Monthly Archives: September 2011

twittering towards One Term

I criticized Mr. Obama’s mishandling of his twitter Town Hall and the deficit reduction drama.  He took the New New Thing and turned it into an inescapable lunch with your boring uncle.  But, like the Wile E. Coyote he seems to be channeling, Obama and his team are back with a new twitter scheme flowing out of their new website.

AttackWatch is Obama’s attempt to harness the wisdom and effort of the crowd to discover smears, attack, and lies, damned lies, and statistics the Other Guys launch against Hope, Change, and ReElection.  Internet citizens can join at AttackWatch then twitter their gotchas.  Sounds like a smart persuasion play, right?  Organize people through a common website, let them do some of the heavy lifting in finding attacks, then give them the chance to make commitments to your cause.  You got your Norms.  You got your Commitment/Consistency Cue.  You got your New New Thing.


You can read this brief account of what’s actually happening.  The Other Guys are using twitter and AttackWatch to mock the Persuasion Play!  Who-da thunk it?  The article writer notes examples.

Another concerned citizen reported, “I saw 6 ATM’s in an alley, killing a job. It looked like a hate crime!” The site’s Twitter page recently featured so many zingers aimed at the president that it was hard to find actual Obama supporters whining about his critics. One tweeter noted that “the GOP won seats in NY and NV . . . I suspect interference by sane people . . . check that out please.” Another said, “Hey kids, are mommy and daddy talking bad about Obama? Be sure to report them at #attackwatch.”

How clever.  Using twitter to promote the full throated exchange between different factions!  Unite all the voices at the twitter Table of Brotherhood!  That’s using persuasion to get re-elected!

Mavens keep the point.  Politics matters not a whit here.  This is pure persuasion performance.  It’s about the Other Guy, Stupid.  Democrat or Republican, who cares.  Do you change the Other Guy?  Obama is a case study in learning from another guy’s failures.

P.S.  I keep trying to find the zig on the zag with Mr. Obama’s  persuasion efforts since Scott Brown’s Senate election victory killed the Democrats legislative majority in the Congress, and even more so since the 2010 midterm stomping.  Nothing works for the guy and I’m not talking policy, I’m talking sheer persuasion.  He can’t change anybody on anything.  On every Play he fumbles or misuses it and worse still usually shoots himself in the foot.  He was supposed to be an effective grass roots organizer which led me to believe he at least had some persuasion street smarts if not some Harvard Law persuasion smarts, too.  He clearly never earned anything with persuasion.  He can still get re-elected, but he’s not talking his way into it.

twittering for Life, Truth, and Justice, but Not Persuasion

My persuasion training leads me to pronounce the various Web 2.0 platforms as nothing new persuasion; they are only your Father’s Oldsmobile restyled. If you are a 2.0 insider, I hold a Peithos laurel over your heads and will crown you – as long as you actually bring that golden IPO to market. Otherwise, do 2.0 like 1.0, just with interestingly spelled neologisms. Today I offer more evidence of the ineffectiveness of twitter for mavens.

Troy Davis is scheduled for execution in Georgia on Wednesday, September 21, 2011 for the murder of a police officer in 1989. Many doubt the evidence for the conviction and have argued for a stay of execution, a new trial, or even immediate release. Protests continue with all available persuasion weapons.

The denial of clemency by the parole board prompted an outpouring of anger and despair from hundreds of Twitter users and several celebrity supporters of Davis’s campaign. The prisoner’s lawyer, Brian Kammer, said he was “shocked and disappointed at the failure of our justice system at all levels to correct a miscarriage of justice”.

When twitter has become just another way to express anger and despair with people, and especially celebrities, you know that twitter is not even the Emperor’s New Clothes, but merely a new wrinkle in the old fabric of change. You don’t have to have an opinion on this particular case to realize that twitter brings nothing new to the persuasion effort. “We’re using twitter for goodness sake and they still won’t change!”

Just as All Bad Persuasion Is Sincere, All Bad Persuasion Tools Are Sincere.

Netflix, Power, and Persuasion

Netflix is in the news lately for all the wrong reasons. The company started with a great premise – fast, cheap, and convenient access to first run movies through mailed DVDs – and rode its share price on the Wall Street rocket from $7 to $300. Then they infamously screwed it up by proudly announcing a large increase in fees which promptly cost them one million customers and a tumble in share price from that $300 to $160. How do you handle this?


Reed Hastings, Netflix CEO, sent me (an every other Netflix customer) a personal email which you can read at their Blog. Very sincere. Very thoughtful. So thoughtful and sincere, in fact, that I replied back to Mr. Hastings with the reasons why Melanie and I recently changed our service plan – to drop the incompetent streaming service – and wish him luck. And, I got a reply! Click to enlarge.

Please think like a persuasion maven for a minute. Your business is getting the kind of press coverage and customer response reserved for serial killers, deposed dictators, and George W. Bush. Worse still, you’ve lost 50% of your market value in just a few weeks. You develop a persuasion plan to address this continuing disaster and hit upon the idea of a CEO apology to each customer with a personalized greeting. You smartly include a Reply-To function that lists the CEO’s name and title, making it look like a valid email address.

And then you return all replies as undeliverable?

Netflix presents itself as a Web business, a business that leverages technological smarts to provide products and services in ways only possible through the magic of the Internets. And, they can’t use email as a communication channel for persuasion? The Hastings Apology email could have been a valuable source of specific customer information for Netflix. They could have easily accumulated all replies as normal email traffic and engaged an on-going conversation with each message they received. My email contained specific statements about failures in their streaming service, for example. I suspect that others replied with other details.

And Netflix, a technology company, blocks and returns as UNDELIVERED, all that specific, real time, feedback.

Look, I get that a valid email address for Reed Hastings is not the magic bullet here. But, if you are a maven, then you concede nothing, especially during disasters. You seek every available means and opportunity for persuasion. And, you do not overlook anything simply because it holds some technical problems. You’re getting killed.

I view this Nail for the Horseshoe as indictative not of a lost war, but of a losing general. Reed Hastings and his crew at Netflix know how to send and receive DVDs through the mail, a business model that is a kind of power.   However, they do not know how to persuade anyone to do anything. And because they mishandled basic relationships with their customers they now find themselves in a position where mere business cannot save their business. They must persuade.

While I am dubious about the communication and persuasion value of Web 2.0, especially as a New New Thing, there are still obvious, if Your Fathers Oldsmobile, uses for it. Internet based communication is so cheap to produce and maintain and so easy to database and analyze. Web 2.0 does not suspend the Laws of Physics or the Rules of Persuasion as cheerleaders like Marc Andreessen would shout (for their persuasion purposes), but you can still perform basic communication and persuasion functions with Web 2.0.

Remember the Rule:  Power Corrupts Persuasion.


Storming Wall Street with twitter

With all the IPO buzz on those groovy 2.0 platforms, consider a different way to take Wall Street with twitter.

It worked in Tahrir Square. Now, taking their cue from social-media fueled uprisings in places like Egypt and Iran, a band of online activists are hoping it will work on Wall Street . . . Kalle Lasn, co-founder of the venerable counterculture magazine AdBusters, has taken to Twitter and other websites to help organize a campaign encouraging tens of thousands of Americans to hold a nonviolent sit-in on Saturday in lower Manhattan, the heart of the U.S. financial district — a protest monikered, hashtag and all, as #occupywallstreet.

Here’s the maven test for this brash and bold piece of persuasion.  Recall the Rule:  If You Can’t Count It, You Can’t Change It.  What’s the count with twitter?

Just showing up doesn’t count because Righteous Lefties have been protesting Wall Street since Wall Street was a muddy lane.   Wearing a twitter lapel pin won’t count either because you could hand those out like Mentos tabs.  And, even though the organizers chickened out by calling for a Saturday march (have you ever been on Wall Street on the weekend – you could have sex on the sidewalk and no one would see you), if twitter makes the Arab Spring difference, then not only do more protesters appear, but they stay until Mayor Bloomberg orders the cops to throw foie grais into the crowd.

Now.  Mavens should count Kalle Lasn as some kind of potentially clever.  Just adding twitter to your protest is smart like just adding Nudge to government policies; twitter is hot now the way Nudge was hot then.  Call a protest that no one is likely to notice but add a whisper of twitter in the shout and people are listening.  Fan in a wisp of Arab Spring and you’ve got the CNN amplifier blowing your breeze.  Kudos to Kalle!

But if twitter makes the difference in the protest, how will you know?

Didn’t twitter take down the Pharaoh in Egypt?  Run the Colonel out of his capitol in Libya?  Spill the blood of martyrs in the streets of Damascus?

Playing the twitter card makes clear:  Kalle Lasn expects a Day of Last Things this Saturday on Wall Street.

P.S.  Hey, Cool Table, what happened with Nudge along the road to Hope and Change?  Nudgers sold that persuasion play as invincible.  Not enough Message Framing, perhaps.

Yeats, O’Casey, and Sincerity

Among the things that dramatic action must burn up are the author’s opinions.  WB Yeats, Letter to Sean O’Casey.

First, to principles.  In persuasion, as with poetry, sincere expression produces bad outcomes.  No one cares how you truly feel because It’s About The Other Guy, Stupid.  Authenticity is persuasive or poetic only when it does what you want to the Other Guy, a most rare and happy confluence, and the supreme expression according to the redoubtable Oscar Wilde.  Most often, however, our sincere and authentic expression is beyond our careful control and leads us to worry more about ourselves than the Main Point:  Change the Other Guy.  Sure, you can be both sincere and successful, if you are a god of Oscar’s highest rank, so more prudently if you seek the latter, drop the former.

Second, to the back story.  Feel the Irish nationalism in the 1920.  WB Yeats, Nobel poet and Irish icon, runs the Abbey Theatre in Ireland.  Sean O’Casey, a great Irish playwright, has written a new play, The Silver Tassie, an anti-war drama set in the aftermath of World War I.  Yeats, as artistic director, rejects O’Casey’s request to run the play with the Abbey, finding the work to lack artistry, noting . . .

Among the things that dramatic action must burn up are the author’s opinions.

Or:  All Bad Persuasion Is Sincere.

P.S. I am a weak reader of Yeats and have learned more about him through Professor Bloom than my own efforts.  I found this Yeats observation in Bloom’s book, The Anatomy Of Influence.  Bloom might be the best reader to date in the history of the English language.  Anytime I think I’m smart, I read Bloom then find a seat in the front of the room and take notes.

P.P.S.  Sean O’Casey plays are still widely performed.  I worked in Purple Dust in academic theatre in the 1970s, as a sincere example.  Interestingly, however, The Silver Tassie is rarely done despite its anti-war theme, so appealing to directors and actors.  Yeats wrote both true and tough in his rejection.

WHO Dat? Campbell, Stanley,and Livingstone

You’ll recall the terrifying news that a prestigious international scientific association from the World Health Organization determined that cell phones cause cancer.  I’ll requote myself quoting their lead expert.

“After reviewing all the evidence available, the IARC working group classified radiofrequency electromagnetic fields as possibly carcinogenic to humans,” panel chairman Jonathan Samet, MD, chair of preventive medicine at the USC Keck School of Medicine, said at a news teleconference.

Well, now another prestigious national scientific source, the Journal of the National Cancer Institute weighs in on the threat.  Here’s the news.

A European study involving nearly 1,000 participants has found no link between cellular-phone use and brain tumors in children and adolescents, a group that may be particularly sensitive to phone emissions.  The study, published in the Journal of the National Cancer Institute, was prompted by concerns that the brains of younger users may be more vulnerable to adverse health effects—such as cancer—from cellphones.

What to believe?  Who to believe?

The story writer returns to the WHO commission and recounts their work.

In May, based on a review of existing science, the World Health Organization announced that cellphones were “possibly carcinogenic” to humans. Yet even that technical classification didn’t specifically link cellphone use to cancer. Instead, in the WHO’s own words, it meant that while a link had been observed, “chance, bias or confounding [factors] could not be ruled out with reasonable confidence.”

That last quote is most strange.  A scientific group finds a Link that can also be explained through Chance, Bias, or Confounding, but still believes it is a Link to Death.  In scientific parlance we call things like Chance or Bias, “threats to internal and external validity” which is what science tries desperately to rule out when looking for Links.  My training on threats to validity flows out of the work from Campbell and Stanley.  Given the WHO comments, they must be confusing Campbell and Stanley with Stanley and Livingstone.

They are all explorers!  Just looking with different rules.

Roll Back the Barrel with II or Affirmation!

When you know what you are doing the Abstract explains everything.  No murder mystery whodunit style with good science.  So:

Objective: To test the ability of a new, brief means of affirming the self (the “self-affirming implementation intention”) to decrease alcohol consumption against a standard means of self-affirmation (the self-affirming “kindness” questionnaire) and an active control condition; to test whether self-affirmation effects can be sustained beyond the experimental session; and to examine potential moderators of the effects. Method: Two hundred seventy-eight participants were randomly allocated to one of three conditions: control questionnaire, self-affirming questionnaire, and self-affirming implementation intention. All participants were exposed to a threatening health message, designed to inform them about the health risks associated with consuming alcohol. Main Outcome Measures: The main outcome measure was subsequent alcohol intake. Results: There were significant public health gains and statistically significant decreases (>1 unit/day) in alcohol consumption in the two experimental conditions but not in the control condition. At the end of the study, participants in the control condition were consuming 2.31 units of alcohol per day; people in the self-affirming questionnaire condition were consuming 1.52 units of alcohol per day; and people in the self-affirming implementation intention condition were consuming 1.53 units of alcohol per day. There were no significant differences between the self-affirming questionnaire and self-affirming implementation intention, and adherence did not moderate the effects. Self-affirmation also improved message processing, increased perceived threat, and led to lower message derogation. Conclusions: The findings support the efficacy of a new, brief self-affirmation manipulation to enhance the effectiveness of health risk information over time. Further research is needed to identify mediators of the effects of self-affirmation on health behavior change.

This from Christopher Armitage and colleagues in the newest issue of Health Psychology (volume 30, number 5).  We’ve seen Armitage on this exact topic and intervention before and with useful results.  Armitage (and Mark Connor) are testing Implementation Intentions with fabulous results on a wide variety of TACTs.  This study is another in a long line of successes.

Note in this case that they tried adding Affirmation to the basic II tactic.  We’ve also seen the Joys of Affirmation observing that getting self affirmations before you hit the Other Guy with a persuasion attempt tends to lower resistance and make the ensuing play more effective.  Here’s how the Armitage team did it.

The manipulation consisted of 10 questions designed to encourage participants to recall and give examples of past acts of kindness, for example: “Have you ever forgiven another person when they have hurt you? yes-no.” When participants responded “yes,” they were asked to provide specific examples of their behavior.

The researchers ran the II manipulation like ones we’ve seen in the past.  Here’s their description.

In order to turn these responses into if-then statements in accordance with Gollwitzer’s (1993) recommendations (see Chapman, Armitage, & Norman, 2009), participants were presented with the stem, adapted from Harris et al. (2011), “If I feel threatened or anxious, then I will…” Participants were presented with four options, also adapted from Harris et al. (2011): “… think about the things I value about myself,” “… remember things that I have succeeded in,” “… think about what I stand for,” and “… think about things that are important to me” and were asked to write out their chosen option on three blank lines. To ensure that participants wrote out the self-affirming implementation intention in full, they were prompted with “If…” at the beginning of the first blank line.

We have 3 conditions in this field experiment.  People were randomly assigned to Control, Affirmation, and II With Affirmation.  Participants completed self reports on all key variables including amount of drinking at pretest and again 30 days later.  Thus, we can see how drinking changed over time and across the 3 randomly assigned conditions.  Here’s the key Table.  Click to enlarge.

That’s a one shot reduction per day and that’s no small beer in this application.  Note, too, that there is obviously no difference between Affirmation and II With Affirmation, but both produce that one drink reduction.

The first thing that pops out for me on that Table is the change in standard deviation from Pre to Post.  It gets noticeably smaller in the Affirmation and II With Affirmation groups.  That means there’s probably less extreme drinking in these groups along with a Large Windowpane effect.  Realize that the one drink decrease is a one standard deviation drop if you use the Post test values.  And, realize how easy it is to get this decrease – just those brief II and Affirmation completion tasks.

Now, why didn’t II With Affirmation have any additional impact?  The paper does not discuss this in detail.  To a certain extent, when you are succeeding like this, it’s going to be hard to get more effect.  It appears that either Affirmation or II can produce these large and easy changes.  Look at this Table.  Click to enlarge.

The Armitage team conducted a very nice messaging processing analysis (threat, message derogation, etc.) which showed that both Affirmation and II With Affirmation had large and beneficial effects on message processing.  With either treatment, people did not get defensive, felt higher self esteem, and apparently thought more about their drinking behavior in a highly Objective Central Route fashion.  Both manipulations thus produced that High WATT, Long Conversation in the Head, just in different ways.  To use a racing metaphor, both treatments motivated people to run as fast as they can; combining them makes no difference, because either manipulation motivates the best they can do.

Here’s the jerk way of thinking about this.  If you combined either Affirmation or II with a proven loser like the Health Beliefs Model or Message Framing, you might be both surprised and pleased with the results and you might even go so far as to think you’ve made a major theoretical breakthrough with HBM or Framing.  Jeepers, HBM alone gets a 48/52 Windowpane, but add Affirmation and it zooms up to 25/75!  So it’s now HBM+ with susceptibility, severity, barriers, benefits, and Affirmation!  Of course, Affirmation is doing all the work, but S2 and B2 find a way to squeeze on the victor’s pedestal nonetheless, kinda like me and Usain Bolt winning a 2 X 200 meter relay race for old timers.  Yeah, me and him, that’s the winning ticket.

Let’s get out of here.

You’d think I was either the Mother or the Press Agent for these dangerous Brits, Armitage, Connor, and their Guys.  They consistently deliver excellent science with obvious practical applications.  I think of them primarily with II, but they know how to do good work with any concept.  Even if you are not interested in II or Affirmation, just read this report as a refreshing example of skill.  If you teach, give this to your students as an Exemplar.  If you research, read ‘em and weep.  This is why you’re having trouble getting that paper accepted.  If you practice, steal this report!

Armitage, C. J., Harris, P. R., & Arden, M. A. (2011). Evidence that self-affirmation reduces alcohol consumption: Randomized exploratory trial with a new, brief means of self-affirming. Health Psychology, 30(5), 633-641.


Bias Prefers Observation to Experiment

Bastardi, Uhlmann, and Ross provide a nice little experiment that stimulates the post title.  People were asked to read two studies, one an experiment that randomly assigned participants to conditions, the other an observational matching study (case-control in epi-speak) then rate the quality of the evidence.  The results from both studies either supported a key attitude or contradicted the key attitude.  The key question Bastardi et al. asked was how did ratings of the observational study vary.  Here’s the key figure that displays the ratings.

What this means is that people with a bias (that key attitude) found the observational study “better” than the experiment when it supported the key attitude (M = .55) but when they did not have a bias, they found the observational study “worse” than the experimental study (M= -.43).  This is a Large Windowpane effect size.  Thus, the crucial element in the rating of the evidence clearly came from the existing belief in the participant.  When people had that key attitude, supporting data from a weak method was rated stronger.

All Bad Persuasion Is Sincere!

Thus, bias prefers observation to experiment!

Wishful Thinking:  Belief, Desire, and the Motivated Evaluation of Scientific Evidence.   Published online before print April 22, 2011

doi: 10.1177/0956797611406447 Psychological Science, April 22, 2011.

The TpB You’ve Got versus The One You’d Like

Jim Dillard presents a useful and interesting self report survey that employs TpB to understand the behavior of women obtaining an HPV vaccine. The report is useful because somebody at Penn State University could take his results and design a persuasion intervention to encourage vaccines (and these results may be more generally useful to large public universities as well and perhaps most generally to women of this age range.). The report is interesting because it conducts a thoughtful data test of TpB theory. And, if you enjoy reading well done science, the paper is worth your time. Dillard is consistently one of the best persuasion researchers and writers working in the past 30 years and this paper is yet another example of his patience, skill, and thoughtfulness. Having done this affirmation manipulation, now let’s begin with a problem.

Dillard draws a random list of 1800 Penn State undergrad women and invites them through email to complete an online survey about women’s vaccinations. About 10% of these women actually and properly complete the survey with a final total of 174. This is ultimately a convenience sample of respondents, but at least Dillard starts with a fair selection and ever better he actually takes a paragraph to discuss it under Limitations. You see the Problem. This is both a random and a convenience sample. Theory and practice demonstrates that convenience samples can produce results that are little more than imaginary. While I tend to trust the reliability and validity of the results Dillard presents, that doesn’t mean you should. Think about it the way you should always think about convenience sampling in observational studies. Always. As in always wear a condom or always look both ways or always wear a seat belt. Always think about convenience sampled data.

Now, with the single largest problem in the method noted, let’s continue to the useful and interesting stuff.

Dillard surveys the women on standard TpB measures (intention, attitude, subjective norm, and perceived control) with semantic differential scales. He also includes specific belief items for attitude, norm, and control based on a focus group elicitation of Doers (women who had HPV vaccines) and NonDoers (women who hadn’t). The 174 women complete these items and then Dillard analyzes.

He finds that attitude, norm, and control combine to explain 75% of the variance with intention, a Large Windowpane effect and entirely consistent with TpB studies (of course many folks prefer Health Beliefs or Message Framing; here we can call that Dissonance Reduction). Dillard then includes two way interaction terms among attitude, norm, and control and as a block they explain an additional 7% of the intention variance, a Small Plus Windowpane. Finally, Dillard correlates those specific beliefs from the Doer-NonDoer focus group and finds several Medium and Large Windowpane effects in the larger sample of respondents.

Thus, we know that this TpB analysis explains a large amount of intention to act with the lion’s share of impact coming from main effects (attitude – Large beta at .50; norm – Small beta at .17; control – SmallPlus beta at .24) and a smaller, but noticeable amount coming from their interaction. Better still we have several strong belief statements that bear out the focus group. Beliefs around security, parental approval, close friend and boyfriend support directly drive the more general attitude, norm, and control components.

The consistency of these results with other TpB studies tends to argue that the convenience sampling here may not be a source of bad bias. These results just make sense. If I was running an intervention, I might draw another convenience sample (like in large lecture classes) and compare the results. Persuasion never operates in a perfect world and you’ve got to go to war with the army you’ve got rather than the one you’d like to quote that underappreciated persuasion theorist, Donald Rumsfeld. It makes sense that attitude is the largest driver of getting a vaccine for something related to sexual behavior. Hey, it’s your body so other people’s opinions (norms) are nice, but ultimately not more important. And, double-hey, how much control do you need to get a shot?

Let’s get practical from this. Women’s attitudes are the single strongest driver of HPV vaccination with norms and control coming in at much smaller effects. Yet, the specific beliefs that most strongly predict intention are norm beliefs about parents, girl friend, and boy friend approval. I would consider a double barreled persuasion campaign that delivered two different messages to two different groups. For the women who need the vaccine, I’d run an attitude based message with an emphasis upon protection against HPV and feelings of security and confidence about health as the dominant content. For parents and girl and boy friends, I’d run a different message aimed at encouraging them to express support for the vaccine. The attitude campaign aimed at women would motivate their behavior and the norms campaign aimed at their primary relational sources would provide support for that behavior.

Now, let’s go theory and research. Dillard finds that two of the three double interactions between attitude, norm, and control are statistically significant. Combined as a block the three interactions (A x SN, A x PC, SN x PC) add about 7% more variance. So? While it is stupid to do this, if you ran the interaction terms first in this regression, they probably would not be ssd. Furthermore, the effects are Smallish and given the convenience sampling, I’m reluctant to trust the outcome. If we had a true random sample, I’m not sure the effect would obtain. Mere convenience is sufficient to explain these Smallish outcomes for me. Just a few weird cases could produce these interactions with weirdness being another way of saying a convenience sample.

Dillard does make some interesting observations about the role of perceived control in TpB and suggests that control is better understood as a moderator rather than a primary direct impact variable like attitude and norm from the traditional Theory of Reasoned Action. My first impulse is to agree. His data here, plus clear thinking, support this line of reasoning. However, I’ve got experience with excellent data from the Wheeling Walks campaign that showed perceived control alone – neither attitude nor norm – motivated walking behavior. It’s worthwhile to pursue Jim’s thinking here with more research, but for now, I’ll stay conservative and play with TpB both in theory and practice.

The last piece of this report is perhaps the most fertile. Dillard invents an interesting way of measuring beliefs with a formula he calls the Room For Improvement Index (RFII). The formula is a ratio that essentially compares how many people who do agree with an item versus how many should agree. If relatively few people endorse an item that is shown to drive intention, then there is a lot of Room For Improvement and this suggests a good avenue for message design. For example, in the Milk studies, we found that a lot of people thought lower fat milk was a lot more expensive and that expense was strongly related to their purchase behavior. Thus, the RFII on cost was very large. We then designed messages that pointed out lower fat milk did not cost more (who looks at the price of a product they aren’t buying?), we changed Attitude which changed Intention which changed Behavior.

The RFII provides a quick, convenient, and intuitive number that ranges from 0 to 100% with the higher percentage indicating more room to the top. Combine the RFII with the simple correlation between the item and intention (or behavior if you’ve got that) and select items that have high RFII percentages and high correlations. You are essentially targeting the big differences in beliefs between the Doers and the NonDoers with this strategy.

Now, to dangers, risks, and perils. I’ve got enough old guy stat experience in me to know that invented ratio indices are very dangerous things. When you start messing around with your measurement, you can invent yourself into the Land of Oz. The concern here is that artificial top and bottom and how different items may form different distributions under different conditions. If a gearhead like my former office mate at WVU, Tim Levine now at Michigan State, ran a bunch of Monte Carlo demonstrations on theoretical distributions of the RFII under different response formats (1-5 versus 1-15) and different item means, he would probably find some interesting effect and invent a new Greek symbol to describe it. Then maybe Tim and Jim could engage in the Jane, You Ignorant Slut exchange in HCR!

It would be interesting for somebody to take the RFII and figure out the distributional qualities and perhaps how to handle it in difference or association statistics (t-tests or correlations, right?). As I’ve noted many times in the Persuasion Blog, a lot of interventionists obtain poor outcomes in part because of bad messaging. The RFII could provide a simple, reliable (?), and valid (?) quantitative index that screams off the output, yelling, Pick Me!

Past this propeller head quibbling, RFII is an artful rule of thumb that can be used skillfully as long as you keep your thumb in the right location. Use it to find big, obvious, black and white differences and never to find shade, tone, or nuance. Unless you are using Health Beliefs or Framing; you’re doing voodoo anyway, so go ahead and stick your thumb anywhere you want.

Let’s get out of here . . .

From a simple observational convenience sample, we get a lot of ideas. Sure, Dillard warns about the convenience and I double warn to always think about observational studies. With that in mind, we see, Yet Again, another strong illustration of TpB in action with strong effects entirely consistent with both the theory and the literature. We have interesting arguments about interactions in TpB and the role of perceived control. We have that nice set of data on specific beliefs and the RFII to identify promising lines of message development. And, for you researchers types out there, we have a great example of good scientific thinking and writing in Dillard’s paper. Finally, I actually have something nice to say about observational data!

Dillard, JP. (2011). An Application of the Integrative Model to Women’s Intention to Be Vaccinated Against HPV: Implications for Message Design. Health Communication, Jul-Aug;26(5):479-86. Epub 2011 Jun 24.

DOI: 10.1080/10410236.2011.554170

P.S. Dr. Fishbein would have probably appreciated this one.