The National Cancer Institute is wasting taxpayer dollars on
slanted e-cigarette research that didn’t ask or answer an obvious and important
question.
Consider the recent NCI-funded study by Drs. Erin Maloney
and Joseph Cappella at the UPenn Annenberg School of Communication (abstract
here).
Maloney and Cappella recruited daily smokers, intermittent
smokers and former smokers (there were no significant results in the middle
group so I won’t discuss them). They
divided smokers into three subgroups: controls who didn’t see an ad, those who
saw e-cig ads with vaping (called a cue) and those who viewed ads with no
vaping. Participants answered questions
about their inclination to smoke a cigarette, to quit smoking or to continue to
abstain. Maloney and Cappella developed
a scoring system to measure responses.
The results they pitched to the media are in the table.
All groups had lower urges to smoke after the experiment, but
smokers who saw the cue had less of a lower urge, which was significant in the
authors’ scoring. Similarly, all former
smokers had high scores for continuing to abstain, but those who saw the cue
had a lower high score.
| E-Cigarette Ads and Urges in Daily Smokers and Former Smokers | ||||||
|---|---|---|---|---|---|---|
| Daily Smokers | Former Smokers | |||||
| Cue | No Cue | No Ad | Cue | No Cue | No Ad | |
| Urge to Smoke | ||||||
| Pre-test | 3.99 | 3.83 | 3.84 | 1.86 | 1.69 | 1.76 |
| Post-test | 3.63* | 3.14 | 3.25 | 1.42 | 1.34 | 1.32 |
| Intention to: | ||||||
| Quit | 2.14 | 2.15 | 2.06 | --- | --- | --- |
| Abstain | --- | --- | --- | 12.39* | 13.10 | 13.14 |
*Significantly different than No Cue or No Ad.
The authors acknowledged that “effect sizes reported in this
manuscript were not large.” In fact, the
differences are so small that they may not be meaningful for actual behavior. Take 12.39 versus 13.14 in the table as an example. The authors reported that higher numbers are better, and both numbers look “high” when compared with a previous study by Cappella that used the score (abstract here). He showed former smokers anti-smoking ads in that study and got scores around 3.0 to 3.5. This looks like e-cigarette ads are far better for former smokers than anti-smoking ads.
There is a glaring defect in the report. The researchers collected a lot of basic
information (e.g., education, quitting history and time since last cigarette) that
could affect how participants responded to questions, but the results weren't adjusted for these important characteristics.
It is possible that the cue, no-cue and no-ad groups had important differences
in basic information that affected their scores.
The study’s biggest weakness is that no data was collected on urges and intentions to VAPE. After all, that is the most important goal of
e-cigarette ads, and it is an obvious outcome to measure.
This study is a failure to communicate.
3 comments:
FDA/NIH funded Andrea King (at Univ. of Chicago) conducted and reported and very similar study (at recent SRNT conference described on pages 32 & 33 of abstract book at http://www.srnt.org/conferences/SRNT_2015_Abstracts_WEB.pdf )
During the past several years, DHHS has given hundreds of millions of dollars to activists in academia to conduct junk science studies and to issue fear mongering conclusions and headlines claiming e-cigs can and may cause lots of potentially awful things for vapers and nonvapers alike, while simultaneously denying (or never acknowledging) that e-cigs have provided enormous health benefits to several million smokers.
The only reason DHHS is funding this junk science and deceitful criticisms of e-cigs is to lobby for its deeming regulation, which will ban >99.9% of vapor products now on the market, and will give the entire legal e-cig industry to Big Tobacco companies, which will be the only entities that have the expertise and can afford the $10 million or more for each FDA Premarket Tobacco Application for a cigalike e-cig.
Bill Godshall
As someone who has published several papers on cue reactivity, there are a number of conceptual problems with this paper, not to mention the effects found are trivial. First, there is no clear understanding how "urge" or "craving" actually drives drug use in the real world. It's commonly assumed that urge drives the majority of drug use, but the association is surprisingly weak. That is, people often use in the absence of any urge and often don't use under strong urges. Like hunger, you sometimes eat when you're not hungry and sometimes don't eat when you are. That stimuli associated with smoking can raise urge is a really easy effect to find. (I've found it in the laboratory many times and the effect sizes are typically much larger than found here.) But, the effect of increased urge on actual smoking behavior is often very weak. What they found in this study is fairly typical. In current smokers, 35.7% in the cue condition smoked a cigarette during the experiment, versus 21.6% in the no-cue condition, something the authors' call a "marginally significant" effect. In layman's terms, an unreliably small effect. In technical terms, consistent with urge accounting for about 10% of the influence on smoking behavior when isolated in an experimental setting.
Second, of the multitude of environmental stimuli that could help push someone toward smoking (not to mention the internal states like depressed mood or the desire to increase arousal) the idea that exposure to a smattering of e-cigarette ads constitutes a powerful force that causes current smokers to smoke even more is absurd. This very limited influence, in the grand scheme of things, could only be trivial. Not unlike asserting a handful of candy bar ads causes obese people to consume too many calories.
The authors' overextend this trivial finding by asserting a relapse risk for former smokers. They base this on the clinically insignificant differences in the "intention to abstain" scores noted above. It is well understood in psychology that assessing someone's intention to do something is a terrible proxy for what they will actually do in a given situation. People are poor predictors of their own behavior. In the case of this study, we have a measure of the actual behavior in question: smoking. NONE of the former smokers smoked a cigarette during the study. The e-cigarette ad may have shaved a few decimal points off their stated intention, but not one person was actually driven to pick up a cigarette by watching the e-cigarette ads. Again, not surprising. What is surprising and completely unjustified by the findings is the authors' assertion that "for former smokers, these cues in advertising may undermine abstinence efforts." When an undergraduate makes this kind of statement in a term project they are marked down a grade with the comment "gross over-interpretation of data."
In short, this paper offers nothing new, unexpected, meaningful, or interesting about the potential effects of e-cigarette advertising. The very premise of the paper, that the effects of cue reactivity strongly translate to real world use, is seriously flawed.
I'd have to agree with what Brian Carter said above. The assertions being made are very much over interpreting their findings. I feel that a bigger more in depth project would be able to tell if there is any actual link here.
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