Disparities in Ownership of Smart Devices and Health Apps and Correlates of Health App Ownership: Findings from the Health Information National Trends Survey (HINTS)

Theoretical Background and research questions/hypothesis:  The availability of and demand for smart devices (e.g., tablets) and mobile health technology applications (“health apps”) have increased, and research demonstrating the efficacy of health apps to track and promote health behaviors continues to thrive. However, questions regarding the overall population reach and adoption of these tools remain. The aims of this study were to (a) identify demographic disparities in smart device and health app ownership and (b) examine correlates of health app ownership. 

Methods:  Using data from the National Cancer Institute’s 2014 Health Information National Trends Survey (HINTS 4, Cycle 4; N=3677), smart device (tablet/smartphone) and health app ownership were assessed. In one set of analyses, bivariate associations between smart device ownership (yes/no) and demographics were examined. Demographic variables associated with smart device ownership (p<0.10) were entered into a multivariable binary logistic regression model to explore these associations while controlling for other significant demographic variables. In a second set of analyses, bivariate associations were examined between health app ownership (yes/no) and demographics, beliefs about chronic disease prevention (e.g., smoking cessation), lifestyle behaviors (e.g., fruit/vegetable intake), and health-related factors (e.g., comorbidities, health insurance status). Variables associated with health app ownership (p<0.10) were entered into a multivariable binary logistic regression model to assess these associations while controlling for other significant variables. All analyses were conducted in SAS 9.4. To provide nationally-representative estimates, analyses were weighted using jackknife replicate weights.

Results:  Overall 2392 respondents (76%) reported having a smart device. Among smart device owners, 819 (36%) reported having a health app.  In the model examining smart device ownership, individuals with an income of <$20,000 had lower odds of having a smart device than individuals with an income of ≥$50,000 (aOR: 0.14, 95% CI: 0.08, 0.23); this finding was similar for all lower-income groups. Similarly, individuals with a high school education or less had lower odds of having a smart device (aOR: 0.60, 95% CI: 0.41, 0.87) than college graduates. In the model examining health app ownership among people with smart devices, individuals with a high school education or less (aOR: 0.40, 95% CI: 0.0.27, 0.61) and those without health insurance (aOR: 0.49, 95% CI: 0.27, 0.89) had lower odds of having a health app than college graduates and the insured, respectively. Obese individuals had higher odds of having a health app (aOR: 1.74, 95% CI: 1.21, 2.50) than non-obese individuals. 

Conclusions:  Findings suggest a demographic digital divide in smart device ownership. Additionally, some groups of socioeconomically disadvantaged owners rarely possess health apps even if they own a smart device.

Implications for research and/or practice:  Evidence-based health apps have potential to facilitate the collection of health-related information from and improve the health of populations at risk for poor health outcomes such as obese individuals and socioeconomically disadvantaged groups. Opportunities exist to enhance the benefit of health apps in these populations. Collaborations among public health professionals, app developers, and health communication scientists can increase the reach and adoption of health communication technology to enhance public health and advance health equity.