This paper is in the following e-collection/theme issue:

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1301) Back Pain (101) mHealth for Rehabilitation (233) mHealth for Wellness, Behavior Change and Prevention (2728) Chatbots and Conversational Agents (458) Artificial Intelligence (1186) Occupational Health and Ergonomics/Prevention at the Workplace (220) Innovations in Exercise Rehabilitation (202) Portable and Mobile Technologies for Rehabilitation (142)

Published on in Vol 9, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27535, first published .
Effects of an Artificial Intelligence–Assisted Health Program on Workers With Neck/Shoulder Pain/Stiffness and Low Back Pain: Randomized Controlled Trial

Effects of an Artificial Intelligence–Assisted Health Program on Workers With Neck/Shoulder Pain/Stiffness and Low Back Pain: Randomized Controlled Trial

Effects of an Artificial Intelligence–Assisted Health Program on Workers With Neck/Shoulder Pain/Stiffness and Low Back Pain: Randomized Controlled Trial

Authors of this article:

Tomomi Anan1, 2 Author Orcid Image ;   Shigeyuki Kajiki1, 2, 3 Author Orcid Image ;   Hiroyuki Oka4 Author Orcid Image ;   Tomoko Fujii4 Author Orcid Image ;   Kayo Kawamata4 Author Orcid Image ;   Koji Mori1 Author Orcid Image ;   Ko Matsudaira4 Author Orcid Image
Article Authors Cited by (38) Tweetations (5) Metrics

Journals

  1. Yang Y, Boulton E, Todd C. Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework. Journal of Medical Internet Research 2022;24(6):e30817 View
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  3. Itoh N, Mishima H, Yoshida Y, Yoshida M, Oka H, Matsudaira K. Evaluation of the Effect of Patient Education and Strengthening Exercise Therapy Using a Mobile Messaging App on Work Productivity in Japanese Patients With Chronic Low Back Pain: Open-Label, Randomized, Parallel-Group Trial. JMIR mHealth and uHealth 2022;10(5):e35867 View
  4. Hasan F, Mudey A, Joshi A. Role of Internet of Things (IoT), Artificial Intelligence and Machine Learning in Musculoskeletal Pain: A Scoping Review. Cureus 2023 View
  5. Barreveld A, Rosén Klement M, Cheung S, Axelsson U, Basem J, Reddy A, Borrebaeck C, Mehta N. An artificial intelligence-powered, patient-centric digital tool for self-management of chronic pain: a prospective, multicenter clinical trial. Pain Medicine 2023;24(9):1100 View
  6. Matsudaira K. Multifaceted Rehabilitation for Chronic Low Back Pain and Its Methods：Treatment Strategies Based on a Multi-layered Model of Pain. The Japanese Journal of Rehabilitation Medicine 2023;60(7):605 View
  7. An R, Shen J, Wang J, Yang Y. A scoping review of methodologies for applying artificial intelligence to physical activity interventions. Journal of Sport and Health Science 2024;13(3):428 View
  8. Zhandarov K, Blinova E, Ogarev E, Sheptulin D, Terekhina E, Telpukhov V, Vasil’ev Y, Nelipa M, Kytko O, Chilikov V, Panyushkin P, Drakina O, Meilanova R, Mirontsev A, Shimanovsky D, Bogoyavlenskaya T, Dydykin S, Nikolenko V, Kashtanov A, Aliev V, Kireeva N, Enina Y. Intervertebral Canals and Intracanal Ligaments as New Terms in Terminologia anatomica. Diagnostics 2023;13(17):2809 View
  9. Jang S, Lee B, Lee E, Kim J, Lee J, Lim J, Hwang J, Jang S. A Systematic Review and Meta-Analysis of the Effects of Rehabilitation Using Digital Healthcare on Musculoskeletal Pain and Quality of Life. Journal of Pain Research 2023;Volume 16:1877 View
  10. Komoto N, Sakebayashi H, Imagawa N, Mizuno Y, Nakata I, Shigetoh H, Kodama T, Miyazaki J. Cluster Analysis of Subjective Shoulder Stiffness and Muscle Hardness: Associations with Central Sensitization-Related Symptoms. Medicina 2023;59(10):1831 View
  11. Kheirinejad S, Visuri A, Suryanarayana S, Hosio S. Exploring mHealth applications for self-management of chronic low back pain: A survey of features and benefits. Heliyon 2023;9(6):e16586 View
  12. Rujiret U, Keerin M, Julaporn P, Petcharatana B, Wattana J, Chutima J. Validity of “OfficeCheck”: A self-musculoskeletal assessment tool for screening work-related musculoskeletal disorders in office workers. Work 2023;76(4):1501 View
  13. Barati Jozan M, Ghorbani B, Khalid M, Lotfata A, Tabesh H. Impact assessment of e-trainings in occupational safety and health: a literature review. BMC Public Health 2023;23(1) View
  14. Al’Saani S, Raza L, Fatima K, Khan S, Fatima M, Ali S, Amin M, Siddiqui M, Liaquat A, Siddiqui F, Naveed W, Naqvi T, Bibi Z. Relationship between musculoskeletal discomfort and cell phone use among young adults: A cross-sectional survey. Work 2023;76(4):1579 View
  15. Sumner J, Lim H, Chong L, Bundele A, Mukhopadhyay A, Kayambu G. Artificial intelligence in physical rehabilitation: A systematic review. Artificial Intelligence in Medicine 2023;146:102693 View
  16. Okeibunor J, Jaca A, Iwu-Jaja C, Idemili-Aronu N, Ba H, Zantsi Z, Ndlambe A, Mavundza E, Muneene D, Wiysonge C, Makubalo L. The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review. Frontiers in Public Health 2023;11 View
  17. Nagel J, Wegener F, Grim C, Hoppe M. Effects of Digital Physical Health Exercises on Musculoskeletal Diseases: Systematic Review With Best-Evidence Synthesis. JMIR mHealth and uHealth 2024;12:e50616 View
  18. Marks R. Artificial intelligence and rehabilitation: what’s new and promising. International Physical Medicine & Rehabilitation Journal 2023;8(2):135 View
  19. Kang J, Hsieh E, Lee C, Sun Y, Lee T, Hsu J, Chang T. Assessing Non-Specific Neck Pain through Pose Estimation from Images Based on Ensemble Learning. Life 2023;13(12):2292 View
  20. Mitsea E, Drigas A, Skianis C. Digitally Assisted Mindfulness in Training Self-Regulation Skills for Sustainable Mental Health: A Systematic Review. Behavioral Sciences 2023;13(12):1008 View
  21. Lee H, Choi E, Shin J, Kim T, Oh J, Shin B, Sim J, Shin J, Kim M. The Impact of Intervention Design on User Engagement in Digital Therapeutics Research: Factorial Experiment With a Mixed Methods Study. JMIR Formative Research 2024;8:e51225 View
  22. Shrivastava M, Ye L. Neuroimaging and artificial intelligence for assessment of chronic painful temporomandibular disorders—a comprehensive review. International Journal of Oral Science 2023;15(1) View
  23. Abd-Elsayed A, Robinson C, Marshall Z, Diwan S, Peters T. Applications of Artificial Intelligence in Pain Medicine. Current Pain and Headache Reports 2024;28(4):229 View
  24. Martindale A, Ng B, Ngai V, Kale A, Ferrante di Ruffano L, Golub R, Collins G, Moher D, McCradden M, Oakden-Rayner L, Rivera S, Calvert M, Kelly C, Lee C, Yau C, Chan A, Keane P, Beam A, Denniston A, Liu X. Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines. Nature Communications 2024;15(1) View
  25. Wang X, Jin Z, Feng T, Fang S, Sun C, Qin X, Sun K, Liang L, Liu G, Zhu L, Wei X. The immediate effect of cervical rotation-traction manipulation on cervical paravertebral soft tissue: a study using soft tissue tension cloud chart technology. BMC Musculoskeletal Disorders 2024;25(1) View
  26. Robinson C, D'Souza R, Yazdi C, Diejomaoh E, Schatman M, Emerick T, Orhurhu V. Reviewing the Potential Role of Artificial Intelligence in Delivering Personalized and Interactive Pain Medicine Education for Chronic Pain Patients. Journal of Pain Research 2024;Volume 17:923 View
  27. Anisha S, Sen A, Bain C. Evaluating the Potential and Pitfalls of AI-Powered Conversational Agents as Human-like Virtual Health Carers in the Remote Management of Non-Communicable Diseases: A Scoping Review (Preprint). Journal of Medical Internet Research 2024 View
  28. Laymouna M, Ma Y, Lessard D, Schuster T, Engler K, Lebouché B. Roles, Users, Benefits and Limitations of Chatbots in Healthcare: A Rapid Review (Preprint). Journal of Medical Internet Research 2024 View
  29. Cevasco K, Morrison Brown R, Woldeselassie R, Kaplan S. Patient Engagement with Conversational Agents in Health Applications 2016–2022: A Systematic Review and Meta-Analysis. Journal of Medical Systems 2024;48(1) View
  30. Pedersini P, Tovani-Palone M. Artificial Intelligence in Geriatric Rehabilitation. Topics in Geriatric Rehabilitation 2024;40(2):95 View
  31. Shetty A, Delanerolle G, Deng C, Thillainathan A, Cavalini H, Yang X, Bouchareb Y, Boyd A, Phiri P, Shi J, Deer T. A systematic review and bayesian meta-analysis of medical devices used in chronic pain management. Scientific Reports 2024;14(1) View
  32. Armfield N, Elphinston R, Liimatainen J, Scotti Requena S, Eather C, Edirippulige S, Ritchie C, Robins S, Sterling M. Development and use of mobile messaging for individuals with musculoskeletal pain conditions: a scoping review (Preprint). JMIR mHealth and uHealth 2023 View
  33. Delage N, Cantagrel N, Soriot-Thomas S, Frost M, Deleens R, Ginies P, Eschalier A, Corteval A, Laveyssière A, Phalip J, Bertin C, Pereira B, Chenaf C, Doreau B, Authier N, Kerckhove N. Mobile Health App and Web Platform (eDOL) for Medical Follow-Up of Patients With Chronic Pain: Cohort Study Involving the French eDOL National Cohort After 1 Year. JMIR mHealth and uHealth 2024;12:e54579 View
  34. Griefahn A, Zalpour C, Luedtke K. Identifying the risk of exercises, recommended by an artificial intelligence for patients with musculoskeletal disorders. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Mer A, Virdi A. The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part A. View
  2. Niwa M, Hara Y. Mobile Health (mHealth). View
  3. McMahon J, Craig A, Cameron I. Service-Oriented Computing – ICSOC 2023 Workshops. View