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Predicting Prediabetes Through Facebook Postings: Protocol for a Mixed-Methods Study.

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Area of Science:

  • Infodemiology and digital health surveillance.
  • Behavioral science and public health.

Background:

  • Infodemiology leverages social media to track disease spread.
  • Rising global rates of type 2 diabetes necessitate early detection methods.
  • Social media behavior may indicate prediabetes, enabling timely interventions.

Purpose of the Study:

  • To investigate social media behavior patterns in individuals with prediabetes.
  • To develop a taxonomy of prediabetes indicators from social media data.
  • To identify themes associated with prediabetes diagnosis through Facebook content.

Main Methods:

  • Pilot study involving 20 adults with prediabetes.
  • Retrospective analysis of Facebook posts (3 months pre- to 3 months post-diagnosis).
  • Qualitative and quantitative content analysis of social media data.

Main Results:

  • Data coding and analysis are ongoing.
  • First results are anticipated for publication in 2019.
  • Results will detail participant characteristics and social media post comparisons.

Conclusions:

  • This pilot study initiates the creation of a social media indicator taxonomy for prediabetes.
  • A validated taxonomy can aid researchers and clinicians in identifying at-risk individuals.
  • Early identification via social media can support type 2 diabetes prevention efforts.