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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jun 2, 2021
Date Accepted: Mar 21, 2022

The final, peer-reviewed published version of this preprint can be found here:

Social Networking Service, Patient-Generated Health Data, and Population Health Informatics: National Cross-sectional Study of Patterns and Implications of Leveraging Digital Technologies to Support Mental Health and Well-being

Ye J, Wang Z, Hai J

Social Networking Service, Patient-Generated Health Data, and Population Health Informatics: National Cross-sectional Study of Patterns and Implications of Leveraging Digital Technologies to Support Mental Health and Well-being

J Med Internet Res 2022;24(4):e30898

DOI: 10.2196/30898

PMID: 35486428

PMCID: 9107051

Social networking service, patient-generated health data, and population health informatics: patterns and implications for using digital technologies to support mental health

  • Jiancheng Ye; 
  • Zidan Wang; 
  • Jiarui Hai

ABSTRACT

Background:

Mental health issues, such as depression and anxiety disorder, are severe psychiatric diseases with high prevalence and elevated risks for recurrence and chronicity. Globally, more than 260 million people of all ages have suffered from mental illnesses, which is a leading cause of disability worldwide and is a major contributor to the overall global burden of disease. Studies have demonstrated that mental health issue is a strong indicator of poor general health, unhealthy alcohol use, and sleep problems.Poor sleep quality has been linked to an increased endorsement of drinking motives, especially for young adults.It is critical for these patients to receive health care and social services capable of providing treatment and social support.

Objective:

To describe and compare characteristics of the population with and without mental health issues (depression or anxiety disorder), including physical health, sleep, and alcohol use. We also examined the patterns of social networking service use, patient-generated health data on the digital platforms, and health information sharing attitudes and activities.

Methods:

We drew data from the National Cancer Institute's 2019 Health Information National Trends Survey (HINTS). Participants were divided into two groups by mental health status. Then, we described and compared the characteristics of social determinants of health, health status, sleeping and drinking behaviors, and patterns of social networking service use and health information data sharing between the two groups. Multivariable logistic regression models were applied to assess the predictors of mental health. All analyses were weighted to provide nationally representative estimates.

Results:

Participants with mental health issues are significantly more likely to be younger, White, female, have a lower income, have a history of chronic diseases, less capable of taking care of their own health; regarding behavioral health, they sleep less than six hours on average, have worse sleep quality, consume more alcohol; meanwhile, they are more likely to visit and share health information on social networking sites, write online diary blogs, participate online forum or support groups, watch health-related videos.

Conclusions:

This study illustrates that individuals with mental health issues have inequitable social determinants of health, poor physical health, and behavioral health. However, they are more likely to use social network platforms and services, share their health information, and have active engagements with patient-generated health data (PGHD). Leveraging these digital technologies and services could be beneficial to develop tailored and effective strategies for self-monitoring and self-management, thus supporting mental health.


 Citation

Please cite as:

Ye J, Wang Z, Hai J

Social Networking Service, Patient-Generated Health Data, and Population Health Informatics: National Cross-sectional Study of Patterns and Implications of Leveraging Digital Technologies to Support Mental Health and Well-being

J Med Internet Res 2022;24(4):e30898

DOI: 10.2196/30898

PMID: 35486428

PMCID: 9107051

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