As you are walking through a university commons area, I approach you, clipboard in hand, maybe wearing a blue polo shirt, definitely smiling. “Excuse me, would you be willing to participate in a short marketing study. We need help rating pictures of people that we’ll use in a later study.” I’ve got really white teeth and it’s a good day, so you agree.

I give you the clipboard with the survey. The cover sheet has some questions about demographics, then you turn the page and see the picture. You are randomly assigned to see one of three images: a lamp (Control), a fit young woman (Positive), a fat young women (Negative). The women look like this.

You then rate the picture on a variety of dimensions. That’s it; I told you it was short! Now, please go over to that other researcher, yes, the one in the blue polo shirt with the big white smile. That smiley guy thanks you and holds out a bowl of candy as a little appreciation for your participation. You take as many wrapped candies as you please and move on.

Mavens, this is so easy. You’re testing the priming effect of those images, Fit or Fat, on candy taking. When people see the Fat image, they take fewer candies because they don’t want to look like that! Easy-peesey. Let’s get technical and read what the researchers found.

Results revealed only a significant effect of prime (F(2, 53) p 3.88, p = .03). In support of our prediction, planned contrasts revealed that those who saw the image of an overweight person took significantly more candies (M = 2.2) than those in the healthy weight (M = 1.4; F(1, 53) = 7.03, p = .02) or in the neutral control condition (M = 1.5; F(1, 53) = 4.77, p = .04). There was no difference between those in the healthy weight and neutral conditions (F(1, 53) p < .25, NS).

Great Cazart! Read that again. People took MORE candy when they saw the FAT image?!? That can’t be right. Or if it is we’ve got another one of those puny Observational Fairy Tale effect sizes. Do the math. Take that F(1, 53) = 7.03, derive the square root of 7.03 which converts that F to a t, then get the formula and convert it to a Windowpane and find . . . jeepers, a Medium effect, 35/65.

Huh. Fat images prime more candy taking. And obviously, practically so. Campbell and Mohr provide an extensive, Full Cycle, five study package to demonstrate why this is true and how difficult it can be to change Other Guys, especially with common sense. I will not detail each study (and the several pretest projects) Campbell and Mohr report and will leave that as a useful and highly recommended activity for any and every maven out there. This is excellent research. But to our immediate purpose.

Campbell and Mohr combine the theoretical and the practical in this research working with stereotype activation and healthy eating. They explore how information about the Bad Behavior can have the perverse effect of increasing rather than decreasing the Bad Behavior. We’ve seen recurring examples of this failure among the Lifestyle Drum and Bugle Corps with their rancid warning labels that elicit Reactance rather than Compliance. And, like virtually all human action, our behavior is complex and the result of many factors. Campbell and Mohr’s work adds stereotype activation to the list. Let me quote them on their key conceptual discovery.

Increased accessibility of the countervailing health goal and increased accessibility of the link between the behavior and membership in the stereotyped group both limit the effect of stereotype activation on stereotype-conducive behavior.

De-geeked, this means that prosocial persuasion perversely does two things: 1) it activates a goal for the Bad Behavior and 2) it activates a feeling of membership in the Bad Behavior group. Thus, if you see a picture of a Fat person, you prime the goal of Getting Food and also activate a link between your Self and belonging to the Fat Group.

While Campbell and Mohr may not agree with this, I interpret the outcomes as entirely consistent ELM and Low WATT processing. The results from their Experiment 4 run this basic finding through what I would consider High WATT versus Low WATT conditions. Under Low WATT that basic stereotype activation occurs and people take more candy following the Fat image; under High WATT conditions, there’s no difference.

People are simply not High WATT Objective processors of all the relevant information about their weight, their health, and their normal behaviors. They are floating through the mess of life when, as in Experiment 1, somebody with a bright white smile glides up beside with a clipboard and a request to help out very quickly. Sure, they are thinking enough to accurately complete the survey and examine the picture, but they avoid all that cognitive work in the Long Conversation in the Head over calories and exercise and ideal weight and on and on. In that Low WATT state, Cues like stereotypes, group membership, and priming effortlessly guide thinking and, if the Local provides it, easy, almost automatic, action. Here, look at this picture; want a candy?

Like virtually all public persuasion, most prosocial persuasion hits Other Guys in a wide variety of Locals. Thus, the same message about health may elicit Reactance in these Guys while producing this boomerang Stereotype in those Guys. Often times mavens think the problem is competition from other sources. Hey, the Food Police struggle against Big Food and Big Marketing with their Big Bucks, but if you know what’s going on you realize the larger problem is the Other Guys themselves. They are so variable in their WATTage and the Local changes so rapidly between and across Other Guys that finding one message or type of message that makes a practical difference is just damn difficult.

Some people think that Tailoring is the way to go, but even this kind of specificity misses the mark. Usually Tailoring aligns the persuasive content with demographic or psychological characteristics of the Other Guys. What’s missing is the persuasion tailoring where you match the message to the WATTage and the Local the Other Guys variably confront. That’s the essence of a Persuasion Engine. Sure, you can swap out pictures in a message that match the skin color, age, sex, gender orientation, and on and on, but those qualities are considerably less important and powerful than understanding the Other Guys’ WATTage and whether their Local predisposes them to Stereotype Activation, Reactance, or something else. A Persuasion Engine approach aims to match message and Other Guys on the basis of persuasion principles.

Well, now I’m babbling just a bit. Let’s get out of here.

Campbell and Mohr shine a light on the Low WATT problem of Stereotype priming wherein you make things worse with your prosocial effort. They also display a great illustration of that Full Cycle research that takes a concept and runs it through the research wringer, testing a basic X-Y relationship and demonstrating its mediators and moderators. This is yet another example of persuasion science.

Persuadin’ ain’t easy, mavens. And Campbell and Mohr explain why.

Margaret C. Campbell and Gina S. Mohr (2011). Seeing Is Eating: How and When Activation of a Negative Stereotype Increases Stereotype-Conducive Behavior. Journal of Consumer Research , Vol. 38, No. 3 (October), pp. 431-444

DOI: 10.1086/659754

Please consider these two graphs. First, for men.

Now, women.

More Life, to quote Roy Batty, is the Big TACT from the Lifestyle Drum and Bugle Corps and their parades for biking and broccoli, lifting and low fatting, grunting and chewing. I’d prefer a graph with standard deviations, but the semi-interquartile range is a pretty handy measure of variability as long as you remember that SD cuts would be farther out than the 25th or 75th percentiles are. Effect size considerations from the SIQ range are bigger than the Windowpane.

Nevertheless, you see patterns. Men punch out sooner than women at all ages. Women show greater variability. And, sigh, the downward trend for both men and women.

Now, realize visually how piddling most of those diet and exercise admonitions are against all this variability within the smaller and tighter semi inter-quartile ranges. Most admonitions deliver less than Small Windowpanes, just a couple of years at best and even that is questionable given the Tooth Fairy design of the studies with convenience samples and self report measurement of how many ounces of red meat you eat in a week or how many drinks of alcohol you had today or how many METs you cooked off running, lifting, or stretching. Everyone is stretching here, including the Tooth Fairies.

Longevity is not the Strategic Persuasion here, folks. In fact, longevity is probably the worst scientific Argument you might offer to Other Guys about their lifestyle. And you can tell that Other Guys are no longer listening. Consider a torrid example torn from today’s headlines.

Paula Deen is diabetic!

And while the Corps would have you believe that her Southern high fat comfort food kills like cigarettes, no credible scientific source will publicly declare Deen’s cooking caused Deen’s diabetes. And with good reason. Go to PubMed and look up: meta-analysis, Type II diabetes, and risk factors. Chase down the Methods and Results sections and you’ll find those Big Parade, But Small Effect Sizes for diet no matter how you frame the question. Proving Deen’s diet caused her ailment is like trying to determine whether Anthony Bourdain is high on liquor or marijuana in Amsterdam just by looking at him.

How about a counter-example.

Remember Jim Fixx? He is credited as a godfather of running for health in the 1970s. Back when running was definitely not the Cool Table, Fixx literally wrote the book on all the physical and psychological benefits of running. Then at 52 while on his regular run on the road, he dropped dead of a heart attack.

So. No one recommends running, right?

Whether expressed as colorful graphs or two over the top media examples, the Falling Apples on longevity shout, Variation! The Observational Tooth Fairies would have you believe that they can read the self reports and discern death from an extra serving of alcohol or red meat or fried chicken when clinicians looking at patients cannot accurately predict death. No one knows.

While the researchers were finally able to single out 16 indexes that hold promise in helping doctors predict how long a patient might live, there was “insufficient evidence at this time” to recommend any of them for widespread clinical use. None of the indexes had been tried with groups of individuals other than the initial test group to confirm reliability, and every single one had a potential source of bias. Some studies were never able to follow up on the final outcomes of a substantial subset of patients; others used researchers intimately involved with the development of the prognostic tool, and not impartial observers, to validate findings.

The variability in life and death precludes accurate prediction beyond the folk tale take that men die sooner than women and older pass sooner than younger.

You Cannot Persuade A Falling Apple.

This perspective from a clinical physician nicely illustrates the tension between learning from science and learning from direct experience.

When I entered medical school in 1997, I joined a generation of doctors that was supposed to practice evidence-based medicine. First in small groups, and later during clinical rotations, we learned to interpret the medical literature and apply the conclusions of randomized, controlled trials to our clinical decision making. Working within this new paradigm, we were going to rise above the apprentice-based training of our forbears and make decisions on the basis of gold-standard, Level I evidence.

The scientific clinician. Huzzah!

But real life has intruded on the carefully catalogued odds ratios that I memorized as an intern. I’ve come to appreciate that the influence of a randomized, controlled trial — no matter how well conducted or generalizable — pales in comparison with that of the audible bleeding of a profound postpartum hemorrhage. As I tell residents and fellows, in the human mind, adverse anecdote — what I’ve come to call Level IV evidence — is more convincing than even the tightest of confidence intervals.

You always trust your own experience more than data. Persuasion counts on that.

Randomized, controlled trials may be the gold standard, but their results can take decades to make their way from the pages of peer-reviewed medical journals to actual effects on routine care. Adverse anecdote can transform a clinician’s practice patterns in an instant.

The well told story, the compelling anecdote, the flashbulb memory – whatever you want to call that powerful single experience – is perhaps the strongest persuasion play of all. If you can design a Box that provokes an intense memorable, sensory, and affective response, you can create a Change that it is extremely difficult to change.

The easiest example for me to offer explodes out of Dissonance. Make people think they freely chose a path that leads to self relevant, but aversive, consequences and that collision will produce some of the largest and most enduring change you can find in the persuasion and influence literature.

Now, let’s pivot off this personal anecdote to the larger context: Changing medical practice. John Ioannidis, with his colleagues, continues his one-man crusade to get physicians to act more scientifically. We’ve consider Ioannidis’s work before with his investigations of Scientific Science and he now shifts his view to how physicians and medical science resist, of all things, science. Ioannidis asks medical science to consider how much practice is unproven, yet persistent. He considers how often medical science tests the commonplace.

Rarely, some investigators find the courage to test established “truths” with large, rigorous randomized trials. When this happens, empirical evidence suggests that “medical reversals” may be quite common. In an evaluation of 35 trials that were published in a major clinical journal in 2009 and that tested an established clinical practice, 16 (46%) reported results consistent with current beneficial practice, 16 (46%) reported evidence that contradicted current practice and constituted a reversal, and another 3 (9%) were inconclusive.

Please re-read the last sentence in that quote. In those 35 scientific tests of established practices, nearly half disconfirmed the practice, finding instead evidence of harm or no effect. One might scientifically challenge this evidence, noting it’s not a systematic review and focuses only upon research published in 2009. But, if you’re sharp enough to raise those concerns, how do you understand a field that calls itself scientific, yet can find at least 16 standard practices that are worthless? Maybe these are the only 16 rituals and by dumb luck they were all tested and published in the same year.

Or maybe you can see the persuasive power of personal experience as revealed in the opening example of this post. See this tension, too, in the recent and on-going uproar over the value of various medical tests as with prostate cancer. You’ll recall that a US Taskforce decided against routine screening for prostate cancer, citing a considerable number of gold standard RCTs as contrary evidence. Then, the unsurprising chorus of disagreement from physicians who found their experience more compelling than the scientific review of that Taskforce.

You see the primary clash between persuasion and science, between human nature and falling apples in these examples. People who aspire to science constantly find themselves trapped by their human nature as especially illuminated through persuasion science. They have a field committed to science that conducts standard practices that are worthless at best and sometimes harmful at worst. When confronted with large, careful, and public disconfirmations of those practices – as with the prostate screening example – they find narrow exceptions, errors, and inaccuracies and drive through the truck of their personal experience.

You can feel a wind of warning here. Where do you fail to follow your science and instead persist with what you know best and trust most, your experience? But, more importantly, understand how your knowledge of persuasion science aids your development as a scientist. The science of persuasion describes and explains why science resists itself.

Human nature always forgets falling apples until the fruit falls upon it.

My experience as the persuasion guy on health and safety projects quickly taught me to understand as well as I could the basic science behind any intervention I served.  Part of that drive to knowledge was due to my unfortunate temperament that compels a ceaseless need to think about everything.  The bigger part, however, came from getting burned by zealots parading as scientists who fooled me into thinking they had a Big TACT when all they had was either a Big Heart or a Big Ego.  When you work in health and safety, you need to know the difference because you can waste limited resources feeding a fool rather than Changing the World.  Consider this great example of plain old science.

A team of researchers took a sample of 99 zebra finches born from randomly paired adult birds in a captive population at a research facility.  These 99 birds were then tracked from hatchlings to the natural end of their lives.  Along the way this team studied the impact of diet and reproduction in one experiment, then kept the birds in safe cages until all naturally died.  They waited 9 years.  Throughout the study period, the researchers regularly took blood samples from each bird and measured the length of telomeres.  I suspect you know as much about telomeres as I do, so you’ll appreciate an expert quotation rather than Sayings from Chairman Steve.

Telomeres are highly conserved, noncoding, repetitive sequences of DNA that, together with a number of shelterin proteins, form caps at the ends of eukaryotic chromosomes, enabling chromosome ends to be distinguished from double-stranded breaks (3). In the absence of restoration, telomeres shorten during each round of normal somatic cell division because RNA polymerase cannot completely replicate the lagging strand (3, 4). The loss of DNA from the telomeric cap protects the coding sequences from attrition and also limits cell replicative potential; once telomeres reach a critically shortened length, cells stop dividing and enter a state of replicative senescence (3, 5).

Telomeres are DNA contents that play a role in aging.  As cells replicate normally across the lifespan, telomeres get shorter until they lose their protective function and the cells stop working.  That’s basically why after a certain age you can’t touch your toes, eat or drink like you did, or remember where you put your keys.  The telomeres run out which starts a cascade of change leading to cell death.  The interesting question here is just how important telomeres are to the lifespan.  The zebra finch study provides insight.

There was a highly significant relationship between early life telomere length and longevity: individuals that had longer telomeres at 25 d had a significantly longer lifespan (F1, 86.11 = 16.75, P < 0.001, Fig. 3).

You can translate the F = 16.75 into an effect size and you get a Large Windowpane of nearly 20/80.  Birds born with longer telomere sequences through 25 days lived a lot longer than birds with shorter sequences.  It’s also interesting to note that the length difference in telomeres exists at very young ages and does not carry over across the adult life span.

Telomere length declined with age (F [5, 158.92] = 20.92, P < 0.001), with loss being most marked during the first year (Fig. 1).

I cannot compute an effect size from this test, but the magnitude is not Small.  Here’s a graph to illustrate it.

This suggests that if we can do anything to affect telomere size or depletion, we better do it young.  If ever there was an interesting and potentially useful area for More Research, this must be it.

Let’s consider now longer life.  Assuming that our cells are like zebra finch cells and that a telomere is a telomere is a telomere, it’s apparent that the cards you are dealt determines the hand you can play at a Large Windowpane.  Now, contrast that against all the various Fairy Tale effects from the Lifestyle Drum and Bugle Corps.  As I’ve frequently noted in the Persuasion Blog, people will cry out for a Change that isn’t even Small, yet something that requires Congressional action.  Call this the Mallomar Redemption.  Make laws about diet to Save the World.

Now, contrast the Mallomar Redemption with the Telomere Limit.  A variety of well done lab studies creates a growing research literature that documents the Very Large impact of the factor.  For now, the operation of telomeres is not widely understood and we certainly are forever and a day away from the pill.  But, for now we can usefully quote Shakespeare, ” . . . the fault, dear Brutus, is not in our stars, but in ourselves . . . ”

See the feeble and foolish attempt to change telomeres with mallomars, as if we can affect this DNA function with broccoli and bean sprouts.

You Cannot Persuade a Falling Apple.

Researchers asked 23 college adults to participate in a series of evaluation tasks.  For the first evaluation task, participants were randomly assigned to read about a student website that contained either a speech about God or a speech about Pluto and its status as a planet.  A series of filler tasks followed this, then a key behavior task.  All participants did a taste test on a new cookie.  They were left alone with the bag of cookies for ten minutes and told to consume at least one, but as many as they wished, then complete an evaluation of the product.

We predicted that participants who first read about God would display better temptation resistance (i.e., eat fewer cookies) than other participants.  Consistent with this prediction, participants reminded of God ate fewer cookies (M = 2.82, SD = 1.54) than did control participants (M = 7.67, SD = 5.31), t(21) = 2.91, p < .01.

Jumping Jehoshaphat!  Convert that t value into the Windowpane and you get a Large effect, 25/75!  Read a speech about God, complete a bunch of unrelated tasks, and a few minutes later you eat about 3 cookies.  Read a speech about Pluto, complete those same tasks, and you eat nearly 8 cookies.

Talk about self control!  Talk about resisting temptation!  Praise the Lord and pass by the cookie tray!  Communion coming soon to Weight Watchers!  McDonald’s is adding the Ten Commandments to its Menu!

!!!

This from a six study package exploring the cognitive and behavioral effects of thinking about God.  I encourage you to read the report because it is interesting and complicated, but the main point falls from that cookie experiment.  Thinking about God, especially as the omnipotent and omniscient Creator of All Things, affects self regulation and behavior, most interestingly here, that health behavior of eating.

You might recall an earlier Persuasion Blog post looking at a religion meta analysis on health behaviors, notably mortality.  Here’s the main finding.

The results of the meta-analyses showed that religiosity/spirituality was associated with reduced mortality in healthy population studies (combined hazard ratio = 0.82, 95% CI = 0.76-0.87, p <0.001), but not in diseased population studies (combined hazard ratio = 0.98, 95% CI = 0.94-1.01, p = 0.19). Notably, the protective effect of religiosity/spirituality in the initially healthy population studies was independent of behavioral factors (smoking, drinking, exercising, and socioeconomic status), negative affect, and social support.

Of course, all that data is from Observational Research with convenience sample and the Windowpane is Small.  But, if you believe the Tooth Fairy Tales from the Lifestyle Drum and Bugle Corps, you’ve also got to accept this finding as a True, too.

Whether thinking about God or visiting His houses, the Ultimate Ground of Being changes the way people will think, feel, and act.  Self control.  Moderation.  Conscientiousness.

Ever want that from Other Guys?  Persuading with God primes produces that Change!

Now.  What has this got to do with Nietzsche?  If you read the article you’ll find that across the six studies the researchers looked to see whether God primes worked only with Believers and especially not with Atheists.  They reported no difference in thought or action between the two different groups.  Even among nonbelievers, thinking about God produces change.  To a modern atheist this sounds stupid because if you are an atheist, you don’t believe in God or even god, so how can this possibly happen?  Nietzsche figured it out a hundred years ago.

Nietzsche argued that Western society lived in a God-saturated world and whether God was understood as the Jewish, Christian, or Muslim God or the God of Socrates, Plato, and Aristotle as the Prime Unmoved Mover, people still built their lives around an immaterial creative force.  Thus, Nietzsche argued there really wasn’t much difference between deists and atheists because atheists still believed in Something that makes it all happen.  For Nietzsche, the only difference between most atheists and deists of any stripe was merely the label.  Whether you call it God or Variation With Selection, for example, it is still the Ultimate Ground of Being.  Thus, Nietzsche would be unsurprised by these results.

Don’t preach.  Just prime.

Laurin, K., Kay, A. C., & Fitzsimons, G. M. (2012). Divergent effects of activating thoughts of God on self-regulation. Journal of Personality and Social Psychology, 102(1), 4-21.

doi:10.1037/a0025971