Abstract:Background
Peripheral artery disease (PAD) is a cardiovascular disease that can be improved by risk factor modification. Mobile health (mHealth) intervention is an effective method of healthcare delivery to promote behavior changes. An mHealth platform can encourage consistent involvement of participants and healthcare providers for health promotion. This study aimed to develop an mHealth platform consisting of a smartphone application (app) synchronized with a wearable activity tracker and a w… Show more
“…Additionally, patient-centered considerations of the design and interface before the development of an app might be helpful to promote behavior change. One study suggested iterative development through a user-centered design approach involving the following 3 phases: analysis, design, and implementation to achieve less fragmented care [54]. This systematic approach could encourage patients, survivors, and health care providers to participate in the development and quality assessment of mobile apps.…”
Section: Recommendations For Future Developmentmentioning
Background
The number of mobile health apps is rapidly increasing. This means that consumers are faced with a bewildering array of choices, and finding the benefit of such apps may be challenging. The significant international burden of breast cancer (BC) and the potential of mobile health apps to improve medical and public health practices mean that such apps will likely be important because of their functionalities in daily life. As the app market has grown exponentially, several review studies have scrutinized cancer- or BC-related apps. However, those reviews concentrated on the availability of the apps and relied on user ratings to decide on app quality. To minimize subjectivity in quality assessment, quantitative methods to assess BC-related apps are required.
Objective
The purpose of this study is to analyze the content and quality of BC-related apps to provide useful information for end users and clinicians.
Methods
Based on a stepwise systematic approach, we analyzed apps related to BC, including those related to prevention, detection, treatment, and survivor support. We used the keywords “breast cancer” in English and Korean to identify commercially available apps in the Google Play and App Store. The apps were then independently evaluated by 2 investigators to determine their eligibility for inclusion. The content and quality of the apps were analyzed using objective frameworks and the Mobile App Rating Scale (MARS), respectively.
Results
The initial search identified 1148 apps, 69 (6%) of which were included. Most BC-related apps provided information, and some recorded patient-generated health data, provided psychological support, and assisted with medication management. The Kendall coefficient of concordance between the raters was 0.91 (P<.001). The mean MARS score (range: 1-5) of the apps was 3.31 (SD 0.67; range: 1.94-4.53). Among the 5 individual dimensions, functionality had the highest mean score (4.37, SD 0.42) followed by aesthetics (3.74, SD 1.14). Apps that only provided information on BC prevention or management of its risk factors had lower MARS scores than those that recorded medical data or patient-generated health data. Apps that were developed >2 years ago, or by individuals, had significantly lower MARS scores compared to other apps (P<.001).
Conclusions
The quality of BC-related apps was generally acceptable according to the MARS, but the gaps between the highest- and lowest-rated apps were large. In addition, apps using personalized data were of higher quality than those merely giving related information, especially after treatment in the cancer care continuum. We also found that apps that had been updated within 1 year and developed by private companies had higher MARS scores. This may imply that there are criteria for end users and clinicians to help choose the right apps for better clinical outcomes.
“…Additionally, patient-centered considerations of the design and interface before the development of an app might be helpful to promote behavior change. One study suggested iterative development through a user-centered design approach involving the following 3 phases: analysis, design, and implementation to achieve less fragmented care [54]. This systematic approach could encourage patients, survivors, and health care providers to participate in the development and quality assessment of mobile apps.…”
Section: Recommendations For Future Developmentmentioning
Background
The number of mobile health apps is rapidly increasing. This means that consumers are faced with a bewildering array of choices, and finding the benefit of such apps may be challenging. The significant international burden of breast cancer (BC) and the potential of mobile health apps to improve medical and public health practices mean that such apps will likely be important because of their functionalities in daily life. As the app market has grown exponentially, several review studies have scrutinized cancer- or BC-related apps. However, those reviews concentrated on the availability of the apps and relied on user ratings to decide on app quality. To minimize subjectivity in quality assessment, quantitative methods to assess BC-related apps are required.
Objective
The purpose of this study is to analyze the content and quality of BC-related apps to provide useful information for end users and clinicians.
Methods
Based on a stepwise systematic approach, we analyzed apps related to BC, including those related to prevention, detection, treatment, and survivor support. We used the keywords “breast cancer” in English and Korean to identify commercially available apps in the Google Play and App Store. The apps were then independently evaluated by 2 investigators to determine their eligibility for inclusion. The content and quality of the apps were analyzed using objective frameworks and the Mobile App Rating Scale (MARS), respectively.
Results
The initial search identified 1148 apps, 69 (6%) of which were included. Most BC-related apps provided information, and some recorded patient-generated health data, provided psychological support, and assisted with medication management. The Kendall coefficient of concordance between the raters was 0.91 (P<.001). The mean MARS score (range: 1-5) of the apps was 3.31 (SD 0.67; range: 1.94-4.53). Among the 5 individual dimensions, functionality had the highest mean score (4.37, SD 0.42) followed by aesthetics (3.74, SD 1.14). Apps that only provided information on BC prevention or management of its risk factors had lower MARS scores than those that recorded medical data or patient-generated health data. Apps that were developed >2 years ago, or by individuals, had significantly lower MARS scores compared to other apps (P<.001).
Conclusions
The quality of BC-related apps was generally acceptable according to the MARS, but the gaps between the highest- and lowest-rated apps were large. In addition, apps using personalized data were of higher quality than those merely giving related information, especially after treatment in the cancer care continuum. We also found that apps that had been updated within 1 year and developed by private companies had higher MARS scores. This may imply that there are criteria for end users and clinicians to help choose the right apps for better clinical outcomes.
“…The text message library may be revised through this process; subsequently, the effectiveness of an EMA-triggered text message intervention should be investigated in patients with PAD. The developed text message library combined with the EMA survey may be applied to structure exercise programs or smartphone-based exercise intervention programs (Kim et al, 2022a) to encourage exercise engagement.…”
Section: Discussionmentioning
confidence: 99%
“…In previous studies, barriers to exercise in patients with PAD were reported to include personal and environmental aspects (Abaraogu et al, 2018; Barbosa et al, 2015; Bentley & Kelechi, 2018; Cavalcante et al, 2015), but it is necessary to identify any additional barriers that might be present in the Korean population through behavior analysis. Therefore, we conducted face-to-face interviews to explore participants’ experiences performing exercise and focused on deriving exercise barriers and facilitators for the development of a text messaging intervention using a mobile application for patients with PAD (Kim et al, 2022a).…”
This study developed an ecological momentary assessment (EMA)-triggered text message library based on the behavior change wheel framework to encourage exercise engagement in patients with peripheral artery disease (PAD). This study was conducted in three steps. In Step 1, semi-structured interviews were conducted with 15 patients with PAD. Their accounts of their exercise experiences revealed six barriers and three facilitators through thematic analysis. In Step 2, based on the findings from the prior step, the EMA survey was developed; its items included barriers to exercise, PAD-related leg symptoms, and general conditions. In Step 3, intervention functions to overcome exercise barriers were mapped, and 120 text messages were generated. Responses to the exercise barriers in the EMA survey triggered the automatic text messages. Additional studies are needed to examine the end-user acceptability of the text message library and the effectiveness of EMA-triggered text message interventions.
“…1) Personalized health monitoring: These systems use AI technologies to collect, process, and analyze health-related data, allowing for personalized health monitoring and support to the users. The automatic collection of data, such as vital signs, physical activity levels, and sleep patterns, can help detect health-related issues in real-time [8], [49], [61], [69].…”
Section: B Opportunitiesmentioning
confidence: 99%
“…One of the main advantages of these systems is their ability to provide users with real-time feedback, allowing www.ijacsa.thesai.org them to make informed health decisions [3]. Furthermore, these systems can offer personalized health recommendations, such as lifestyle changes or exercise programs [69] to assist users in improving their overall health.…”
In recent years, the integration of artificial intelligence (AI) technologies has greatly benefited smart city healthcare, meeting the growing demand for affordable, efficient, and real-time healthcare services. Patient monitoring is one area where artificial intelligence has shown great promise. Improved health outcomes have been made possible by the advancement of AI-based monitoring systems, which enable more personalized and continuous patient monitoring. However, to fully maximize the benefits of these systems, a user-centered approach is essential, which prioritizes patients' needs and experiences while ensuring their privacy and autonomy are respected. This study focuses on the application of user-centered design principles in the development and deployment of AI-driven monitoring systems in smart city healthcare. Addressing the challenges and opportunities of AI-driven monitoring systems, the article considers issues such as privacy and security concerns, data accuracy, and user acceptance. Finally, some possible future directions to the challenges are suggested. A user-centered approach to AI monitoring systems is recommended for healthcare providers to enhance patient experience in smart city healthcare.
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