The impact of teenage years is intensely confusing, which is sometimes linked to having suicidal tendencies. Recently, it was found out that researchers are in the process of developing an app; which aims to prevent suicides by flagging those most at risk. With the use of computer algorithm, it is found to record conversations, which is then expected to analyze what people say and how they speak.
The App And Its Features
As experts have revealed its features, Daily Mail reports that by picking up on a range of subtle verbal and non-verbal cues, the app is said to have the ability of potentially classifying if someone is suicidal with 93 percent accuracy. It was found that at the heart of the app is a machine learning algorithm which classifies the person based on their responses.
On the other hand, Cincinatti has further revealed that suicide still remains to be the third leading cause of death of kids age 10 to 14, and is second among people aged 15 to 34 years old. Furthermore, records show that in every 14 minutes, someone commits suicide.
Study lead author Dr. John Pestian, a researcher from the Cincinnati Children's Hospital Medical Center, has claimed that these computational approaches are known to provide novel opportunities to apply technological innovations in suicide care and prevention, and it surely is needed. Pestian was found to have spent nearly a decade immersed in the language of suicide in an effort to try and keep kids alive.
The app was called Spreading Activation Mobile, or SAM, which can be used to record a counseling session. It was found that the app has the ability of comparing the language being used as well as other non-verbal cues such as sighing, laughing or pauses in order to classify who is at a greater risk of suicide. However, Dr. Pestian has highly emphasized that the app has no ability of stopping a person from committing suicide; rather, the technology can only say "We have an issue over here." Thus, the experts still believes that early intervention still plays a crucial part in order to get a path to get to care.
