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R E S E A R C H A R T I C L E Open Access
Estimating the accuracy of muscle response
testing: two randomised-order blinded
studies
Anne M. Jensen
1,2*
, Richard J. Stevens
1,2
and Amanda J. Burls
3
Abstract
Background: Manual muscle testing (MMT) is a non-invasive assessment tool used by a variety of health care
providers to evaluate neuromusculoskeletal integrity, and muscular strength in particular. In one form of MMT
called muscle response testing (MRT), muscles are said to be tested, not to evaluate muscular strength, but neural
control. One established, but insufficiently validated, application of MRT is to assess a patient’s response to semantic
stimuli (e.g. spoken lies) during a therapy session. Our primary aim was to estimate the accuracy of MRT to
distinguish false from true spoken statements, in randomised and blinded experiments. A secondary aim was to
compare MRT accuracy to the accuracy when practitioners used only their intuition to differentiate false from true
spoken statements.
Methods: Two prospective studies of diagnostic test accuracy using MRT to detect lies are presented. A true
positive MRT test was one that resulted in a subjective weakening of the muscle following a lie, and a true negative
was one that did not result in a subjective weakening of the muscle following a truth. Experiment 2 replicated
Experiment 1 using a simplified methodology. In Experiment 1, 48 practitioners were paired with 48 MRT-naïve test
patients, forming unique practitioner-test patient pairs. Practitioners were enrolled with any amount of MRT
experience. In Experiment 2, 20 unique pairs were enrolled, with test patients being a mix of MRT-naïve and not-
MRT-naïve. The primary index test was MRT. A secondary index test was also enacted in which the practitioners
made intuitive guesses (“intuition”), without using MRT. The actual verity of the spoken statement was compared to
the outcome of both index tests (MRT and Intuition) and their mean overall fractions correct were calculated and
reported as mean accuracies.
Results: In Experiment 1, MRT accuracy, 0.659 (95% CI 0.623 - 0.695), was found to be significantly different (p < 0.
01) from intuition accuracy, 0.474 (95% CI 0.449 - 0.500), and also from the likelihood of chance (0.500; p < 0.01).
Experiment 2 replicated the findings of Experiment 1. Testing for various factors that may have influenced MRT
accuracy failed to detect any correlations.
Conclusions: MRT has repeatedly demonstrated significant accuracy for distinguishing lies from truths, compared
to both intuition and chance. The primary limitation of this study is its lack of generalisability to other applications
of MRT and to MMT.
Study registration: The Australian New Zealand Clinical Trials Registry (ANZCTR; www.anzctr.org.au; ID #
ACTRN12609000455268, and US-based ClinicalTrials.gov (ID # NCT01066312).
Keywords: Sensitivity, Specificity, Muscle weakness, Lie detection, Kinesiology
* Correspondence: dranne@drannejensen.com
1
Department of Primary Care Health Sciences, University of Oxford, Oxford,
UK
2
Department for Continuing Education, University of Oxford, Oxford, UK
Full list of author information is available at the end of the article
© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492
DOI 10.1186/s12906-016-1416-2
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Abstrakt
Ziele: Abschätzung der Treffgenauigkeit von kinesiologischem, manuellem Muskelabtasten (Muskelabtasten im
kinesiologischen Stil) (MRT) zum Unterscheiden zwischen Lügen und Wahrheit in gesprochenen Aussagen.
Studiendesign: Zwei prospektive Studien über diagnostische Treffgenauigkeit von MRT zur Entdeckung von Lügen
werden präsentiert. Eine tatsächlich positives MRT Testresultat liegt vor, wenn eine Muskelabschwächung resultierte
und ein tatsächlich negatives MRT bei keiner Muskelabschwächung. Versuch 2 wiederholte Versuch 1 unter
Anwendung einer vereinfachten Methodik.
Durchführungsort: Private Praxen in Grossbritannien und Vereinigte Staaten, mit einem Fundus an Testpatienten
(TPs) aus der lokalen Gesellschaft.
Teilnehmende: Im Versuch 1, 48 Fachausübende wurden mit 48 MRT unbefangenen TPs verkuppelt und formten
damit einmalige Paare von Fachausübenden-TP („Paare“). Fachausübende mit irgend welcher MRT Erfahrung
wurden zugelassen. Im Versuch 2 wurden 20 einmalige Paare zugelassen, wobei die TPs aus einem Mix von MRT
Unbefangenen und Befangenen bestanden.
Testindex: Der prmäre Testindex war MRT. Ein sekundärer Testindex wurde ebenfalls durchgeführt, bei welchem
die Fachausübenden intuitive Vermutungen („Intuition“), ohne Anwendung von MRT., anstellten.
Angewendeter Standardtest (Referenzstandardtest): Der effektive Wahrheitsgehalt der gesprochenen Aussage
wurde verglichen mit dem Resultat des Textindex und das Gesamtmittel des korrekten. Aussageanteils wurde
berechnet und als durchschnittliche Treffgenauigkeit ausgewiesen.
Resultate: Im Versuch 1, MRT Treffgenauigkeit, 0.659 (95% CI 0.623 - 0.695), wurde als signifikant unterschiedlich (p
< 0.01) von intuitiver Treffgenauigkeit, 0.474 (95% CI 0.449 - 0.500),und wie auch von der Zufallswahrscheinlichkeit
(0.500; p < 0.01) identifiziert. Experiment 2 reproduzierte die Ergebnisse des Versuchs 1. Es konnten keine
Korrelationen von anderen Faktoren identifiziert werden, welche die MRT Treffgenauigkeit hätten beeinflussen
können.
Fazit: MRT hat wiederholt signifikante Treffgenauigkeit zum Unterscheiden zwischen Lügen und Wahrheit gezeigt
im Vergleich zu Intuition und Zufall. Die primäre Einschränkung dieser Studie liegt in Mangel der Uebertragbarkeit
auf andere Anwendungsgebiete der MRT.
Background
Manual muscle testing (MMT) is a non-invasive assess-
ment tool used by a variety of health care providers, in-
cluding physiotherapists, chiropractors, osteopaths and
medical doctors, to evaluate neuromusculoskeletal integ-
rity for a variety of purposes [1, 2]. One form of MMT,
muscle response testing (MRT), in which muscles are
tested, not to evaluate muscular strength, but neural
control, emerged following work in the 1970s and1980s by
Goodheart and others [3, 4]. Because MRT is estimated to
be used by over 1 million people worldwide [5], assessing
its validity is necessary. Distinguishing MRT from other
types of manual muscle testing, typically only one muscle
is used for testing, and is tested repeatedly, to detect the
presence of potential target conditions, such as low back
pain [6]. simple phobia [7, 8], and food allergies [9].
One established application of MRT is to assess a pa-
tient’s response to semantic stimuli (e.g. spoken state-
ments) during a therapy session [3, 10, 11]. The semantic
stimulus can be spoken by the patient or the practitioner,
and practitioners monitor a patient’smuscularresistance
to pressure they apply at the same time as they, or the
patients, speak statements. A previous study of 89 test
subjects showed that following the speaking of true state-
ments, a muscle resists significantly more force compared
to after speaking false statements [12]. However, key de-
tails were not reported, such as the number of practi-
tioners taking part and, in particular, the level of blinding.
A protocol was published in 2009 for a randomised con-
trolled trial of such a therapy which uses MRT, but trial
results have not yet reached journal publication [13].
Our primary aim was to estimate the accuracy of MRT
to distinguish false from true spoken statements, in ran-
domised and blinded experiments. A secondary aim was
to compare MRT accuracy to the accuracy when practi-
tioners used only their intuition to differentiate false
from true spoken statements.
Methods
These studies were prospective studies of diagnostic test ac-
curacy, were registered with two clinical trials registries: the
Australian New Zealand Clinical Trials Registry (ANZCTR;
www.anzctr.org.au; ID # ACTRN12609000455268), and
US-based ClinicalTrials.gov (ID # NCT01066312); and
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 2 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
received ethics committee approval to collect data in the
United Kingdom and the United States. For data collection
in the United Kingdom ethics approval was granted from
the Oxford Tropical Research Ethics Committee (OxTREC
Reference Numbers 34-09 and 41-10), and for data col-
lection in the United States, from the Parker University
Institutional Review Board (Approval Numbers R09-09
and R15-10). Consent to publish was obtained from
everyone featured in both Fig. 1 and the Additional file
videos 1 and 2. Written informed consent was obtained
from all participants, and all other tenets of the Declar-
ation of Helsinki were upheld. In addition, these studies
are reported in accordance with the Standards for the
Reporting of Diagnostic Test Accuracy Studies (STARD)
guidelines [14–16]. For STARD Checklists, see Additional
file 3: Table S6 and Additional file 4: Table S7.
The paradigm tested in this study was one in common
use in clinical practice: lying (i.e. speaking a false state-
ment) results in a weak MRT response, whereas telling
the truth (i.e. speaking a true statement) results in a strong
response. We treat a weak muscle response as a positive
index test for diagnosing a lie. If the muscle stayed strong,
it was considered a negative test result for deceit.
For comparison, a second index test was also evalu-
ated: intuition. During this phase, practitioners were
asked to use their intuition (or to “guess”) in order to as-
certain the truthfulness –without using MRT. Because
deceit is known to be accompanied by various physio-
logical changes [17–19], practitioners were asked to use
only their senses to detect deceit: sight (e.g. by observing
body language and facial expressions), hearing (e.g.
changes in voice qualities) and touch (e.g. changes in
skin temperature).
In both experiments, four blocks of 10 MRTs alter-
nated with 4 blocks of 10 intuitions, always beginning
with a MRT block. Practitioners alone determined the
outcome of the MRTs and intuitions, and they them-
selves entered the results into a computer using a
keyboard.
Experiment 1
Participants
Two groups of participants were recruited: (1) Healthcare
practitioners (“practitioners”;n= 48) who routinely use
MRT in practice, and (2) Test Patients (“TPs”;n= 48) who
were naïve to MRT. Each practitioner was paired with a
unique TP and together they formed a unique testing pair
(“pair”;hence,n= 48 unique pairs). Recruitment was by
direct contact (via email or telephone), social media and
word of mouth. Any volunteer was eligible if he or she
was aged 18–65 years, had fully functioning and painfree
upper extremities, and was fluent in English. Volunteers
were excluded if they were blind, deaf or mute. TPs were
also paired with practitioners they did not know. All prac-
titioners who wished to participate and met the inclusion
criteria were enrolled, regardless of their profession, MRT
technique(s) used, or extent of MRT expertise or experi-
ence. No practitioner’s muscle testing ability was assessed
in any way prior to enrolment.
The Primary Index Test: MRT
During a MRT, an external force is applied to a body ap-
pendage and resisted by a particular muscle. At first the
patient holds a specific joint in a fixed position, usually
in partial flexion. The practitioner then applies pressure,
usually into extension, as the patient resists this pressure
using an isometric contraction. For example, the practi-
tioner may ask the patient to hold his shoulder (i.e. the
glenohumeral joint) in 90° flexion, palm facing down,
while he tests the anterior deltoid (see Fig. 1). The prac-
titioner then subjectively determines if the muscle went
“weak”or stayed “strong.”
Practitioners may vary in the amount of pressure ap-
plied and location of the practitioner’s hand [20]. The lo-
cation is routinely on the distal forearm of the patient,
just proximal to the wrist joint, but for the purposes of
this study practitioners were instructed to follow their
usual clinical practice in muscle testing.
Test methods
TPs spoke 40 statements of mixed verity as follows.
They viewed pictures on a computer screen placed out
of view of the practitioners. While viewing a picture se-
lected at random by computer, the TPs were given in-
structions by computerised voice via an earpiece
inaudible to the practitioners. Instructions took the
form, “Say, ‘I see a ________.’” The verity of the state-
ments (that is, whether the instructed statement was
chosen to match the picture on screen) were randomly
allocated by software (DirectRT Research Software,
Fig. 1 An example of a practitioner performing MRT using a
patient's right deltoid muscle
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 3 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Empirisoft Corporation, New York, NY), with overall
prevalence of lies set to be 50 ± 3%. The practitioner also
viewed a computer screen and was randomly shown ei-
ther the same picture as the TP (i.e. not blind) or a blank
black screen (i.e. blind). Participants were blind to study
aims and were not informed of the proportions of True/
False statements or Blind/Not Blind cases. Pictures of
neutral valence (i.e. emotionally neutral) were chosen
from the International Affective Picture System (IAPS;
National Institute of Mental Health Center for Emotion
and Attention, University of Florida, Gainesville, FL)
[21] and paired with neutral words selected from the
Affective Norms for English Words (ANEW; National
Institute of Mental Health Center for Emotion and At-
tention, University of Florida, Gainesville, FL) [22].
Following each statement spoken by the TP, the practi-
tioner was asked to estimate the verity of the statement:
ten times using MRT, followed by ten times using intu-
ition alone, and alternating in blocks of ten thereafter
(see Additional file 5: Figure S1). The practitioner en-
tered their estimate for each statement by single key
press on a keyboard connected to the study computer,
which automatically collated results. Practitioners and
TPs were allowed a short period to familiarise them-
selves with study layout and procedures before begin-
ning, and the principal investigator was present in the
room during data collection but did not take part.
Participants were asked to complete two short ques-
tionnaires, one before testing started and one after test-
ing was completed. The TP Pre-testing Questionnaire
included questions about age, gender, handedness, MRT
experience, and levels of confidence in MRT, in their
practitioner, and their practitioner’s MRT. The pra-
ctitioner pre-testing questionnaire included questions
about age, gender, handedness, type of practitioner, years
in practice, years of MRT experience, self-rated MRT ex-
pertise, specific MRT techniques used, and levels of con-
fidence in MRT in general and their own MRT ability.
Levels of confidence were measured using a 10 cm
Visual Analogue Scale (VAS) with the left end marked
“None”and the right end marked with “Complete Confi-
dence.”All participants were asked to use a “|”to mark
the VAS, which was subsequently assigned a score out of
10. Practitioners were asked to rate their own MRT ex-
pertise using a 5-point Likert scale from 0 (None) to 4
(Expert). We combined categories 1 and 2 of self-
reported expertise due to low numbers (e.g. n= 1 whose
reported their expertise was at level 1). Lengths of time,
such as ages and years in practice, were kept as con-
tinuous variables, while other variables, such as gender,
profession, and MRT techniques used, were kept as cat-
egorical variables.
In the Post-testing Questionnaire, participants were
again asked to rate the same levels of confidence. In
addition, in the Post-testing Questionnaire, TPs were
asked to make open-ended comments about anything
they noticed during the MRT, in order to establish if
they deduced the paradigm under investigation (i.e.
lies result in a “weak”MRT response), so that re-
sponse bias can be measured [23, 24]. As a means of
fidelity assurance during this experiment, the principle
investigator (AJ) was present during all testing and
assessment.
Experiment 2
Following completion and analysis of Experiment 1, a
replication experiment was designed as follows.
Participants
Participants were enrolled in a similar way to Experi-
ment 1; however, the sample size was reduced to 20
pairs, and some non-MRT-naïve TPs were recruited and
enrolled. Also included were some pairs that were
acquainted with each other.
Test methods
The methodology of this study followed that of Experiment
1, with the following exceptions: (1) practitioners in this
study were invariably blind to the verity of the TPs’state-
ments; (2) the pairs were alone in the room for all tests; (3)
practitioners rated their subjective state anxiety prior to
testing; and (4) the prevalence of lies was fixed at 0.50. See
Additional file 6: Figure S2 for the participant flow diagram,
and Fig. 2 for an example of the testing layout.
Statistical methods
For each practitioner-TP pair, accuracy of MRT was de-
fined as the overall fraction correct when using MRT with
the practitioner blinded to the true result. For Experiment
1, pilot data was used to estimate a sample size. In the
pilot, MRT accuracy was found to be 67.7% correct (95%
CI 52.6% to 82.8%). Based on this statistic and using a
95% confidence interval and 80% power, it was estimated
that a study of 48 practitioner-TP pairs would be adequate
to demonstrate whether trained practitioners can use
MRT to distinguish a lie from a truth.
We report mean accuracy of MRT across all patients,
with 95% confidence intervals. Accuracy of intuition was
defined and reported similarly. Prior to analysis, normality
assumptions were checked graphically (data not shown).
Paired t-tests were used to test the null hypothesis that
the mean difference in accuracy between MRT and intu-
ition and zero. Secondary outcomes sensitivity, specificity,
positive predictive value (PPV) and negative predictive
value (NPV) were reported and analysed similarly. Linear
regression was used to test for associations between
accuracy and covariates: age, gender, profession, years in
practice, current practice status, length and degree of
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 4 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
MRT experience, types of MRT techniques trained in, left-
or right-handedness, self-reported score for confidence in
using MRT, and self-reported degree of testing anxiety. All
analyses were restricted to tests for which the practitioner
was blinded to the true answer. Analyses were conducted
in Stata 12.1 (StataCorp LP, College Station, Texas).
Results
Experiment 1
Participants
Forty-eight unique practitioner-TP pairs were enrolled
between June 2010 and October 2011, in the United
Kingdom and the United States. Four volunteer practi-
tioners did not meet the age criteria (i.e. they were
aged > 65 years), one lacked fluency in English and one
was hearing impaired. Of the 48 TPs enrolled, 31 were
female and 17, male, and their mean (Standard Devi-
ation, SD) age was 39.0 (11.4) years. In the sample of
practitioners, there were 16 males and 32 females, the
mean (SD) age was 49.3 (12.0) years, the median
(Interquartile Range, IQR) number of years in practice
was 11.5 (7.3 to 20.8) years, the median (IQR) years of
MRT experience was 11.5 (5.3 to 17.3) years, and the
median (IQR) hours of performing MRT/day was 2.9
Fig. 2 Testing Scenario Layout: aExperiment 1. The Test Patient (TP; red) viewed a monitor (also red) which the Practitioner could not see, had an ear
piece in his ear through which he received instructions, and used a mouse to advance his computer to the next picture/statement. The Practitioner (blue)
also viewed a monitor (also blue) which the Test Patient could not see and entered his results on a keyboard. Note that the Practitioner was presented
with the same picture as the Test Patient or a blank, black screen. Also note that the Principal Investigator (PI) was present in the room and observing
during all assessments. bExperiment 2. The TP (red)viewedamonitor(alsored) which the Practitioner could not see, had an ear piece in his ear through
whichhereceivedinstructions,andusedamousetoadvancehiscomputertothe next picture/statement. In this Experiment, the Practitioner did not view
a monitor, and still entered his results on a keyboard. Note that the Principal Investigator (PI) was absent during this Experiment
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 5 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
(1.0 to 6.0) hours. The mean (SD) self-ranked MRT
Expertisewasfoundtobe3.1(0.2)onascaleof0to4.
For a summary of practitioner demographics, see
Additional file 7: Table S1.
Test results
The primary outcome, MRT accuracy (i.e. overall frac-
tion correct) during tests when the practitioner was
blinded to the truth of the statement, ranged between
0.400 and 0.917, and the mean (95% Confidence Inter-
val, CI) was 0.659 (0.623 to 0.695). The accuracy of intu-
ition for detecting lies during tests when the practitioner
was blinded ranged between 0.238 and 0.636, and the
mean (95% CI) was 0.474 (0.449 to 0.500). The mean ac-
curacy of MRT for detecting lies was significantly greater
than mean accuracy of intuition for detecting lies (p=
0.01; see Table 1). The mean accuracy of MRT for de-
tecting lies was also significantly greater than 0.5 (i.e.
chance;p< 0.01). There was no significant correlation
between practitioners’accuracy using MRT to detect
lies and their accuracy using their intuition to detect
lies (r= -0.03, p= 0.86, 95% CI -0.31 to 0.26).
The mean (95% CI) sensitivity of MRT for detecting
lies was 0.568 (0.504 to 0.633) and the mean (95% CI)
specificity (i.e. accuracy for identifying truth) was 0.734
(0.687 to 0.782), while the mean (95% CI) PPV for MRT
was 0.663 (0.607 to 0.718) and the mean (95% CI) NPV
for MRT was 0.667 (0.625 to 0.708). See Table 1, which
also contains the same statistics for the intuition condi-
tion. The 2x2 tables for each practitioner-TP pair can be
found in Additional file 7: Table S2.
Table 2 shows analyses of accuracy by practitioner
characteristics, and excludes two practitioners who did
not complete the questionnaire. Mean MRT accuracy
(95% CI) by practitioner profession for the 20 chiroprac-
tors who participated was 0.670 (0.611 to 0.729), and for
non-chiropractors, 0.642 (0.593 to 0.691), which were
not significantly different (p= 0.45) in MRT accuracy.
Mean accuracy (95% CI) for those in full-time practice
(n= 26) was 0.663 (0.612 to 0.715), part-time practice (n
= 13), 0.682 (0.618 to 0.746), and not practising (n= 7),
0.569 (0.465 to 0.673), which also were not significantly
different (p= 0.45) in MRT accuracy. Mean MRT accur-
acy (95% CI) of those practitioners who ranked them-
selves in the highest category for expertise as “Expert”
muscle testers (level 4 of 4; n= 15) was 0.682 (0.617 to
0.747), of those who ranked themselves in the second
highest category (level 3 of 4; n= 19) was 0.666 (0.605 to
0.728), and of those who ranked themselves in lower cat-
egories (levels 1 or 2 of 4; n= 12), 0.600 (0.528 to 0.672),
with p= 0.35 for difference between expertise levels.
Table 2 also compares the mean accuracies in
practitioner-TP pairs in which the TP reported guessing
the paradigm with those whose TPs did not. When the
TP reported guessing the paradigm (n= 21), the mean
accuracy of MRT was 0.661 (95% CI 0.591 to 0.730),
and for those pairs in which the TP did not report
guessing the paradigm (n= 27), the mean accuracy of
MRT was 0.649 (95% CI 0.610 to 0.688), and there was
no significant difference between these two groups (p
= 0.38) in MRT accuracy. See Table 2.
There was no obvious trend in accuracy over time
during the course of experiments (see Additional file
7: Table S3 and Additional file 8: Figure S3). A post
hoc analysis found no significant difference between
results in a location which was particularly noisy
compared to other study sites (p= 0.46). With the ex-
ception of shoulder muscle fatigue (n=7 out of 96
participants), no adverse events were reported during
testing.
Experiment 2
Participants
Twenty unique practitioner-TP pairs were enrolled be-
tween July and November 2011, in the United Kingdom
and the United States, including 13 female and 7 male
practitioners, and 8 female and 12 male TPs. The mean
(SD) age for practitioners was 49.3 (12.0) years, and for
TPs, 40.8 (12.8) years. Of the 20 practitioners enrolled
there were 14 chiropractors, 2 mental health pro-
fessionals, 1 acupuncturist, and 3 other health
Table 1 Comparing mean accuracy statistics (with 95% Confidence Intervals) of MRT and Intuition, for Experiments 1 and 2
Experiment 1 Experiment 2
(n= 48) (n= 20)
MRT Intuition MRT Intuition
Mean 95% CI Mean 95% CI p-value Mean 95% CI Mean 95% CI p-value
Overall Fraction Correct 0.659 0.623 - 0.695 0.474 0.449 - 0.500 <0.01* 0.594 0.541 - 0.647 0.514 0.483 - 0.544 0.01*
Sensitivity 0.568 0.504 - 0.633 0.429 0.374 - 0.484 <0.01* 0.583 0.534 - 0.631 0.603 0.555 - 0.650 0.61
Specificity 0.734 0.687 - 0.782 0.479 0.416 - 0.542 <0.01* 0.613 0.553 - 0.673 0.494 0.427 - 0.561 0.01
Positive Predictive Value 0.663 0.607 - 0.718 0.527 0.460 - 0.594 <0.01* 0.685 0.616 - 0.754 0.603 0.555 - 0.650 0.06
Negative Predictive Value 0.667 0.625 - 0.708 0.392 0.335 - 0.448 <0.01* 0.503 0.421 - 0.584 0.425 0.356 - 0.494 0.07
MRT muscle response testing, CI confidence interval; *reached significance
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 6 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 2 The influence on various categorical participant characteristics on MRT Accuracy. (1) Practitioner profession, (2) Practitioner’s practising status, (3) Practitioner’s
self-ranked MRT expertise,
c
and (4) If the test patient reported guessing the paradigm
MRT ACCURACY
(1) (2) (3) (4)
Practitioner profession Practitioner practising status Self-ranked MRT experise TP reported guessing the paradigm?
Chiropractors All others Full Time Part Time Not Practising 4 3 1 or 2 Yes No
(n= 20) c (n=26) (n= 13) (n=7) (n= 15) (n= 19) (n=12) (n= 21) (n=27)
Experiment 1 Mean 0.670 0.642 0.663 0.682 0.569 0.682 0.666 0.600 0.661 0.649
95% CI 0.611 - 0.729 0.593 - 0.691 0.612 - 0.715 0.618 - 0.746 0.465 - 0.673 0.617 - 0.747 0.605 - 0.728 0.528 - 0.672 0.591 - 0.730 0.610 - 0.688
p-value 0.45
a
0.13
b
0.35
b
0.38
Experiment 2 Chiropractors All other Full Time Part Time Not Practising 4 3 2 Yes No
(n= 14) (n=6) (n=14) (n=4) (n=2) (n=7) (n= 10) (n=3) (n=6) (n=14)
Mean 0.607 0.563 0.561 0.706 0.600 0.611 0.590 0.567 0.621 0.582
95% CI 0.535 - 0.679 0.478 - 0.647 0.504 - 0.618 0.508 - 0.905 0.000 - 1.000 0.470 - 0.751 0.518 - 0.662 0.387 - 0.746 0.507 - 0.735 0.515 - 0.650
p-value 0.36 0.07 0.86 0.49
MRT muscle response testing, CI confidence interval;
a
t-test result;
b
ANOVA result;
c
Practitioners were asked to rank their own MRT ability from 0 (“None”)to4(“Expert”)
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 7 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
professionals. Fourteen practitioners were in full-time
practice, 4 were in part-time practice, and 2 were not
currently practising. The practitioners’median (IQR)
number of years in practice was 18.0 (17.0) years, the
median (IQR) years of MRT experience was 14.0 (16.0),
and the median (IQR) hours of performing MRT/day
was 4.0 (4.0). The mean (SD) self-ranked MRT Expertise
was found to be 3.2 (0.7) on a scale of 0 to 4. For a sum-
mary of practitioner demographics, see Additional file 7:
Table S1.
Test results
In Experiment 2, the mean (95% CI) MRT accuracy (i.e.
overall fraction correct) for detecting lies was 0.594
(0.541 to 0.647), and ranged between 0.425 and 0.825.
The mean (95% CI) accuracy when using intuition for
detecting lies was 0.514 (0.483 to 0.544), and ranged
between 0.375 and 0.625. The mean accuracy when
using MRT for detecting lies was significantly greater
than when using intuition (p= 0.01; see Table 1). The
mean accuracy of MRT was also significantly greater
than 0.5 (i.e. chance;p< 0.01). There was no significant
correlation between practitioners’accuracy using MRT
for detecting lies and their accuracy using their intu-
ition (r= 0.07, p= 0.77, 95% CI -0.38 to 0.50).
The mean (95% CI) sensitivity for MRT for detecting
lies was 0.583 (0.534 to 0.631) and the mean (95% CI)
specificity (i.e. the accuracy of MRT for detecting truth)
was 0.631 (0.553 to 0.673), while the mean (95% CI)
PPV for MRT was 0.685 (0.616 to 0.754) and the mean
(95% CI) NPV for MRT was 0.503 (0.421 to 0.584). See
Table 1, which also contains the same statistics for the
intuition condition. The 2x2 tables for each practitioner-
TP pair can be found in Additional file 7: Table S4.
Analyses of MRT accuracy by practitioner characteris-
tics can be found in Table 2. The mean MRT accuracy
(0.607; 95% CI 0.535 to 0.679) for the 14 chiropractors
who participated was not significantly different (p= 0.36)
from the mean MRT accuracy (0.563; 95% CI 0.478 to
0.647) for the 6 non-chiropractors. The mean accuracy
(95% CI) for those in full-time practice (n= 14) was
0.561 (0.504 to 0.618), part-time practice (n= 4), 0.706
(0.508 to 0.905), and not practising (n= 2), 0.600 (0.000
to 1.000), and there was no significant difference between
these groups (p= 0.07) in MRT accuracy. The mean MRT
accuracy (95% CI) of those practitioners who ranked
themselves in the highest category for expertise (i.e. “Ex-
pert”) in muscle testing (level 4 of 4; n= 7) was 0.611
(0.470 to 0.751), of those who ranked themselves in the
second highest category (level 3 of 4; n= 10) was 0.590
(0.518 to 0.662), and of those who ranked themselves in
lower categories (levels 1 or 2 of 4; n= 3), 0.567 (0.387 to
0.746), and there was no significant difference between
these groups (p= 0.86) in MRT accuracy. Table 2 also
compares the mean accuracies in practitioner-TP pairs in
which the TP reported guessing the paradigm with those
which the TPs did not. When the TP reported guessing
the paradigm (n= 6), the mean accuracy of MRT was
0.621 (95% CI 0.507 to 0.735), and for those pairs which
the TP did not report guessing the paradigm (n=14), the
mean accuracy of MRT was 0.582 (95% CI 0.515 to 0.650),
and no significant difference was found between these two
groups (p= 0.49) in MRT accuracy. See Table 2. Similar to
Experiment 1, with the exception of muscle fatigue (n=4
out of 40 participants), no adverse events were reported
during testing.
Discussion
Statement of the principal findings
Muscle response testing (MRT) used for distinguishing
false from true spoken statements was consistently
found to be more accurate than would be expected by
chance. It was also better than intuition employed by the
same practitioner, indicating that success was due to the
muscle testing component rather than, for example,
body language or voice qualities. These studies provide
one step toward proof of concept for this application of
MRT. They also demonstrate that scientific methods, in-
cluding blinding and randomisation, can be used in the
assessment of tests used by complementary and alterna-
tive medicine practitioners, such as MRT.
All analyses presented here were for tests for which
the practitioner was blinded to the true answer; results
for test in which the practitioner was not blinded, and
for a further experiment in which the practitioner was
actively deceived, have been reported elsewhere [25].
Strengths and limitations
These studies did not standardise MRT methods, for in-
stance, by utilising force plates to monitor pressure. The
strength of this approach is that the MRT performed in
these studies is comparable to that used by these practi-
tioners in their clinical practice. Supporting this deci-
sion, previous studies using force plates showed a
distinct difference between muscles labelled “strong”and
“weak”[12, 26, 27], making their use in these studies re-
dundant. Other strengths include the high degree of
blinding and well-defined reference standard and target
condition. However, the statements used as reference
standard were not designed to be representative of those
that might be of interest in clinical practice. We did not
evaluate MRT against other widely-used methods of ‘lie
detection’, such as polygraph [28]. Other proposed appli-
cations of MRT, such as for the diagnosis of a food al-
lergy [9, 29] or the need for a nutritional supplement
[30] or to assess athletic performance [31–33], are be-
yond the scope of our studies.
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 8 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Although practitioners were blinded to veracity of the
statement, test patients necessarily were not. However,
there was no significant difference in results between pairs
in which the test patient guessed the paradigm (that
strong response indicated a true statement) and other
pairs, making it less likely that results are explained by test
patients consciously or nonconsciously biasing the test. In
addition, these studies would have been strengthened if
the order of the blocks were randomised, with some pairs
starting with MRT and other pairs starting with Intuition.
Strengths and weaknesses in relation to other studies
One other published study attempted to estimate the ac-
curacy of MRT to distinguish truth from lies [12]. How-
ever, in this study, specific characteristics about the
practitioners performing the MRT are unclear, such as
how many were enrolled, how they were recruited, the in-
clusion/exclusion criteria, and the degree of practitioner
blinding [12]. These important features may have limited
the usefulness of this study. Another study assessed practi-
tioners ability to distinguish weak from strong responses,
but did not examine whether this was correlated with true
and false, therefore a practical comparison is difficult [34].
Implications for clinical practice and future research
We have provided one step toward proof of concept that
MRT is better than chance alone at distinguishing true
from false statements. However, the statements studied
here are not necessarily typical of those relevant in prac-
tice, and the average accuracy, though significantly bet-
ter than chance or intuition, was found to be 60 to 70%.
The accuracy necessary for improving patient outcomes
in practice is unclear and may depend upon factors be-
yond the scope of our studies [35, 36]. The variation in
accuracy between those pairs assessed may suggest the
existence of practitioner characteristics that influence ac-
curacy; if so, and if these are modifiable characteristics,
it may be possible to develop protocols for consistently
high accuracy.
We have demonstrated that scientifically rigorous
methods, including blinding, randomness, use of a com-
parator, and formal statistical analysis, can be applied
constructively to MRT research. Research is needed to
assess the usefulness of MRT for detecting other
commonly-used target conditions, such as the need for
nutritional supplementation [13, 20, 36, 37] or in the
identification of an allergy or hypersensitivity or toxicity
[3, 9, 11, 22, 38–45].
Future research in the diagnostic usefulness of MRT
should employ rigorous methods, including: (1) a clear
and specific research objective, (2) a well-defined target
condition, (3) explicit outcomes that are easy to inter-
pret, (4) an appropriate sample of the target population
(who were objectively selected), (5) an objective
reference standard, (6) an adequate sample size, and (7)
appropriate blinding [36].
Finally, due to its widespread use [5], MRT’s true clinical
value must be explored [38, 46–50]. Toward this end, the
efficacy of MRT technique systems must be investigated
via rigorously-designed randomised, controlled trials
(RCTs). For example, future researchers may want to ex-
plore the effectiveness of alternative stress reduction tech-
niques which use MRT, such as HeartSpeak, for such
conditions as depression or panic attacks, compared to
traditional psychological approaches, such as cognitive be-
havioural therapy.
Conclusion
Muscle response testing (MRT) has repeatedly been
found to be significantly more accurate than both intu-
ition and chance, for one application of this common as-
sessment method: distinguishing lies from truths. No
test is perfect: 100% accurate, easy to use, risk-free and
low cost [36, 41]. However, these results are encour-
aging. It is hoped that this report will encourage further
research on the clinical utility of MRT.
Additional files
Additional file 1: Sample Test Patient Stimuli. (WMV 4350 kb)
Additional file 2: Sample of Pair testing. (WMV 6250 kb)
Additional file 3: Table S6. STARD checklist for reporting of studies of
diagnostic accuracy: Experiment 1. (DOCX 19 kb)
Additional file 4: Table S7. STARD checklist for reporting of studies of
diagnostic accuracy: Experiment 2. (DOCX 19 kb)
Additional file 5: Figure S1. Participant Flow Diagram - Experiment 1.
(JPG 56 kb)
Additional file 6: Figure S2. Participant Flow Diagram - Experiment 2.
(JPG 59 kb)
Additional file 7: Table S1. Demographics of Practitioners - Experiments
1&2.Table S2. 2x2 Table for MRT for each Pair (n=48) in Experiment 1.
Table S3. Correlations (r) with p-values among MRT. Table S4. 2x2 Tables
for MRT for each Pair in Experiment 2 (n=20). Table S5. Correlations (r)
among MRT Accuracy and Practitioner haracteristics for Experiments 1 & 2.
p(2-tailed)< 0.05. (XLS 75 kb)
Additional file 8: Figure S3. kMMT Accuracy by Block with 95%
Confidence Intervals. (DOCX 18 kb)
Abbreviations
CI: Confidence interval; FN: False negatives; FP: False positives; IQR: Interquartile
range; MMT: Manual muscle testing; MRT: Muscle response testing; NPV: Negative
predictive value; PPV: Positive predictive value; SD: Stand ard deviati on;
STARD: Standards for the Reporting of Diagnostic Test Accuracy
Studies; TP: Test patient
Acknowledgements
We are grateful to all study participants for their contributions, and for the
support from Wolfson College (Oxford University), Parker University and those
practitioners who offered the use of their facilities during data collection.
Portions of this study have been presented in poster or abstract form at
scientific conferences [51–59].
Funding
None.
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 9 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Availability of data and materials
Summary statistics are available from the principle investigator upon request.
Authors’contributions
All authors make substantial contributions to conception and design, and/or
acquisition of data, and/or analysis and interpretation of data; all authors
participate in drafting the article or revising it critically for important intellectual
content; and all authors give final approval of the version to be submitted and
any revised version. Concept development: AMJ, AJB; Design: AMJ, RJS, AJB;
Supervision: AMJ, RJS, AJB; Data collection: AMJ; Data processing: AMJ, RJS;
Analysis/interpretation: AMJ, RJS; Literature search: AMJ; Writing: AMJ; Critical
review: AMJ, RJS, AJB; All authors read and approved the final manuscript.
Competing interests
The authors declared that they have no competing.
Consent for publication
Consent to publish was obtained from every participant appearing in any
image, figure or video.
Ethics approval and consent to participate
These studies received ethics committee approval to collect data in the
United Kingdom and the United States. For data collection in the United
Kingdom ethics approval was granted from the Oxford Tropical Research
Ethics Committee (OxTREC; Reference Numbers 34-09 and 41-10), and for
data collection in the United States, from the Parker University Institutional
Review Board (Approval Numbers R09-09 and R15-10). Written informed
consent was obtained from all participants.
Transparency declaration
The lead author affirms that this manuscript is an honest, accurate, and
transparent account of the studies being reported; that no important
aspects of the studies have been omitted; and that any discrepancies from
the studies as planned (and, if relevant, registered) have been explained.
Author details
1
Department of Primary Care Health Sciences, University of Oxford, Oxford,
UK.
2
Department for Continuing Education, University of Oxford, Oxford, UK.
3
School of Health Sciences, City University London, London, UK.
Received: 29 November 2015 Accepted: 18 October 2016
References
1. Kendall FK, McCreary EK. Muscles: Testing & Function. 4th ed. Baltimore:
Williams & Wilkins; 1993.
2. Magee DJ, Sueki D. Orthopedic physical assessment atlas and video:
Selected special tests and movements. St. Louis: Elsevier Saunders; 2011.
3. Thie J, Thie M. Touch for health: A practical guide to natural health.
Camarillo (CA): DeVorss Publications; 2005.
4. Walther DS. Applied Kinesiology: Synopsis, vol. 1. 2nd ed. Pueblo: Systems
DC; 2000.
5. Jensen AM. Estimating the prevalence of use of kinesiology-style manual
muscle testing: A survey of educators. Adv Intern Med. 2015;2(2):96–102.
6. Pollard H, Bablis P, Bonello R. Can the ileocecal valve point predict low back
pain using manual muscle testing? Chiropr J Austr. 2006;36:58–62.
7. Peterson KB. A preliminary inquiry into manual muscle testing response in
phobic and control subjects exposed to threatening stimuli. J Manipulative
Physiol Ther. 1996;19(5):310–6.
8. Jensen AM, Ramasamy A. Treating spider phobia using Neuro Emotional
Technique™: Findings from a pilot study. J Altern Complement Med. 2009;
15(12):1363–74.
9. Garrow JS. Kinesiology and food allergy. Br Med J. 1988;296(6636):1573–4.
10. Walker SW. Neuro Emotional Technique® Certification Manual. Encinitas
(CA): Neuro Emotional Technique, Inc.; 2004.
11. Touch for Health Instructors Association of Australia. 2013. Retrieved 11
June 2013, from http://www.touch4health.org.au.
12. Monti DA, Sinnott J, Marchese M, Kunkel EJS, Greeson JM. Muscle test
comparisons of congruent and incongruent self-referential statements.
Percept Mot Skills. 1999;88(3):1019–28.
13. Brown BT, Bonello R, Pollard H, Graham P. The influence of a
biopsychosocial-based treatment approach to primary overt
hypothyroidism: A protocol for a pilot study. Trials. 2010;11:106. https://
www.ncbi.nlm.nih.gov/pubmed/21073760.
14. Bossuyt PMM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM,
Moher D, Rennie D, De Vet HCW, Lijmer JG. The STARD statement for
reporting studies of diagnostic accuracy: Explanation and elaboration.
Clin Chem. 2003;49(1):7–18.
15. Bossuyt PMM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM,
Lijmer JG, Moher D, Rennie D, de Vet HC. Towards complete and accurate
reporting of studies of diagnostic accuracy: The STARD initiative. Br Med J.
2003;326:41–4.
16. Bossuyt PM, Leeflang MM. Chapter 6: Developing Criteria for Including
Studies. In: Cochrane Handbook for Systematic Reviews of Diagnostic Test
Accuracy Version 0.4 [updated September 2008]. London: The Cochrane
Collaboration; 2008.
17. Yamaoka K. A psychophysiological study of determinants for detection of
deception. Bull Tokyo Med Dent Univ. 1976;23(1):11–22.
18. Williams JA, Burns EL, Harmon EA. Insincere utterances and gaze: Eye
contact during sarcastic statements. Percept Mot Skills. 2009;108(2):565–72.
19. Ben-Shakhar G, Elaad E. The validity of psychophysiological detection of
information with the guilty knowledge test: A meta-analytic review. J Appl
Psychol. 2003;88(1):131–51.
20. Schmitt WH, Cuthbert SC. Common errors and clinical guidelines for
manual muscle testing: “The arm test”and other inaccurate procedures.
Chiropr Osteopat. 2008;16:16. https://www.ncbi.nlm.nih.gov/pubmed/
19099575.
21. Lang PJ, Bradley MM, Cuthbert BN. International Affective Picture System
(IAPS): Affective ratings of pictures and instruction manual. Technical Report
A-8. Gainesville: University of Florida; 2008.
22. Bradley MM, Lang PJ. Affective Norms for English Words (ANEW): Stimuli,
instruction manual and affective ratings. Technical report C-1. Gainesville:
The Center for Research in Psychophysiology, University of Florida; 1999.
23. McGrath RE, Mitchell M, Kim BH, Hough L. Evidence for response bias as a
source of error variance in applied assessment. Psychol Bull. 2010;136(3):
450–70.
24. King MF, Bruner GC. Social desirability bias: A neglected aspect of validity
testing. Psychol Mark. 2000;17(2):79–103.
25. Jensen AM. The accuracy and precision of kinesiology-style manual muscle
testing, DPhil. Oxford: University of Oxford; 2015.
26. Caruso W, Leisman G. The clinical utility of force/displacement analysis of
muscle testing in Applied Kinesiology. Int J Neurosci. 2001;106(3–4):147–57.
27. Conable K, Corneal J, Hambrick T, Marquina N, Zhang J. Electromyogram
and force patterns in variably timed manual muscle testing of the middle
deltoid muscle. J Manipulative Physiol Ther. 2006;29(4):305–14.
28. Grubin D, Madsen L. Lie detection and the polygraph: A historical review.
J Forens Psychiatry Psychol. 2005;16(2):357–69.
29. Teuber SS, Porch-Curren C. Unproved diagnostic and therapeutic
approaches to food allergy and intolerance. Curr Opin Allergy Clin
Immunol. 2003;3(3):217–21.
30. Triano JJ. Muscle strength testing as a diagnostic screen for supplemental
nutrition therapy: A blind study. J Manipulative Physiol Ther. 1982;5(4):179–82.
31. Jensen AM. A mind-body approach for precompetitive anxiety in power-
lifters: 2 case studies. J Chiropr Med. 2010;9(4):184–92.
32. Jensen AM. The use of Neuro Emotional Technique with competitive
rowers: A case series. J Chiropr Med. 2011;10(2):111–7.
33. Jensen AM, Ramasamy A, Hall MW. Improving general flexibility with a
mindbody approach: A randomized, controlled trial using Neuro Emotional
Technique. J Strength Cond Res. 2012;26(8):2103–12.
34. Caruso W, Leisman G. A force/displacement analysis of muscle testing.
Percept Mot Skills. 2000;91(2):683–92.
35. Altman DG. Practical statistics for medical research. London: Chapman &
Hall/CRC; 1999.
36. Peeling RW, Smith PG, Bossuyt PM. A guide for diagnostic evaluations.
Nat Rev Microbiol. 2010;8(12 Suppl):S2–6.
37. Buhler CF, Burgess PR, VanWagoner E. Changes in physical strength during
nutritional testing. J Scientific Exploration. 2008;22(4):495–515.
38. Ferrante Di Ruffano L, Hyde CJ, McCaffery KJ, Bossuyt PMM, Deeks JJ.
Assessing the value of diagnostic tests: A framework for designing and
evaluating trials. BMJ (Online). 2012;344(7847):e686. https://www.ncbi.nlm.
nih.gov/pubmed/22354600.
Jensen et al. BMC Complementary and Alternative Medicine (2016) 16:492 Page 10 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
39. Kleine-Tebbe J, Herold DA. Inappropriate test methods in allergy.
Ungeeignete Testverfahren in der Allergologie. 2010;61(11):961–6.
40. Wüthrich B. Unproven techniques in allergy diagnosis. J Investig Allergol
Clin Immunol. 2005;15(2):86.
41. Riedel M. Diagnosing pulmonary embolism. Postgrad Med J. 2004;80(944):
309–19.
42. Banis U. Diagnosis of allergy with kinesiology - A critical view.
Allergiediagnostik mit der kinesiologie - Eine kritische betrachtung. 2001;
42(6):414–7.
43. Schmitt Jr WH, Leisman G. Correlation of Applied Kinesiology muscle
testing findings with serum immunologobulin levels for food allergies.
Int J Neurosci. 1998;96(3–4):237–44.
44. Staehle HJ, Koch MJ, Pioch T. Double-blind study on materials testing with
Applied Kinesiology. J Dent Res. 2005;84(11):1066–9.
45. Schwartz SA, Utts J, Spottiswoode SJP, Shade CW, Tully L, Morris WF,
Nachman G. A double-blind, randomized study to assess the validity of
Applied Kinesiology (AK) as a diagnostic tool and as a nonlocal proximity
effect. Explore (NY). 2014;10(2):99–108.
46. Fryback DG, Thornbury JR. The efficacy of diagnostic imaging. Med Decis
Making. 1991;11(2):88–94.
47. Bossuyt PMM. Defining biomarker performance and clinical validity. J Med
Biochem. 2011;30(3):193–200.
48. Schünemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, Vist GE,
Williams Jr JW, Kunz R, Craig J, Montori VM, et al. GRADE: Grading quality of
evidence and strength of recommendations for diagnostic tests and
strategies. BMJ. 2008;336(7653):1106–10.
49. Bossuyt PMM, Reitsma JB, Linnet K, Moons KGM. Beyond diagnostic accuracy:
The clinical utility of diagnostic tests. Clin Chem. 2012;58(12):1636–43.
50. Glasziou P, Irwig L, Deeks JJ. When should a new test become the current
reference standard? Ann Intern Med. 2008;149(11):816–21.
51. Jensen AM, Stevens R, Burls A. The accuracy of kinesiology-style manual
muscle testing to distinguish congruent from incongruent statements
under varying levels of blinding: Results from a study of diagnostic test
accuracy. In: European Chiropractors’Union (ECU) 2012 Convention: May
2012; Amsterdam, The Netherlands.
52. Jensen AM, Stevens R, Burls A. Is muscle testing a form of biofeedback?
Results from a study of diagnostic test accuracy. In: Association for Applied
Psychophysiology & Biofeedback (AAPB) Annual Meeting: March 2012;
Baltimore, MD.
53. Jensen AM, Stevens R, Kenealy T, Stewart J, Burls A. The accuracy of
kinesiology-style manual muscle testing: A proposed testing protocol and
results from a pilot study. In: Association of Chiropractic Colleges Research
Agenda Conference (ACC RAC). Edited by Johnson C. Las Vegas, NV.
54. Jensen AM, Stevens R, Kenealy T, Stewart J, Burls A. The accuracy of
kinesiology-style manual muscle testing to distinguish congruent from
incongruent statements under varying levels of blinding: Results from a
study of diagnostic test accuracy. In: World Federation of Chiropractic 11th
Biennial Congress: 6–9 April 2011; Rio de Janiero, Brazil.
55. Jensen AM, Stevens RJ, Burls AJ. Developing the evidence for kinesiology-
style manual muscle testing: Designing and implementing a series of
diagnostic test accuracy studies. In: Evidence Live 2013. Oxford, UK; 2013.
56. Jensen AM, Stevens RJ, Burls AJ. The accuracy of kinesiology-style manual
muscle testing to distinguish true spoken statements from false: The results
of 2 studies of diagnostic test accuracy. In: 5th Sacro Occipital Technique
Research Conference: 2 May 2013: Sacro Occipital Technique Organization.
57. Jensen AM, Stevens RJ, Burls AJ. Developing the evidence for kinesiology-
style manual muscle testing: Designing and implementing a series of
diagnostic test accuracy studies. In: European Chiropractors’Union (ECU)
2014 Convention: May 2014; Dublin, Ireland.
58. Jensen AM, Stevens RJ, Burls AJ. Developing the evidence for kinesiology-
style manual muscle testing: Designing and implementing a series of
diagnostic test accuracy studies. In: 1st Annual General Meeting of The
Royal College of Chiropractors: 29 January 2014; London: Royal College of
Chiropractors.
59. Jensen AM, Stevens RJ, Burls AJ. Developing the evidence for kinesiology-
style manual muscle testing: Designing and implementing a series of
diagnostic test accuracy studies. In: International Research Conference on
Integrative Medicine & Health (IRCIMH): 13–16 May 2014; Miami, Florida, USA.
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