Psychophysiological Models to Identify and Monitor Elderly with a Cardiovascular Condition: The Added Value of

Victor Kallen1,2, Jan Willem Marck1,3, Jacqueline Stam1,2

  • 1The Netherlands Organization for applied Sciences (TNO), Anna van Buerenplein 1, 2595 DA The Hague, The Netherlands.

Insights

Psychosocial factors like depression significantly improve cardiovascular health assessments in older adults. Combining these with physiological data offers more accurate and efficient health supervision for the elderly.

Area of Science:

  • Gerontology
  • Cardiology
  • Psychology

Background:

  • The aging population requires advanced health monitoring solutions.
  • Cardiovascular health is influenced by both physiological and psychosocial factors.

Purpose of the Study:

  • To assess the role of psychosocial factors in distinguishing elderly individuals with and without cardiovascular conditions.
  • To evaluate if psychosocial data enhances the accuracy of cardiovascular health assessments.

Main Methods:

  • Compared 15 elderly patients with cardiovascular diagnoses to 15 healthy peers.
  • Conducted six bi-weekly lab assessments including autonomic tests, a 6-minute step test, and psychological questionnaires.
  • Utilized statistical models to analyze physiological and psychosocial data.

Main Results:

  • Psychosocial factors, particularly depressive symptoms, effectively predicted cardiovascular markers.
  • A prognostic model including depressive symptoms, negative life events, and social isolation showed high accuracy.
  • This combined model slightly outperformed a physiological-only model in identifying cardiovascular conditions.

Conclusions:

  • Integrating psychosocial parameters into cardiovascular assessments for the elderly can enhance efficiency and feasibility in ambulant settings.
  • This approach maintains or improves prognostic accuracy without compromising patient comfort or technological requirements.

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