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

Big Data Analytics for Elder Care (33) Demographics of Users, Social & Digital Divide (899) Internet Access and Digital Technology Use in an Elderly Population (310) Aging with Chronic Disease (170) Web-based and Mobile Health Interventions (3956) Mobile Health (mhealth) (3410) Mobile Apps for Cancer Care and Cancer Prevention and Screening (258)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44777, first published .
Examining the Impact of Selected Sociodemographic Factors and Cancer-Related Fatalistic Beliefs on Patient Engagement via Health Information Technology Among Older Adults: Cross-Sectional Analysis

Examining the Impact of Selected Sociodemographic Factors and Cancer-Related Fatalistic Beliefs on Patient Engagement via Health Information Technology Among Older Adults: Cross-Sectional Analysis

Examining the Impact of Selected Sociodemographic Factors and Cancer-Related Fatalistic Beliefs on Patient Engagement via Health Information Technology Among Older Adults: Cross-Sectional Analysis

Authors of this article:

Maryum Zaidi1 Author Orcid Image ;   Priscilla Gazarian2 Author Orcid Image ;   Heather Mattie3 Author Orcid Image ;   Lisa Kennedy Sheldon4 Author Orcid Image ;   C Ann Gakumo5 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

  1. Zaidi M, Sarkar S, Arakelyan S, Poghosyan H. Relationship Between Fatalistic Cancer Beliefs and Risky Health Behaviors. Western Journal of Nursing Research 2024;46(10):757 View
  2. Zaidi M, Gazarian P, Sheldon L, Kragen B, Cooley M, Li W, Enah C. Nurse PATHIT: An Adapted Framework for Nurse Support for Patient Activation Through Health Information Technology. Journal of Advanced Nursing 2025;81(8):5080 View
  3. Zhang Y, Rosli Y, Mohd Saat N, Abd Talib R, Tang S. Scoping review of the e-health literature in older adults. DIGITAL HEALTH 2025;11 View

Conference Proceedings

  1. Huang X, Dai Z, Wang K, Luo X. Proceedings of the 2024 9th International Conference on Mathematics and Artificial Intelligence. Machine Learning-Based Prediction of Binge Drinking among Adults in the United State: Analysis of the 2022 Health Information National Trends Survey View
  2. Hao Y, Löeckenhoff C, Lee H, Zwerling J, Kalantari S. Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing. The i-SDM Framework: Developing AI-based Tools in Shared Decision-Making for Cancer Treatment with Clinical Professionals View