Why bother with professional help when you can get diagnosed via Facebook?

 Greetings from CarpeLearning!

While perusing the overabundance of articles, information, assumptions, and ‘stuff’ out ‘there’ this morning, I ran across an article of curiosity.  It’s a doozy.  It got me thinking.  So here I am.

Statistics are amazing things.  They can be complied to make you believe almost anything, anytime, any viewpoint.  Quite a feat, actually.  Sort of like when your Doctor told you the shot would hurt him more than it would hurt you.  We all know how that turned out.  But because he, a respected Dr., said it we sort of hoped – right?  Yeah.

This brings me to the point of this post.  Facebook and its recent stats assumptions. Positive Facebook Updates Get More Likes, Negative Get More Comments [INFOGRAPHIC] After half-heartedly clicking on the link (as I heard the ever-Doctorly internal comment of “Duh” resonating through my head) I was appalled at what I read.  While the infographic (and text) state clearly what the stats show with regard to age, gender, content, etc. the qualifiable assumptions made from that quantifiable data is stupefying.  It appears as if Facebook has suddenly gone into the practice of Psychoanalysis and, overnight, became a certified and licensed Psychologist!  I didn’t even know they were in Graduate school!

Based on the assumptions they made with their stats it blatantly leads to a diagnosis of Depression.  Wow!  That seems to be a huge leap from having a grumpy set of friends, posts about family, and random stuff.  Sure, those may be boring but boring hardly qualifies one for a therapeutic diagnosis.  Yet there it is.  “This Help for Depression infographic illustrates how we use Facebook to share our feelings. Its data is based on a study of 83 13-year-old girls’ communications habits, including Facebook, among other things.”

A couple of things come to mind with the above quote.

1) Help for Depression:  Who said anyone was depressed?  Boring FB posters (and yes, there are many) are automatically depressed.  They’re just boring.  It’s the difference between not inviting them to your party and having them involuntarily committed.

2) How we use Facebook to share our feelings: See comment 3.

3) Based on a study of 83 13-year-old girls’ communication habits, including Facebook, among other things: Where to start?  83 is a small number to base a study on.  13-year-old girls?  Have you been around 13-year-old girls?  Have you been one?  Sharing their feelings is what they do, constantly.  They are all over the place and it’s not pretty.  Basing a study on a 13-year-old girls’ emotional communication and transfer those results/assumptions over to the general population is ridiculous (not to mention potentially dangerous for those who may think they’re depressed because “if Facebook says it it must be true and I have no health insurance so I can’t see a real Dr. to figure it out and get help”).   I find it irresponsible.

4) The infographic:  It’s a nice one, I’ll give them that.  I like it for what it is.  What I don’t like is I do not see the correlation of what they say it says and what it says.  I do not see the direct connection between the likes and negative comments as a direct indication, or even a hint at, DEPRESSION.  It appears to me that the big D word is a scare tactic – get attention, make people nervous, make people worried, etc.  I don’t subscribe to those tactics.  They are childish.  Speak plainly – don’t hype – and make your point.  That’s my wiring.

So, after all of this, why am I blogging about it on the CarpeLearning blog?  Very simple.  Dr. Bobby and I deal with data: learning data; teaching data; software data; emotional data; you name it.  We have built this company on data, based on quantifiable & qualifiable data-based experience.  We both have seen bad studies that seem to carry a weight of their own.  We both have seen the damage done to the teaching/learning environment when this data is pushed forward as ‘Truth” and “Best Practices” and “Standards” – all because somebody, somewhere, saw some  numbers, made assumptions and ran with  it as truth. With no questions asked. This is not good.  For anybody.

When presented with data from our own research, or that of others, we have made it a point to sit still. We reflect.  We discuss.  We recreate the study if possible.  We validate.  We do not make gross assumptions based on a few numbers of a few people of a questionable population.  That gets no one anywhere.  We are careful.  We are precise.  We are diligent.  We are as concerned about how we use our data for your benefit as you are about your data being used for your benefit.  We get it.

Be mindful of how you read statistics.  Ask yourself the content, motive, economic chain, and benefits of all parties involved when reviewing studies (or conducting your own).  Those questions will allow you to get a clearer view of what you’re being told is “The Truth” and let you see through someone else’s agenda of reality.

Dr. Heidi L. Maston



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