Psychopathology

Psychopathology is a term which refers to either the study of mental illness or mental distress or the manifestation of behaviours and experiences which may be indicative of mental illness or psychological impairment.

The many different professions may be involved in studying mental illness or distress.

Most notably, psychiatrists and clinical psychologists are particularly interested in this area and may either be involved in clinical treatment of mental illness, or research into the origin, development and manifestations of such states, or often, both.

More widely, many different specialties may be involved in the study of psychopathology.

For example, a neuroscientist may focus on brain changes related to mental illness.

Therefore, someone who is referred to as a psychopathologist, may be one of any number of professions who have specialised in studying this area. Psychiatrists in particular are interested in descriptive psychopathology, which has the aim of describing the symptoms and syndromes of mental illness.

This is both for the diagnosis of individual patients (to see whether the patient’s experience fits any pre-existing classification), or for the creation of diagnostic systems (such as the Diagnostic and Statistical Manual of Mental Disorders) which define exactly which signs and symptoms should make up a diagnosis, and how experiences and behaviours should be grouped in particular diagnoses (e.g.

clinical depression, schizophrenia). Psychopathology is not the same as psychopathy, which has to do with antisocial personality disorders and criminality..

For more information about the topic Psychopathology, read the full article at Wikipedia.org, or see the following related articles:

Other Biases that Affect Risk

We have other heuristics and biases about risks. One common one is called “optimism bias”: we tend to believe that we’ll do better than most others engaged in the same activity. This bias is why we think car accidents happen only to other people, and why we can at the same time engage in risky behavior while driving and yet complain about others doing the same thing. It’s why we can ignore network security risks while at the same time reading about other companies that have been breached. It’s why we think we can get by where others failed.

Basically, animals have evolved to underestimate loss. Because those who experience the loss tend not to survive, those of us remaining have an evolved experience that losses don’t happen and that it’s okay to take risks. In fact, some have theorized that people have a “risk thermostat,” and seek an optimal level of risk regardless of outside circumstances.18 By that analysis, if something comes along to reduce risk–seat belt laws, for example–people will compensate by driving more recklessly.

And it’s not just that we don’t think bad things can happen to us, we–all things being equal–believe that good outcomes are more probable than bad outcomes. This bias has been repeatedly illustrated in all sorts of experiments, but I think this one is particularly simple and elegant.19

Subjects were shown cards, one after another, with either a cartoon happy face or a cartoon frowning face. The cards were random, and the subjects simply had to guess which face was on the next card before it was turned over.

For half the subjects, the deck consisted of 70% happy faces and 30% frowning faces. Subjects faced with this deck were very accurate in guessing the face type; they were correct 68% of the time. The other half was tested with a deck consisting of 30% happy faces and 70% frowning faces. These subjects were much less accurate with their guesses, only predicting the face type 58% of the time. Subjects’ preference for happy faces reduced their accuracy.

In a more realistic experiment,20 students at Cook College were asked “Compared to other Cook students–the same sex as you–what do you think are the chances that the following events will happen to you?” They were given a list of 18 positive and 24 negative events, like getting a good job after graduation, developing a drinking problem, and so on. Overall, they considered themselves 15% more likely than others to experience positive events, and 20% less likely than others to experience negative events.

The literature also discusses a “control bias,” where people are more likely to accept risks if they feel they have some control over them. To me, this is simply a manifestation of the optimism bias, and not a separate bias.

Another bias is the “affect heuristic,” which basically says that an automatic affective valuation–I’ve seen it called “the emotional core of an attitude”–is the basis for many judgments and behaviors about it. For example, a study of people’s reactions to 37 different public causes showed a very strong correlation between 1) the importance of the issues, 2) support for political solutions, 3) the size of the donation that subjects were willing to make, and 4) the moral satisfaction associated with those donations.21 The emotional reaction was a good indicator of all of these different decisions.

With regard to security, the affect heuristic says that an overall good feeling toward a situation leads to a lower risk perception, and an overall bad feeling leads to a higher risk perception. This seems to explain why people tend to underestimate risks for actions that also have some ancillary benefit–smoking, skydiving, and such–but also has some weirder effects.

In one experiment,22 subjects were shown either a happy face, a frowning face, or a neutral face, and then a random Chinese ideograph. Subjects tended to prefer ideographs they saw after the happy face, even though the face was flashed for only ten milliseconds and they had no conscious memory of seeing it. That’s the affect heuristic in action.

Another bias is that we are especially tuned to risks involving people. Daniel Gilbert again:23
We are social mammals whose brains are highly specialized for thinking about others. Understanding what others are up to–what they know and want, what they are doing and planning–has been so crucial to the survival of our species that our brains have developed an obsession with all things human. We think about people and their intentions; talk about them; look for and remember them.

In one experiment,24 subjects were presented data about different risks occurring in state parks: risks from people, like purse snatching and vandalism, and natural-world risks, like cars hitting deer on the roads. Then, the subjects were asked which risk warranted more attention from state park officials.

Rationally, the risk that causes the most harm warrants the most attention, but people uniformly rated risks from other people as more serious than risks from deer. Even if the data indicated that the risks from deer were greater than the risks from other people, the people-based risks were judged to be more serious. It wasn’t until the researchers presented the damage from deer as enormously higher than the risks from other people that subjects decided it deserved more attention.

People are also especially attuned to risks involving their children. This also makes evolutionary sense. There are basically two security strategies life forms have for propagating their genes. The first, and simplest, is to produce a lot of offspring and hope that some of them survive. Lobsters, for example, can lay 10,000 to 20,000 eggs at a time. Only ten to twenty of the hatchlings live to be four weeks old, but that’s enough. The other strategy is to produce only a few offspring, and lavish attention on them. That’s what humans do, and it’s what allows our species to take such a long time to reach maturity. (Lobsters, on the other hand, grow up quickly.) But it also means that we are particularly attuned to threats to our children, children in general, and even other small and cute creatures.25

There is a lot of research on people and their risk biases. Psychologist Paul Slovic seems to have made a career studying them.26 But most of the research is anecdotal, and sometimes the results seem to contradict each other. I would be interested in seeing not only studies about particular heuristics and when they come into play, but how people deal with instances of contradictory heuristics. Also, I would be very interested in research into how these heuristics affect behavior in the context of a strong fear reaction: basically, when these heuristics can override the amygdala and when they can’t.

Risk Heuristics

The first, and most common, area that can cause the feeling of security to diverge from the reality of security is the perception of risk. Security is a trade-off, and if we get the severity of the risk wrong, we’re going to get the trade-off wrong. We can do this both ways, of course. We can underestimate some risks, like the risk of automobile accidents. Or we can overestimate some risks, like the risk of a stranger sneaking into our home at night and kidnapping our child. How we get the risk wrong–when we overestimate and when we underestimate–is governed by a few specific brain heuristics.
Prospect Theory

Here’s an experiment that illustrates a particular pair of heuristics.12 Subjects were divided into two groups. One group was given the choice of these two alternatives:
Alternative A: A sure gain of $500.
Alternative B: A 50% chance of gaining $1,000.

The other group was given the choice of:
Alternative C: A sure loss of $500.
Alternative D: A 50% chance of losing $1,000.

These two trade-offs aren’t the same, but they’re very similar. And traditional economics predicts that the difference doesn’t make a difference.

Traditional economics is based on something called “utility theory,” which predicts that people make trade-offs based on a straightforward calculation of relative gains and losses. Alternatives A and B have the same expected utility: +$500. And alternatives C and D have the same expected utility: -$500. Utility theory predicts that people choose alternatives A and C with the same probability and alternatives B and D with the same probability. Basically, some people prefer sure things and others prefer to take chances. The fact that one is gains and the other is losses doesn’t affect the mathematics, and therefore shouldn’t affect the results.

But experimental results contradict this. When faced with a gain, most people (84%) chose Alternative A (the sure gain) of $500 over Alternative B (the risky gain). But when faced with a loss, most people (70%) chose Alternative D (the risky loss) over Alternative C (the sure loss).

The authors of this study explained this difference by developing something called “prospect theory.” Unlike utility theory, prospect theory recognizes that people have subjective values for gains and losses. In fact, humans have evolved a pair of heuristics that they apply in these sorts of trade-offs. The first is that a sure gain is better than a chance at a greater gain. (“A bird in the hand is better than two in the bush.”) And the second is that a sure loss is worse than a chance at a greater loss. Of course, these are not rigid rules–given a choice between a sure $100 and a 50% chance at $1,000,000, only a fool would take the $100–but all things being equal, they do affect how we make trade-offs.

Evolutionarily, presumably it is a better survival strategy to–all other things being equal, of course–accept small gains rather than risking them for larger ones, and risk larger losses rather than accepting smaller losses. Lions chase young or wounded wildebeest because the investment needed to kill them is lower. Mature and healthy prey would probably be more nutritious, but there’s a risk of missing lunch entirely if it gets away. And a small meal will tide the lion over until another day. Getting through today is more important than the possibility of having food tomorrow.

Similarly, it is evolutionarily better to risk a larger loss than to accept a smaller loss. Because animals tend to live on the razor’s edge between starvation and reproduction, any loss of food–whether small or large–can be equally bad. That is, both can result in death. If that’s true, the best option is to risk everything for the chance at no loss at all.

These two heuristics are so powerful that they can lead to logically inconsistent results. Another experiment, the Asian disease problem, illustrates that.13 In this experiment, subjects were asked to imagine a disease outbreak that is expected to kill 600 people, and then to choose between two alternative treatment programs. Then, the subjects were divided into two groups. One group was asked to choose between these two programs for the 600 people:
Program A: “200 people will be saved.”
Program B: “There is a one-third probability that 600 people will be saved, and a two-thirds probability that no people will be saved.”

The second group of subjects were asked to choose between these two programs:
Program C: “400 people will die.”
Program D: “There is a one-third probability that nobody will die, and a two-thirds probability that 600 people will die.”

Like the previous experiment, programs A and B have the same expected utility: 200 people saved and 400 dead, A being a sure thing and B being a risk. Same with Programs C and D. But if you read the two pairs of choices carefully, you’ll notice that–unlike the previous experiment–they are exactly the same. A equals C, and B equals D. All that’s different is that in the first pair they’re presented in terms of a gain (lives saved), while in the second pair they’re presented in terms of a loss (people dying).

Yet most people (72%) choose A over B, and most people (78%) choose D over C. People make very different trade-offs if something is presented as a gain than if something is presented as a loss.

Behavioral economists and psychologists call this a “framing effect”: peoples’ choices are affected by how a trade-off is framed. Frame the choice as a gain, and people will tend to be risk averse. But frame the choice as a loss, and people will tend to be risk seeking.

We’ll see other framing effects later on.

Another way of explaining these results is that people tend to attach a greater value to changes closer to their current state than they do to changes further away from their current state. Go back to the first pair of trade-offs I discussed. In the first one, a gain from $0 to $500 is worth more than a gain from $500 to $1,000, so it doesn’t make sense to risk the first $500 for an even chance at a second $500. Similarly, in the second trade-off, more value is lost from $0 to -$500 than from -$500 to -$1,000, so it makes sense for someone to accept an even chance at losing $1,000 in an attempt to avoid losing $500. Because gains and losses closer to one’s current state are worth more than gains and losses further away, people tend to be risk averse when it comes to gains, but risk seeking when it comes to losses.

Of course, our brains don’t do the math. Instead, we simply use the mental shortcut.

There are other effects of these heuristics as well. People are not only risk averse when it comes to gains and risk seeking when it comes to losses; people also value something more when it is considered as something that can be lost, as opposed to when it is considered as a potential gain. Generally, the difference is a factor of 2 to 2.5.14

This is called the “endowment effect,” and has been directly demonstrated in many experiments. In one,15 half of a group of subjects were given a mug. Then, those who got a mug were asked the price at which they were willing to sell it, and those who didn’t get a mug were asked what price they were willing to offer for one. Utility theory predicts that both prices will be about the same, but in fact, the median selling price was over twice the median offer.

In another experiment,16 subjects were given either a pen or a mug with a college logo, both of roughly equal value. (If you read enough of these studies, you’ll quickly notice two things. One, college students are the most common test subject. And two, any necessary props are most commonly purchased from a college bookstore.) Then the subjects were offered the opportunity to exchange the item they received for the other. If the subjects’ preferences had nothing to do with the item they received, the fraction of subjects keeping a mug should equal the fraction of subjects exchanging a pen for a mug, and the fraction of subjects keeping a pen should equal the fraction of subjects exchanging a mug for a pen. In fact, most people kept the item they received; only 22% of subjects traded.

And, in general, most people will reject an even-chance gamble (50% of winning, and 50% of losing) unless the possible win is at least twice the size of the possible loss.17

What does prospect theory mean for security trade-offs? While I haven’t found any research that explicitly examines if people make security trade-offs in the same way they make economic trade-offs, it seems reasonable to me that they do at least in part. Given that, prospect theory implies two things. First, it means that people are going to trade off more for security that lets them keep something they’ve become accustomed to–a lifestyle, a level of security, some functionality in a product or service–than they were willing to risk to get it in the first place. Second, when considering security gains, people are more likely to accept an incremental gain than a chance at a larger gain; but when considering security losses, they’re more likely to risk a larger loss than accept the certainty of a small one.

Neurosis

In modern psychology, the term neurosis, also known as psychoneurosis or neurotic disorder, is a general term that refers to any mental imbalance that causes distress, but does not interfere with rational thought (i.e., psychosis) or an individual’s ability to function in daily life (i.e., psychosis or a personality disorder)..

Ego psychology

Ego psychology is a school of psychoanalysis that originated in Sigmund Freud’s ego-id-superego model.
After Freud, a number of prominent psychoanalytic theorists began to elaborate on Freud’s functionalist version of the ego.

They put much effort into theorizing the ego’s various functions and how they can be impaired in psychopathology.

Much of their work focused around strengthening the ego so it could better cope with the pressures from the id, super-ego, and society in general. The central functions of the ego were traditionally seen as reality-testing, impulse-control, judgment, affect tolerance, defence, and synthetic functioning.

An important conceptual revision to Freud’s structural theory was made when Heinz Hartmann argued that the healthy ego includes a sphere of autonomous ego functions that are independent of mental conflict.

Memory, motor coordination, and reality-testing, for example, ought to be able to function without the intrusion of emotional conflict.

According to Hartmann, psychoanalytic treatment aims to expand the conflict-free sphere of ego functioning.

By doing so, Hartmann believed, psychoanalysis facilitates adaptation, that is, more effective mutual regulation of ego and environment..