A Markov Chain Model for Mental Health Interventions

Details

• Personal Author:
  Albano T ; Claudio D ; Ibe E ; Miller N ; Moyce S ; O'Leary M
• Description:
  Poor mental health affects nearly one billion people worldwide and can end in suicide if not treated. Unfortunately, stigma and a lack of mental healthcare providers are barriers to receiving needed care. We developed a Markov chain model to determine whether decreasing stigma or increasing available resources improves mental health outcomes. We mapped potential steps in the mental health care continuum with two discrete outcomes: getting better or committing suicide. Using a Markov chain model, we calculated probabilities of each outcome based on projected increases in seeking help or availability of professional resources. Modeling for a 12% increase in awareness of mental health concerns yielded a 0.39% reduction in suicide. A 12% increase in access to professional help yielded a 0.47% reduction in suicide rate. Our results show that expanding access to professional services has a higher impact on reducing suicide rates than creating awareness. Any intervention towards awareness or access positively impacts reducing suicide rates. However, increased access results in a higher reduction in suicide rates. We have made progress in increasing awareness. Awareness campaigns help to increase recognition of mental health needs. However, focusing efforts on increasing access to care may have a higher impact on reducing suicide rates. [Description provided by NIOSH]
• Subjects:
  Mental Health Nervous System Occupational Health Safety Suicide
• Keywords:
  Absorbing Chains Author Keywords: Markov Chains Health Care Intervention Effectiveness Mental Health Models Statistical Analysis
• ISSN:
  1660-4601
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Massachusetts ; Montana ; OSHA Region 1 ; OSHA Region 8
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  20
• Issue:
  4
• NIOSHTIC Number:
  nn:20067039
• Citation:
  Int J Environ Res Public Health 2023 Feb; 20(4):3525
• Contact Point Address:
  David Claudio, Department of Mechanical and Industrial Engineering, University of Massachusetts Lowell, Lowell, MA 01854
• Email:
  david_claudio@uml.edu
• Federal Fiscal Year:
  2023
• Performing Organization:
  University of Massachusetts - Lowell
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  International Journal of Environmental Research and Public Health
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:77d88db7eac37427d8bed04d6e28835da008cabeaac7f435c0c98843d9162d492b32e3e06422998afa0fe2d56c76f96df87870b65582e9936a7e87b165fb7505
• Download URL:
  https://stacks.cdc.gov/view/cdc/231259/cdc_231259_DS1.pdf
• File Type:
  [PDF - 2.73 MB ]