Teenage sui­cide is re­ally dif­fi­cult to pre­dict: Ma­chines could fill that gap

The best apps will have pre­dic­tive ma­chine learn­ing al­go­rithms

The East African - - OUTLOOK - By PETER HOLLEY The Washington Post

In any given week, Ben Crotte, a be­havioural health ther­a­pist at Chil­dren’s Home of Cincin­nati in the US, speaks to dozens of stu­dents in need of an out­let. Their chal­lenges run the ado­les­cent gamut, from mi­nor stress about an up­com­ing test to se­vere de­pres­sion, so­cial iso­la­tion and bul­ly­ing.

Amid the flood of con­ver­sa­tions, meet­ings and paperwork, the chal­lenge for Crotte — and men­tal health pro­fes­sion­als ev­ery­where — is sep­a­rat­ing hope­less ex­pres­sions of pain and suf­fer­ing from cru­cial warn­ing signs that sug­gest a stu­dent is at risk for com­mit­ting sui­cide.

It’s a daunt­ing, high-pres­sure task, which ex­plains why Crotte was will­ing to add an­other po­ten­tially use­ful tool to his di­ag­nos­tic kit: An app that uses an al­go­rithm to an­a­lyse speech and de­ter­mine whether some­one is likely to take their own life. Its name: “Spread­ing Ac­ti­va­tion Mo­bile” or “SAM.”

“Los­ing a child is my worst night­mare, and we all live with the fear that we might miss some­thing,” Crotte said, re­fer­ring to men­tal health pro­fes­sion­als who work in ed­u­ca­tion. “Some­times we have to go with our gut to make a de­ci­sion, so this is one more tool to help me make a fi­nal de­ter­mi­na­tion about some­one’s health.”

SAM is be­ing tested in a hand­ful of Cincin­nati schools this year and ar­rives at a time when re­searchers across the coun­try are de­vel­op­ing new forms of ar­ti­fi­cial in­tel­li­gence that may for­ever change the way men­tal health is­sues are di­ag­nosed and treated.

“Tech­nol­ogy is here to stay, and if we can use it to pre­vent sui­cide, we should do that,” said physi­cian Jill Harkavy-fried­man, vice pres­i­dent of re­search at the Amer­i­can Foun­da­tion for Sui­cide Pre­ven­tion.

There are thou­sands of apps ded­i­cated to im­prov­ing men­tal health, but ex­perts say the most promising will be­gin to in­cor­po­rate pre­dic­tive ma­chine learn­ing al­go­rithms into their de­sign. By analysing a pa­tient’s lan­guage, emo­tional state and so­cial me­dia foot­print, th­ese al­go­rithms will be able to as­sem­ble in­creas­ingly ac­cu­rate, pre­dic­tive por­traits of pa­tients us­ing data that is far be­yond the reach of even the most ex­pe­ri­enced clin­i­cians.

“A ma­chine will find 100 other pieces of data that your phone has ac­cess to that you wouldn’t be able to mea­sure as a psy­chi­a­trist or gen­eral prac­ti­tioner,” said Chris Dan­forth, a Univer­sity of Ver­mont re­searcher who helped de­velop an al­go­rithm that can spot signs of de­pres­sion by analysing so­cial me­dia posts.

Us­ing data from more than 5,000 adult pa­tients with a po­ten­tial for self-harm, Colin Walsh, a data sci­en­tist at Van­der­bilt Univer­sity Med­i­cal Cen­tre, also cre­ated ma­chine-learn­ing al­go­rithms that pre­dict the like­li­hood that some­one will at­tempt sui­cide within the next week. The risk de­tec­tion is based on such in­for­ma­tion as the pa­tient’s age, gen­der, med­i­ca­tions and prior di­ag­noses.

Dan­forth’s al­go­rithm — which he de­vel­oped with Har­vard re­searcher An­drew Reece — can spot signs of de­pres­sion by analysing the tone of a pa­tient’s In­sta­gram feed. The pair cre­ated a sec­ond al­go­rithm that pin­points the rise and fall of some­one’s men­tal ill­ness by scan­ning the lan­guage, word count, speech pat­terns and de­gree of ac­tiv­ity on their Twit­ter feed.

“The dom­i­nant con­trib­u­tor to the dif­fer­ence be­tween de­pressed and healthy classes was an in­crease in us­age of neg­a­tive words by the de­pressed class, in­clud­ing ‘don’t,’ ‘no,’ ‘not,’ ‘mur­der,’ ‘death,’ ‘never’ and ‘sad,’” the re­searchers wrote in their lat­est study iden­ti­fy­ing men­tal ill­ness on Twit­ter. “The sec­ond largest con­trib­u­tor was a de­crease in pos­i­tive lan­guage by the de­pressed class, rel­a­tive to the healthy class, in­clud­ing fewer ap­pear­ances of ‘photo,’

Tech­nol­ogy is here to stay, and if we can use it to pre­vent sui­cide, we should do that.” Jill Harkavyfried­man, Amer­i­can Foun­da­tion for Sui­cide Pre­ven­tion

Pic­ture: File

Re­searchers are de­vel­op­ing new forms of ar­ti­fi­cial in­tel­li­gence that may for­ever change the way men­tal health is­sues are di­ag­nosed and treated.

Newspapers in English

Newspapers from Kenya

© PressReader. All rights reserved.