assessment regulations and standards for MHAs. The Mobile Application Rating Scale (MARS) is the most widely used instrument to assess the quality of MHAs, and available in English, Italian, Spanish, German, French, Arabic and Japanese. However, the scale is currently not available in the Turkish language.

OBJECTIVE

This study aimed to cross-culturally adapt the MARS into Turkish and evaluate the validity and reliability of the scale.

METHODS

The MARS was translated and adapted into Turkish according to the international guidelines. A total of 52 pregnancy tracking apps were evaluated by two independent raters. Internal consistency (Cronbach's alpha), inter-rater reliability (Intraclass Correlation Coefficient [ICC]), convergent validity and concurrent validity were explored. Regarding convergent validity, MARS-TR scores were compared with the ENLIGHT scale.

RESULTS

The MARS-TR was highly aligned with the original MARS. The MARS-TR showed excellent internal consistency (Cronbach's alpha of 0.95 for both raters) and excellent inter-rater reliability (ICC = 0.94; SEM = 0.02), with a smallest detectable change (95 % confidence level) of 0.05 points for the total score. Cronbach's alphas for the subscales ranged from 0.76 to 0.94 for the two raters. Correlations between the MARS-TR and ENLIGHT demonstrated adequate convergent validity (P < 0.05). No ceiling or floor effects were observed.

CONCLUSION

The results provide evidence that the Turkish version of MARS is a valid and reliable tool for researchers and experts to assess the quality of MHAs in Turkey.

Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach

The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions via mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R 2) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.

Digitization and Health in Germany: Cross-sectional Nationwide Survey

Background

Digital technologies are shaping medicine and public health.

Objective

The aim of this study was to investigate the attitudes toward and the use of digital technologies for health-related purposes using a nationwide survey.

Methods

We performed a cross-sectional study using a panel sample of internet users selected from the general population living in Germany. Responses to a survey with 28 items were collected using computer-assisted telephone interviews conducted in October 2020. The items were divided into four topics: (1) general attitudes toward digitization, (2) COVID-19 pandemic, (3) physical activity, and (4) perceived digital health (eHealth) literacy measured with the eHealth Literacy Scale (eHEALS; sum score of 8=lowest to 40=highest perceived eHealth literacy). The data were analyzed in IBM-SPSS24 using relative frequencies. Three univariate multiple regression analyses (linear or binary logistic) were performed to investigate the associations among the sociodemographic factors (age, gender, education, and household income) and digital technology use.

Results

The participants included 1014 internet users (n=528, 52.07% women) aged 14 to 93 years (mean 54, SD 17). Among all participants, 66.47% (674/1014) completed up to tertiary (primary and secondary) education and 45.07% (457/1017) reported a household income of up to 3500 Euro/month (1 Euro=US $1.18). Over half (579/1014, 57.10%) reported having used digital technologies for health-related purposes. The majority (898/1014, 88.56%) noted that digitization will be important for therapy and health care, in the future. Only 25.64% (260/1014) reported interest in smartphone apps for health promotion/prevention and 42.70% (433/1014) downloaded the COVID-19 contact-tracing app. Although 52.47% (532/1014) reported that they come across inaccurate digital information on the COVID-19 pandemic, 78.01% (791/1014) were confident in their ability to recognize such inaccurate information. Among those who use digital technologies for moderate physical activity (n=220), 187 (85.0%) found such technologies easy to use and 140 (63.6%) reported using them regularly (at least once a week). Although the perceived eHealth literacy was high (eHEALS mean score 31 points, SD 6), less than half (43.10%, 400/928) were confident in using digital information for health decisions. The use of digital technologies for health was associated with higher household income (odds ratio [OR] 1.28, 95% CI 1.11-1.47). The use of digital technologies for physical activity was associated with younger age (OR 0.95, 95% CI 0.94-0.96) and more education (OR 1.22, 95% CI 1.01-1.46). A higher perceived eHealth literacy score was associated with younger age (β=–.22, P<.001), higher household income (β=.21, P<.001), and more education (β=.14, P<.001).

Conclusions

Internet users in Germany expect that digitization will affect preventive and therapeutic health care in the future. The facilitators and barriers associated with the use of digital technologies for health warrant further research. A gap exists between high confidence in the perceived ability to evaluate digital information and low trust in internet-based information on the COVID-19 pandemic and health decisions.

Mobile-based interventions for common mental disorders in youth: a systematic evaluation of pediatric health apps

BACKGROUND

The access to empirically-supported treatments for common mental disorders in children and adolescents is often limited. Mental health apps might extend service supplies, as they are deemed to be cost-efficient, scalable and appealing for youth. However, little is known about the quality of available apps. Therefore, we aimed to systematically evaluate current mobile-based interventions for pediatric anxiety, depression and posttraumatic stress disorder (PTSD).

METHODS

Systematic searches were conducted in Google Play Store and Apple App Store to identify relevant apps. To be eligible for inclusion, apps needed to be: (1) designed to target either anxiety, depression or PTSD in youth (0-18 years); (2) developed for children, adolescents or caregivers; (3) provided in English or German; (4) operative after download. The quality of eligible apps was assessed with two standardized rating systems (i.e., Mobile App Rating Scale (MARS) and ENLIGHT) independently by two reviewers.

RESULTS

Overall, the searches revealed 3806 apps, with 15 mental health apps (0.39%) fulfilling our inclusion criteria. The mean overall scores suggested a moderate app quality (MARS: M = 3.59, SD = 0.50; ENLIGHT: M = 3.22, SD = 0.73). Moreover, only one app was evaluated in an RCT. The correlation of both rating scales was high (r = .936; p < .001), whereas no significant correlations were found between rating scales and user ratings (p > .05).

CONCLUSIONS

Our results point to a rather poor overall app quality, and indicate an absence of scientific-driven development and lack of methodologically sound evaluation of apps. Thus, future high-quality research is required, both in terms of theoretically informed intervention development and assessment of mental health apps in RCTs. Furthermore, institutionalized best-practices that provide central information on different aspects of apps (e.g., effectiveness, safety, and data security) for patients, caregivers, stakeholders and mental health professionals are urgently needed.

Quality and Adoption of COVID-19 Tracing Apps and Recommendations for Development: Systematic Interdisciplinary Review of European Apps

BACKGROUND

Simulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps.

OBJECTIVE

This study's primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified.

METHODS

Eligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human-computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted.

RESULTS

We discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9% (SD 12.5%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5% and 43.6%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity.

CONCLUSIONS

European national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app's engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development.