We performed this study according to the guidelines of scoping studies by Colquhoun et al [8]. Colquhoun et al [8] advanced the 6 stages of scoping studies by Arksey and O’Melley [9]. They elaborated on different stages of research such as the identification of a research question and literature, study selection, charting data, summarizing, and consulting [9]. To ensure rigor and transparency, this literature review was guided by our research question [9]. We started the scoping study with a database search of PubMed using the keywords “health apps AND wearables” (Figure 1). The scoping of literature was limited to articles published in the English language from 2015 to March 2019 because literature on health apps and wearables, as well as the boom of using those technologies, experienced a steep increase in 2015 [10]. The search identified 37 potential items. A second search was conducted via Google Scholar by using the keywords “health apps (and) wearables,” limiting the search again to literature published in the English language from 2015 to March 2019, and 36 items were identified. Then, another 2 articles in the German language and 2 survey studies in the German language were included in the study through purposeful sampling [11] because they were recommended. We conducted a third database search through JMIR using the search terms “health apps AND wearables” and identified 59 articles published from 2015 to March 2019 in English. We conducted other trial searches using other keywords such as “mHealth,” “fitness apps,” “health apps,” and “health data sharing” but the sampled literature had little fit with the research question. Hence, when searching only for the search term “health apps,” JMIR returned 698 search results. However, we chose the search term “health apps AND wearables” for our study because this is the closest that the published literature gets in terms of the German DIGA concept [12].

Conference papers, conference reports, protocols, viewpoints, letters, Bachelor and Master theses, or other grey literature were not included. First, we screened articles by title and abstract. Literature relating to the themes of patient treatment with health apps or wearables, preventive care with apps or wearables, market studies about health app and wearable use, data privacy concerns, and patient use of health apps and wearables were included in this study. Hence, duplicates and ineligibility were further reasons for exclusion. Regarding the inclusion themes selected via purposeful sampling [11], 55 of 136 articles were included in this scoping study, and we analyzed the articles using a qualitative thematic analysis approach (see Multimedia Appendix 1 and Multimedia Appendix 2).

A study by GfK reported that 33% of survey participants from 16 different countries used wearables or health apps to track their fitness or health on average [6]. The main reasons for people to use these devices is to improve their personal level of fitness or for self-motivation. In Germany, about 28% of people currently track their health — more men than women and rather younger than older people [6]. Another survey conducted by Statista [13] showed similar results. Users mainly focus on self-optimization. The youngest user group (18-29 years) has the largest proportion of app users [13].

Wiesner et al [14] conducted a field study and surveyed participants from a regional road race event about their use of wearables. They decided to survey sport-enthusiast runners because they anticipated that mainly young and active people use health apps and wearables. The study showed that 73% of the runner community used one or more wearables to track their activity [14]. Just 1% of the respondents used wearables sponsored by their health insurer [14]. The authors further asked about data privacy concerns of nonvoluntary data sharing, and 42% of the respondents “stated that they would not be concerned if data were shared in such a manner” [14]. This result might be significantly different when surveying a group of chronically ill or nonactive people. The results further show that the willingness to share data with different agents decreases for respondents in older age groups [14]. Most respondents of a US market study used health apps and wearables to monitor personal activity, nutrition, weight loss, or learn a new exercise [15]. The majority of the surveyed users used their health or fitness apps at least once a day [15]. Just 20% of the respondents discovered an app through the recommendation of a physician [15]. Among the most frequent reasons for people to not use health apps and wearables were lack of interest, high prices, and lack of trust in data security [15].

Park et al [16] conducted a similar study in South Korea and achieved similar results. The main reasons to use health apps and wearables were concerns about personal health status, self-optimization, innovative propensity, and trust in beneficial results. Surprisingly, the results indicated that the quality of the app has less influence on the decision whether to continue to use an app than social-cognitive factors [16]. Paré et al [17] also analyzed the motivation of people using health apps or wearables in Canada. They concluded that about 41% of the respondents used digital devices to self-track their health and physical activity (PA), which is significantly more than the German average. Furthermore, “a majority of digital self-trackers are young or mature adults (18-34 years), highly educated …, wealthy … and people who perceive themselves to be in good or very good health” [17]. Mosconi et al [18] and Ernsting et al [19] agreed with this statement and determined that young people in particular are interested in these technologies. Users feel generally more informed about their health when tracking different parameters, and 7 of 10 respondents improved or maintained their health condition by using an app or wearable [17]. Nevertheless, “one-third of consumer wearables end up in a drawer 6 months after purchase” [17]. This phenomenon occurs mainly with people with poor health or a chronic illness, indicating that this group loses interest in the technology when constantly reminded about a chronical condition or illness. Those people might feel pressured to be physically active [17].

Canhoto and Arp [20] agreed with Paré et al [17] by stating that many wearable and health app users stop using their devices after a while. Many insurance companies offer their members financial incentives and bonus programs to adopt a certain app or track specific health parameters [20]. The authors claimed that the inclusion of wearables and health apps in the health care system might have a significant positive influence on the treatment of chronic disease, like obesity or diabetes [20]. The widespread adoption and acceptance of these technologies are the key to their effectivity.

Christóvão [21] analyzed in his paper the influencing factors leading to app usage and the potential of health apps recommended and monitored by physicians. Perceived ease of use, perceived usefulness, peer influence, seniority, age, and gender were among the most important factors [21]. The author surveyed 199 fully qualified doctors and medical students to analyze the perceived usefulness of introducing health apps and wearables into patient care. Senior physicians and female physicians tended to use health apps less frequently if there was little peer influence, little perceived usefulness, and high complexity of usage [21]. A majority of the respondents could imagine recommending health apps and wearables to patients. Collado-Borrell et al [22], Davis et al [23], and Lipschitz et al [24] stated that many patients, nonetheless, already use health apps and wearables and are generally interested in the adaption of these technologies, independent of their age. However, Krebs and Duncan [15] rejected the view that all influencing factors are equally important. Wiesner et al [14] disagreed that gender significantly influences app usage, and Mackert et al [25] stated that health literacy plays an important role in the willingness to use these technologies.

Somers et al [26] conducted a contingent evaluation about the willingness-to-pay (WTP) for and willingness-to-accept (WTA) the use of health apps with different features. The results indicated that people value the promotion of wellbeing, social connectivity, and health care control [26]. Hence, Peng et al [27] identified the price of a wearable or health app as a significant influencing factor for the decision to adopt. The main reasons for people to abandon health apps or wearables after a certain period are, according to Peng et al [27], lack of time and effort and the lack of motivation and discipline. This means that apps or wearables alone cannot trigger a tremendous lifestyle change. The authors identified important reasons for people to use and continue to use health apps and wearables such as social competition, intangible rewards, tangible rewards, hedonic factors, and internal dedication [27]. To set incentives for nonactive or chronically ill patients to adopt health apps or wearables, tangible rewards like bonus programs might be the most promising tool in the future because “money is one of the biggest motivators” [27]. Petersen et al [28] concluded that tracking health parameters and communication through internet platforms triggers more self-consciousness and leads to patient empowerment.

A study from the German Ministry of Health [29] assigned health apps and wearables a significant role in the future and singled out the importance of incorporating self-tracked data into the physician’s daily routine and diagnostics. The stagnating telemedical development in Germany might be one of the major obstacles for the incorporation of DIGAs into the German health care system and needs further attention. However, Albrecht [29] argued that apps should be developed in cooperation with physicians, pharmaceutical companies, and health insurers to better meet the needs of the patients. The author claimed that the continuous use of health apps has a positive effect on personal health [29].

Mercer et al [30] conducted a participant’s study and provided wearables to 32 chronically ill participants (aged >50 years), which they evaluated according to questions derived from the technology acceptance model. They found out that older and chronically ill people perceive wearables as “useful and acceptable.” The use of wearables could enhance the level of PA because the devices create awareness of real motion [30]. Many older participants have not used a smartphone or tablet before and have strong concerns about their competencies. Yet, the technologies could remove barriers between physicians and patients [30]. Ehn et al [31] conducted a similar study. The authors concluded that the overall PA of the elderly increased during the study and that the wearables acted as a significant motivator [31]. However, they defined similar barriers for the use of wearables [31]. Schoeppe et al [32] reviewed 25 apps for children and adolescents and concluded that these apps have moderate quality overall. User engagement while using the app was not satisfactory, and the apps did not respond to individual needs. The authors ascribed to health apps for children and adolescents a high potential effectivity of sustainable behavioral change through gamification. They suggested, similar to Albrecht [29], cooperation of physicians, pharmaceutical companies, health insurers, and app developers [32]. Hartzler et al [33] and Hoffmann et al [34] also stressed the inclusion of gamification and interactive features as main factors for the success of health apps and wearables.

Firth and Torous [35] concluded their literature search by stating that there is still little empirical research available on the effectivity of health apps, specifically as a complementary treatment for schizophrenia: “People with schizophrenia are willing and able to use smartphones to monitor their symptoms, engage in self-directed therapeutic interventions, and increase their physical exercise.” Patients not officially diagnosed with schizophrenia or patients in acute stages report problems with app adherence [35]. Urrea et al [36] predicted that the use of health apps is an effective tool for the prevention of cardiovascular disease. Interventions via apps related to improvement and monitoring of smoking behavior, nutrition, and PA show positive results [36]. Hartmann et al [37], Christmann et al [38], and Ose et al [39] found significant potential of health apps and wearables for the treatment of depression. DIGAs might personalize care and reduce communication barriers with medical doctors. Gabriels and Moerenhout [40] and Martinez-Millana et al [41] concluded that the use of health apps and wearables help improve patients’ awareness and health education.

Haghi et al [42] ascribed to bring-your-own, self-tracked data an important role because of the predictions and simulations that could be achieved using big data: “The Internet of Things is a new concept, providing the possibility of health care monitoring using wearable devices.” Health monitoring could be done to a large extent autonomously, using sensors like motion trackers, vital signs, and gas detectors [42]. Dimitrov [43] identified 4 main strategies: descriptive analysis, prescriptive analysis, predictive analysis, and simulations. The author predicted potential future savings in the health care sector because most patients could monitor their health by themselves and upload their data to a medical Internet of Things. Data analysis could be achieved using big data and digital health advisors, which could decrease the number of necessary annual visits to physicians [43]. Turankhia and Kaiser [44] agreed with Dimitrov [43] and identified the monitoring of patients at risk of atrial fibrillation with health apps and wearables as tools to increase the rate of early detection and therefore decrease physician visits. Heintzman [45] also argued that the management and monitoring of diabetes through apps could decrease costs for the health care system because the technologies offer individualized guidance. Henriksen et al [10] criticized that self-tracked data is, in most cases, uploaded to brand-specific repositories, which makes it difficult to share data with medical staff or compare data between different applications.

Vahabzadeh et al [46] identified mHealth primarily as a game changer in the treatment of depression and even as a measure of suicide prevention. The author stated that there is great potential to detect the risk of suicide early and to help individuals with specific apps tailored to their needs. However, medical doctors should not solely rely on these technologies for detection and treatment, given the tremendous pitfalls of a potential error [46]. Lüttke et al [47] agreed with the points made by Vahabzadeh et al [46]. They see great potential in the use of DIGAs as complementary to therapy.

Genes et al [48] researched the effectivity of asthma monitoring through health apps and concluded that there was improvement in asthma control and a decrease in necessary physician contact. More importantly, the use of the app helped to reduce barriers within patient-physician communication [48]. Yet, another study showed that the incorporation of bring-your-own, self-tracked data in preventive care programs might be very promising. The reason for the positive outlook is the advancement of patient education through data visualization and a better self-monitoring strategy [1]. However, the widespread adoption of these technologies and integration of the data in routine physician care are challenging [1]. Lobelo et al [1] recommended that health app developers, researchers, regulators, and medical staff conjointly develop solutions to ensure compliance, compatibility, and health data security. Brandt et al [49] conducted a study by interviewing general practitioners in Denmark, and a majority of the general practitioners already used health apps and are generally convinced about the effectiveness but do not “translate that into lifestyle change guidance for their patients.” The authors suggested that health apps and wearables have significant potential to improve diagnostics and are a complimentary treatment for patients.

Chung et al [50] found that patients get better insights about their specific condition and feel empowered and connected. Cresswell et al [51] ascribed the integration of bring-your-own, self-tracked data into the daily routine of physicians as an aspirational role in preventive care and diagnostics. Furthermore, Cresswell et al [51] agreed with Chung et al [50] that self-monitoring of vital parameters and data visualization empower and educate patients.

Knight and Bidargaddi [52] concluded that self-management of mental diseases through apps leads to patient empowerment and the improvement of clinical care through better understanding. Ramkumar et al [53] agreed with this argument.

Wichmann et al [54] criticized, despite all the potential benefits, the general academic enthusiasm about introducing DIGAs into the health care system, even though there is little empirical evidence about their long-term effectivity, or the usage over several years. Urban [55] conducted qualitative interviews to research the user perception of elderly people. The author claimed that health apps and wearables motivate elderly people to increase their activity, but they also cause them “to develop negative emotions that stand in a charged relationship to aging stereotypes.” Elderly, who suffer from severe chronic conditions, feel discomfort integrating these technologies into their daily routine because the apps constantly remind them of their illness [55].

McCallum et al [56] agreed with Urban [55] and argued that the use of DIGAs are currently limited to mainly young and sportive people. To achieve widespread use, the usability and acceptability, especially of people with chronic conditions, need to be improved [56]. Data security issues are one of the main concerns for chronically ill people because they fear discrimination in different parts of their daily life [56]. Montgomery et al [57] supported this claim and demanded government regulation to enhance fairness and equity but also to protect personal data from the sale to third parties.

Groß and Schmidt [58] suggested that patients could be overstrained with the amount of data and sensors available. Hence, patients are not sufficiently trained to read and properly analyze health data and peak graphs. They are not able to assess the data and identify their relevance, which could lead to misinterpretation [58]. The authors also listed positive effects resulting from the use of health apps and wearables for patients like efficiency, control, goal orientation, and better organization [58]. Another major problem discussed in the paper is the concern about data security, the consequences of potential data theft, and data sales to third parties [58].

Hicks et al [59] and Huckvale et al [60] discussed in their studies privacy risks that could result from the use of fitness and health apps. Users of health and fitness apps rely on the ethical operation of app services and need to trust the apps they use [59,60]. However, app services, especially those offering free operation, mainly sell the collected data to third parties and hide these conditions in very long policy terms. The authors examined the privacy policies of 79 popular health apps and found that 89% of the apps communicate with online services and 90% also communicate with “one or more third-party services directly” [60]. The authors criticized that most health and fitness apps “rely mainly on self-declared compliance” [60]. Armstrong [61] came to the same conclusion with a similar study and suggested government regulation for health data processing. Tabi et al [62] and Jamaladin et al [63] also criticized the lack of clarity of conventional app stores and emphasized the need for professional health app stores and medical doctors’ recommendation to their patients. Becker et al [64] agreed with Huckvale et al [60] and Armstrong [61] because most health apps are not certified as a medical device, which means that their data protection terms are, in most cases, not supervised by a government agency. However, certification processes take a long time and are expensive. Incentives for the certification of apps are currently missing. However, the German digital care act enables fast track certification for DIGAs, which allows for early market access and a 1-year test phase to prove a positive health care effect [3].

This study might be affected by the limited amount of available research resulting from the search terms. This might give a unilateral perspective on the effectivity of health apps and wearables. Hence, we are always concerned about the selection bias of articles. However, the multidisciplinary perspective on the field of study, enhanced through articles from different schools of thought and different research disciplines, as well as the applied rigor of scoping studies, have contributed to eliminate the selection bias to a large extent. Further research should be conducted after the first DIGAs are certified and have entered the German health care market.

To conclude, 55 of the 136 articles were analyzed within this scoping study. First, 4 key themes were identified: users of health apps and wearables; effectivity of health apps and wearables to improve health; potential of bring-your-own, self-tracked data; and concerns and data privacy risks.

In December 2019, Germany passed the digital care act, which enables the statutory financed prescription of digital health devices by medical doctors. Based on this scoping study, we predict an overall beneficial effect for German patients, treatment quality, and general health literacy of the population. The main benefits are going to be visible in the fields of preventive care and patient monitoring and disease management. Three main stages of potential benefits for the health care system were identified: using health apps and wearables, continuing to use health apps and wearables, and sharing bring-your-own, self-tracked data with different agents in the health care sector.