Table 3.

Overview of journal papers 12-23 included in the scoping review.

Author, country	Study objective	Study design	Medical field	App type	User
Da Silva et al [59], Brazil and Germany	Describe a system designed to enhance hypertensive patients’ treatment compliance.	Quantitative research: experiment	Hypertension	Health self-management	Consumers, physicians, patients’ family members
De Carvalho et al [52], the Netherlands and Romania	Review the development process of a smartphone app for skin cancer risk assessment.	Quantitative research: retrospective study	Skin cancer	Diagnosis	Consumers, physicians
Denecke et al [53], Switzerland, Norway, New Zealand, the United Kingdom, Australia, and Spain	Investigate how AIa is affecting the field of participatory health and which AI apps exist in the field from a patient’s and a clinician’s perspective.	Systematic review	Diabetes, pain management, hypertension, cancer, intestinal diseases, mental health, respiratory diseases, other chronic diseases	Diagnosis, health self-management, health care information inquiry	Consumers, physicians
Fan et al [54], China, Canada, and the United States	Investigate how an AI-driven health chatbot that is extensively deployed in China can be used in the real world, what problems and barriers exist in its use, and how the user experience can be improved.	Quantitative research: case analysis	General practice	Diagnosis	Consumers
Koren et al [55], Israel and the United States	Develop and evaluate an algorithmic tool that provides symptom information to the public and their physicians to aid in decision-making.	Quantitative research: case analysis	General practice	Diagnosis	Consumers
Lau and Staccini [56], Australia and France	Examine how AI methods are presently being used by patients and consumers, present representative papers in 2018, and highlight untapped opportunities in AI research for patients and consumers.	Systematic review	Depression, mental disease, breast cancer, mental health	Health self-management	Consumers
Romero et al [48], the United Kingdom	Screen for obstructive sleep apnea based on the analysis of sleep breathing sounds recorded by consumers using smartphones at home.	Quantitative research: experiment	Obstructive sleep apnea screening	Diagnosis	Consumers
Sangers et al [57], the Netherlands and the United States	Examine the diagnostic accuracy of dermatology mobile health (mHealth) apps currently approved for consumer use in Europe, Australia, and New Zealand for the detection of precancerous and malignant skin lesions.	Quantitative research: experiment	Skin cancer	Diagnosis	Consumers
Sefa-Yeboah et al [58], Ghana and the United States	Propose an AI-based app powered by a genetic algorithm to help users with obesity self-management.	Quantitative research: experiment	Obesity	Health self-management	Consumers, nursing staff
Tschanz et al [49], Switzerland	Introduce an electronic medication management assistant to remind patients to take medication, record compliance data, inform patients of the importance of medication compliance, and provide health care teams with patients’ up-to-date medication data.	Quantitative research: case analysis	General practice	Health self-management	Consumers, physicians
Zhang et al [60], the United States and China	Investigate patients’ perceptions and acceptance of the use of AI to explain radiology reports.	Qualitative research: interview	Radiology	Diagnosis	Consumers
Zhang et al [61], the United States and China	Evaluate the effect of different AI explanations on consumer perceptions of AI-powered health care systems.	Quantitative research: experiment	Radiology	Diagnosis	Consumers

^aAI: artificial intelligence.