Home|Journals|Articles by Year Follow on Twitter

Directory for Medical Articles

Open Access

Original Research

The use of self-monitoring modalities to promote health behavior among adults: A cross-sectional survey

Caress Alithia Dean,Kahee Mohammed,Brittany Ventline,Jacob Moosekian,Diana Zhang,Keith Elder.

Background: U.S. adults experience challenges in performing and sustaining healthy behaviors to improve their cardiovascular health. Self-monitoring modalities may facilitate these lifestyle changes. Therefore, the objective of this cross-sectional study was to examine the use of self-monitoring modalities and the association between the use of multiple self-monitoring modalities and participants’ population characteristics and health behaviors and status. Methods: Data was drawn for the Health Information National Trends Survey 5, Cycle 1. The study included 3,285 U.S. adults, 18 years or older. Descriptive statistics examined the use of the different types of self-monitoring modalities. Binary and ordered logistic regression analyses examined the relationship between types of self-monitoring modalities and participants’ population characteristics and health behaviors and status. Tableau Software was used to illustrate study results. Results: The average age of participants was 54.3 years. Smartphone/tablet users were more likely to have completed college (45.28%) compared to electronic monitoring device (EMD) users (41.06%) and online medical record users (34.04%). Among smartphone/tablet users, participants had significantly higher odds of consuming more > 4 cups of fruits/vegetables than < 4 cups of fruits/vegetables (OR=2.27, 95 CI=1.32-3.90). An increase in the number of self-monitoring modalities used was associated with a higher odds of participants consuming >4 cups of fruits/vegetables compared to participants who consumed 150 minutes/week. Further research is warranted to understand how to utilize population characteristics and health behavior and status to promote the efficacy of self-monitoring.

Key words: ehealth,self-monitoring modalities, electronic self-monitoring devices, cardiovascular disease, cardiovascular health, digital health, cardiovascular health promotion, electronic self-monitoring

Similar Articles

Using the Health Belief Model to examine travelers' willingness to vaccinate and support for vaccination requirements prior to travel.
Suess C, Maddock J, Dogru T, Mody M, Lee S
Tourism management. 2022; 88(): 104405

Exploring the Alzheimer's disease neuroepigenome: recent advances and future trends.
Zhang H, Elefant F
Neural regeneration research. 2022; 17(2): 325-327

Growth differentiation factor 5: a neurotrophic factor with neuroprotective potential in Parkinson's disease.
Goulding SR, Anantha J, Collins LM, Sullivan AM, O'Keeffe GW
Neural regeneration research. 2022; 17(1): 38-44

Environmental stocks, CEO health risk and COVID-19.
Fernández-Méndez C, Pathan S
Research in international business and finance. 2022; 59(): 101509

Differentiating Human Pluripotent Stem Cells to Vascular Endothelial Cells for Regenerative Medicine, Tissue Engineering, and Disease Modeling.
Bertucci T, Kakarla S, Kim D, Dai G
Methods in molecular biology (Clifton, N.J.). 2022; 2375(): 1-12

Full-text options

Latest Statistics about COVID-19
• pubstat.org

Add your Article(s) to Indexes
• citeindex.org

Covid-19 Trends and Statistics
Follow ScopeMed on Twitter
Author Tools
eJPort Journal Hosting
About BiblioMed
License Information
Terms & Conditions
Privacy Policy
Contact Us

The articles in Bibliomed are open access articles licensed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
ScopeMed is a Database Service for Scientific Publications. Copyright © ScopeMed® Information Services.

ScopeMed Web Sites