Men and Cheating

The identification of suicide risk factors in teenagers

The identification of suicide risk factors in teenagers is a difficult process. As a result, recent years have seen an upsurge in teen suicide rates. “Teenage suicide is incredibly difficult to foresee,” according to the article. That is why some experts are turning to machines for assistance. They believe that there is a need for machines to monitor suicide inclinations among kids in order to avert fatalities.

“Spreading Activation Mobile” (SAM)

“Spreading Activation Mobile” (SAM), according to Holley, is the technical frontier that will allow for the speedy and effective identification and treatment of mental health concerns. The challenge that is experienced in instituting intervention in the case of suicides among the teenagers demands the employ of artificial intelligence (Holley). Such intelligence facilitates productive interpretation of human behavior to prevent suicide and other mental health conditions. SAM assembles an accurate portrait of the patients through the employ of data that is often overlooked by the most experienced physicians.

Technological interventions for mental ailments

Some of the technological interventions that have been instituted to further the treatment of mental ailments include Danforth’s algorithms, which can identify depression through the assessment of the feed on one’s Instagram page (Holley). The machine learning algorithms created by Colin Walsh infer, with a 90 percent accuracy, the likelihood of suicide within the limits of the next seven days (Holley). Still, the success of these machines and technologies will depend on their ability to infer correct data and thus the need for the incorporation of SAM. Currently, the systems are still underdeveloped and cannot be used to fully predict the manifestations of mental challenges.

Lack of longitudinal research and the future of SAM technology

Conclusively, the article contends that there is a gaping lack of longitudinal research which would facilitate the development of algorithms that encourage the correct inference of risk-behavior and the successful mitigation of suicide cases. The development of the SAM technology was predicated on the need to alleviate suffering through the employ of technology. Still, its full development could be five to 10 years away.

Work Cited

Holley, Peter. “Teenage Suicide is extremely difficult to predict. That’s why some experts are turning to machines for help”. The Washington Post, Sept. 2017. https://www.washingtonpost.com/news/innovations/wp/2017/09/25/teenage-suicide-is-extremely-difficult-to-predict-thats-why-some-experts-are-turning-to-machines-for-help/?utm_term=.62b69febc6b9. Accessed Oct. 14, 2017.