Accepted for/Published in: JMIR Cancer
Date Submitted: Sep 5, 2020
Date Accepted: Nov 5, 2020
Date Submitted to PubMed: Nov 6, 2020
eHealth Practices for Health-Promoting Behaviors and Patient-Clinician Communication: a Latent Class Analysis among Cancer Survivors with Overweight and Obesity
ABSTRACT
Background:
Electronic health (eHealth) technologies have been found to facilitate health-promoting practices among cancer survivors with overweight or obesity. However, little is known about the characteristics of cancer survivors who demonstrate engagement with eHealth to promote weight management and facilitate patient-clinician communication.
Objective:
The objective was to determine whether eHealth use was associated with sociodemographic characteristics, as well as medical history and experiences (i.e., patient-related factors) among cancer survivors with overweight or obesity.
Methods:
Data from cancer survivors with overweight and obesity were analyzed from a nationally representative cross-sectional survey (National Cancer Institute’s Health Information National Trends Survey). Latent class analysis was used to derive distinct classes among cancer survivors based on sociodemographic and medical attributes and medical experiences. Logistic regression was used to examine whether class membership was associated with different eHealth practices.
Results:
Three distinct classes of cancer survivors with overweight or obesity emerged: younger-no comorbidities, younger-comorbidities, and older-comorbidities. Compared to the other classes, the younger-comorbidities class had the highest probability of identifying as female (73%) and Hispanic (46%) and feeling that clinicians did not address their concerns (75%). The older-comorbidities class was 6.5 times more likely than the younger-comorbidities class to share eHealth data with a clinician (OR=6.53; 95% CI: 1.08-39.43). In contrast, cancer survivors in the younger-no comorbidities class were more likely than those in the older-comorbidities class to use a computer to look for health information (OR=1.93; 95% CI: 1.10-3.38); use an electronic device to track progress toward a health-related goal (OR=2.02; 95% CI: 1.08-3.79); and use the Internet to watch health-related YouTube videos (OR=2.70; 95% CI: 1.52-4.81).
Conclusions:
Class membership was associated with different patterns of eHealth engagement, indicating the importance of tailored digital strategies for delivering effective deliver care. Future eHealth weight loss interventions should investigate strategies to engage younger cancer survivors with co-morbidities and address racial/ethnic disparities in eHealth use.
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