Researchers are using modern technologies to develop advanced tools to assist with the assessment of mental health problems. We hear a lot about “big data” and genetic sequencing, which can be expensive and complex, but there are also promising tools that are not so pricey or complex, even if they do employ components of big data and genetics.
Two examples caught my eye this week:
- A speech analysis program that predicted with 100 percent accuracy who would develop psychosis
- A blood test and app combo that predicts suicide risk with 90 percent accuracy
The speech analysis program was tested on 34 subjects, so we’ll have to see if the results hold up. But the idea makes sense. Well trained clinicians can already assess disjointed speech patterns and reach similar conclusions. But the computer seems to do an even better job, and more importantly, could ultimately make such techniques feasible for a much broader population who don’t have ready access to psychiatric services. And all while lowering the cost of assessment dramatically.
I’ve always thought it was quite primitive and even bizarre for clinicians to assess suicide risk by asking patients if they were thinking of killing themselves. So I’m pleased that a new tool combines a series of questions about energy level, feelings and accomplishments and uncertainty with a blood biomarker test. Again, this approach could ultimately be simpler and cheaper to administer, and more consistent than existing methods.
We won’t be replacing physicians any time soon, but these new approaches are emblematic of what we can expect as developers make better use of available data, analytics approaches, and distribution methods. I’m most excited about increased diagnostic accuracy, earlier availability of information, more widespread availabilty, and lower cost.
Image courtesy of Ambro at FreeDigitalPhotos.net