Re: Single vs multiple set

[Guest guest]

************

Posted by: " Drew Baye " drew@... drew_baye

Cowell asked:

" Honestly, is there anyone out there who truly believes that a single

set protocol is superior to a multi-set protocol for strength, power

or hypertrophy gains? "

In most cases, yes, if for no other reason than it will produce similar

results with less time invested. Like many things, however, it depends on

the individual.

**********************

I recently performed a meta-regression that has been submitted for publication

and is currently under review. My analysis dramatically improves upon the

limitations of previous meta-analyses by Rhea, Wolfe, and others. These papers

have been heavily criticized (and rightly so) for their methodology. I did an

analysis using much stricter inclusion criteria, along with analysis of the

presence of publication bias as well as sensitivity analyses. I also used a

superior statistical model (random effects hierarchical meta-regression).

My analysis clearly shows multiple sets to produce superior strength gains, in

both trained AND untrained subjects. The results were very robust in the

sensitivity analyses, and there was no evidence of publication bias.

I cannot reveal very much since it's currently under review, but it is clear

that the burden of proof lies upon Baye and others to show that single sets are

equivalent to multiple sets. Yet no scientific data is presented. And studies

continue to emerge, in journals other than JSCR (which Baye and others claims to

be biased), by authors not affiliated with Dr. Kraemer or Stone (who also Baye

and others claim to be biased), showing multiple sets to be superior.

However, I think that, despite the accumulating body of evidence indicating a

superiority of multiple sets, Baye and others from the HIT camp will continue to

commit the fallacy of confirmation bias and assert that single sets are

equivalent.

Krieger, M.S., M.S.

Research Associate

20/20 Lifestyles

http://www.2020lifestyles.com

Bellevue, WA

Editor, Journal of Pure Power

http://www.jopp.us

[Guest guest]

Jim,

Please alert the group when that manuscript is accepted for publication. It will

be an invaluable contribution to the field. Of course we can expect the HITters

to dismiss it as " irrelevant " as they continue their nonsense.

Regards,

Plisk

Excelsior Sports, Shelton CT

www.excelsiorsports.com

Prepare To Be A Champion!

=========================

wrote:

I recently performed a meta-regression that has been submitted for publication

and is currently under review. My analysis dramatically improves upon the

limitations of previous meta-analyses by Rhea, Wolfe, and others. These papers

have been heavily criticized (and rightly so) for their methodology. I did an

analysis using much stricter inclusion criteria, along with analysis of the

presence of publication bias as well as sensitivity analyses. I also used a

superior statistical model (random effects hierarchical meta-regression) .

My analysis clearly shows multiple sets to produce superior strength gains, in

both trained AND untrained subjects. The results were very robust in the

sensitivity analyses, and there was no evidence of publication bias.

I cannot reveal very much since it's currently under review, but it is clear

that the burden of proof lies upon Baye and others to show that single sets are

equivalent to multiple sets. Yet no scientific data is presented. And studies

continue to emerge, in journals other than JSCR (which Baye and others claims to

be biased), by authors not affiliated with Dr. Kraemer or Stone (who also Baye

and others claim to be biased), showing multiple sets to be superior.

However, I think that, despite the accumulating body of evidence indicating a

superiority of multiple sets, Baye and others from the HIT camp will continue to

commit the fallacy of confirmation bias and assert that single sets are

equivalent.

Krieger, M.S., M.S.

Research Associate

20/20 Lifestyles

http://www.2020life styles.com

Bellevue, WA

Editor, Journal of Pure Power

http://www.jopp. us

========================

[Guest guest]

There are several really good papers which study the number of sets that produce

optimal benfits. A really good paper to look up is by Rhea et al.

Garrison, CSCS*D

Mesa,AZ

Mesa Community College

================================

To: Supertraining@...: Yngvai@...: Thu, 10 Jan 2008

17:02:47 +0000Subject: Re: Single vs multiple set

************Posted by: " Drew Baye " drew@... drew_baye Cowell

asked: " Honestly, is there anyone out there who truly believes that a singleset

protocol is superior to a multi-set protocol for strength, poweror hypertrophy

gains? " In most cases, yes, if for no other reason than it will produce

similarresults with less time invested. Like many things, however, it depends

onthe individual.**********************I recently performed a meta-regression

that has been submitted for publication and is currently under review. My

analysis dramatically improves upon the limitations of previous meta-analyses by

Rhea, Wolfe, and others. These papers have been heavily criticized (and rightly

so) for their methodology. I did an analysis using much stricter inclusion

criteria, along with analysis of the presence of publication bias as well as

sensitivity analyses. I also used a superior statistical model (random effects

hierarchical meta-regression).My analysis clearly shows multiple sets to produce

superior strength gains, in both trained AND untrained subjects. The results

were very robust in the sensitivity analyses, and there was no evidence of

publication bias.I cannot reveal very much since it's currently under review,

but it is clear that the burden of proof lies upon Baye and others to show that

single sets are equivalent to multiple sets. Yet no scientific data is

presented. And studies continue to emerge, in journals other than JSCR (which

Baye and others claims to be biased), by authors not affiliated with Dr. Kraemer

or Stone (who also Baye and others claim to be biased), showing multiple sets to

be superior.However, I think that, despite the accumulating body of evidence

indicating a superiority of multiple sets, Baye and others from the HIT camp

will continue to commit the fallacy of confirmation bias and assert that single

sets are equivalent. Krieger, M.S., M.S.Research Associate20/20

Lifestyleshttp://www.2020lifestyles.comBellevue, WAEditor, Journal of Pure

Powerhttp://www.jopp.us

====================================

[Guest guest]

Yes, I would love to see this analysis as well.

Plisk wrote:

> Jim,

>

> Please alert the group when that manuscript is accepted for

> publication. It will be an invaluable contribution to the field. Of

> course we can expect the HITters to dismiss it as " irrelevant " as they

> continue their nonsense.

>

> Regards,

>

> Plisk

> Excelsior Sports, Shelton CT

> www.excelsiorsports.com

> Prepare To Be A Champion!

>

> =========================

> wrote:

>

> I recently performed a meta-regression that has been submitted for

> publication and is currently under review. My analysis dramatically

> improves upon the limitations of previous meta-analyses by Rhea,

> Wolfe, and others. These papers have been heavily criticized (and

> rightly so) for their methodology. I did an analysis using much

> stricter inclusion criteria, along with analysis of the presence of

> publication bias as well as sensitivity analyses. I also used a

> superior statistical model (random effects hierarchical meta-regression) .

>

> My analysis clearly shows multiple sets to produce superior strength

> gains, in both trained AND untrained subjects. The results were very

> robust in the sensitivity analyses, and there was no evidence of

> publication bias.

>

> I cannot reveal very much since it's currently under review, but it is

> clear that the burden of proof lies upon Baye and others to show that

> single sets are equivalent to multiple sets. Yet no scientific data is

> presented. And studies continue to emerge, in journals other than JSCR

> (which Baye and others claims to be biased), by authors not affiliated

> with Dr. Kraemer or Stone (who also Baye and others claim to be

> biased), showing multiple sets to be superior.

>

> However, I think that, despite the accumulating body of evidence

> indicating a superiority of multiple sets, Baye and others from the

> HIT camp will continue to commit the fallacy of confirmation bias and

> assert that single sets are equivalent.

>

> Krieger, M.S., M.S.

> Research Associate

> 20/20 Lifestyles

> http://www.2020life styles.com

> Bellevue, WA

> Editor, Journal of Pure Power

> http://www.jopp. us

>

> ========================

>

> __

> .

>

>

--

Hobman

Saskatoon, CANADA

[Guest guest]

> " Honestly, is there anyone out there who truly believes that a single

>set protocol is superior to a multi-set protocol for strength, power

>or hypertrophy gains? "

>

>In most cases, yes, if for no other reason than it will produce similar

>results with less time invested. Like many things, however, it depends on

>the individual.

It appears to me that some of the correspondents here are willfully

ignoring statements and evidence give by proponents of the " other " side.

Just because they are from the " other " side.

In this particular instance some have characterized Drew as a closed

minded advocate of HIT. In the above statement he clearly says " similar "

results with " less time invested. " To me this means that folks whose

main interest is spending little time might be happier with some form of

HIT. Those who have time and want maximal benefit might be happier with

multiple sets. On the other hand it depends on the individual may refer

to the info' that both Drew and I heard presented at a HIT seminar in

Indianapolis that some people (simplistically described as sprinter

types) get better results from HIT and that some people (marathoners)

clearly get superior results from multiple set protocols. My personal

interest in HIT is particular to my personal situation, 70 years old,

wanting to maintain my current high strength levels with the absolute

minimum of weight room time spent. It works a treat for me, as I'm as

stronger than I was 20 years ago when I started it and I only spend 25

minutes once a week in the weight room. The rest of my time is free to

be a kayaker, a computer junky and a traveler. That's what I want.

What is 'superior' or 'better' depends on the goals of the exerciser,

their personal genetic peculiarities, etc. Why all the heat here? And

yes, lets see more references to scientifically adequate studies and

less ad hoc personal criticism.

There that's my quarterly message to Super Training and I'll hush up now.

--

Fair winds and happy bytes,

Dave Flory,

Flower Mound, TX, U.S.A.

--

Speak softly, study Aikido, & you won't need to carry a big stick!

My photos are @ <http://homepage.mac.com/dflory>

[Guest guest]

****************

There are several really good papers which study the number of sets

that produce optimal benfits. A really good paper to look up is by Rhea

et al.

******************

The papers by Rhea et al have a lot of limitations to them. In fact,

one of the purposes that I performed this meta-regression was to

address the shortcomings of these papers.

Krieger, M.S., M.S.

Research Associate

20/20 Lifestyles

http://www.2020lifestyles.com

Bellevue, WA

Editor, Journal of Pure Power

http://www.jopp.us

[Guest guest]

All studies have limitations. Rhea et al can still be a a good paper, right?

Hopefully we can build on a body of research. If you are building on

Rhea et al., then I would say it is a _good_ study.

:^)

shredaholic wrote:

> ****************

> There are several really good papers which study the number of sets

> that produce optimal benfits. A really good paper to look up is by Rhea

> et al.

> ******************

>

> The papers by Rhea et al have a lot of limitations to them. In fact,

> one of the purposes that I performed this meta-regression was to

> address the shortcomings of these papers.

>

> Krieger, M.S., M.S.

> Research Associate

> 20/20 Lifestyles

> http://www.2020lifestyles.com <http://www.2020lifestyles.com>

> Bellevue, WA

> Editor, Journal of Pure Power

> http://www.jopp.us <http://www.jopp.us>

>

> _

> .

>

>

--

Hobman

Saskatoon, CANADA

[Guest guest]

> Casler writes:

>

> Hi .

>

> I am a proponent of " intensity " as a VERY significant training

element, and

> to that end have taken to posting to HIT based forums quite often. The

> amount of training mythology is staggering and the resistance to

evidence

> based discussion is beyond description.

>

> The interesting thing zeros in on your above suggestion, and that

is, there

> is little discussion of training science, or applications, but a

focused and

> endless barrage of personal attacks.

>

> While we all know how the intensity we apply to an exercise makes the

> difference as to the result, that community has taken to applying

" reduced "

> elements of intensity and calling them " more " intense. They fail to

> understand the Physiology, and the Physics of what takes place, and

wish to

> replace it with a " perceptive reality " and unquantifiable element of

how

> " HARD " the exercise feels.

>

> Regards,

>

> Casler

> TRI-VECTOR 3-D Force Systems

> Century City, CA

>

:

Amen. There are times when I consider the " HIT " community as the

HITtites due to the dogged refusal to consider evidence based, data

driven science combined with most all of the markings of a religious

community akin to the Flat Earth Society basing itself on the

revelations now going on forty years of age of Arthur . Personal

attacks combined with " opinion based " autodidactic polemics renders

discussion with such groups impossible. Worse still is the refusal to

come to grips with the fact that with the possible exception of Casey

Viator's 1971 Mr America win, HIT has never fielded a drug free

champion. ' original contention was that his HIT removed the need

for drugs, making the playing field even. Many a HITtite now has Mike

Mentzer on a pedestal of worship, forgetful that Mentzer's sole

contribution to bodybuilding (and catalyzing his own early death) was

the admonition (by means of his behavior) that those with propensity

to substance addiction disorders are treading on shaky ground with

steroids - and other " energetic aids " . So, the big question remains -

what has HIT really accomplished?

Of late HIT devotees have gleefully referred us all to Youtube for

videos of the late Arthur sharing his idiosyncratic crackpot

philosophy with the world. made a major contribution to the

field of exercise equipment in the 20th century; however, his personal

opinions on a wide range of topics well demonstrates how power,

prestige combined with a lack of formal education ensuring skills in

critical thinking easily results in the kind of foolishness rampid

with radio talk show hosts and television news pundits.

I well remember reading when only Ironman Magazine publisher

Peary Rader saw fit to present him to the open forum that remains

Ironman. By that time, 1971, steroids were the biggest open secret of

strength training. offered sobriety. So much so that he openly

advised parents to keep their kids out of bodybuilding and away from

the bad influences of bodybuilders. Many of us benefitted from his

sage advise regarding moderation. Many today criticize early for

" too much volume " .

I'm afraid that without " volume density " and sustained training

intensity we simply will not send athletes to the field of competition

with any staying power. Strapped into a dozen machines emphasizing

sagital plan movement, we will send athletes to the field ready for

injuries in the unconditioned transverse and lateral planes of movement.

It should be noted that Dr Ellington Darden has in recent years

published two books on the theme of " the New HIT " . Due to his own

data, he now offers sample training programs based on both 2 and 3 way

splits, thus up to six days of weekly training. He's also broken the

age old HIT mold with advocacy of " set extending " methods - drop sets,

pre-exhaust, post-exhaust, stage sets, and other protocols used for

decades in the gyms of the world. As I said in my Ironman Magazine

review article of those two books last year, it's doubtful HIT

fundamentals will take his sage advise to heart - it breaks with

traditional models despite his data showing it's the next step. So

while Darden promotes an open-ended empirically driven approach to

HIT, the majority of those populating his site cannot. Those who do

seem largely driven away in resignation to ongoing epiphanies of the

type so well characterizes.

best

Ken O'Neill

Austin, Texas

[Guest guest]

>

> All studies have limitations. Rhea et al can still be a a good paper,

right?

>

> Hopefully we can build on a body of research. If you are building on

> Rhea et al., then I would say it is a _good_ study.

>

Rhea has 2 meta analyses out there, and IMO neither one of them are

very good papers. And unfortunately the flaws in these papers have

given the HIT camp a lot of ammo to work with.

In their first one (published in Res Quarterly), they included studies

that did not meet their reported inclusion criteria. They also

included 93 multiple, non-independent effect sizes (ESs) in their

analysis. This can produce bias in the outcome if you do not use an

appropriate statistical model to account for this. My analysis uses a

statistical model that addresses this issue.

In their second one (published in MSSE), they did not have strictly

defined inclusion/exclusion criteria, and they included studies on

ergogenic aids, diseased populations, and children. So, their study

population was extremely heterogeneous, which doesn't allow for

meaningful analysis of any type of dose-response effect of the number

of sets. This is akin to doing an epidemiological study on the effects

of total fat intake on heart disease, without taking into consideration

confounding factors like energy intake, fat type, activity, etc. They

did not do a statistical analysis of the ESs, and there was little

control for group or study level variables that would affect the

outcomes. Also, this paper suffers from the same issue of non-

independent ESs like their previous paper. I address all of these

issues in my paper.

Krieger, M.S., M.S.

Research Associate

20/20 Lifestyles

http://www.2020lifestyles.com

Bellevue, WA

Editor, Journal of Pure Power

http://www.jopp.us

[Guest guest]

Fair enough! I look forward to reading your paper, as I said. Thanks

for the explanation.

>

> >

> > All studies have limitations. Rhea et al can still be a a good

> paper,

> right?

> >

> > Hopefully we can build on a body of research. If you are building on

> > Rhea et al., then I would say it is a _good_ study.

> >

>

> Rhea has 2 meta analyses out there, and IMO neither one of them are

> very good papers. And unfortunately the flaws in these papers have

> given the HIT camp a lot of ammo to work with.

>

> In their first one (published in Res Quarterly), they included studies

> that did not meet their reported inclusion criteria. They also

> included 93 multiple, non-independent effect sizes (ESs) in their

> analysis. This can produce bias in the outcome if you do not use an

> appropriate statistical model to account for this. My analysis uses a

> statistical model that addresses this issue.

>

> In their second one (published in MSSE), they did not have strictly

> defined inclusion/exclusion criteria, and they included studies on

> ergogenic aids, diseased populations, and children. So, their study

> population was extremely heterogeneous, which doesn't allow for

> meaningful analysis of any type of dose-response effect of the number

> of sets. This is akin to doing an epidemiological study on the effects

> of total fat intake on heart disease, without taking into

> consideration

> confounding factors like energy intake, fat type, activity, etc. They

> did not do a statistical analysis of the ESs, and there was little

> control for group or study level variables that would affect the

> outcomes. Also, this paper suffers from the same issue of non-

> independent ESs like their previous paper. I address all of these

> issues in my paper.

>

> Krieger, M.S., M.S.

> Research Associate

> 20/20 Lifestyles

> http://www.2020lifestyles.com

> Bellevue, WA

> Editor, Journal of Pure Power

> http://www.jopp.us

Hobman

Saskatoon, Canada

[Guest guest]

The study was hetergenous on purpose, but either way you look at it, both

studies clearly showed that multiple sets is better than one, in real world

application.

Garrison, CSCS*D

Mesa, AZ

Mesa Community College

To: Supertraining@...: Yngvai@...: Thu, 10 Jan 2008

22:05:07 +0000Subject: Re: Single vs multiple set

>> All

studies have limitations. Rhea et al can still be a a good paper, right?> >

Hopefully we can build on a body of research. If you are building on > Rhea et

al., then I would say it is a _good_ study.> Rhea has 2 meta analyses out there,

and IMO neither one of them are very good papers. And unfortunately the flaws in

these papers have given the HIT camp a lot of ammo to work with.In their first

one (published in Res Quarterly), they included studies that did not meet their

reported inclusion criteria. They also included 93 multiple, non-independent

effect sizes (ESs) in their analysis. This can produce bias in the outcome if

you do not use an appropriate statistical model to account for this. My analysis

uses a statistical model that addresses this issue.In their second one

(published in MSSE), they did not have strictly defined inclusion/exclusion

criteria, and they included studies on ergogenic aids, diseased populations, and

children. So, their study population was extremely heterogeneous, which doesn't

allow for meaningful analysis of any type of dose-response effect of the number

of sets. This is akin to doing an epidemiological study on the effects of total

fat intake on heart disease, without taking into consideration confounding

factors like energy intake, fat type, activity, etc. They did not do a

statistical analysis of the ESs, and there was little control for group or study

level variables that would affect the outcomes. Also, this paper suffers from

the same issue of non-independent ESs like their previous paper. I address all

of these issues in my paper. Krieger, M.S., M.S.Research Associate20/20

Lifestyleshttp://www.2020lifestyles.comBellevue, WAEditor, Journal of Pure

Powerhttp://www.jopp.us

=======================

[Guest guest]

>

> The study was hetergenous on purpose,

And this is exactly what makes the paper flawed.

If you look at any other meta analysis in any other field, you rarely

see such a large body of heterogeneous studies collected. There are

numerous reasons for this.

1. A meta-analysis is only as good as the studies included. When you

include studies on ergogenic aids, on diseased populations, etc., you

are bringing in many confounding factors that will affect your

results. If you do not somehow address these confounding factors

(which they did not), your results have very little meaning or value.

Also, a meta-analysis of poorly designed studies (they did not

control for study quality) is going to give you skewed results. For

example, if I do a meta-analysis of some poorly designed drug studies

that show a drug to be effective, then my meta-analysis will also show

the drug to be effective. But how can I have confidence in my results

if the studies are poorly designed? My positive result may be more of

an artifact of the poorly designed trials rather than a true positive

effect of the drug.

2. A meta-analysis is essentially an epidemiological study of

studies. In epidemiology, researchers use multivariate models to

control for confounding factors that can affect the outcome. For

example, let's say I do an epidemiological study looking at how total

fat intake relates to heart disease. I find that, as total fat intake

goes up, heart disease goes up. However, how do I know that it's not

a higher calorie intake that's causing it? Higher fat intakes are

associated with higher energy intakes. Or, maybe people with higher

fat intakes are less active. So maybe the lower activity levels are

the reason for the higher heart disease. Or maybe people that have

higher total fat intake are eating more saturated fat. If I don't

account for these things, then my results can be misleading.

The same holds true for Rhea's MSSE paper. For example, they claimed

4 sets to be optimal for trained subjects. However, maybe many of the

studies that used 4 sets also had higher training intensities. Or

maybe the studies that used 4 sets tended to have weaker subjects who

will see greater gains. Or maybe the studies that used 4 sets

involved creatine supplementation or some other ergogenic aid. There

are SO many confounding factors that could play a role. Rhea did not

account for any of this, so you have to take their results with a

grain of salt.

3. If you're going to include a large number of studies with a lot of

heterogeneity, then you NEED to use a statistical model to account for

this heterogeneity and accurately describe the data. For example, my

published meta-analysis on diet (see AJCN February '06) had a

heterogeneous body of studies, but I used a statistical model (random

effects hierarchical meta-regression) to account for this

heterogeneity. Rhea et al did not use any statistical model to

describe their data.

4. Rhea et al simply compared means. Similar to #3, without a

statistical model to describe and compare those means, the results

carry little meaning, as you are not accounting for the level of

uncertainty in your results. For example, maybe the mean ES for 4

sets was higher than 3 sets, but without any confidence intervals or

analysis of these differences, I cannot be sure whether this is a true

difference or just a chance finding.

In fact, I'm surprised the paper by Rhea was even published. If I had

been a reviewer, I would have rejected it outright.

Krieger, M.S., M.S.

Research Associate

20/20 Lifestyles

http://www.2020lifestyles.com

Bellevue, WA

Editor, Journal of Pure Power

http://www.jopp.us

[Guest guest]

>

> The study was hetergenous on purpose,

And this is exactly what makes the paper flawed.

If you look at any other meta analysis in any other field, you rarely

see such a large body of heterogeneous studies collected. There are

numerous reasons for this.

1. A meta-analysis is only as good as the studies included. When you

include studies on ergogenic aids, on diseased populations, etc., you

are bringing in many confounding factors that will affect your

results. If you do not somehow address these confounding factors

(which they did not), your results have very little meaning or value.

Also, a meta-analysis of poorly designed studies (they did not

control for study quality) is going to give you skewed results. For

example, if I do a meta-analysis of some poorly designed drug studies

that show a drug to be effective, then my meta-analysis will also show

the drug to be effective. But how can I have confidence in my results

if the studies are poorly designed? My positive result may be more of

an artifact of the poorly designed trials rather than a true positive

effect of the drug.

2. A meta-analysis is essentially an epidemiological study of

studies. In epidemiology, researchers use multivariate models to

control for confounding factors that can affect the outcome. For

example, let's say I do an epidemiological study looking at how total

fat intake relates to heart disease. I find that, as total fat intake

goes up, heart disease goes up. However, how do I know that it's not

a higher calorie intake that's causing it? Higher fat intakes are

associated with higher energy intakes. Or, maybe people with higher

fat intakes are less active. So maybe the lower activity levels are

the reason for the higher heart disease. Or maybe people that have

higher total fat intake are eating more saturated fat. If I don't

account for these things, then my results can be misleading.

The same holds true for Rhea's MSSE paper. For example, they claimed

4 sets to be optimal for trained subjects. However, maybe many of the

studies that used 4 sets also had higher training intensities. Or

maybe the studies that used 4 sets tended to have weaker subjects who

will see greater gains. Or maybe the studies that used 4 sets

involved creatine supplementation or some other ergogenic aid. There

are SO many confounding factors that could play a role. Rhea did not

account for any of this, so you have to take their results with a

grain of salt.

3. If you're going to include a large number of studies with a lot of

heterogeneity, then you NEED to use a statistical model to account for

this heterogeneity and accurately describe the data. For example, my

published meta-analysis on diet (see AJCN February '06) had a

heterogeneous body of studies, but I used a statistical model (random

effects hierarchical meta-regression) to account for this

heterogeneity. Rhea et al did not use any statistical model to

describe their data.

4. Rhea et al simply compared means. Similar to #3, without a

statistical model to describe and compare those means, the results

carry little meaning, as you are not accounting for the level of

uncertainty in your results. For example, maybe the mean ES for 4

sets was higher than 3 sets, but without any confidence intervals or

analysis of these differences, I cannot be sure whether this is a true

difference or just a chance finding.

In fact, I'm surprised the paper by Rhea was even published. If I had

been a reviewer, I would have rejected it outright.

Krieger, M.S., M.S.

Research Associate

20/20 Lifestyles

http://www.2020lifestyles.com

Bellevue, WA

Editor, Journal of Pure Power

http://www.jopp.us