Exploring direct and indirect predictors of heart disease information seeking

Hovick, Shelly R.; Rhodes, Nancy; Bigsby, Elisabeth; Thomas, Samuel S.; Freiberger, N.

doi:10.1080/17538068.2022.2076549

Cited by 1 publication

(1 citation statement)

References 62 publications

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“…With access to the internet, individuals routinely seek and find information about diseases, prevention, diagnoses, treatments, and how they affect their quality of life [22][23][24]. The internet has also allowed a two-way communication channel between providers and patients.…”

Section: Introductionmentioning

confidence: 99%

Variations in Pattern of Social Media Engagement between Individuals with Chronic Conditions and Mental Health Conditions

Ayangunna,

Shah,

Kalu

et al. 2024

Informatics

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The use of the internet and supported apps is at historically unprecedented levels for the exchange of health information. The increasing use of the internet and social media platforms can affect patients’ health behavior. This study aims to assess the variations in patterns of social media engagement between individuals diagnosed with either chronic diseases or mental health conditions. Data from four iterations of the Health Information National Trends Survey Cycle 4 from 2017 to 2020 were used for this study with a sample size (N) = 16,092. To analyze the association between the independent variables, reflecting the presence of chronic conditions or mental health conditions, and various levels of social media engagement, descriptive statistics and logistic regression were conducted. Respondents who had at least one chronic condition were more likely to join an internet-based support group (Adjusted Odds Ratio or AOR = 1.5; Confidence Interval, CI = 1.11–1.93) and watch a health-related video on YouTube (AOR = 1.2; CI = 1.01–1.36); respondents with a mental condition were less likely to visit and share health information on social media, join an internet-based support group, and watch a health-related video on YouTube. Race, age, and educational level also influence the choice to watch a health-related video on YouTube. Understanding the pattern of engagement with health-related content on social media and how their online behavior differs based on the patient’s medical conditions can lead to the development of more effective and tailored public health interventions that leverage social media platforms.

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Section: Introductionmentioning

confidence: 99%