A close friend of mine once suddenly committed suicide. He had been receiving treatment for depression. For about 2 years, he’d shown good progress to both his doctor and his therapist. But in his suicide note, he wrote that the depression never left. Given the extreme step that he ended up taking, I believed the note. Especially since I knew that there was nothing that could’ve explained such an extreme step, one fine day, just out of the blue (I was with him ALL THE TIME). 

I can’t say that I blame the doctor for missing the “signs” because I really don’t think there were any. On the internet, I found a similar case. That of Linkin Park lead singer, Chester Bennington. His family issued a press release that he seemed excited, encouraged and happy just hours before his suicide. They concluded that depression had no face or mood. 

This was definitely true for my friend, and it’s also true for many other people. It means that there are some serious inadequacies in existing mental health diagnostics. To be clear, I’m not trashing the existing science. I just think that there is a dire need to keep improving on it. There has to be something more that people can do about unforeseen mental health outcomes than listen to How to save a life by The Fray. 

The following methods can be used to establish new findings and tools in the field of mental health: 

Behavior experiments

For example, say you wanted to know the average case for the time a person takes to learn happy birthday on the piano. Then you could pick a random bunch of people and then ask them to learn. Then you could average their times. Experimenting on people’s behaviors is a good way to figure out reliable tools, instruments and measurements.

Brain imaging 

This is currently done on three types of subjects: 1) A normal person doing a task 2) A differently abled person doing a task 3) A dead person (post-mortem). Basically, you look at images of the brain as the task is being performed to learn more about the changes and how they can be measured. 


The person being tested gives their own measurements for the tasks on the test. For example, on depression questionnaires, the person is asked to score the quality of their sleep on a scale of “Excellent-Very poor.” Self-reports, in my view, are not always reliable. I am a former mental health patient and I always lied about my own scores. I also know a lot of other people that did the same. But I can’t say that there aren’t also those who were honest with their self-reports. 

Case studies and naturalistic observation

With case studies, you focus on a particular case. For example, I focused on my own case and then compared with others to determine certain universal truths about my own mental health conditions. They can be useful, if you are good at abstracting high level ideas from the specifics of the case. For example, in my case, I noticed that I hardly ever knew what I was doing as I tried to overcome a certain problem. From that, I got the high level idea that the level of mindfulness as opposed to mindlessness goes a long way towards determining how in-control you feel regarding your own effort. 

Naturalistic observations are conducted in everyday situations. You just sit back and observe. We have all done this at some point or another, and drawn conclusions about “people” in general. The trick, as far as accuracy and reliability are concerned, is that you observe a large number of diverse people before you make a general conclusion. For instance, if you made a conclusion by only observing a college crowd, then that’s a biased conclusion – not accurate or reliable. Similarly, if you did so by only observing 2 or 3 people, then that’s a biased conclusion as well. In the end, like I said, the trick is to observe at least 30 people (preferably even more) and be sure that they are not all from the same kind of crowd. 

Computer Simulations and Artificial Intelligence

This is, perhaps, the best way to do it, if you really know how. Computers allow us to manipulate variables in a way that field experiments never could. They also allow us to obtain mathematical precision when we model the equation that connects the variables and the outcome. Since data is basically everywhere these days, it’s not hard to pool everything into one source and then feed the computer program with it and allow it to play. Artificial intelligence is basically teaching computers to think and make conclusions. You can imagine how that’s both easier and more consistent than a human being doing it. 

Let’s conclude

We started by outlining a case where current mental health findings and tools failed. Thus, we brought out the urgency of continued innovation in field of mental health. We have elaborated on a few techniques to do this too. So, now is as good a time as any to get cracking! If you have any stories or insights to share, we’d love to hear them in the comments!