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

Ethics, Privacy, and Legal Issues (457) Innovations and Technology for Physical Activity Education (702) Innovations and Technology for Healthy Eating Education (400) mHealth for Wellness, Behavior Change and Prevention (2743) Ubiquitous Health (uHealth) (116)

Published on in Vol 23, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24236, first published .
Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey

Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey

Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey

Authors of this article:

Holly Clarke1 Author Orcid Image ;   Stephen Clark1, 2 Author Orcid Image ;   Mark Birkin1, 2 Author Orcid Image ;   Heather Iles-Smith3, 4 Author Orcid Image ;   Adam Glaser1, 3, 5 Author Orcid Image ;   Michelle A Morris1, 5 Author Orcid Image
Article Authors Cited by (10) Tweetations (10) Metrics

Journals

  1. Vermeulen E, Grobbelaar S. The structure and information spread capability of the network formed by integrated fitness apps. Information Technology & People 2022;35(8):311 View
  2. Dolan E, Shiells K, Goulding J, Skatova A. Public attitudes towards sharing loyalty card data for academic health research: a qualitative study. BMC Medical Ethics 2022;23(1) View
  3. Cumyn A, Ménard J, Barton A, Dault R, Lévesque F, Ethier J. Patients’ and Members of the Public’s Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review. Journal of Medical Internet Research 2023;25:e45002 View
  4. Saarijärvi H, Sparks L, Närvänen E, Erkkola M, Fogelholm M, Nevalainen J. From transactions to transformations: exploring transformative food retailing. The International Review of Retail, Distribution and Consumer Research 2024;34(1):104 View
  5. Cheng G, You Q, Shi L, Wang Z, Luo J, Li T. A survey of topic models: From a whole-cycle perspective. Journal of Intelligent & Fuzzy Systems 2023;45(6):9929 View
  6. Dolan E, Goulding J, Marshall H, Smith G, Long G, Tata L. Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models. Nature Communications 2023;14(1) View
  7. Møller F, Junker T, Kold Sørensen K, Eves C, Wohlfahrt J, Dillner J, Torp-Pedersen C, Wilkowski B, Chong S, Pers T, Yakimov V, Müller H, Ethelberg S, Melbye M. Assessing household lifestyle exposures from consumer purchases, the My Purchases cohort. Scientific Reports 2023;13(1) View
  8. Liu S, Sloan L, Al Baghal T, Williams M, Jessop C, Serôdio P. Linking survey with Twitter data: examining associations among smartphone usage, privacy concern and Twitter linkage consent. International Journal of Social Research Methodology 2024:1 View
  9. Lund J, Cacciatore J, Tylock R, Su I, Sharma S, Hinton S, Smith S, Nowels M, Chen X, Duberstein P, Hanson L, Mohile S. Development and Evaluation of a Multisource Approach to Extend Mortality Follow-Up for Older Adults With Advanced Cancer Enrolled in Randomized Trials. JCO Clinical Cancer Informatics 2024;(8) View
  10. van Kessel R, Ranganathan S, Anderson M, McMillan B, Mossialos E. Exploring potential drivers of patient engagement with their health data through digital platforms: A scoping review. International Journal of Medical Informatics 2024;189:105513 View