A Markov Chain Model for Mental Health Interventions
- PMID: 36834220
- PMCID: PMC9961139
- DOI: 10.3390/ijerph20043525
A Markov Chain Model for Mental Health Interventions
Abstract
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.
Keywords: Markov chains; absorbing chains; mental health.
Conflict of interest statement
The authors declare no conflict of interest.
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References
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- World Health Organization, United for Global Mental Health, and the World Federation for Mental Health World Mental Health Day: An Opportunity to Kick-Start a Massive Scale-Up in Investment in Mental Health. 2020. [(accessed on 27 January 2022)]. Available online: https://www.who.int/news/item/27-08-2020-world-mental-health-day-an-oppo....
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