It's important to note that this is a preliminary finding, based on weak evidence, and that "creativity" is not necessarily the core concept of "openness" in the OCEAN five-factor model of human personality. The "big five" personality model is still developing,
and "openness" is the most poorly defined of the five personality factors in the model. It is plain, on stronger and better replicated evidence, that the factor "neuroticism" is a risk factor for many bad outcomes, including shorter lifespan. Some investigators have proposed specific interventions to reduce neuroticism in the general population.
The relationship of "openness" to creativity is still debatable, and still more debatable is the relationship of openness (or creativity) to mortality.
I should also note that the study described in the article kindly submitted here doesn't allow for the causal inference, or verify the proposed mechanism, made in the quoted statements in the article.
That word "Predicts" is dangerous. It strongly suggests causation, though it only reflects a statistical correlation.
Many external causes are known to negatively effect both creativity and life-span. Most chronic illnesses reduce both. Alcoholism reduces both. Genetic disorders such as Down's syndrome or Huntington's reduce both.
Given many known mechanisms for external factors causing both factors in a correlation study, and only speculative mechanisms for how one factor causes the other, even hinting at causation is bad journalism.
> That word "Predicts" is dangerous. It strongly suggests causation, though it only reflects a statistical correlation.
REALLY? What do you WANT them to say? Accuracy of a prediction implies some sort of causal relationship, but not a direct one by any means. All of the thing you suggest are causal links. A genetic disorder causing a decrease in both lifespan and creativity is causation. "A predicts B" does NOT AT ALL imply "A causes B" - tinsel, wreaths, and increased toy buying predict Christmas.
If you're not convinced that the reporters are trying to suggest causation with the word "predicts", try swapping the two terms. Would they write a headline, "Longer life predicts creativity"?
If the statistics show that creative people are correlated with longer life, but that longer life is only correlated with creativity if factors X, Y, Z are also present (but not necessarily just X, Y, Z without creativity), then it would be correct to say "creativity predicts longer life" but not "longer life predicts creativity"; while not implying any causation.
Also it could be that some long living people are creative and all creative people are long living; while creative still not being a cause of the longer life. (let's say all creative people eat peanut butter sandwiches, and it was infact the peanut butter that caused a longer life.)
"The weatherman predicts the weather". Are you saying in this sentence, causation is implicitly referenced?
It doesn't work the other way because of temporal constraints, not causality. A person's creativity happens before their longevity is determined. Similarly, you wouldn't write "election predicts poll results."
That said, if I was looking at records of the deceased and first discovered a person's age at time of death, then I could use the correlation to predict that I am likely to further find that they were creative.
>> That word "Predicts" is dangerous. It strongly suggests causation, though it only reflects a statistical correlation.
> REALLY?
Yes -- really. It is very misleading.
> What do you WANT them to say?
Replace "predicts" with "is correlated with." That's the meaning of the work being described -- a correlation between A and B has been observed. But this doesn't mean that A predicts B, or A causes B, or even that B causes A. Both may result from some unevaluated cause C.
Science is not description, it is explanation. The linked article describes, and then draws a conclusion that goes far beyond the description. But it never presumes to explain why the author's conclusion might be so.
> "A predicts B" does NOT AT ALL imply "A causes B"
It certainly does. Rain predicts puddles. Puddles do not predict rain, they follow from it.
"A predicts B" means "A precedes B, and knowing A will substantially improve your guess about B." Obviously, puddles do not predict rain - they happen after. As someone else said, though, the weather man predicts rain, but rain doesn't follow from the weatherman's statements - the causal relationship there is substantially indirect; measurements of various phenomena are fed into models, themselves developed from past observation, which causes various information to be printed on a screen which causes the weatherman to say certain things that, yes, correlate strongly but not perfectly with the weather tomorrow. This is not hugely different, in terms of information flow, than us predicting a lower longevity for Steve based on observation of his lesser creativity, both caused perhaps by the same gene (leading to the correlation we are exploiting to make the prediction).
You're missing the crucial distinction between describing and explaining. A correlation is a description, and descriptions aren't science. Only by proposing an explanation, then testing it, do we enter the domain of science. We also have the chance to turn a correlation into something more than a coincidence.
"The article is simply reporting a correlation, which is not good science" is a separate objection from "predicts implies causation, and none exists here." The latter was what I was objecting to; specifically the first part.
If you want to separately discuss the former, I don't have a strong opinion about it any which way. We do need to document correlations somewhere, because 1) they are a useful starting point when looking for causal relationships, and 2) we might be able to make use of them before we understand why they work. We do need some quality controls to ensure that we are finding correlations that really exist, and I don't see a problem with using the infrastructure around "properly" scientific experiment to this end, but if you propose we move it somewhere else or simply call it something else I don't see any big problems with that.
In statistics, which this is, a "prediction" is an outcome that the statistics suggests would happen. The "cause" isn't involved. A predicts B, means that having factor A means factor B is likely present also. And that is that. There is no suggestion of causation.
This is a science magazine, the reporter would have read a lot of papers over his career, and because "A predicts B" is such a common use to denote correlation in statistics, I wouldn't blame him/her.
False! Creativity is correlated with a longer life.
> A large body of research links neuroticism with poorer health and conscientiousness with superior health. [Emphasis added.]
There's that word again -- "links". Neuroticism is not linked with poorer health, it is correlated with poorer health.
And so forth -- frankly, the linked article is a piece of pseudoscientific trash.
Psychologists would be so much happier if there simply wasn't any science at all, rather than the kind they practice -- the kind that avoids control groups, experimental discipline, can't seem to express correlations accurately, and draw nonsense conclusions like this:
"...the results suggest that practicing creative-thinking techniques could improve anyone's health by lowering stress and exercising the brain."
Without a control group, without a disciplined, prospective, double-blind, replicated study, the "results" suggest no such thing. Isn't obvious that creative thinking may be an effect, not a cause, of good physical and mental health?
Reading articles like this, I begin to suspect that in school, psychologists are told, "say the word 'science' a lot -- that's how you do science."
Predict is something you can do if something is "correlated"!
Having creativity is highly correlated with a longer life, therefore, creativity can be used as a factor to predict whether a person has longer life.
It doesn't mean that if you get more creative you live longer, just that if you look at the existing population, the more creative people are likely to live longer also.
See?
Search for this phrase in this paper "We show how simple image statistics can be used to predict the presence and absence of objects in the scene before exploring the image."
> Predict is something you can do if something is "correlated"!
This is false. I saw a puddle, so I predict that the puddle will cause rain. See the problem? You can't "predict" until you have a cause-effect relationship.
A quote: "The opposite belief, correlation proves causation, is a logical fallacy by which two events that occur together are claimed to have a cause-and-effect relationship. The fallacy is also known as cum hoc ergo propter hoc (Latin for "with this, therefore because of this") and false cause. It is a common fallacy in which it is assumed that, because two things or events occur together, one must be the cause of the other."
> You can see how "predict" is a word for an action you can take if something is correlated.
You may be able to do that. Scientists require evidence.
Evidence of a correlation is all that's necessary to do that, scientist or not. What a correlation tells me is that if I observe A, I am likely to observe B. In the case of rain and puddles, there is a temporal component that seems to be confusing you. Rain now is correlated with puddles for a while in the future. Puddles now may not be correlated with rain now or in the future[1]. Observing puddles now, I can't tell you anything about rain in the future because there is no correlation, not because there is no causation.
[1] If the weather in the area tends to be the same day to day, then I can absolutely predict rain tomorrow based on puddles today, to occasionally be frustrated by weather change or sprinklers.
Please respond to the point of my post, if you are going to respond. "I'm not confused, you are" adds nothing to the discussion - obviously, we both think that. And yes, confusing correlation with causation is a common logical error - one that, I believe, you have become oversensitive to such that you are spotting it where it doesn't exist. This, I thought, was already established before your post here.
You broke your own example by inserting the word "cause" into the sentence. Of course your example is a cause-effect relationship.
Statistical evidence suggesting correlation of two factors A and B are enough for one to say "The presence of A predicts B" as well as "The presence of B predicts A".
Please, don't warp the meaning of the word "predict".
"I predict tomorrow is going to rain" There is no way that sentence suggests a cause-effect relationship.
"This specific color pattern in the image is a great predictor of the presence of rain when the photograph was taken" Neither does this sentence suggests a cause-effect relationship.
No one here is confused between correlation and causation. I'm simply insisting the word "predict" has to do with correlation, not causation.
Yes -- evidence of a correlation, not a cause-effect relationship.
> Of course your example is a cause-effect relationship.
Puddles and rain? Yes, but it is only a description, not an explanation. Science requires explanations. Otherwise we open the door to pseudoscience, to people claiming any associations they care to claim.
> Please, don't warp the meaning of the word "predict".
It is you who is doing that -- look at the definitions at the bottom of this post.
Here's another example. I have a cure for the common cold -- I shake a dried gourd over the patient's head until he get better. Sometimes it takes a week, but my treatment always works. The correlation is perfect, therefore I deserve a Nobel Prize for ridding the world of this scourge.
My dried gourd treatment "predicts" that the cold sufferer will get better -- always.
> I'm simply insisting the word "predict" has to do with correlation, not causation.
And you are mistaken. Rain is a predictor for bumper crops, but bumper crops are not a predictor for rain. Teenage driving is a predictor for car crashes, but car crashes are not a predictor for teenage driving.
A recent bogus study found a correlation between marijuana use and lower IQ. But the marijuana use did not predict the IQ drop, it was only correlated with it, and the researchers included this fact in their article. Needless to say, the science journalists ignored the qualifiers in the article and announced that marijuana use predicted a fall in IQ:
Here's another account of the same study that makes a claim in its title that the article body contradicts. Title: "Smoking Pot In Teen Years Lowers IQ Later". A quote from the article: "But those who consistently smoke marijuana may simply make less intellectually stimulating choices at critical points in life."
Here is another bogus study: "Low I.Q. Predicts Heart Disease":
Except for the fact that it's only a correlation, and use of the term "predicts" is nonsense. Needless to say, the article doesn't consider that the low IQ might predict the heart disease, not the reverse.
> I'm simply insisting the word "predict" has to do with correlation, not causation.
You can't try to refute only some of my points and not others.
I meant to say your example of course implied a cause-effect relationship, since you added the word 'cause' to it. (of course it wasn't a cause-effect relationship, do you think I am stupid?)
>> My dried gourd treatment "predicts" that the cold sufferer will get better -- always.
If your treatment is indeed correlated with a cold sufferer getting better, significantly enough, then yes, your treatment does in fact predicts it, even though it might not have been the cure. This is consistent with the definition of prediction being only related to correlation.
>> Rain is a predictor for bumper crops, but bumper crops are not a predictor for rain. Teenage driving is a predictor for car crashes, but car crashes are not a predictor for teenage driving.
That is correct; since bumper crops were only aided by rain if factors X1, Y1 are true, bumper crops are not a predictor of past rain unless X1, Y1 is true. Car crashes are correlated with teenage driving if factors X2, Y2 are true, car crashes are not a predictor of teenage driving unless X2, Y2 is true.
X1, Y1 = (Crops are water dependent, crops were not also thoroughly irrigated by other means)
X2, Y2 = (Teenager was intoxicated, teenager riding in car with more than 3 other members, all male)
>> But the marijuana use did not predict the IQ drop, it was only correlated with it, and the researchers included this fact in their article.
Yes it did, correlation means you can use the statistics to predict it, even if it wasn't the cause.
Predict means correlation, and correlation means what you think correlation means. You have the meaning of predict wrong. It has as much to do with causation as correlation has. i.e not much (though some nonetheless, since if there is a causation it is likely to be correlated).
"In statistics, prediction is a part of statistical inference. One particular approach to such inference is known as predictive inference, but the prediction can be undertaken within any of the several approaches to statistical inference. Indeed, one description of statistics is that it provides a means of transferring knowledge about a sample of a population to the whole population, and to other related populations, which is not the same as prediction over time."
If you are talking about prediction and correlation in the same sentence, you are in the realm statistics and therefore should abide by its use of language.
You also did not address my two examples of use of predict in laymen sentences showing the word "predict" did not have anything to do with causation.
>> "to declare or tell in advance; prophesy; foretell: to predict the weather; to predict the fall of a civilization."
>> "to declare or indicate in advance; especially : foretell on the basis of observation, experience, or scientific reason"
Neither of those definitions have any semblance of implying causation. Observation, experience, or scientific reason can all be instances of correlation.
Maybe we shouldn't be so scared about dying and instead try to make the most out of our (supposedely short) lives. After all, a guy like Alexander the Great was only in his early 30s when he had already conquered half of the known-world (yes, this is a Euro-centrist view)
http://www.ocf.berkeley.edu/~johnlab/2008chapter.pdf
and "openness" is the most poorly defined of the five personality factors in the model. It is plain, on stronger and better replicated evidence, that the factor "neuroticism" is a risk factor for many bad outcomes, including shorter lifespan. Some investigators have proposed specific interventions to reduce neuroticism in the general population.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2792076/
The relationship of "openness" to creativity is still debatable, and still more debatable is the relationship of openness (or creativity) to mortality.
I should also note that the study described in the article kindly submitted here doesn't allow for the causal inference, or verify the proposed mechanism, made in the quoted statements in the article.