More than 350,000 mobile health (mHealth) apps are available in major app stores worldwide, including medical, health care, and fitness apps [1]. Although there is no standardized definition of mHealth, it broadly refers to health care supported by mobile and wireless devices to deliver, educate, and exchange health care information and monitor and promote health conditions or behaviors [2-4]. Many of these apps are focused on condition management, such as mental and behavioral health disorders, diabetes, and heart and circulatory system conditions [1]. One survey of American adults who had used an mHealth app found that approximately 70% of them had used it to keep track of their health, 39% to obtain health information, and 25% to share health information with their providers [5]. A Pew Research Center study reported that 62% of smartphone users used their devices to gather health-related information [6], and 90% of physicians used smartphones at work to access electronic health records, communicate with their team, reference information, or manage their schedule [7]. Similar to physicians, many nurses use apps for professional purposes [8].

Despite the ubiquity of mHealth apps for health care consumers and providers, health information technology implementation is frequently unsuccessful [9]. Previous research has found that apps may not align with end-user behavior and organizational needs, essentially showing a mismatch between how the app is designed to function and how the intended end user expects it to work [10-12].

Nurses are uniquely positioned to help address the challenge of this mismatch. The American Nurses Association Code of Ethics for Nurses includes multiple provisions emphasizing the centrality of the patient in health care, stating that “[t]he nurse’s primary commitment is to the patient” and that “[t]he nurse promotes, advocates for, and protects the rights, health, and safety of the patient” [13]. Integrating nurses as product development team members brings this patient-centered perspective to the development process. It has the potential to create apps that contain validated, current evidence-based health-related content that is meaningful to end users. Nurse informaticists, in particular, can ensure that the usability and features of the app are relevant for all end users and are incorporated into clinical workflows, leveraging interoperability standards [14].

Despite this potential, the extent to which nurses are involved in all aspects of the development process remains unclear. A thorough understanding of the role of nurses in mHealth app development is critical for several reasons. The first and most essential is that nursing professionals represent the largest segment of the health care workforce, spend the most time with patients, and coordinate all aspects of patient care [15]. Previous research has found that physicians in the intensive care unit spend 15% to 18% of their time with patients, whereas nurses in the same study spent 33% of their time in patient rooms and an additional 11% to 12% of their time directly outside patient rooms [16]. A longitudinal study of hospital nurses found that nurses spend 37% of their time with patients, and that direct care, indirect care, medication management, and communicating with other health professionals consumed >76% of the nurses’ time [17]. Therefore, nurses have a holistic view of health care processes and are keenly aware of what problems need to be solved.

To better understand nurses’ role in mHealth app development, this scoping review aims to determine the extent of the evidence regarding the role of nurses in app development and describe the apps nurses are involved in developing by answering the following research questions: (1) what role or roles do nurses perform in mHealth app development? (2) in what phases are nurses involved in mHealth app development? and (3) what type of apps are nurses involved in developing?

A scoping review was selected as the appropriate methodology, as the objectives of the project were to determine the extent of the evidence and to identify gaps in the existing literature, both of which were identified by Arksey and O’Malley [18] as the rationale for a scoping review [18]. This review followed the 6-stage methodology proposed by Levac et al [19]: (1) identifying the research question, (2) identifying all relevant publications, (3) selecting studies using inclusion and exclusion criteria, (4) charting the data to be extracted from each study, (5) synthesizing the data, and (6) reporting results. As the research questions of interest are described in the Objectives section, the Methods section will outline stages 2 to 5. The protocol for this scoping review was registered in Open Science Framework [20].

We conducted an extensive search combining natural language and controlled vocabulary searching to capture the concepts of mHealth, app development, and nurses. We defined an mHealth app as a portable device that must interface with a patient or consumer and facilitate the information and data collection and delivery. It may interface with sensors, wearables, or cameras and may be connected to the internet. It includes health-related data and may assist with clinical decision-making. We defined app development as 1 of the first 5 phases of the Software Development Life Cycle (SDLC): planning, gathering requirements, design and prototyping, software development, and testing [21]. Planning includes allocating resources, scheduling the project, and determining costs. Requirements gathering engages subject matter experts (SMEs), technology specialists, and others to understand the necessary elements of the tool. Design and prototyping involve rapid preliminary prototyping to identify possible technical solutions. Software development advances the app from prototype to functional software. Finally, testing before deployment ensures that the app is fully operational and ready to be implemented in production. We chose to focus on these preimplementation phases of development, as nurses’ roles in implementation and adoption have been more fully explored in previous systematic reviews [22-24]. Health care providers included all licensed nurses, those in training to become nurses, subject matter nurse experts and health information technology nurse experts.

A librarian conducted the search across 14 databases: CINAHL via EBSCO, Cochrane via Wiley, Compendex via Engineering Village, Education Source via EBSCO, Embase via Ovid, ERIC via EBSCO, Global Index Medicus, Google Scholar, IEEE Xplore, MEDLINE via Ovid, PsycINFO via Ovid, PubMed, Scopus, and Web of Science Core Collection. The selected databases were chosen to represent an array of subject areas, including nursing, medicine, psychology, psychiatry, education, computer science, and engineering. Broad, multidisciplinary databases, such as Clarivate’s Web of Science Core Collection, Elsevier’s Scopus, and Google Scholar, were selected because of their coverage of nonarticle research outputs, such as conference papers and abstracts. A complete search strategy is presented in Multimedia Appendix 1. No restrictions were placed on the language, geography, or study design. The search was restricted to items published since 2016 to focus on the most recent developments in this field. The search was conducted in April 2021 and was updated in April 2023. To ensure that no potentially relevant studies were overlooked, we also hand searched the reference lists of the included publications. The results were compiled and deduplicated in EndNote (Clarivate).

Items were first reviewed as titles and abstracts, followed by a full-text screening phase. A total of 2 independent researchers reviewed every item using Rayyan, a web-based tool that facilitates screening [25]. During the initial piloting phase, discrepancies were discussed as a group to establish a shared understanding of criteria and aims. Following this initial phase, a third researcher resolved discrepancies. We excluded publications that did not include an mHealth app, did not reference nurse involvement, did not include one of the relevant SDLC phases, or were published before 2016. We excluded review papers, including systematic reviews, and papers describing or reviewing previously developed apps. These exclusion criteria were used during the project’s title-abstract screening and full-text screening phases. Items retrieved through hand searching followed the same screening process and used the same inclusion and exclusion criteria. During the full-text screening phase, reasons for exclusion were recorded and reported in a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) diagram.

A total of 2 reviewers extracted data from each article into REDCap (Research Electronic Data Capture; Vanderbilt University), a secure web-based data capture and management platform [26]. We used this platform to gather the following data: the SDLC phase or phases included in the publication, the role of the nurse in any of the phases, details regarding the app, and bibliographic details of the publication. Details regarding the app included the primary and secondary users, meaning the intended audience and other individuals who could engage with the app such as for data entry; the functionality of the app; the version of the app; and the condition or purpose of the app. The app’s functionality was identified using the IMS Institute for Healthcare Informatics functionality scoring system [27], a well-established scale for functionality assessment [28-30]. The IMS Institute for Healthcare Informatics functionality scoring system consists of 7 main categories and 4 subcategories, and the overall functionality score, between 0 and 11, is calculated by summing the scores across individual items, where 1 indicates presence and 0 indicates absence. Where the publication was in a language not spoken by the research team members, Google Translate was used to create an English-language translation, as Google Translate had been previously found to have a high level of accuracy when used to facilitate data extraction in evidence synthesis [31].

After data extraction was completed, the findings were summarized according to the 3 research questions. Descriptive statistics were used to assess the frequency of roles, phases according to the SDLC, and the co-occurrence of specific roles and phases. The summary of the description of the apps included the IMS functionality, the condition of interest or purpose of the app, the primary and secondary users, the version of the app, and whether technical or content standards were used during the development of mHealth apps.

We retrieved 5483 items through database searching, 2492 (45.45%) of which were duplicates, resulting in 2991 (55.55%) items being screened at the title-abstract level. Following the title-abstract screening, 11.03% (330/2991) of the items were reviewed in full text, leading to 4.88% (146/2991) of publications that met the inclusion criteria [32-176]. Hand searching of reference lists identified additional 8.5% (11/130) of publications [177-187], resulting in 2.8% (157/5613) of included publications. There were 0.4% (22/5483) of items in the title-abstract screening phase that could not be retrieved for full-text screening through the resources available via any of the institutions or via interlibrary loans. Reasons for exclusion are presented in Figure 1.

The characteristics of the included studies are summarized in Table 1. Of the 157 included publications, 132 (84.1%) either described usability testing or were original research papers [32-49,51,52,55,56,58-65,67-75,77-81,83,85-87,89-107,110,112-117,119-124 ,126,129,130,132-134,136,138,140-145,147-160,162-169,171-173,175-187].

Of the 157 publications, 8 (5.1%) were conference abstracts [76,82,125,137,161,170,174,188], 7 (4.5%) were case reports [84,108,111,118,127,128,146], and 3 (1.9%) were commentaries or editorials [66,88,135]. The remaining publications (7/157, 4.5%) were protocols or descriptions of theoretical frameworks [50,53,54,57,109,130,139]. A total of 34 countries were represented in the publications, most frequently Brazil (29/157, 18.5%) [36,37,40,45,48,60,61,65,70,83,87,114,115,117,120, 134,136,138,142,143,152-154,157,163,165,177,182,183], the United States (26/157, 16.6%) [33,38,41,42,44,47,54, 57,66,68,69,71,76,81,89,97,102,103,107,113,121,132,160,164, 170,181], South Korea (10/157, 6.4%) [56,58,101,105, 118,133,149,156,180,184], and China (9/157, 5.7%) [90,95,110,127,167,172,173,176,186].

Nurses played a role in all the stages of development. Nurses were most represented in the design and prototyping phase (112/157, 71.3%) [32-37,39,41-43,45,46,49,51-53,55-58, 60,63-65,67-70,73-79,81,84-88,90-93,96,99-102,104,106,107,110-118, 121-129,131-136,138,139,141,142,144-146,148,149,151-153,155, 157,158,160-165,167,169,171,173-177,180,182,184-186,188], followed by the requirements gathering phase (98/157, 62.4%) [32-37,39-41,43,46,48-50,52-54,56,58,59,61,63,64,67,71-81,83, 84,86,89-92,95,98,99,101,102,104-110,114,116,118,119, 123-126,129,130,132,134-138,146,148,150,151,153-155,158-160, 162-171,173,178,181,184-188] and the testing phase (80/157, 51%) [33,35,37,38,40,41,43-45,47,49,51,52,55-57,62,64,72,73, 80,82,83,87,90,91,94,96-98,100-105,114,119,120, 122,128-133,135,139,140,142,143,145-147, 149-152,155-160,162,164,165,167-169,172,175-180,183,184,188]. Nurses were infrequently involved in the software development phase (20/157, 12.7%) [33,41,42,49,51,52,56,66,79,104, 114,128,136,143,155,158,163,172,178,188] and the planning phase (33/157, 21%) [33,50,72,77,78,80,81,83-86,92, 99,102,104,106,110,123-126,134,136,139,142,144,152,153,155,160,167,169,170].

Nurses most frequently assumed the role of evaluator, with 123 (78.3%) of 157 publications indicating that nurses took on this role in at least 1 phase [32-37,39-49,51-53,55,56,58, 60-65,67,68,70,72-75,77,79,80,82-88, 90-94,96-107,110-123,127-131,133-135,138-143,145-152,155, 157-160,162,164,165,167-169,171,172,175-180,182-186].

This was followed by the role of informant or SME (106/157, 67.5%) [32-37,39-41,43,46,49,50,52-56,58-61,63,64,67,69,72- 75,77,79-81,83-86,89-91,93,95,98,99,102, 104,106-110,113,114,116,119,121,123- 127,129,132-134,137-139,141,146,148-160, 162-171,173-175,177,178,181,182,184-188], designer or creator (31/157, 19.7%) [42,45,56,57,72,78,88,92,101,110,123,125,126, 131,134-136,146,151-153,162-166,169,171,173-175], or content developer (27/157, 17.2%) [42,45,56-58,78,88,92,101, 104,110,114,123,125,126,129,132, 135,136,151,153,158,165,168,173,184,188].

Nurses served in different roles across different phases of development. The most common co-occurrence was a nurse acting as an informant or SME during the requirements gathering phase (88/157, 56.1%) [32-37,39-41,43,46,49,50,52-56,58,59,61,63,64,67,72-75, 77,79-81,83,84,86,89-91,95,98,99,102, 104,106-110,114,116,119,123-126,129,132,134,136-138,146,148,150, 153-155,158-160,162-171,173,178,181,184-188], closely followed by acting as an evaluator during the design and prototyping phase (84/157, 53.5%) [32-34,36,37,39,41, 43,45,46,49,51-53,55,56,58,60,63-65,67,68,70,73-75,77, 79,84-88,90-93,96,99-102,104,106,107,111-118,121-123, 127,129,131,133-135,138-142,146,148,149,151, 157,158,164,165,167,169,171,180,182,184-186] or acting as an evaluator during the testing phase (71/157, 45.2%) [35,37,40,41,43-45,47,49,51,52,55,62,72,73,80,82,83,87, 90,91,94,96-98,100-105,114,119,120,122,128-130,133,135,139,140,142, 143,145-147,149-152,155,157-160, 162,164,165,167-169,172,175-180,183,184].

Roles were not mutually exclusive in the various development phases. The authors indicated that nurses took on between 1 and 4 roles within a development phase and more frequently took on a greater number of roles during earlier development phases. In total, 36% (12/33) of the publications describing the planning phase indicated nurses taking on >1 role [85,92,102,104,110,123,125,126,134,136,139,152]. Nurses taking on >1 role grew to 42 (43%) out of 98 publications in the requirements gathering phase [36,37,39,52,55,56,58,61,78,83,84,86,89,92, 99,101,104,110, 114,116,123,125,126,129,132,134,136,139,146,151,153,158,164-169,171,173,184,188] and 50 (44.6%) out of 112 publications in the design and prototyping phase [34,36,37,39,42,43,45,46,51,56-58,60,75,78, 88,92,93,101,104,110,113,114,121,123,125-127,131-136,138,141,142,146,151, 157,158,162-164,169,171,173-175,184]. None of the nurses took on >1 role during the software development phase, whereas 12 (15%) out of 80 publications noted nurses taking >1 role during the testing phase [38,43,47,51,56,132,135,139,149, 151,152,160].

Nurses were equally involved in developing apps for care providers and apps for health care consumers. Care providers were most frequently nurses (69/157, 43.9%) [32,35-37,40,44,46,47,49,50,52,55,59,62,64,66,68,69,72-74,79, 80,82-84,86,88-92,94,99,100,102,106,107,111,112,114-119, 122,124,134,135,138,142,143,146-148,153,155,158,164,165,167,169,172,175,176,183,187,188], followed by nonnurse providers (30/157, 19.1%) [35,36,49,50,52,55,59,64,74,79,80,86,88,90,91,94,102, 106,112,116,117,119,122,135,143,169,170,175,183,187], and student nurses (16/157, 10.2%) [50,77,96,97,103,115,120,124,130,131,136,149,151,158,177,182]. In 49.7% (78/157) of the publications, clients or patients were included as primary end users [38,42,43,48,51,52,54,56-58,60-65,67,70,71,75,76,78,81, 82,84,85,87,88,90,93,95,99-101,104,105,108-111,113,116,119,123,125-129, 132,137,139,140,145,150,152,154,156,157,159-163,166-171,173,174,178-180,184-186]; in 15.9% (25/157) of the studies, caregivers were considered primary end users [33,34,39,41,45,52,53,70,71,81,90,91, 98,109,121,129,133,141,144,159,166,167,171,181,188]. This pattern continued when considering secondary end users, which we defined as individuals interacting with the app to enter data but who may not be the intended market for the app. Although care providers were more prominent than health care consumers as secondary end users, both were represented. Nurses were secondary end users in 57.3% (90/157) of the publications [32-35,38,40,41,44,49,52-55,61-64,66,67,71-75,79-84,86-88, 90-92,94,98-100,102,104-109,111,113-116,119-122,128,129,132,135,137,139- 142,145,146,148,150,152-154,157,158,160,162-170,172,173,176,179,184,185], whereas nonnurse providers were noted as secondary end users in 42.7% (67/157) of the publications [35,38,41,46,49,52-55,61,63,64,68,69,71,72,74, 79-81,86-88,90,91,94,98,102,105,106,108,109,113,116,118-123,128,129,132,135,137,139- 141,145,147,150,152,154,157,160,162,163,166,167,169,170,172,173,175,179,184,185], and clients or patients were noted as secondary end users in 26.8% (42/157) of the publications [42,49,51,52,56-58,60,62,64,76, 78,82,84,85,88,90,93,95,99,101,104,106,110,111, 114,116,119,123,125,126,128,129,132,143,154,161,167-171].

In general, the apps focused on specific conditions, most frequently cancer (27/157, 17.2%) [38,43,53,54,57,60,68,70,76,78,82,84,87,90,94, 99,110,116,127,149,156,159,166,178,186,188, 189], cardiovascular disease (12/157, 7.6%) [42,58,65,97,98,120,125,126,128,145,171,187], pregnancy or neonatal care (11/157, 7%) [40,41,67,91,103,133,152,157,164,180,184], and diabetes (8/157, 5.1%) [35,51,85,104,114,139,165,168]. These apps were often in the early stages of development, although 26.1% (41/157) of the publications described multiple versions of the app [33,34,41-43,57,58,63,71,73,77,78,83,86,92, 95,99,102,104, 116,119,122,123,126,128,129,135,136,145,146,148,153,158-160,171,172,175,177,178,184]. Most commonly, the apps were the alpha or prototype versions (117/157, 74.5%) [32,33,35,37,39-43,45,46,49, 51,52,55-58,60,61,63,65,67,68,71,73-75,77-80,83-88,90-93,95, 98-107,110-119,121-126,128,129,131,132,134-136,138,140-143,146-167,169-181,184], followed by the storyboard or wireframe (32/157, 20.4%) [33,41,43,48,57,59,70,71,76,78,81,83,86,92,102,108,116,122,123, 126,128,129,136,146,148,153,158,171,177,178,185,186], beta (29/157, 18.5%) [33,34,36,38,42,43,47,58,63,69,71-73,77, 89,95,97,99,104,119,133,135,145,159,160,168,172,175,184], and release (10/157, 6.4%) [33,34,62,66,71,94,120,135,145,188] versions. In total, 10.2% (16/157) of the publications did not report the version of the app or described apps that had not yet been created [44,50,53,54,64,82,96,109,127,130,137,139, 144,182,183,187].

The median number of functions based on the IMS Institute for Healthcare Informatics Functionality was 5 (range 1-11). A total of 2 apps scored 11, the maximum possible score on the IMS Institute for Healthcare Informatics Functionality score [99,126]. Most publications (142/157, 90.4%) described multifunctional apps, with only 15 (9.6%) out of 157 publications describing an app with only a single function. The most frequently reported functionalities were to inform (101/157, 64.3%) [34-37,39,41-43,45,48,49,56,57,59-61,63-67,70-72,75,76,78,79,81, 83-88,90,91,93,97-99,101,103-110,113-116,120,122,123,125-130,132-136, 138,140,141,146,147,149-151,153,154,157,159-166,168, 173,174,176-178,180-184,186-188], collect data (100/157, 63.7%) [33,35,38,43,44,46,47,49,51,52,55,57-64,67-69,72,73, 75,77,78,80,81,84,86-92,94,98-102,104-106,108,112-114, 116-119,121,122,124,126-128,130,132,133,135,137,138, 140-143,145,147-150,152-159, 162-164,167-169,172,173,175,176,178,179,181,183-186], or instruct (80/157, 51%) [33-37,39,40,42,43,45,56,57,60,64-67,70-72,75, 76,78,79,85,91,93,97-99,101-104,106-109,114,115,120,122,123,125-131,134-136,141, 143,146,147,149-151,154,157,160,161,164-166,168,170, 173,174,178,180-184,186-188]. The least frequently reported functionalities were to intervene (29/157, 18.5%) [33,38,40,49,51,52,59,68,84,86, 89,92,99,101,107,116-118,122,126,128,147,148,153,154,156,169,178,181], remind or alert (41/157, 26.1%) [33,38, 43,44,52,59,60,63, 72,75,81,84,87,91,94,99,101,105,107-109,113,116,126,140,145,146,148,150,157,159,160, 162,166,168,169, 179,180,184,185,189], and evaluate data (48/157, 30.6%) [35,43,44,47,51,52,55,58,62,64,80, 84,86,89,91,92,94,98,99,101,102,106,112-114,116-119,122,126,128,135,142, 143,147,148,151,153,154,165,167,169,170,172,176,184,186]. Some of the apps integrated with other tools, with a majority integrating with some form of communication (39/157, 24.8%) [34,38,44,51,54,58,60,64,67,71,74,75,81,83,84,86,88,91,94,99, 106,119,126,128,133,138,143, 145,148,152,154,157-160,169,180,184,186], external resources (30/157, 19.1%) [32,34,36-39,43,48,54,58,60,61,71,75,81,83,84,89, 105,111,118,123,126,128,133,135,145,146,159,184], or electronic health record (21/157, 13.4%) [38,44,47,58,59,73,77,81, 84,88,91,126,132,135,145,152,159,164,167,169,175]. Apps less frequently integrated with portals (15/157, 9.6%) [38,52,59-63,84,86,99,105,118,119, 126,145], sensors or add-ons (8/157, 5.1%) [38,49,62,72,86,105,160,179], or other tools (ie, cloud-based servers and storage or databases; 5/157, 3.2%) [33,103,141,172,176]. Many apps (85/157, 54.1%) did not report integration with other devices.

The use of technical standards and standards for guiding content was also variable. In total, 26.8% (42/157) of the publications used ≥1 standard. In total, 8.9% (14/157) of the publications included content standards [41,96,97,102,127,153,164,167,177,181,182,184,186,187], such as clinical practice guidelines or recommendations for patient care, whereas 14% (22/157) included technical standards that informed the app’s development [37,40,52,59,60,67,75,88,104,108,114,115,117,123,134,151,159,165,172,173,178, 179], and 3.8% (6/157) of the publications included both technical and content standards [36,68,69,145,154,158]. Most of the manuscripts (115/157, 73.2%) did not indicate using a standard when developing their app.

This scoping review illuminated the various roles of nurses in mHealth app development. However, considering the number of published materials, few publications describe the development process of mHealth apps. This review reinforces previous findings that the levels of overall provider representation in app development are low, despite the recognition that provider involvement is key to creating effective apps [190-193]. Although nurses were represented throughout the development process in this review, the level of involvement was concentrated in specific phases and roles. Nurses were most frequently involved in the requirements gathering, designing and prototyping, and testing phases of development. Despite established recommendations for co-design and participatory design in mHealth, which reinforce the importance of involving clinicians and patients early and throughout the process [194,195], we found more limited involvement of nurses in the planning and software development phases. This parallels the findings of a recent rapid review on co-design practices in mHealth, which found that both patients and health care providers were most frequently engaged in needs identification, prototype design, and feedback and testing [196].

We found that the most common role for a nurse was an SME during the requirements gathering phase, followed by an evaluator during the testing phase. However, the roles for nurses as research experts, patient advocates, or informaticists were rare. This concentration in specific phases and roles reinforces the previous findings. A systematic review of clinician involvement in developing predictive clinical decision support tools found that clinicians most frequently served as informants (specifically, identifiers of system needs and requirements and developing clinically relevant content) but were less involved in evaluation [197]. Another systematic review of pain management apps found that most apps included in their study indicated that a health care professional was involved in the development, which was limited to content development or the role of a SME [198]. Although our study found that nurses were involved in content development and served as SMEs, involvement in testing and evaluation was prominent. The role of patient advocate may be implicit given the patient-centered focus of nurses; however, the role was rarely named as such. Although not named as patient advocates, nurses were frequently involved in the development of apps that included patients or caregivers as primary end users. This may be in recognition of the nurses’ understanding of patient needs concerning their health, diagnoses, and treatment options, given that nurses spend time and interact with patients more than any other health care provider. Patients are most likely to adopt an mHealth app when they believe that the information and services provided are trustworthy [199,200], and previous systematic reviews have found a strong, positive relationship between a patient’s perception of the opinions of those important to them and the intention to use mHealth apps [199,201]. In 1 study of older adults, 64% either agreed or strongly agreed that they would use an mHealth app if their health care provider recommended it [202]. A systematic review of barriers and facilitators in mHealth in oncology noted that “[n]urses seemed to the stakeholders with the greatest potential to push mHealth uptake” [203].

In the case of patient-facing solutions, nurses often have a unique perspective as patient advocates. For example, nurses can routinely answer questions from patients and families related to the use of apps or their health data [189,204]. Leveraging first-hand accounts of these experiences can provide important insights into how an app may be best designed for optimal patient engagement and ease of use [205]. Nurse-led and nurse-supported mHealth interventions have been associated with increased patient compliance, more complete self-reporting, and healthier lifestyle choices [206,207]. We believe that nurses should play an integral role in developing apps intended for patient or caregiver use and that their role as patient advocates should be integrated throughout the development process.

Nurses frequently assumed the role of evaluator throughout the development process. Although nurses responded to information, decisions, or app functionality, they were less frequently tasked with developing the app or designing its content. Nurses are more frequently evaluating or informing, rather than designing and developing, which may reflect previous findings that nurses have had limited involvement in mHealth app development [204]. The apps described in this scoping review lack robust functionality such as facilitating communication between systems and health care teams and evaluating data entered by the end user. These findings are not surprising because apps are relatively new to health care systems [208]. Our results partially parallel the IMS Institute’s findings, in which the authors assessed 23,682 apps to determine their functionality according to the IMS Institute for Healthcare Informatics Functionality. They found that the most widely available individual functionality was to inform, followed by instruct, and noted that most apps supported only a single functionality rather than being multifunctional. The authors noted that “most of the healthcare apps available today are only simple in design and do little more than provide information” [27]. Most apps included in our study were multifunctional, unlike those evaluated by the IMS Institute. However, the most frequent functionalities were focused on providing information to users. Although some more advanced functionalities were available in the apps included in our study, such as facilitating bidirectional communication with health care providers or providing reminders or alerts to patients, this was less common.

Previous systematic reviews have noted that apps have limited clinical utility and do not facilitate intervention or adjustment of care plans; instead, they focus on collecting patient data or providing basic information [191]. As apps become more sophisticated with sensor technology and interoperable with clinical decision support systems, adopting mHealth standards to support more advanced functions and features will be essential. Standards for mHealth app development exist but are rarely described in the literature, with the vast majority of publications lacking a description of technical standards or content standards. The lack of documentation describing the evidence base underlying these apps is a glaring omission and, unfortunately, is consistent with the findings of previous research [192,209,210]. Equally important to content standards are app development standards to ensure interoperability with other systems, usability, effective data capture and transfer, and the protection of patient information.

Further complicating the disorganized approach to mHealth development is an absent organizing body to establish and manage standards, ways to update and maintain systems, an overarching interoperable plan in health care, and the enterprising nature of technology. Those who develop technologies, including technologies for health care, are business oriented with a budget and prioritize profits over collaboration. Instead, businesses prefer to have more clients and purchasers than to become interoperable with competing systems.

To overcome some of these barriers, nurses have a role in planning and developing mHealth apps. Interoperable systems that support data sharing and transfer strengthen the provision of quality care to patients, who are now more involved in their care and decision-making. Creating these systems requires individuals with a knowledge base of institutional systems and health care as well as working knowledge of the fundamental needs of patients. These characteristics define a nurse informaticist. A nurse informaticist offers a clinical perspective combined with expertise in the technological systems and structures underlying patient care. Nurse informaticists are uniquely qualified because they have expertise in the health care environment and technology, functioning as liaisons between the clinical team, patients, and developers. The nurse informaticist transforms data into information and knowledge to be leveraged by technologies within a given environment to improve health, health care equity, safety, quality, and outcomes [211].

It is not surprising that apps focusing on cancer were the most prevalent in publications included in our review. Oncology has been recognized as a key space for nurse informaticists because of the complexity of coordinating care across multiple specialties and settings and the subsequent range of eHealth tools that have emerged as a result of this complexity [212-214]. Although cancer was the most predominant condition, many of the apps included in this review focused on complex, chronic conditions, such as cardiovascular diseases, diabetes, chronic kidney disease, and mental health. Chronic conditions have been previously identified as an opportunity for mHealth, given that the management of chronic conditions requires frequent data collection and transfer better suited to mHealth interventions than conventional office visits [215,216]. Patient engagement is key to the success of mHealth interventions for managing of chronic conditions. As previously noted, nurses can have a pivotal role in both motivating patients to start using the app and providing ongoing support and guidance for its continued use.

mHealth apps are still in their infancy, as is the nurses’ role in these apps. Nurses have a depth and breadth of knowledge in the health care environment, disease management, organizational infrastructure, quality, safety, patient education, and evidence-based practice. As McGonigle and Mastrian [217] note, “nursing is an information-intensive profession,” and “[a]t the heart of all of these [patient care] skills lies the management of data and information.” The accuracy of the information and the guidance an app may offer cannot be validated without due diligence by the health care professionals and patients. One way to ensure that health-related content is valid, based on evidence, and meets the needs of the end user is to incorporate nurses into the early stages of app creation [204]. Interventions fail most frequently because of misalignment between the app and existing workflows and clinical processes, leading to increased workloads or cumbersome workflows [218]. The technological burden for clinicians is at an all-time high. This technological stress contributes to clinician burnout, resulting in clinicians leaving the workforce [219,220]. Including nurses in the development of technologies can provide a sense of value while simultaneously increasing the likelihood of successful implementation by addressing workflow and clinical misalignment issues during the design process.

The full spectrum of app development efforts might not be fully documented or reported in the published literature. Although this review included conference presentations, abstracts, and protocol papers to capture ongoing projects and projects communicated outside of research articles, there may be previous or ongoing development efforts in which nurses are involved that are described only in internal documents or materials restricted owing to intellectual property considerations. Although we developed a search strategy in accordance with best practices and attempted to be as comprehensive as possible, our search terms may not include relevant terminology in every discipline. Despite this, we believe that we have captured all publications meeting our inclusion criteria.

Our decision to include protocol papers means that some description of nurse involvement and the phase of involvement is anticipated rather than having been completed. Although it is possible that projects ultimately deviate from their published protocols, we believe that these descriptions of planned involvement, nevertheless, contribute to addressing our overall research questions.

Our review is limited to examining the reported role of nurses in mHealth app development and does not account for the postimplementation involvement of nurses. Our analysis is also limited to what is described in the publication. It is possible that the nurses took on additional roles or were engaged in other phases that were not described in the publication. Future research should consider additional research methods, such as surveys, to understand the role and experience of nurses in mHealth app development beyond what is documented in the literature. Similarly, it is possible that technical and content standards were used more broadly, but their use was not described in publication. More complete reporting of standards would more effectively communicate which standards are most broadly implemented and subsequently promote further awareness and adoption.

This scoping review did not examine the efficacy of mHealth apps or their impact on clinically relevant outcomes. As more randomized controlled trials become available, future research may consider quantifying the impact of nurse involvement in mHealth app development on clinical outcomes.

Although we did not assess the risk of bias in the included studies, as this is not a component of scoping reviews, there is a lack of clarity regarding funding sources. Depending on the funding models for app development, there may be a conflict of interest on the part of the authors describing the app development process or its outcomes. This lack of information makes it difficult to assess whether any conflict of interest existed. Although the potential conflict of interest may not directly affect our findings, clear reporting of funding sources and any conflicts of interest enables a more thorough examination of the quality of the research.

Regardless of the type of health system, nurses must work toward nurse representation on all technology-specific committees and task forces influencing health care services. Currently, the role of nurses in mHealth app development is limited, although the potential benefit of incorporating this expertise throughout the development process would be to patients, providers, and care systems. Advocacy for nurse involvement in planning, development, implementation, and evaluation is a vital role for nursing leadership in all care systems, and widespread communication and dissemination of these roles can serve as an example for those developing mHealth apps.