Javascript must be enabled to continue!
The Association of eHealth Literacy Skills and mHealth Application Use Among US Adults With Obesity: Analysis of Health Information National Trends Survey Data (Preprint)
View through CrossRef
BACKGROUND
Physical inactivity and a poor diet are modifiable behaviors that contribute to obesity. Obesity is a well-recognized risk factor for chronic diseases, including diabetes. Mobile health (mHealth) apps can play an important adjuvant role in preventing and treating chronic diseases and promoting positive health behavior change among people with obesity, and eHealth literacy skills have the potential to impact mHealth app use.
OBJECTIVE
The purpose of this study was to explore the associations between the 2 dimensions, access and application, of eHealth literacy skills and mHealth app use among US adults (≥18 years of age) with obesity (BMI ≥30 kg/m<sup>2</sup>).
METHODS
Data were obtained from February to June 2020 using the Health Information National Trends Survey 5. A total of 1079 respondents met the inclusion criteria of adults with obesity and owners of smartphones. Individual associations between mHealth app use and sociodemographic variables were explored using weighted chi-square and 2-tailed <i>t</i> tests. A multivariable weighted logistic regression model was fitted, and adjusted odds ratios (ORs) of using mHealth apps with corresponding 95% CIs were reported across multiple sociodemographic variables. An Ising model-weighted network visualization was produced. A receiver operating characteristic curve was calculated, and the area under the curve was reported with the corresponding Delong 95% CI.
RESULTS
A majority of respondents were female (550/923, 59.6%) or non-Hispanic White (543/923, 58.8%). Individuals in households earning less than US $50,000 comprised 41.4% (382/923) of the sample. All sociodemographic variables were found to be univariately significant at the 5% level, except employment and region. Results from the multivariable weighted logistic regression model showed that the adjusted odds of using an mHealth app are 3.13 (95% CI 1.69-5.80) and 2.99 (95% CI 1.67-5.37) times higher among those with an access eHealth literacy skill of using an electronic device to look for health or medical information for themselves and an application eHealth literacy skill of using electronic communications with a doctor or doctor’s office, respectively. Several sociodemographic variables were found to be significant, such as education, where adjusted ORs comparing subgroups to the lowest educational attainment were substantial (ORs ≥7.77). The network visualization demonstrated that all eHealth literacy skills and the mHealth app use variable were positively associated to varying degrees.
CONCLUSIONS
This work provides an initial understanding of mHealth app use and eHealth literacy skills among people with obesity, identifying people with obesity subpopulations who are at risk of a digital health divide. Future studies should identify equitable solutions for people with obesity (as well as other groups) and their use of mHealth apps.
JMIR Publications Inc.
Title: The Association of eHealth Literacy Skills and mHealth Application Use Among US Adults With Obesity: Analysis of Health Information National Trends Survey Data (Preprint)
Description:
BACKGROUND
Physical inactivity and a poor diet are modifiable behaviors that contribute to obesity.
Obesity is a well-recognized risk factor for chronic diseases, including diabetes.
Mobile health (mHealth) apps can play an important adjuvant role in preventing and treating chronic diseases and promoting positive health behavior change among people with obesity, and eHealth literacy skills have the potential to impact mHealth app use.
OBJECTIVE
The purpose of this study was to explore the associations between the 2 dimensions, access and application, of eHealth literacy skills and mHealth app use among US adults (≥18 years of age) with obesity (BMI ≥30 kg/m<sup>2</sup>).
METHODS
Data were obtained from February to June 2020 using the Health Information National Trends Survey 5.
A total of 1079 respondents met the inclusion criteria of adults with obesity and owners of smartphones.
Individual associations between mHealth app use and sociodemographic variables were explored using weighted chi-square and 2-tailed <i>t</i> tests.
A multivariable weighted logistic regression model was fitted, and adjusted odds ratios (ORs) of using mHealth apps with corresponding 95% CIs were reported across multiple sociodemographic variables.
An Ising model-weighted network visualization was produced.
A receiver operating characteristic curve was calculated, and the area under the curve was reported with the corresponding Delong 95% CI.
RESULTS
A majority of respondents were female (550/923, 59.
6%) or non-Hispanic White (543/923, 58.
8%).
Individuals in households earning less than US $50,000 comprised 41.
4% (382/923) of the sample.
All sociodemographic variables were found to be univariately significant at the 5% level, except employment and region.
Results from the multivariable weighted logistic regression model showed that the adjusted odds of using an mHealth app are 3.
13 (95% CI 1.
69-5.
80) and 2.
99 (95% CI 1.
67-5.
37) times higher among those with an access eHealth literacy skill of using an electronic device to look for health or medical information for themselves and an application eHealth literacy skill of using electronic communications with a doctor or doctor’s office, respectively.
Several sociodemographic variables were found to be significant, such as education, where adjusted ORs comparing subgroups to the lowest educational attainment were substantial (ORs ≥7.
77).
The network visualization demonstrated that all eHealth literacy skills and the mHealth app use variable were positively associated to varying degrees.
CONCLUSIONS
This work provides an initial understanding of mHealth app use and eHealth literacy skills among people with obesity, identifying people with obesity subpopulations who are at risk of a digital health divide.
Future studies should identify equitable solutions for people with obesity (as well as other groups) and their use of mHealth apps.
Related Results
Problem-Based mHealth Literacy Scale (PB-mHLS): Development and Validation
Problem-Based mHealth Literacy Scale (PB-mHLS): Development and Validation
Background
Mobile devices have greatly facilitated the use of digital health resources, particularly during the COVID-19 pandemic. Mobile health (mHealth) has b...
Social Media and eHealth Literacy Among Older Adults: Systematic Literature Review (Preprint)
Social Media and eHealth Literacy Among Older Adults: Systematic Literature Review (Preprint)
BACKGROUND
The advent of social media has significantly transformed health communication and the health-related actions of older adults, offering both obsta...
Health Maintenance Organization–mHealth Versus Face-to-Face Interaction for Health Care in Israel: Cross-Sectional Web-Based Survey Study (Preprint)
Health Maintenance Organization–mHealth Versus Face-to-Face Interaction for Health Care in Israel: Cross-Sectional Web-Based Survey Study (Preprint)
BACKGROUND
Health maintenance organization–mobile health (HMO-mHealth) services have a direct impact on patients’ daily lives, and HMOs regularly expand the...
Health Maintenance Organization–mHealth Versus Face-to-Face Interaction for Health Care in Israel: Cross-Sectional Web-Based Survey Study
Health Maintenance Organization–mHealth Versus Face-to-Face Interaction for Health Care in Israel: Cross-Sectional Web-Based Survey Study
Background
Health maintenance organization–mobile health (HMO-mHealth) services have a direct impact on patients’ daily lives, and HMOs regularly expand their r...
Readiness and Acceptance of eHealth Services for Diabetes Care in the General Population: Cross-sectional Study (Preprint)
Readiness and Acceptance of eHealth Services for Diabetes Care in the General Population: Cross-sectional Study (Preprint)
BACKGROUND
Diabetes management is a growing health care challenge worldwide. eHealth can revolutionize diabetes care, the success of which depends on end us...
Readiness and Acceptance of eHealth Services for Diabetes Care in the General Population: Cross-sectional Study
Readiness and Acceptance of eHealth Services for Diabetes Care in the General Population: Cross-sectional Study
Background
Diabetes management is a growing health care challenge worldwide. eHealth can revolutionize diabetes care, the success of which depends on end user a...
Ehealth Communication
Ehealth Communication
Ehealth, also known as E-health, is a relatively new area of health communication inquiry that examines the development, implementation, and application of a broad range of evolvin...
A Gig mHealth Economy Framework: Scoping Review of Internet Publications
A Gig mHealth Economy Framework: Scoping Review of Internet Publications
BackgroundThe gig economy (characterized by short-term contracts rather than being a full-time employee in an organization) is one of the most recent and important tendencies that ...

