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1. Evidence of Human-Level Bonds Established With a Digital Conversational Agent: Cross-sectional, Retrospective Observational Study

JMIR Form Res 2021;5(5):e27868

25467 41 170
2. Artificial Intelligence–Based Chatbot for Anxiety and Depression in University Students: Pilot Randomized Controlled Trial

JMIR Form Res 2021;5(8):e20678

12207 17 146
3. Recommendations for Health Equity and Virtual Care Arising From the COVID-19 Pandemic: Narrative Review

JMIR Form Res 2021;5(4):e23233

5785 23 135
4. Self-Administered Skills-Based Virtual Reality Intervention for Chronic Pain: Randomized Controlled Pilot Study

JMIR Form Res 2020;4(7):e17293

16600 170 131
5. Understanding Health Behavior Technology Engagement: Pathway to Measuring Digital Behavior Change Interventions

JMIR Form Res 2019;3(4):e14052

12899 55 111
6. Governing Data and Artificial Intelligence for Health Care: Developing an International Understanding

JMIR Form Res 2022;6(1):e31623

3967 77 99
7. Chatbot-Delivered Cognitive Behavioral Therapy in Adolescents With Depression and Anxiety During the COVID-19 Pandemic: Feasibility and Acceptability Study

JMIR Form Res 2022;6(11):e40242

3580 11 95
8. Artificial Intelligence Chatbot for Depression: Descriptive Study of Usage

JMIR Form Res 2020;4(11):e17065

13845 6 89
9. Accuracy of a Chatbot (Ada) in the Diagnosis of Mental Disorders: Comparative Case Study With Lay and Expert Users

JMIR Form Res 2019;3(4):e13863

8932 22 89
10. Deconstructing TikTok Videos on Mental Health: Cross-sectional, Descriptive Content Analysis

JMIR Form Res 2022;6(5):e38340

22286 7 85
11. Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study With Medical Students and Professionals

JMIR Form Res 2022;6(3):e28750

3522 5 85
12. Reasons People Who Use Opioids Do Not Accept or Carry No-Cost Naloxone: Qualitative Interview Study

JMIR Form Res 2020;4(12):e22411

4747 10 73
13. The Impact of the COVID-19 Pandemic on Physical and Mental Health in China and Spain: Cross-sectional Study

JMIR Form Res 2021;5(5):e27818

3416 3 73
14. Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation

JMIR Form Res 2022;6(6):e36501

2892 20 69
15. Accuracy of ChatGPT on Medical Questions in the National Medical Licensing Examination in Japan: Evaluation Study

JMIR Form Res 2023;7(1):e48023

824 13 67
16. A 3-Item Measure of Digital Health Care Literacy: Development and Validation Study

JMIR Form Res 2022;6(4):e36043

7126 43 65
17. Co-Designing a Mobile App to Improve Mental Health and Well-Being: Focus Group Study

JMIR Form Res 2021;5(2):e18172

4364 5 63
18. Acceptance of Mobile Health Apps for Disease Management Among People With Multiple Sclerosis: Web-Based Survey Study

JMIR Form Res 2018;2(2):e11977

6304 46 61
19. Smartphone-Based Meditation for Myeloproliferative Neoplasm Patients: Feasibility Study to Inform Future Trials

JMIR Form Res 2019;3(2):e12662

9148 1 59
20. Chatbot-Based Assessment of Employees’ Mental Health: Design Process and Pilot Implementation

JMIR Form Res 2021;5(4):e21678

5573 6 56
21. Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study

JMIR Form Res 2022;6(6):e35807

2880 4 55
22. Assessment and Prediction of Depression and Anxiety Risk Factors in Schoolchildren: Machine Learning Techniques Performance Analysis

JMIR Form Res 2022;6(8):e32736

2284 5 55
23. A Mind-Body Physical Activity Program for Chronic Pain With or Without a Digital Monitoring Device: Proof-of-Concept Feasibility Randomized Controlled Trial

JMIR Form Res 2020;4(6):e18703

2095 2 54
24. Development and Usability of ADappt: Web-Based Tool to Support Clinicians, Patients, and Caregivers in the Diagnosis of Mild Cognitive Impairment and Alzheimer Disease

JMIR Form Res 2019;3(3):e13417

3451 4 53
25. A Stress Management App Intervention for Cancer Survivors: Design, Development, and Usability Testing

JMIR Form Res 2018;2(2):e19

7267 27 53

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