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

Theoretical Frameworks and Concepts (252) Participatory Medicine & E-Patients (773) Quantified Self and Wellness (77)
Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies

Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies

Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies

Authors of this article:

Manal Almalki1, 2 Author Orcid Image ;   Kathleen Gray1 Author Orcid Image ;   Fernando Martin-Sanchez1, 3 Author Orcid Image
Article Authors Cited by (24) Tweetations (17) Metrics

Journals

  1. Zhang Y, Li D, Zhang C, Zhang H. Quantified or nonquantified: How quantification affects consumers' motivation in goal pursuit. Journal of Consumer Behaviour 2019;18(2):120 View
  2. Stiglbauer B, Weber S, Batinic B. Does your health really benefit from using a self-tracking device? Evidence from a longitudinal randomized control trial. Computers in Human Behavior 2019;94:131 View
  3. Jin D, Halvari H, Maehle N, Olafsen A. Self-tracking behaviour in physical activity: a systematic review of drivers and outcomes of fitness tracking. Behaviour & Information Technology 2022;41(2):242 View
  4. Wu X, Zhao M, Liao H, Sun S. A Scientometric Analysis of Self-tracking in Relation to Artificial Intelligence and Big Data. IOP Conference Series: Materials Science and Engineering 2020;806(1):012014 View
  5. Costa Figueiredo M, Caldeira C, Reynolds T, Victory S, Zheng K, Chen Y. Self-Tracking for Fertility Care. Proceedings of the ACM on Human-Computer Interaction 2017;1(CSCW):1 View
  6. Riggare S, Unruh K, Sturr J, Domingos J, Stamford J, Svenningsson P, Hägglund M. Patient-driven N-of-1 in Parkinson’s Disease. Methods of Information in Medicine 2017;56(S 01):e123 View
  7. Borda A, Gray K, Fu Y. Research data management in health and biomedical citizen science: practices and prospects. JAMIA Open 2020;3(1):113 View
  8. Sathyanarayana A, Joty S, Fernandez-Luque L, Ofli F, Srivastava J, Elmagarmid A, Arora T, Taheri S. Sleep Quality Prediction From Wearable Data Using Deep Learning. JMIR mHealth and uHealth 2016;4(4):e125 View
  9. Almalki M, Gray K, Martin-Sanchez F. Development and Validation of a Taxonomy for Characterizing Measurements in Health Self-Quantification. Journal of Medical Internet Research 2017;19(11):e378 View
  10. Ng K, Tynjälä J, Kokko S. Ownership and Use of Commercial Physical Activity Trackers Among Finnish Adolescents: Cross-Sectional Study. JMIR mHealth and uHealth 2017;5(5):e61 View
  11. De Moya J, Pallud J. From panopticon to heautopticon: A new form of surveillance introduced by quantified‐self practices. Information Systems Journal 2020;30(6):940 View
  12. Gray K, Martin-Sanchez F, Lopez-Campos G, Almalki M, Merolli M. Person-generated Data in Self-quantification. Methods of Information in Medicine 2017;56(01):40 View
  13. Almalki M, Gray K, Martin-Sanchez F. Refining the Concepts of Self-quantification Needed for Health Self-management. Methods of Information in Medicine 2017;56(01):46 View
  14. Karanasios S, Nardi B, Spinuzzi C, Malaurent J. Moving forward with activity theory in a digital world. Mind, Culture, and Activity 2021;28(3):234 View
  15. Feng S, Mäntymäki M, Dhir A, Salmela H. How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review. Journal of Medical Internet Research 2021;23(9):e25171 View
  16. Fan X, Fan J, Li J. The Effect of Presentation Characteristics of “Quantified Self” Data on Consumers’ Continuance Participation Intention: An Empirical Study Based on Health-Related Apps. Psychology Research and Behavior Management 2022;Volume 15:2859 View
  17. Peterson Fronczek L, Mende M, Scott M. From self‐quantification to self‐objectification? Framework and research agenda on consequences for well‐being. Journal of Consumer Affairs 2022;56(3):1356 View
  18. Trupia D, Mathieu-Fritz A, Duong T. The Sociological Perspective of Users’ Invisible Work: A Qualitative Research Framework for Studying Digital Health Innovations Integration. Journal of Medical Internet Research 2021;23(11):e25159 View
  19. Lei L, Zhu Y, Liu Q, Xiong F. Analysis on Quantified Self‐Behavior of Customers in Food Consumption under the Perspective of Social Networks. Complexity 2021;2021(1) View
  20. Lee J, Lee J. The Relationship Between the Characteristics of Self-Tracking Data and User Experience Factors for Data-Driven Product Service System Design. Archives of Design Research 2021;34(3):193 View
  21. Lee J, Lee J, Jung E. Proposal of a Reflective Relationship Formation Model between Users and Self-Trackers Based on Data Content Characteristics. Archives of Design Research 2023;36(3):129 View

Books/Policy Documents

  1. Gray K, Gilbert C. Advances in Biomedical Informatics. View
  2. Ilhan A, Fietkiewicz K. Perspectives on Wearable Enhanced Learning (WELL). View
  3. Han J, Zhao J. 2023 4th International Conference on E-Commerce and Internet Technology (ECIT 2023). View