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

Paganini, Sarah; Terhorst, Yannik; Sander, Lasse; Catic, Selma; Balci, Sumeyye; Küchler, Ann-Marie; Schultchen, Dana; Plaumann, Katrin; Sturmbauer, Sarah; Krämer, Lena Violetta; Lin, Jiaxi; Wurst, Ramona; Pryss, Rüdiger; Baumeister, Harald; Meßner, Eva-Maria

doi:10.2196/22587

Cited by 33 publications

(22 citation statements)

References 41 publications

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“…Our quality ratings are in line with the results of previous systematic evaluations deploying the same rating scales on apps for various health conditions and application areas (e.g., depression, PTSD, pain, rheumatism, physical activity, weight management [16,36,38,[44][45][46][52][53][54]), all indicating medium overall app qualities with the MARS and ENLIGHT scales. In our study, the categories with the highest ratings were aesthetics and functionality (M = 3.78; M = 3.81), followed by information quality (M = 3.42) and engagement (M = 3.34).…”

Section: Discussionsupporting

confidence: 85%

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

Domhardt

Meßner

Eder

et al. 2021

Child Adolesc Psychiatry Ment Health

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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.

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Section: Discussionsupporting

confidence: 85%

“…from the stores. The functionality and validity of the program has been proven in previous studies [44][45][46]. For further technical details please see [47].…”

Section: Search Strategy and Inclusion Criteriamentioning

confidence: 88%

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

Domhardt

Meßner

Eder

et al. 2021

Child Adolesc Psychiatry Ment Health

Self Cite

View full text Add to dashboard Cite

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“…Other issues such as the analog social environment, financial barriers, and digital competence and literacy [ 16 ] should also be considered in the future research on digitization and health. Furthermore, amid the ever-growing number of digital technology offers, in particular health-related apps, regulation is required in relation to safety, quality (ie, evidence-based content), and data protection (eg, introducing a quality score or label within the app store) to facilitate health decision-making among users of these offers [ 17 , 18 ].…”

Section: Discussionmentioning

confidence: 99%

Digitization and Health in Germany: Cross-sectional Nationwide Survey

Santis¹,

Jahnel²,

Sina³

et al. 2021

JMIR Public Health Surveill

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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.

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“…Several digital mobile health technologies for self-management of nutrition ( 76 ) and physical activity ( 77 ) have been proposed in the digital market place. Nevertheless, a lack of expert nutrition and physical activity advice provided by current mobile apps is identified, igniting further concerns regarding personalized advice tailored to specific user preferences (including dietary and allergies, PA for heart health, etc.).…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2022

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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 (R2) 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.

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

Cited by 33 publications

References 41 publications

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

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

Digitization and Health in Germany: Cross-sectional Nationwide Survey

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

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