Table 4.

DRsa and CRsb for overcoming the identified limitations or barriers in digital health technologies for osteoporosis.

Identified limitation or barrier and related aspect			Recommendation
App designers and developers without supporting information from clinicians, resulting in a very technologically focused and problem-oriented approach in the design of mHealth apps
	Design perspective	DR1: involve all the stakeholders in all the stages of user requirements, design, and development using a participatory design approach (cocreation)
	Clinical perspective	CR1: active participation in the design, development, and testing stages
Clinicians’ reluctance in adopting mHealth c apps as they envisage that they will replace them
	Clinical perspective	CR1: adopt mHealth technologies in daily practices and in clinical care (measurement, assessment, and recording data) CR2: recommend trustworthy apps to their patients CR3: use mHealth apps to effectively communicate with patients and other health care professionals through the integration of wearables and IoTd
Lack of trustworthy and available smart tools and strict regulations on mHealth tools
	Design perspective	DR1: use adaptive learning algorithms (eg, AIe and machine or deep learning) in the app to make more personalized recommendations and treatments DR2: incorporate clinically validated monitoring, measurement, and assessment tools in the designed app
	Clinical perspective	CR1: evaluate mHealth measurement and assessment tools by concerned clinical experts before disseminating them to public
Underestimation of the security risk and the elevated cost of implementing strong data security and privacy rules
	Design perspective	DR1: implement stringent security regulations (eg, GDPRf [79]) to protect users’ information from any data penetration (security and privacy by design)
Available data are provider oriented rather than patient accessible; limited existing guidelines on how to optimize user interfaces for patients, providers, or both
	Design perspective	DR1: allow patients to access their data (GDPR enforcement in design) DR2: generate feedback and plans (for diet and exercises) based on the gathered data to keep patients engaged and motivated
Inconsistent data collection standards, complexity of data, and lack of quality assurance processes (data cannot be verified)
	Design perspective	DR1: use passive and active gathering of data (medication, symptoms, nutrition management, and physical exercising), in addition to the data gathered from any wearables or IoT sensors
	Clinical perspective	CR1: combine conventional clinical assessment with the app assessment
Difficulties in acquiring, analyzing, and applying structured and unstructured data to treat or manage diseases
	Design perspective	DR1: apply AI-based techniques that help with the prediction, diagnosis, and treatment or management of diseases
Low retention rates of participants
	Design perspective	DR1: provide valuable feedback to the user DR2: use simple and straightforward interfaces DR3: continuously update users’ data DR4: offer financial incentives for healthy habit changes

^aDR: design-related recommendation.

^bCR: clinical recommendation.

^cmHealth: mobile health.

^dIoT: Internet of Things.

^eAI: artificial intelligence.

^fGDPR: General Data Protection Regulation.