The /r/science discussion series is a series of posts by the moderators of /r/science to explain commonly confused and misunderstood topics in science. This particular post was written by myself and /u/fsmpastafarian. Please feel free to ask questions below.
A cornerstone of scientific study is the ability to accurately define and measure that which we study. Some quintessential examples of this are measuring bacterial colonies in petri dishes, or the growth of plants in centimeters. However, when dealing with humans, this concept of measurement poses several unique challenges. An excellent illustration of this is human emotion. If you tell me that your feeling of sadness is a 7/10, how do I know that it’s the same as my 7/10? How do we know that my feeling of sadness is even the same as your feeling of sadness? Does it matter? Are you going to be honest when you say that your sadness is a 7? Perhaps you’re worried about how I’ll see you. Maybe you don’t realize how sad you are right now. So if we can’t put sadness in a petri dish, how can we say anything scientifically meaningful about what it means to be sad?
Subjective experience is worthy of study
To start, it’s worth pointing out that overcoming this innate messiness is a worthwhile endeavor. If we put sadness in the “too hard” basket, we can’t diagnose, study, understand, or treat depression. Moreover, if we ignore subjective experience, we lose the ability to talk about most of what it means to be human. Yet we know that, on average, people who experience sadness describe it in similar ways. They become sad as a response to similar things and the feeling tends to go away over time. So while we may never find a “sadness neurochemical” or “sadness part of the brain”, the empirically consistent structure of sadness is still measurable. In psychology we call this sort of measure a construct. A construct simply means anything you have to measure indirectly. You can’t count happiness in a petri dish so any measure of it will have a level of abstraction and is therefore termed a construct. Of course, constructs aren’t exclusive to psychology. You can’t put a taxonomy of a species in a petri dish, physically measuring a black hole can be tricky, and the concept of illness is entirely a construct.
How do we study constructs?
To start, the key to any good construct is an operationalized definition. For the rest of this piece we will use depression as our example. Clinically, we operationalize depression as a series of symptoms and experiences, including depressed mood, lack of interest in previously enjoyed activities, change in appetite, physically moving slower (“psychomotor slowing”), and thoughts of suicide and death. Importantly, and true to the idea of a consistent construct, this list wasn’t developed on a whim. Empirical evidence has shown that this particular group of symptoms shows a relatively consistent structure in terms of prognosis and treatment.
As you can see from this list, there are several different methods we could use to measure depression. Self-report of symptoms like mood and changes in appetite are one method. Third party observations (e.g., from family or other loved ones) of symptoms like psychomotor slowing are another method. We can also measure behaviors, such as time spent in bed, frequency of crying spells, frequency of psychiatric hospital admissions, or suicide attempts. Each of these measurements are different ways of tapping into the core of the construct of depression.
Creating objective measures
Another key element of studying constructs is creating objective measures. Depression itself may be reliant in part on subjective criteria, but for us to study it empirically we need objective definitions. Using the criteria above, there have been several attempts to create questionnaires to objectively define who is and isn’t depressed.
In creating an objective measure, there are a few things to look for. The first is construct validity. That is, does the measure actually test what it says it’s testing? There’s no use having a depression questionnaire that is asking about eating disorders. The second criteria we use to find a good measure is convergent validity. Convergent validity means that the measure relates to other measures that we know are related. For example, we would expect a depression scale to positively correlate with an anxiety scale and negatively correlate with a subjective well-being scale. Finally, a good measure has a high level of test-retest reliability. That is, if you’re depressed and take a depression questionnaire one day, your score should be similar (barring large life changes) a week later.
That all still sounds really messy
Unfortunately, humans just are messy. It would be really convenient if there were some objective and easy way to measure depression but an imperfect measure is better than no measure. This is why you tend to get smaller effect sizes (the strength of a relationship or difference between two or more measured things) and more error (the statistical sense of the word - unmeasured variance) in studies that involve humans. Importantly, that’s true for virtually anything you study in humans including all sorts of things we see as more reliable like medicine or neuroscience (see Meyer et al., 2001).
Putting it all together (aka the tl;dr)
What becomes clear from our depression example is just how complex developing and using constructs can be. However, this complexity doesn’t make the concept less worthy of study, nor less scientific. It can be messy but all sciences have their built in messiness, this is just psychology’s. While constructs such as depression may not be as objective as bacterial growth in a petri dish or the height or a plant, we use a range of techniques to ensure that they are as objective as possible but no study, measure, technique or theory in any field of science is ever perfect. But the process of science isn’t about perfection, it’s about defining and measuring as objectively as possible to allow us to better understand important aspects of the world, including the subjective experience of humans.
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