01/02/2008 - EHP publish Powerwatch response to Eltiti "Essex" Study
Also in the News
Environmental Health Perspectives, the journal that published the "Essex
Study" (Eltiti et al, 2007), has now published our response
(plus two others - also critical of the study paper) and the authors' overall
responses to them. The study authors refute our letter but not the main
underlying point, which was that their actual study findings do not match
the conclusions they draw in their paper reporting their work.
Symptom Responses
In our letter, we stated that the authors conclusion "[EHS] individuals
are unable to detect the presence of rf-emf [radio frequency electromagnetic
fields] under double-blind conditions" was erroneous, a statement they
claimed was "completely unfounded". They go on to state that the sensitive
participants were unable to detect when the exposure was real (i.e. non-sham).
The definition of "detection" used in the study was finding a statistically
significant level of accuracy in the sensitive participants being able to
identify when they being exposed to a "real" signal. We believe that the
subjective responses should also be considered as part of the detection process
as it is a clearly defined response, even if it is at a subconscious level. In
our letter, we were pointing out that there was a statistically significant
effect on the participants' symptoms for UMTS exposure under double blind
conditions, and we considered this to be a sign of "detection".
The authors in the original paper wrote off this significant result due to
the UMTS exposure being unreasonably predominant in the first test, and
therefore being the product of the order of the tests. However, we believe that
this is unlikely (as demonstrated below), as the GSM exposure was also also
responsible for an increase in symptoms, albeit one that did not achieve
statistical significance.
The authors' response had also assumed that our conclusion arose "from a
misunderstanding of the receiver operating characteristic (ROC) curve analysis".
This was simply a wrong assumption, as it had nothing to do with our ROC
analysis, which was more of a remark that it was a convoluted and unhelpful way
of displaying the data. Our comment arose because the data appeared to show a
fairly consistent difference between the control and sensitive group.
Selection and Resolving Power
There is a serious flaw in that all of the measured responses were entirely
subjective. Initially there was a questionnaire (the methodology of which is
also a peer reviewed and
published paper) that was designed to filter the groups, removing the
subjectively reporting sensitive participants that did not appear to show any
signs of sensitivity. Unfortunately, due to not having enough people for the
tests, this filtering process was not done, and it becomes necessary to find a
separate method of trying to cater for the subjectiveness of the responses.
This was combined with the inadequate resolving power of the study. The
authors state in their response that "the statistical power (0.75) in our study
was actually very high for this field of research", which is entirely
irrelevant. In the paper itself they admitted that this was not sufficient to
detect statistically significance with level of effect expected:
"Assuming there is a small effect of rf-emf on
human health (d=0.40), and that sometimes this effect is positive and
sometimes negative (two-tailed), it was calculated that 66 participants per
group were needed to have a power level of .90 to detect a within-subjects
effect (i.e. difference between real and sham exposure conditions) and 132
participants per group were need to detect a between-subjects effect (i.e.
group by exposure condition interaction) for a total of 264 participants
(Howell, 1997)"
Eltiti et al, 2007
Regardless of how well a resolving power of 0.75 compares to other
studies in the field, if it is not enough to find the expected level then it is
not good enough. Perhaps it is instead evidence that this type of study
is simply not appropriate in the first place, if sufficient resolving power
cannot be expected?
Perceived Sensitivity and Subjectivity
There are also grave questions regarding the accuracy of partipants to
correctly diagnose themselves as objectively sensitive, especially in an area
with such heated controversy. To address this issue, the authors say that
"Second, extensive pilot testing and interviews with study participants
revealed that the people we tested reported that they usually experience their
typical symptoms within minutes of being exposed to EMF signals. The fact that
the symptoms were elicited under the open provocation, but not in the
double-blind session, provides evidence that these sensitive people experienced
a number of unpleasant symptoms, but these were not related to the presence of
an EMF signal."
These is entirely under the assumption that the study participants were
indeed correct in their estimation that they truly reacted within a few minutes
in the way expected. What the study demonstrated very clearly was that there
were very likely to be a number of participants who did not react to the EMF
signal, and that their reaction is considerably more likely to be a nocebo
response. However, this does not exclude the possibility that a sub-section of
the sensitive group were genuinely reacting. As we have already discussed
the resolving power would not be significant enough to detect a statistically
significant effect even if every sensitive participant was objectively
sensitive.
It is already established that the nocebo response is real, and
potentially significant where there is a genuine widespread concern to health
from a perceived cause. It is absolutely essential to address this confounding
factor by making an attempt to analyse the perceived sensitive group and remove
those that appear to have no response difference between the real and sham
exposures. As mentioned, due to the already small number of active participants,
this was never carried out in this study.
Actual Sensitivity and Detection
It is generally accepted (the paper itself refers to this) that the sensitive
group are likely to claim they are being exposed when they are not more often,
and visa-versa with the control group. We confirmed this from the following
analysis from the data in the study (bearing in mind that there are 2 real
exposures to 1 sham "exposure", we would expect participants to guess correctly
that the exposure was real two thirds of the time and that the exposure was sham
only one third of the time - assuming no personal bias on the part of the
participant):
| Participant Group |
Exposure |
Guessed "on" correctly |
Difference to expected (66.7%) |
Guessed "off" correctly |
Difference to expected (33.3%) |
| Sensitive |
Open Provocation |
65.9% |
-0.8% |
36.4% |
+3.1% |
| Sensitive |
Double Blind |
70.5% |
+3.8% |
40.9% |
+7.6% |
| Control |
Open Provocation |
52.2% |
-14.5% |
51.8% |
+18.5% |
| Control |
Double Blind |
47.4% |
-19.3% |
53.5% |
+20.2% |
This confirms that the control group heavily over-reported that they were not
being exposed, though provides little supportive evidence that the sensitive
group over-reported that they were being exposed, but the data is very hard to
interpret. Indeed, this is one of the biggest confounding issues when attempting
to assess the success rate of entirely subjective reponses, especially when it
is well known that at least one group has a strong personal bias to the issue.
However, adequately dealing with this confounder is not as complicated as it
first appears. Assuming that guessing is random (null hypothesis), and
the increased likelihood to guess that the exposure is "on" or "off" is
consistent regardless of the actual exposure, we can use the formula (TP/FN) /
(FP/TN) to create a ratio that compares actual success rate with expected
success rate, regardless of the likelihood to over-report or under-report
exposure:
R (ratio) = (TP/FN) / (FP/TN)
TP = True Positive - Correctly identifying the "real" exposure
FN = False Negative - Falsely identifying the "real" exposure (claiming it is sham)
FP = False Positive - Falsely identifying the "sham" exposure (claiming it is real)
TN = True Negative - Correctly identifying the "sham" exposure
To demonstrate the purpose of this formula, let us assume that person "X"
has a personal bias where they assume that the exposure is real 70% of the time.
If the exposure is real 50% of the time, they will have an elevated number of
"true positives" and "false positives", and will have a reduced number of
"false negatives" and "true negatives". Importantly, these elevations and
reductions will be proportionally the same, so if we assume that the guesses
will be random (aside from the personal bias) both sides of the ratio should
match, giving R = 1. For R to be greater than one would signify that the
proportion of accurate judgements would be greater than the proportion of
inaccurate judgements having taken personal bias into the account, implying a
genuine ability to detect the signal. Similarly, for the value of R to be less
than one would have the opposite result, implying the group had a greater than
expected record at being wrong, having taken personal bias into account.
For a null hypothesis we would expect both groups to have a ratio of 1 on
the double blind tests, but the results come out as follows:
| Participant Group |
TP / FN |
FP / TN |
R |
| Sensitive |
2.30 |
1.39 |
1.65 |
| Control |
0.91 |
0.89 |
1.03 |
As expected, the control group has a ratio extremely close to 1, which
implies that, despite their tendency to guess that the exposure was sham, the
results are very close to expectations for a group without the ability to
discern their exposure. In contrast, the sensitive group were consistently
better at accurately detecting whether the exposure was real or sham despite
their tendency to report a real exposure when one was not present.
As a further attempt to analyse this finding, we pooled together the double
blind results, which gave some solidly supportive evidence that the judgement
was indeed better in the sensitive group (we would expect an overall 50% success
ratio at guessing the signal):
| Participant Group |
Exposure |
Guessed "on" correctly |
Guessed "off" correctly |
Guessed both correctly |
| Sensitive |
Test 4 |
81.5% |
35.3% |
63.6% |
| Sensitive |
Test 5 |
66.7% |
41.2% |
56.8% |
| Sensitive |
Test 6 |
66.7% |
45.5% |
61.4% |
| |
All Tests Average: |
|
60.61% |
| Control |
Test 4 |
67.4% |
36.6% |
48.2% |
| Control |
Test 5 |
59.3% |
30.0% |
43.9% |
| Control |
Test 6 |
72.3% |
34.7% |
56.1% |
| |
All Tests Average: |
|
49.42% |
This shows a very clear increase in accuracy of detection by the sensitive
group in the double blind tests. According to statistical analysis done in the
study itself, this finding was non significant (albeit close to the line between
significance and non-significance).
However, the authors have admitted that the resolving power (based on
number of participants and number of tests) was not good enough to expect a
significant finding - To say that there was no difference between the two
sets of participants in their ability to detect whether the signal is real is a
misrepresentation of the data. This finding in itself should have generated an
official recommendation for further research with better resolving power.
Summary
"Short-term exposure to a typical GSM base
station-like signal did not affect well-being or physiological functions in
sensitive or control individuals. Sensitive individuals reported elevated
levels of arousal when exposed to a UMTS signal. Further analysis, however,
indicated that this difference was likely to be due to the effect of order
of exposure rather than the exposure itself."
Eltiti et al, 2007, Abstract Conclusions
Based on the data above, we believe that the words used by Eltiti
et al in their 2007 provocation paper are highly misleading. We believe
that the sensitive group shows very clear indications that suffered symptoms
do indeed correlate with the real exposures, and it is only due to the
self-confessed insuffient resolving power that the GSM results were not
statistically significant. Considering that the GSM results are elevated (albeit
non-significantly), it is unreasonable to assume that the increase in UMTS
symptom severity is due to that being the first exposure for a disproportionate
number of participants.
We also believe that there is a good argument that the data shows quite
clearly that the sensitive group appear better than the control group at
discerning the difference between real and sham exposures. Again, within the
statistical work of the paper, these increases were found to be non-significant,
but again this is highly likely to be due to the lack of resolving power in the
study.
It would be more suitable to have commented that the findings were not
significant but mention the difficulty of achieving significance due to
resolving power. The findings are therefore not convincing but should be of
concern, and warrant a recommendation of further research with a larger and
filtered set of sensitive participants.
References:
Cohen A et al, (February 2008) Response: Sensitivity to
Mobile Phone Base Station Signals, Environ Health Perspect. 2008 Feb;116(2)
[View Letter]
Eltiti S et al, (November 2007) Does short-term exposure to
mobile phone base station signals increase symptoms in individuals who report
sensitivity to electromagnetic fields? A double-blind randomized provocation
study., Environ Health Perspect. 2007 Nov;115(11):1603-8 [View Abstract]
Eltiti S et al, (February 2007) Development and evaluation
of the electromagnetic hypersensitivity questionnaire, Bioelectromagnetics.
2007 Feb;28(2):137-51 [View Abstract]
Also in the news
Cindy Sage summarises the BioInitiative report on YouTube
The is a 38 minute clip on youtube covering the release of the BioInitiative
report from last year. An interview with Cindy Sage, the primary author of the
report, has been posted on the video sharing service YouTube. This is an excellent summary
of both the report itself, and the decisions and approach that were taken to
produce the report in the first place. It covers some of the sections of the
report in considerable detail.
Martin Walker produces an expose of the Guardian
Entitled "Guardian of What? - The Guardian, the Science Lobby, and the Rise
of Scientific Corporatism", Martin Walker has produced an excellent 19 page
essay covering corporate influence on science and media in the UK. Primarily
focused around much of the Andrew Wakefield / MMR controversy, but also
broadening the remit to cover general issues of misrepresentation of science
in the media (and particularly the Guardian!). It also happens to be
entertaining whilst insightful, and is well worth reading.
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