Evidence-Based Normative Data in Lumbar Flexion Control Tests; a Pilot Study

NORTHUMBRIA UNIVERSITY

SCHOOL OF HEALTH AND LIFE SCIENCES

MSc Physiotherapy (Pre-Registration)

Research Dissertation

‘Evidence-Based Normative Data in Lumbar Flexion

Control Tests; a Pilot Study’

Samuel Stuart BSc (Hons)

05009713

A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE

REQUIREMENTS OF

THE DEGREE OF MASTER OF SCIENCE

Words: 14,881

1st October 2012

ABSTRACT

Study Design: Descriptive pilot study.

Objectives: To develop evidence-based ‘normative’ data for range of movement (ROM)

at the hip, knee and lumbar spine during four clinical tests for lumbar flexion control.

Summary of background data: Recently several studies have highlighted movement

control dysfunction of the lumbar region as a potential diagnostic area. However,

evidence-based ‘normative’ ROM data for a ‘normal’ population has yet to be

uncovered, making lumbar control assessments difficult. This is the first study to utilize

a biomechanical device to evaluate the ROM during lumbar flexion control tests.

Methods: 20 people without LBP performed 4 clinical tests involving the control of

lumbar flexion. ROM during the tests was evaluated using electrogoniometry at the hip,

knee and lumbar spine. The lumbar spine electrode monitored flexion control and 5

degrees of lumbar flexion was classed as a loss of control. Each participant was

recorded performing the tests 3 times after being taught the tests by the researcher.

Results: Average ROM values were shown to be 10-15° less than the previously

reported values. The intra-measure and inter-rater agreement results demonstrated that

the majority of the ROM variables had moderate or above (>0.4) correlation. However,

several of the results showed poor (<0.2) to fair (>0.2 – 0.4) intra-measure agreement

and inter-rater agreement. Bland-Altman Plots showed that the majority of the ROM

differences were within 1°-10°, however there were outliers of up to 30° difference.

Therefore, there were large variations in the ROM measurements between test attempts

due to the limitations of the data collection procedures.

Conclusions: This study was not able to provide accurate ‘normative’ ROM values due

to the limitations of the methodology. However, the conclusion of this pilot study was

that the lumbar flexion control testing methodology is feasible but requires

modifications. Further study is required on the validity of the utilised motor control tests.

TABLE OF CONTENTS

1 CHAPTER 1

Introduction 1

1.1 Literature Review

1.2 Lumbar Stability 4

1.3 Pain Alteration in LBP 6

1.4 Motor Control 7

1.5 Feedback and Feed-forward Control 9

1.6 Motor Control Assessment 11

1.7 Neutral Zone 13

1.8 Reliability and Validity 14

1.9 Range of Movement 16

1.9.1 Research Objectives

2 CHAPTER 2 Methodology

2.1 Rationale 21

2.2 Study Design 21

2.3 Study sample 22

2.4 Ethics 23

2.5 Baseline Measurements 23

2.5.1 Equipment 24

2.6 Lumbar Flexion Motor Control Tests 24

2.7 Electrogoniometry: Reliability and Validity 25

2.8 Data Collection Protocol 26

2.9 Data Analysis 27

3 CHAPTER 3 Results

3.1 Baseline Measurements 30

3.2 Lumbar Flexion Control Tests 31

3.3 Intra-measure Repeatability 40

3.4 Inter-rater Agreement 43

3.5 Association of Other Parameters 44

4 CHAPTER 4 Discussion

4.1 Normative Range of Movement 47

4.2 Methodological Reliability 48

4.3 Novice-Expert Variation 50

4.4 Feed-Forward and Feedback Mechanisms 51

4.5 Skin Movement and Distraction 54

4.6 Fasciae Influence on Range of Movement 57

4.7 Lumbar Spine Neutral Zone Range of Movement 59

4.8 Associated and Compensatory Factors 60

4.9 Recommendations for Future Studies 63

5 CHAPTER 5

Conclusion 64

REFERENCES 66

List of Figures

Figure 1 – Literature Review Search Terms and Results .......................................................................... 19

Figure 2 - Waiters Bow Bland-Altman Plots (Attempt 2 and 3)…………………………………………………35

Figure 3 - Seated Knee Extension Bland-Altman Plots (Attempts 2 and 3)…………………………………..36

Figure 4 - Sitting Forward Lean Bland-Altman Plots (Attempts 2 and 3)………………………………….…..37

Figure 5 - Rocking Backwards in Four Point Kneeling Bland-Altman Plots (Attempts 2 and 3)……..…….38

Figure 6- Lumbar Spine Movement…..……………………………..……………………………………………..46

Figure 7 - Example of Lumbar Spine Electrode Placement…………………………………………….….......61

List of Tables

Table 1 - The ROM results from the review of the literature…………………………………………..……..…19

Table 2 - Study Inclusion and Exclusion Criteria…………………………………………………………….......22

Table 3 - Lumbar Flexion Control Test Procedures…………………………………………………..………….25

Table 4 - Data Collection Procedure……………………………………………………………………..………..27

Table 5 - Baseline Measurements…………………………………………………………………………..........31

Table 6 - Average Number of Test Attempts….……………………………………………………………..…. 31

Table 7 - Summary of Descriptive Data for Lumbar Flexion Control Test ROM (Attempts 1 -3)................34

Table 8 - Summary of Intra-measure Data for Lumbar Flexion Control Tests (Attempts 2-3)……………...39

Table 9- Inter-Rater ROM Agreement for Lumbar Flexion Tests (attempts 1-3)........................................43

Table 10 - Spearman’s Correlations for Hamstring Length (LKEA), Body Mass Index (BMI), Age and Joint

ROM (Attempts 1-3)....................................................................................................................................45

List of Appendices

Appendix 1.0 Data Collection Protocol ................................................................................................... ….84

Appendix 3.0 Data Analysis Procedure………………………………………………………………………..….86

Appendix 4.0 Baseline Measures Raw Data………………………………………………………………..……90

Appendix 5.0 Inter-Rater Agreement Raw Data…………………………………………………………..……..91

Appendix 6.0 Electorgoniometry Kit and Placement Examples……………………….................................92

Appendix 7.0 Other Associated Parameters (LKEA, BMI, Age and Joint ROM)……………………….…….95

Key: MCD; Motor Control Dysfunction, WB; Waiters Bow, SKE; Seated Knee Extension, SFL; Sitting

Forward Lean, RBFPK; Rocking Back in Four Point Kneeling, ROM; Range of Movement, EG;

Electrogoniometry, KROM; Knee ROM, HROM; Hip ROM, LSROMLOC; Lumbar Spine ROM to the point

of Loss of Control, TLSROM; Total Lumbar Spine ROM, LHROM; Lateral Hip ROM, LLSROM; Lateral

Lumbar Spine ROM.

1 Chapter 1

1 Chapter 1

Introduction

Low back pain (LBP) has become a huge financial and social burden in modern

society, with up to 90% of LBP being classified as non-specific LBP (Luomajoki et al,

2007). Non-specific LBP is a diagnosis that means that in medical terms the cause is

unclear and this makes physiotherapy treatment difficult (Tidstrand and Horneij, 2009).

There remains no clear diagnostic clinical test and no treatment has been consistently

effective in reducing typical symptoms, limitations and diability associated with LBP

(Luomajoki et al. 2007, Enoch et al. 2011, Henry et al. 2012). Luomajoki et al. (2007)

stated that sub-groups of LBP classification have been proposed and a classification

system of this nature is the future of LBP diagnosis, treatment and management.

However, in order to be applied to practice a classification system must be reliable,

feasible, generalizable and valid (Henry et al. 2012). Currently there still remains an

absence of specific pathoanatomical diagnosis, as the cause of LBP remains a complex

multi-factorial debate, which involves many factors e.g. genetics, environment,

biopsychosocial issues etc. Therefore, several researchers have called for sub-groups

of LBP based on clinical symptoms and features in order to give specific treatment

(Luomajoki et al. 2007, Henry et al. 2012, Hoffman et al. 2012). As a result, a number of

diagnostic assessment processes have been developed to aid in the diagnosis of LBP

patients’ (Enoch et al., 2011, Luomajoki et al. 2008, O’Sullivan, 2005).

Recently several studies have highlighted the assessment of static and dynamic ‘motor

control’ of the lumbar spine as a possible area for physiotherapeutic clinical diagnosis of

LBP (Enoch et al. 2011, Luomajoki et al. 2007, 2008, Tidstrand and Horneij, 2009, Suni

et al. 2006, Ben-Masaud et al. 2009, Paatelma, Karvonen and Heinonen, 2010).

Luomajoki et al. (2007) reported that motor control dysfunction has several widely used





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2 Chapter 1

synonyms for motor control diagnosis i.e. movement control dysfunction, movement

impairment syndromes, motor control dysfunctions and relative flexibility. In this study

we will use the term motor control dysfunction (MCD).

Murphy et al. (2006) stated that the disruption of the stability system of the spine

during dynamic movements occurs in LBP patients. Motor control is required to maintain

spinal stability to ensure protection of the spine and prevention of injury. Several studies

have demonstrated the importance of spinal stabilization within its neutral zone, as well

as altered muscle activation and recruitment within LBP onset and reoccurrence.

Inappropriate motor control leads to inefficient spinal stabilization, which perpetuates

LBP as subjects with motor control dysfunction are unknowingly damaging themselves

through faulty movement patterns (Murphy et al. 2006, Luomajoki et al. 2007). Motor

control dysfunction (MCD) has been described as having several different components

but a common aspect is a reduced control of active movement (Luomajoki et al. 2007),

which leads to excessive movement, tissue damage and chronic LBP (O’Sullivan,

2005). The complex anatomy of the lumbar region and the movement demands placed

on it create a challenge for specific physiotherapeutic diagnosis. Motor control of the

lumbar spine can be biomechanically tested with particular trunk and limb movements

(Enoch et al. 2011). Comerford and Mottram (2012) stated that to have dysfunctional

motor control a subject must fall outside of the ‘normal’ range of movement for a

particular test. However, there remains no clear consensus for ‘normal’ ROM during

MCD tests and the ‘normal’ ROM’s reported are based upon expert opinion rather than

an objective evidence base.

The detection of uncontrolled movement is a key competence of physiotherapy and

the examination processes involved have been investigated for reliability and validity in





Lumbar Spine ROM.

3 Chapter 1

several studies (Enoch et al. 2011, Luomajoki et al. 2007, 2008, Dankaerts et al. 2006,

Henry et al. 2012). These studies evaluated the reproducibility of the MCD tests

involved and the majority showed satisfactory reproducibility. Reliable observation of

motor control of the lumbar region is important as it aids clinical reasoning, but it

remains difficult to visually assess lumbar movement during MCD testing without

biomechanical equipment (Enoch et al. 2011, Luomajoki et al. 2008). Therefore, there

remains a need for MCD tests with reproducible quantitative methods utilizing

biomechanical devices. Clinical reasoning is an important factor in all physiotherapy

areas and is a key factor in musculoskeletal physiotherapy. Performing accurate

assessments which are evidence based allows practitioners to develop and prescribe

rehabilitation which is accurate, while being as effective as possible (Mottram and

Comerford, 2008). However, Enoch et al. (2011) stated that there remains no clear

consensus as to the ‘normal’ cut-off points for the MCD tests. The lack of a quantitative

evidence-base for ‘normal’ range of movement during motor control dysfunction tests

leads to variability in the descriptions of the tests (Enoch et al. 2011), which makes it

increasingly difficult for inexperienced practitioners to perform accurate assessments. It

would therefore be of benefit for clinicians to have a simple, valid, reliable and

reproducible testing method capable of detecting MCD (Murphy et al. 2006).

The overall aim of this study was to determine the ‘normal’ ROM values for several

motor control dysfunction tests. Therefore a pilot study was performed to acquire

quantitative ROM data using a biomechanical device from individuals without LBP

during four lumbar flexion control tests (i.e. waiters bow, seated knee extension, sitting

forward lean and rocking backwards in four point kneeling). A pilot study was performed

to provide valuable information for the planning and justification of larger studies into





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4 Chapter 1

motor control assessments (Lancaster, Dodd and Williamson, 2002). Lumbar flexion

control was assessed in this study, as Paatelma, Karvonen and Heinonen (2010)

showed lumbar flexion during motor control dysfunction (MCD) testing was clinically

significant. An experimental methodology was developed using electrogoniometry to

evaluate evidence-based normative ROM at the hip, knee and lumbar spine when

performing the above clinical tests. The obtained data provides a methodology to create

evidence-based rather than expert-opinion based guidelines for conducting lumbar

flexion control tests.

1.1 Literature Review

1.2 Lumbar stability

Lumbar spine stability is important, as the lumbar region passes forces from the torso

to the lower limbs during both active and passive movements (Wagner et al. 2005,

Nakipoglu, Karagöz, Özgirgin, 2008). Several studies have stated that three

subsystems are important in maintaining spinal stability; passive (ligaments and spinal

column) active (muscles and fasciae) and control (central and peripheral nervous

system) (Panjabi, 2003, Wagner et al. 2005, Gibson and McCarron, 2004).

Luomajoki et al. (2007) stated that clinical instability and motor control are closely

linked. Similarly, Cook et al. (2006) reported that 88% of specialist LBP physiotherapists

believed that abnormal movement patterns are the main finding in clinical instability.

Originally instability was described by Pope and Panjabi (1985) as ‘’a mechanical entity

and an unstable spine is one that is not in an optimal state of equilibrium’’ and

furthermore ‘’stability is affected by restraining structures that if damaged will lead to

altered equilibrium and thus instability’’. Mulholland (2008) reported that Panjabi





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5 Chapter 1

originally believed instability was caused by a loss of stiffness. However, Gibson and

McCarron (2004) stated that to maintain the equilibrium a subsystem (passive, active or

control) can compensate for a defective subsystem to create spinal stiffness and

decrease the spinal neutral zone (NZ).

Panjabi (1992a, b) introduced the concept of the NZ; describing it as ‘a region of inter-

vertebral motion around the neutral posture where little resistance is offer by the

passive spinal column’. Although in 2003 Panjabi refined his theory and stated that

three areas contribute to the development of LBP; ‘joint stabilisation within its NZ, inter-

segmental instability and altered recruitment patterns of stabilising muscles’. However,

Panjabi (2003) declared that controversy remained over the definition of spinal

instability, but stated that it is commonly defined as ‘’the loss of normal pattern of spinal

motion causing pain and/or neurologic dysfunction’’. Similarly, Sahrmann (2002)

believed that movement occurs through a pathway of least resistance and that if

another a joining area (e.g. the hip) is stiff compared to the lumbar region then

excessive movement will occur in the lower back leading to LBP.

Mulholland (2008) wrote that after the nineties instability became the term used to

denote a diagnosis of abnormal patterns of movement, which usually had increased

ROM. McGill (2007) believed that structural instability which can be found on

radiological examination is rare and this lead to the term instability being used instead of

clinical instability. However, O’Sullivan (2005) defined MCD as “a back problem that

behaves like clinical instability but has no radiological findings”, which is a similar

definition as that of clinical instability given by McGill (2007) (i.e. ‘clinical patterns like

instability but not verifiable by radiography’). Mulholland (2008) stated that Panjabi had

changed his views towards instability after the nineties, as in 2004 Panjabi et al. created





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6 Chapter 1

a new hypothesis for chronic LBP abandoning instability altogether and stating that

damage to ligaments causes pain which leads to MCD. Recently researchers such as

Demoulin et al. (2007) and Enoch et al. (2011) have developed Panjabi’s theories

stating that instability causes tissue damage and leads to MCD.

1.3 Pain Alteration in LBP

LBP often occurs due to harmful loading of the spine causing initial tissue damage,

which causes pain (Wrigley et al. 2005). In the view of Panjabi (2006), Lederman (2011)

and O’Sullivan (2005) motor control dysfunction is a secondary condition caused by

tissue damage (i.e. ligament damage) which causes pain. O’Sullivan (2005) stated that

therefore MCD’s are present in Chronic LBP (CLBP) disorders, which fuelled research

into assessment of motor control of the lumbar region. This focus coincided with the

recognition of the need for early intervention aimed at preventing recurrence of LBP and

the development of CLBP disorders (Suni et al. 2006, O’Sullivan, 2005, Enoch et al.

2011). Lederman (2011) stated that many of the clinical examinations for assessing

posture, structure or biomechanical factors have no value in explaining why patients

develop their condition and are therefore redundant. However, Hodges (2011) stated

that altered, dysfunctional movement due to pain is the target for clinical interventions.

In the view of Hodges (2011) the initial pain from injury causes adaptation to prevent

further pain, which leads to motor control dysfunction (i.e. excessive movement, altered

muscle recruitment etc.). Rather than the pain-spasm-pain model which would state that

pain causes hyperactivity or spasm which leads to more pain (Williams, Haq, Lee,

2010). However, this ‘protective adaptation mechanism’ while having short term benefit





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7 Chapter 1

(i.e. pain relief) has long-term consequences such as decreased ROM and increased

load.

Pain induces pathological changes in ‘motor control’ through an adaptive process, as

activity is redistributed throughout the muscles (Hodges, 2011, O’Sullivan, 2005).

Secondary to motor control changes are later changes in the surrounding

musculoskeletal structures, as the motor control system alters muscle recruitment

patterns in an attempt to compensate for instability and pain (Ben-Masuad et al. 2009).

Marras et al. (2001) stated that changes in muscle recruitment patterns can significantly

affect loading on passive structures (i.e. inter-vertebral joints, ligaments etc.), inducing

LBP or musculoskeletal damage (Renkawitz et al. 2006). Several researchers believe

that control of muscle co-ordination allows for stability of the lumbar region and for the

lumbar region to take the huge force loads applied to it during activities of daily life

(Enoch et al. 2011, Hall et al. 2009, Granata and Orishimo, 2001). O’Sullivan (2005)

and Hodges and Moseley (2003) believed that CLBP develops as a result of altered

motor control (i.e. muscle co-ordination, altered proprioception and lack of active

movement control) which provides a basis for peripherally driven nociceptor

sensitisation.

1.4 Motor Control

Panjabi (2003) stated that neural control mechanisms represent motor control. The

CNS has a large input into motor control dysfunction, as it controls all movements,

postures and muscular activation. Structural and peripheral mechanisms may give an

explanation for the cause of CLBP, but the role of the central nervous system (CNS)

and neural control systems are important aspects to consider in MCD assessments.





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8 Chapter 1

Where muscular or passive stability is compromised further strain may be placed on the

neurological structures, which further exacerbates the instability (van Vliet and

Heneghan, 2006). Understanding motor control is of importance in not only the

management of patients with damaged CNS, but also in the management of

musculoskeletal dysfunction in patients with intact CNS (van Vliet and Henegham,

2006). Therefore, all clinicians involved in assessment and management of LBP should

have a good understanding of the motor control processes involved in maintaining

spinal stability (Comerford and Mottram, 2001a).

The commands for muscular activation are stored as cortical maps within the CNS and

transmitted through peripheral nerves to the muscles. Activity is based on learning

which in the view of Shumway-cook and Woollacot (2001) is developed by repetition

and habituation. Therefore, after an initial injury neural pathways adapt and repeated

dysfunctional movements become automatic. At the same time previous actions and

controls become inefficient and slower (Comerford and Mottram, 2012). In the view of

Comerford and Mottram (2012) this process is an aspect of their uncontrolled range of

movement dysfunction loop. Their dysfunction loop includes; inefficient local and global

muscle recruitment, inhibition of motor unit recruitment, dimished proprioception, pain

and pathology, movement control dysfunction (i.e. uncontrolled ROM), which all create

abnormal strategies and dysfunction. Several studies have provided evidence

supporting altered muscle recruitment (Hodges and Moseley, 2003, Wagner et al.

2005), delayed muscle activation (Massé-Alarie et al. 2012) and increased activity of

global muscles of the lumbo-pelvic region in LBP patients (Hodges et al. 2003,

Comerford and Mottram, 2001a). Cook et al. (2006) also stated that poor co-ordination,

http://www.springerlink.com/content/?Author=Hugo+Mass%c3%a9-Alarie





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9 Chapter 1

proprioception deficits and loss of control over active movements were important in

MCD assessment.

Luomajoki et al. (2007, 2010) stated that the motor control of individual muscles is

linked to MCD. Recent epidemiological studies have shown that the key stabilizing

muscles for the lumbar spine are the transverse abdominus (TrA) and the multifidus

(MF) (Richardson et al. 2004, Hides et al. 2010, Hides et al. 2011, Biely, Smith and

Silfies, 2006, Kavcic, Grenier and McGill, 2004). Kavcic, Grenier and McGill (2004)

showed that TrA and MF activation is linked, forming a ‘corset’ around the waist

(Danneels et al. 2001, Hides et al. 2001, McGill, 2007). Muscular activation causes

fasciae tensioning and extensor moments which support spinal stability (McGill, 2007,

Barker et al. 2004, Tesh et al. 1987, Hodges and Richardson, 1997). However, debate

remains over the combination of global (e.g. erector spinae group) and local (e.g. TrA,

MF) in rehabilitation or isolation of local deep muscles (e.g. TrA). As a result many

rehabilitation programmes have been developed in order to address different aspects of

motor control dysfunction (Hides et al. 2004, Goldby et al. 2006, Hall et al. 2009).

Therefore, with an increase in the focus on motor control as an area for intervention it is

important that the initial clinical assessments for motor control are accurate.

1.5 Feedback and Feed-forward Control

The neuromuscular stability of the lumbar spine is controlled by the CNS. Pain free

dynamic movement involves a combination of feed-forward (open loop) and feed-back

(closed loop) control of trunk stability (Zeinali-Davarani, et al. 2008, Desmurget and

Grafton, 2000), which can be assessed using electromyography (EMG).





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10 Chapter 1

As previously discussed in this section adaptation may be caused by pain from an

initial injury which may cause inhibition of feed-forward mechanisms (Hodges et al.

2003). In the view of van Vliet and Henegham (2006) the primary motor cortex is

functionally organized, which means that practice will invoke a change in response.

Within all subjects (i.e. LBP and non-LBP) even small amounts of practice can create

cortical changes due to improvements in the efficiency of existing synapses which

become stronger. With increased practice comes change in the balance of excitation

and inhibition which is possibly responsible for anatomical changes in synaptic

organization and is an important factor in cortical plasticity with rehabilitation (van Vliet

and Henegham, 2006). Braun et al. (2001) reported that well learned tasks have pre-

existing cortical maps which are functionally organized, which the somatosensory cortex

activates depending on the specific task requirements. Flor (2003) demonstrated that

there are changes in these cortical maps in back pain subjects, with increased

representation of nociceptive information (i.e. nociceptor sensitization) and cortical

excitation. Therefore, an understanding of task or movement specific motor control is

important and how afferent information is integrated with feed-forward and feedback

mechanisms (van Vliet and Henegham, 2006).

Feed-forward mechanisms have been shown to be compromised in trunk muscles of

patients with LBP (Hodges, 2001 and Hodges et al. 2003). Falla et al. (2004) reported

that neck muscle activation during flexion was significantly delayed in patients with

chronic neck pain. Similarly, Rabebold et al. (2001) reported delayed muscle response

in chronic LBP and this was associated with impaired postural control of the lumbar

spine. Feed-forward activity creates anticipatory trunk muscle activation in non-LBP

subjects, which is influenced by all afferent information i.e. nociceptive information,





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11 Chapter 1

altered proprioception, muscle length and muscle tension (van Vliet and Heneghan,

2006). However, there has been little research on the implications of altered feed-

forward mechanisms in LBP subjects or patients with dysfunction. It is believed that

practitioners should know the ‘normal’ feed-forward activity that would occur during the

movement being performed by the subject in order to evaluate the risks of LBP

reoccurrence and provide appropriate rehabilitation (van Vliet and Heneghan, 2006).

There have been a number of studies which have suggested the use of management

programmes for individual muscle retraining and rehabilitation of the lumbar muscles,

but there are none evaluating rehabilitation of feed-forward lumbar control.

1.6 Motor Control Assessment

Clinical tests for motor control are based on the idea of dissociation (Sahrmann, 2002,

Comerford and Mottram, 2012). Dissociation is the ability to activate muscles

isometrically to hold positions or preventing motion in particular segments, while moving

an adjacent segment. Trunk dissociation has been previously assessed using the prone

knee extension test (Woolsey, Sahrmann and Dixon, 1988), which measures the same

activity as when performing backwards rocking in 4 point kneeling (Stevens et al. 2007).

However, there are currently a range of clinical tests for lumbar motor control.

There remains no single sign or physical examination for motor control (Biely, Smith

and Silfies, 2006). Therefore, it is said to be important to have a range of motor control

assessments in order to make a reliable comprehensive clinical judgement about a

patient’s control (Comerford and Mottram, 2001b, Tidstrand and Horneij, 2009).

Comerford and Mottram (2001b) believed that functional testing for ‘normal function’

patterns is a fundamental part of motor control assessments. Mottram and Comerford





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(2008) stated that everyone should have the ability to perform movement patterns which

are unfamiliar to them i.e. outside of ‘normal function’. Performance within these

movement patterns gives physiotherapists tests for motor control (Comerford and

Mottram, 2003). However, Enoch et al. (2011) reported that there remains a need for

more precise test descriptions, with more quantitative and reproducible methods for

measuring motor control. The clinical tests currently utilised by physiotherapist are

based on previous studies which define a clinical judgment via can or cannot, yes or no

and pass or fail. Between these points Enoch et al. (2011) believed that valuable data is

lost and there remains no clear consensus for when particular tests are passed or

failed. Murphy et al. (2006) believed that consensus is difficult as currently

physiotherapists identify dysfunctions using tests which only ‘experienced’ professionals

feel confident in.

Sterling, Jull and Wright (2001) stated that some practitioners who deal with

musculoskeletal pain are able to notice altered movement patterns and controls, but

some changes in motor control are less apparent. Enoch et al. (2011) also identified

that it is clinically difficult to visually estimate how much movement occurs in the lumbar

region during motor control tests without the use of technical equipment (i.e. ultrasound,

electromyography, electrogoniometry, MRI etc.). Similar to this, previous studies of

motor control around the lumbo-pelvic complex have concluded that using

biomechanical equipment could provide much needed quantitative data (O’Sullivan,

2005, Fritz, Erhard and Hagen, 1998, Paatelma, Karvonen, Heinonen, 2010). McGill et

al. (2003) recognised that there is a need for biomechanical analysis of the control of

stability of the lumbar spine, as the biomechanical processes involved may require

particular interventions to prevent chronic LBP development (Suni et al., 2006).





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1.7 The Neutral Zone

Comerford and Mottram (2012) described the NZ as important because the

establishment of a ‘neutral training region’ is fundamental to the MCD assessment

process. The most important aspect of a lumbar MCD test is the ability for a patient to

maintain the neutral lumbar position during the test (Comerford and Mottram, 2012).

Several studies have stated that appropriate motor control (i.e. muscular coordination

etc.) allows the spine to stay within its NZ and maintain stability reducing LBP onset and

reoccurrence (Enoch et al. 2011, Suni et al. 2006, Panjabi, 2003, 2006, Tidstrand and

Horneij, 2009). The control of the NZ has been recognized by many studies as

important in the prevention and management of LBP. Panjabi (1992b) and Enoch et al.

(2011) believed that the control of ROM at the NZ was more relevant to LBP than

maximal end range values. Suni et al. (2006) stated that the control of the lumbar NZ

involves a biomechanical approach and therefore studies have focused on

biomechanical assessment.

The NZ has been measured using in vitro stepwise testing for the past 20+ years,

which has shown that during flexion-extension testing; 4.8° of movement occurs in the

NZ during flexion of the LS (Goertzen, Lane and Oxland, 2004). However, other

researchers have shown that NZ ROM is variable. Yamamoto et al. (1989) stated that

NZ ROM ranged from 5° to 10° depending on the segment, with L5/S1 having the

greatest NZ ROM. A more recent study by Gay et al. (2006) demonstrated that with

loading the lumbar NZ was smaller with a range from 0.78° to 2.11°, which is similar to

the in vitro work of Panjabi et al. (2004) who stated that LS neutral zone ROM with 8mn

of loading was only 0.93° during flexion. Although, previously Panjabi (1992b) stated

that during flexion the lumbar NZ was 1.5°, the elastic zone (EZ) was up to 6.1° and





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ROM was 7.6°. He also described that ROM between L5 and S1 during flexion was as

follows; NZ 3°, EZ 7° and ROM 10°. The above evidence shows that there is debate on

the ROM made in the NZ during flexion, therefore monitoring of the lumbar spine during

MCD tests is a key requirement.

1.8 Reliability and Validity

Physiotherapists currently use various models to deal with LBP disorders i.e. Motor

control model (O’Sullivan, 2005, Vibe Fersum et al., 2009). However, all models involve

the application of accurate clinical examinations. Reliable and valid assessments of

motor control dysfunction of the lumbar spine in patients with and without LBP are vital

in order to aid clinical decisions (Luomajoki et al. 2008). Recently several studies by

Enoch et al. (2011), White and Thomas (2002), Dankaerts et al. (2006) and Luomajoki

et al. (2007) showed that there was good inter and intra-rater reliability when using

certain clinical tests for motor control dysfunctions, although their results rely on the

concept of ‘expert opinion’. Even though these studies reported satisfactory to

substantial inter-rater reliability, specific ‘normal’ ROM values for joints (e.g. Lumbar

spine, hip and knee) during motor control dysfunction tests have received no attention

(Enoch et al. 2011).

Luomajoki et al. (2008) stated that there has been little evidence to denote a difference

between movement patterns in people with or without LBP as much of the research is

based solely on clinical observation of movement (i.e. subjective evaluation). Luomajoki

et al. (2008) therefore created a hypothesis that impaired motor control and

physiotherapists’ lack of knowledge about motor control assessment perpetuates LBP.

This is similar to research by Enoch et al. (2011) and Dankaerts et al. (2006) who





Lumbar Spine ROM.

15 Chapter 1

reported that inexperienced practitioner (i.e. practitioners who are not familiar with MCD

tests) reliability proved insignificant compared to experienced practitioner ‘expert

opinion’. In order for a clinical test to be reliable Enoch et al. (2011) stated that it should

be ‘depended upon with confident certainty’, which in their study was not the case

unless the practitioner was experienced in the area of lumbar motor control diagnosis

and treatment. Therefore, a simple quantitative protocol utilizing a biomechanical device

may improve inexperienced practitioner reliability (Enoch et al. 2011).

Several researchers believe that in order to get precision when using motor control

tests specific quantitative devices and test procedures should be utilised, which could

be used by inexperienced practitioners in clinical settings (Paatelma, Karvonen and

Heinonen, 2010, Borghuis, Hof and Lemmink, 2008, Fritz, Erhard and Hagen, 1998).

Only one of the previous studies (Enoch et al. 2011) based on lumbar motor control has

utilised quantitative procedures. However, all of the previous research has used expert

subjective opinion to assess when a patient passes or fails a particular test, rather than

biomechanical devices.

In the view of Panjabi (2003) biomechanical studies have provided important and

useful understanding of LBP; such as the use of radiographic measurements to

evaluate vertebra movement during lumbar flexion (O’Sullivan, 2000, Gajdosik and

Bohannon, 1987). However, Fritz, Erhard and Hagen (1998) stated that radiographic

imaging only captures passive function of stabilising systems and therefore cannot be

used to assess active motor control. As a result, there remains no clear consensus on

the effect of LBP on the ROM at joints around the lumbo-pelvic complex (Panjabi,

2003).





Lumbar Spine ROM.

16 Chapter 1

1.9 Range of Movement

Clinical observation of ROM is an integral aspect of any motor control test and

accurate objective measurement and interpretation of that measurement results in the

use and development of interventions (Gajdosik and Bohannon, 1987, O’Sullivan, 2005,

Comerford and Mottram, 2001b). Electrogoniometry (EG) technology has been

developed to measure joint ROM in clinical and research settings due to its clinical

application (Wang et al. 2011). In the past EG has been used to clinically evaluate the

end ROM of the lumbar spine in different populations, but no studies have assessed the

ROM made during motor control tests (Intolo et al. 2009, Marras and Wongsam, 1986).

Comerford and Mottram (2001a) stated that during the sitting forward lean test ‘normal’

individuals will be able to maintain a spinal neutral position within 30º of hip flexion

(Table 1), which was based on results of early work by Woolsey, Sahrmann and Dixon

(1988) and Marras and Wongsam (1986). However, Marras and Wongsam (1986) only

assessed lumbar flexion end ranges, which Bible et al. (2010) showed are never

actually achieved during functional activities. In the view of Enoch et al. (2011) clinical

tests should concentrate on motor control in smaller aspects e.g. until anterior pelvic tilt

is observed. Enoch et al. (2011) stated that testing for end range movement misses out

valuable data needed to create cut-off points for a normal population e.g. velocities,

maintenance of spinal neutral zone, flexibility, influence of age, gender, knee angle etc.

Several studies have shown that flexibility of the hamstrings and knee angles during

lumbar flexion tests have an influence on the observed ROM at the lumbar spine

(Borman, Trudelle-Jackson and Smith, 2011, Carregaro and Gilcoury, 2009, Shin et al.

2004, Marras and Wongsam, 1986). Also, Intolo et al. (2009) proved that increasing age

decreases lumbar ROM by approx. 2º every decade. Enoch et al. (2011) stated that





Lumbar Spine ROM.

17 Chapter 1

research should include these factors to contextualize results within a population.

Marras and Wongsam (1986) demonstrated that patients with LBP could only achieve

20º of lumbar flexion and healthy patients could only achieve up to 28º, but they did not

assess hip flexion or include any of the above contextual factors. Therefore, the clinical

tests currently used for motor control assessment may not be accurate, as there is no

research showing any specific objective quantitative data only ‘expert opinion’.

Enoch et al. (2011) highlighted that research has yet to uncover a ‘normal’ set of

values for ROM in motor control clinical tests for a ‘normal’ population i.e. people

without LBP. Normative values have yet to be definitively covered due to the small

sample size or lack of involvement of patients’ without LBP in relevant research i.e.

n=13 (Luomajoki et al. 2007), n=15 (Enoch et al. 2011), n=10 (Roussel et al. 2009a)

n=0 (Paatelma, Karvonen and Heinonen, 2010) etc. The term ‘normative’ refers to a

standard set of degrees of movement at the low back, hip and knee in people without

low back pain during motor control dysfunction tests. The ‘normal’ degrees of movement

are used by practitioners to assess patients with low back pain and not being able to

control movement within the ‘normal’ degrees indicates dysfunction (Sahrmann, 2002,

Comerford and Mottram, 2012).

A search for relevant literature was carried out on 24th March 2012 (Figure 1), which

was combined with a search of relevant text books in order to gain a comprehensive

view of reported ‘normal’ ROM degrees for the four motor control tests involved in this

study. The results of this search show that there was very little research that actually

gave specific ROM values for the tests involved in this study (Table 1). Table 1

demonstrates that there is variation in the ‘normal’ ROM values reported by previous

research, which could confuse clinical reasoning processes (Comerford and Mottram,





Lumbar Spine ROM.

18 Chapter 1

2012). Only the sitting forward lean (SFL) test had the same values within the research

that had reported it (i.e. 30° hip flexion ROM). The other ‘normal’ ROM values were

shown to have large variations of up to 50° (SKE; 30°-50° and 80° ROM). The

differences in the ROM values could be explained by the reliance on expert opinion and

the other factors discussed in this section. The variation in ROM values between the

previous research studies and texts was the basis for this study.

MCD assessment’s are used by practitioners to develop and prescribe appropriate

interventions (Mottram and Comerford, 2008), and should therefore be based on a solid

objectively assessed evidence-base not merely ‘expert opinion’. Normative data based

on biomechanical device testing would also allow for accurate cut-off points to be

developed for subjects with and without LBP, which Luomajoki et al. (2007) stated is the

future for LBP diagnosis, treatment and management. The flexion control movements

involved in this study are also not only used as tests of motor control (Enoch et al. 2011,

Luomajoki et al. 2007, 2008), but are used as interventions (Norris, 2000, Sahrmann,

2002, Comerford and Mottram, 2012). This has implications on rehabilitation as well as

assessment. With no clear consensus on the ‘normal’ ROM during the movements then

using them as an intervention or assessment is not evidence-based practice and could

therefore be ineffective, inefficient and/or potentially dangerous (Grimshaw, Eccles and

Tetroe, 2004).





Lumbar Spine ROM.

19 Chapter 1

Figure 1. Literature Review Search Terms and Results

Table 1. The ROM results from the review of the literature

Test Articles Joint ROM (True Angle)

Waiters Bow

Luomajoki et al. (2007) Norris (2000) Comerford and Mottram (2012)

Hip 50º- 70 º 30°-45°

50°

Seated Knee Extension

Luomajoki et al. (2007) Sarhmann (2002) Norris (2000) Comerford and Mottram (2012)

Knee

30º- 50 º 80 º (10°) 80 º (10°)

75°-80° (10°-15°)

Sitting Forward Lean

Enoch et al. (2011) Comerford and Mottram (2001a) Comerford and Mottram (2012)

Hip

30 º (120°) 30 º (120°)

30°

Rocking Backward in Four Point Kneeling

Comerford and Mottram (2012) Luomajoki et al. (2007) Sarhmann (2002)

Hip

30° (120°) 30 º (120°)

Dysfunctional if LS flexion after 50% of movement





Lumbar Spine ROM.

20 Chapter 1

1.9.1 Research Objectives

Research Question:

What are the evidence-based normative ROM angles during lumbar flexion motor

control tests?

Objectives:

Evaluate a methodology for the development of evidence-based normative data for

the ROM at the lumbar spine, hip and knee during clinical tests for lumbar flexion

motor control.

Establish evidence-based normative ROM data at the lumbar spine, hip and knee

during lumbar flexion control tests.

Establish cut off points of lumbar flexion control ROM for subjects without LBP

during lumbar flexion motor control tests.





Lumbar Spine ROM.

21 Chapter 2

2 Chapter 2

Methodology

2.1 Rationale

Physiotherapy is an autonomous profession, relying on clinical reasoning skills and

evidence based practice to achieve clinical effectiveness (Mead, 2006). Recently motor

control testing for LBP has become an area of interest, which involves the control of

movement of one segment while moving another segment through a ‘normative’ ROM.

It is essential that physiotherapy uses the best available evidence in order to

appropriately provide interventions (Schreiber and Stern, 2005). Interventions are

provided based on failing a motor control test i.e. not being able to control movement

through the ‘normative’ ROM (Mottram and Comerford, 2008). However, no studies

have provided an evidence-base for ‘normative’ ROM values. It is widely recognized

that practice not based on the best available evidence is inefficient, ineffective and in

some cases dangerous (Grimshaw, Eccles and Tetroe, 2004). Therefore, this study

aimed to create an evidence-base for ‘normative’ ROM during four lumbar flexion

control tests.

2.2 Study Design

Descriptive pilot study, as it was self funded and there was a limited time scale for the

submission of the MSc dissertation. Although the design was limited due to the time

scale and sample size (n=20) involved, it was still adequate to allow for a statistical

analysis of the methodology and normative data. Schulz and Grimes (2005) believed

that unbiased trials with imprecise results are better than no results, as research based





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22 Chapter 2

on methodological rigor and not sample size can still be useful to practitioners in a

clinical setting.

2.3 Study Sample

Participants were recruited via the university e-mail system, being sent an invitation

letter (Appendix 1.0), information sheet (Appendix 2.0) and informed consent form

(appendix 3.0) via this system. The e-mail was sent to members of university staff once

ethical approval was obtained, who forwarded it onto students and other staff members.

The first 20 participants to reply were selected for the study, provided that they met the

inclusion criteria (Table 2) and those not chosen were informed via an informal email

(Appendix 4.0). All participants were assigned a random number (1-20) to randomize

the sample.

Table 2. Study Inclusion and Exclusion Criteria

Inclusion Criteria: Exclusion criteria:

Healthy individuals; selected from university staff and students who will have a range of activity levels.

This will be an asymptomatic convenience sample (n=20).

Aged between 18 and 45 years.

Previous medical history of 2 years low back pain or leg pain of spinal origin, within 6 months of spinal trauma.

Any abdominal, Gastro-intestinal, neurological or respiratory condition.

Any non-healed fractures, anomalies or tumours.

Any acute trauma (Luomajoki et al. 2007, Enoch et al. 2011).

In addition, all participants were required to travel to the study location themselves.





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23 Chapter 2

2.4 Ethics

Approval was obtained from Northumbria Universities ethics committee. Participants

were free to leave the study and withdraw their data at anytime without giving reason.

The tests involved in the study were simple physical tests that were performed in static

positions (i.e. sitting, standing and kneeling) and were unlikely to cause any discomfort.

Participants wore shorts with a sports bra (if female) or no top (if male). The testing

took place in a closed room, with only the researcher and supervisor present. Each

subject was not allowed to view other subjects performing the clinical tests, a screen

was placed around the testing area and towels were used to cover the participant when

not performing the tests, maintaining participants’ dignity.

All data gathered was anonymously coded onto a private password protected

computer and original sheets were stored in a locked case for a period of two years

after which they were destroyed. Feedback was given to each participant on the

outcome of their tests once the project was completed.

2.5 Baseline Measures

The test procedure involved baseline measurements of age, gender, height, weight,

BMI, hamstring length (via knee extension angle test, Davis et al. 2008).

Hamstring length has been shown to be an influence on lumbar ROM (Carregaro and

Coury, 2009), therefore this was included as one of the baseline measures of this study.

A review by Davis et al. (2008) demonstrated that the knee extension angle (KEA) test

is the most reliable test of hamstring length and was used in this study. Also, age,





Lumbar Spine ROM.

24 Chapter 2

gender and BMI were recorded at baseline as all of these factors have been shown to

influence lumbar ROM (Intolo et al. 2009, Koley, Kaur and Sandhu, 2009).

KEA test procedure: Participants lay supine on a plinth. Therapist bent their hip and

knee 90°. Participants then extended their knee and held the position. The angle of

the knee was recorded, 5-15º was desirable (Norris and Matthews, 2005). This was

repeated 3 times on each leg with an average taken.

2.5.1 Equipment

A physiotherapy department room at Coach Lane Campus, Northumbria University.

Plinth – height adjustable

Biometrics electrogoniometer kit and software with laptop

Curtain/screen

Stopwatch or clock to monitor time period

Double sided and zinc oxide tape

Towels: enough for each participant to have their own during testing

2.6 Lumbar Flexion Motor Control Tests

There remains no gold standard for motor control tests and all of the currently used

tests rely on observation of the quality and range of movement. This studies aim was to

monitor ROM during several motor control tests using a biomechanical device. Lumbar

flexion control tests were used, as research by Paatelma, Karvonen and Heinonen

(2010) showed that lumbar spine flexion during MCD testing was clinically significant.

Lumbar spine, hip and knee angles were monitored, as Shin et al (2004) and Pal et al.





Lumbar Spine ROM.

25 Chapter 2

(2007) demonstrated that changes in the angles at the hip and knee can alter the ROM

at the lumbar spine.

The clinical tests involved were: waiters bow (WB), sitting forward lean (SFL), sitting

knee extension (SKE) and rocking backward in four point kneeling (RBFPK) (Liebenson

et al. 2009, Enoch et al. 2011, Luomajoki et al. 2007).

Table 3. Lumbar Flexion Motor Control Test Procedures Test Test procedure

WB Standing with feet shoulder width apart and hands on hips. Keeping knees stable but slightly unlocked. Bend forwards at the hips, while not allowing flexion in the lower back (LB). Lower as far as hip flexibility allows while keeping LB in neutral and return to standing position, leading with the hips not the spine.

SKE Upright sitting on plinth with feet unsupported, LB in neutral; extension of the knee without movement (flexion) of low back.

SFL Upright sitting on plinth with feet supported, LB in neutral; knees and hips at 90° with the hands resting on the thighs. Lean forwards from hips as far as flexibility will allow while keeping LB in neutral.

RBFPK Transfer of the pelvis backwards ("rocking") in a quadruped position (i.e. hands and knees in contact with the plinth) as far as flexibility allows while keeping LB in neutral.

2.7 Electrogoniometry: Reliability and Validity

Biometrics Ltd. (2011) data-link electrogoniometry (EG) was used to measure the

ROM at the lumbar spine, hip and knee when performing the MCD tests. Gajdosik and

Bohannon (1987) reported that EG it is a reliable and valid measure of ROM. Since this

early work many studies have utilised this equipment to assess the lumbar spine, due to

the accuracy and ability to monitor several planes of movement at one time to an

accuracy of ±2º (Biometrics Ltd., 2011, Intolo et al. 2009, Marras and Wongsam, 1986).

Rowe et al. (2001) also tested the Biometric flexible EG proving that it is a valid

measure of joint kinematics. EG has been specifically assessed in several studies





Lumbar Spine ROM.

26 Chapter 2

proving that it is a valid and reliable measure for lower extremity ROM (Szulc,

Lewandowski and Marecki, 2000, Bronner, Agraharasamakulam and Ojofeitimi, 2010).

Twin axis EG electrodes (Biometrics Ltd. 2011) were applied using tape at the lumbar

spine and left hip to monitor the saggital and frontal plane ROM during the tests

(Appendix 6.0). The lumbar spine EG was used to monitor the neutral lumbar position,

flexion control of the lumbar spine and lateral movement. A single axis electrode was

used for the left knee to monitor the saggital ROM during the tests. Appendix 6.0

demonstrates the electrode placement at the hip, knee and lumbar spine which were

based on previous studies (Marras and Wongsam, 1986, Mayhew, Norton and

Sahrmann, 1983, Szulc, Lewandowski and Marecki, 2000). The attachment of the

electrodes was performed according to the Biometrics Ltd. (2011) guidelines, with extra

zinc oxide tape over the electrodes to add pressure (Rowe et al. 2001). The electrodes

were attached in a neutral standing position and remained in place for all the testing, as

Piriyaprasarth et al. (2008) stated that removal and reattachment can cause

measurement errors.

2.8 Data Collection Protocol

Each participant attended one testing session at Northumbria University, which took an

average of 60 minutes to complete. The session was run by the researcher with the

support of their supervisor. Table 4 demonstrates the data collection procedure utilised.

An alarm was set in the Biometrics software, which sounded when lumbar flexion went

above 5º, which indicated anterior pelvic tilt and a loss of flexion control. Loss of flexion

control is shown in the trace as a bending moment, as after this point the spine begins

to move beyond the neutral position and into flexion (Panjabi, 1992b). There is variation





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27 Chapter 2

in the reported NZ ROM degrees. Therefore this study used the original widely accepted

ROM degrees from Panjabi (1992b) and the in vitro stepwise spinal testing (Goertzen,

Lane and Oxland, 2004) to base 5° of flexion control on. The Biometrics equipment had

an accuracy of ±2°; therefore analyzing the collected data at 5° gave a true angle of

between 3° and 7°. This potentially gave the point at the final degree of the neutral or

elastic zone (5°-6°), where the LS segments were beginning to go into flexion. Not only

in research but in clinical practice 5° is also seen as the minimum observable clinically

significant change in ROM (Uswatte and Taub, 1999, Zigler, 2004, Pennal et al. 1972).

The data was marked, using the hand held data marker, by the researcher at the point

that the lumbar spine went past 5° of flexion (i.e. when the alarm sounded). This mark

showed as a yellow line on the graphical output of the biometrics software.

Table 4. Data Collection Procedure

Start

Position

The researcher used their hands to position the lumbar spine in a neutral position before each attempt and the lumbar spine electrode was ‘zeroed’ at this point. In contrast the knee and hip electrodes were ‘zeroed’ in a straight position prior to being attached. This allowed the EG to monitor lumbar spine flexion from a neutral lumbar position.

Teaching

of Test

Movement

The participants (n=20) were taught each test by the researcher individually prior to their own performance. Each participant performed the 4 clinical tests several times, with the first attempts being adjusted by the researcher so that the final 3 attempts were deemed competent by the researcher (Enoch et al. 2011). Tactile feedback was given in the first attempts with verbal feedback also given in the first attempts by the researcher. The participants were given a strict set of instructions for each test (Table 3), which was the same for each participant. A demonstration of each of the tests was given by the researcher just prior to the participants own performance.

Test The last 3 attempts were performed with no feedback and were recorded with an average taken. Participants were given a 2 minute break between each test and the order of the tests was the same for each participant (i.e. WB, SKE, SFL, RBFPK) as Luomajoki et al. (2008) believed this represents clinical practice where routines often develop.





Lumbar Spine ROM.

28 Chapter 2

2.9 Data analysis

The data was analyzed to find the ‘normal’ ROM at the hip, knee and lumbar spine to

the point of loss of flexion control (Appendix 4.0). The raw-data was analysed initially on

the Biometrics Ltd. (2011) software (Appendix 3.0). ROM results were then transferred

and statistically analysed using Microsoft Excel (2007) with the Analyse-it statistical

package and Medcalc (2012) version 12.2.1. Mainly descriptive statistics (total means,

standard deviations etc.) were reported for the ‘normal’ ROM results (Table 6), as no

formal power testing had been completed for this pilot study (Lancaster, Dodd and

Williamson, 2002).

Repeatability of each test was based upon the agreement between the final two

attempts (2-3), which were chosen as the learning effect allowed for consistent results.

To show individual measurement errors the standard error of measurement (SEM) was

calculated [SEM = SD differences between attempts 2-3 x √2 (Vet et al. 2006, Enoch et

al. 2011)]. Minimal detectable change (MDC) [MDC = SEM x √2 x 1.96] was also

calculated to show the minimal difference between attempts 2 and 3 not due to error.

The ROM differences must be lower than the MDC in order to be repeatable (Damstra

et al. 2011).

The difference between individual measurements was also calculated using Bland-

Altman plots (Bland and Altman, 1986, 2003). Bland-Altman plots were constructed by

plotting the ROM differences between attempt 2 and 3 (y-axis) against the mean ROM

of attempts 2 and 3 (x-axis) for each ROM variable (Figure 2-5). The dark blue line was

the average difference, the distance between this line and the ‘y=0’ (orange dashed)

line indicates the bias towards one of the attempts. The distance between the dark blue

line (average difference) and each dot represents the difference between the attempts.

The closer the dots are to the dark blue line the less disagreement between ROM





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29 Chapter 2

measures. The brown dashed lines in Figures 2-5 indicates the 95% Limits of

agreement (LoA), which represents the value below which 95% of the differences

should lie if the data is normally distributed (Bisdas et al. 2008).

A statistician was consulted and spearman’s correlation coefficients (rho) were used to

evaluate agreement between individual measures (intra-measure) due to the distribution

of the data (Table 7). The correlation coefficient ratings are as follows; 0-0.2

indicates ‘poor’ agreement: 0.2-0.4 indicates ‘fair’ agreement; 0.4-0.7 indicates

‘moderate’ agreement; 0.7-0.8 indicates ‘strong’ agreement; and >0.8 indicates ‘almost

perfect’ agreement. A high positive rho in this case indicated that ROM differences

between attempts were small.

Inter-rater agreement was analysed between the main researcher (novice) and their

supervisor (expert). The inter-rater agreement was analysed using 4 randomly selected

subject ROM results, which were analysed by both researchers using a set protocol

(Appendix 3.0). Similar to previous studies weighted Kappa correlations were then used

to assess the level of agreement between the two raters.

The ROM data (attempts 1-3) was also examined using rho for association between

different parameters; such as hamstring length (LKEA), body mass index (BMI), age

and the point of loss of flexion control of the lumbar spine compared to total LS ROM.





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30 Chapter 3

3 Chapter 3

Results

The main aim of this study was to create a set of ‘normative’ ROM values for the hip,

knee and lumbar spine during lumbar flexion control tests, which would allow for cut-off

points to be made for non-LBP subjects. In order to do this a quantitative methodology

using a biomechanical device (i.e. Biometrics EG) was created to assess the ROM at

these joints during the tests. This section will discuss the findings of this methodology

and the reliability of the method used.

3.1 Baseline Measurements

20 subjects without LBP were included in the study and Table 1 shows the baseline

data of the subjects. In their sociodemographic background there was little variation in

working status, with the subjects consisting mainly of students (90%) and the minority of

subjects being employed (10%). The participants were tested for ROM on their left side,

but knee extension angle was recorded for both legs. Norris and Matthews (2005)

reported that between 5º and 15º of knee extension is desirable when performing the

LKEA test. However, Table 5 demonstrates that the average left knee extension angles

(LKEA), taken from supine with the hip at 90°, for males (19.7°) and females (26.9°)

were less than the desirable range. This infers that on average all of the participants

(N=20) had shortened or tight hamstring muscles.

There were no adverse effects of the testing performance. However, there were issues

with the participants’ ability to perform the testing with no feedback from the practitioner,

especially during the waiters bow testing. More attempts by the participants than the





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31 Chapter 3

originally planned 5 times were required to gain a good level of proficiency for the

recorded attempts (Table 6), which was based on the therapists’ subjective decision.

Table 5. Baseline Measurements

Participants without LBP (N = 20)

Males Females Average/Total

Age years (Mean, SD) 25.8 (7.1) 25.7 (6.9) 25.75 (7)

Height cm (Mean, SD) 181.3 (6.4) 163.6 (6.2) 172.45 (6.3)

Weight kg (Mean, SD) 74.9 (8) 60.5 (7.3) 67.7 (7.65)

BMI (Mean, SD) 22.8 (2.3) 22.6 (2.4) 22.7 (2.35)

Gender (N. %) 10 (50%) 10 (50%) 20 (100%)

LKEA (Mean, SD) 19.7 (10.7) 26.9 (14.8) 23.3 (12.75)

RKEA (Mean, SD)

Student (N. %)

Working (N. %)

20.5 (10.5)

9 (90%)

1 (10%)

24.3 (14.5)

9 (90%)

1 (10%)

22.4 (12.5)

18 (90%)

2 (10%)

Table 6. Average Number of Test Attempts

Male Female Average

Waiters Bow (Mean, SD)

Seated Knee Extension (Mean, SD)

Sitting Forward Lean (Mean, SD)

Rocking Back in Four Point Kneeling (Mean, SD)

6.9 (1.4)

5.2 (0.4)

5.2 (0.4)

5.7 (1.1)

6.7 (1.1)

5.3 (1)

5.8 (0.6)

5.3 (0.5)

6.8 (1.3)

5.3 (0.7)

5.5 (0.5)

5.5 (0.8)





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32 Chapter 3

3.2 Lumbar Flexion Control Tests

The summarized ROM results shown in Table 7 indicate that the mean ROM’s of the

tests were all 10-15° less than the previously reported ROM degrees; HROM during WB

(30-70°), KROM during SKE (30-80°), HROM during SFL (30°) and HROM during

RBFPK (30°) (Table 1). The particular ROM’s of interest for comparison to previously

reported ROM values were; HROM during WB (16.06°; CI 11.63-20.49), KROM during

SKE (65.09°; CI 60.10-70.08), HROM during SFL (15.35°; CI 12.02-18.67) and HROM

during RBFPK (19.68°; CI 15.24-24.12). However, there were large standard deviation’s

(SD) between many of the ROM values as high as 17.21°, which means the differences

in ROM between attempts (1-3) were large and clinically significant (i.e. >5°)

(Chaudhary, Beaupre and Johnston, 2008, Stuss, Winocur and Robertson, 1999).

Table 7 demonstrates that the D’Agostino-Pearson test for normal distribution was

rejected (r) in five ROM aspects for attempts 1-3, which is due to the skewness and

kurtosis of the data. Three of the ROM aspects had a statistically significant skewness

(<0.05); LHROM during SFL, KROM during WB and LSROMLOC during RBFPK.

Distribution was skewed indicating that the most extreme values were located on the

right (positive value) or left (negative value), which was demonstrated in the Bland-

Altman plots (Figures 2, 4 and 5). Four ROM aspects had a statistically significant

kurtosis (<0.05). LSROMLOC during SFL, LHROM during RBFPK and LLSROM during

WB had a platykurtic distribution (<3), which means that the probability for extreme

values was less than for a normal distribution and the ROM measurements were

widespread around the mean. LLSROM during RBFPK had a leptokurtic distribution

(>3), which means that the ROM measurements had a high probability for extreme

values as the majority of the measurements were concentrated around the mean

(Figure 5).





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33 Chapter 3

The Bland-Altman plots (attempts 2-3) demonstrate that the several of ROM variables

that had rejected normal distribution over the 3 attempts (i.e. KROM during WB,

LSROMLOC and LHROM during SFL and LSROMLOC during RBFPK) had a

distribution of 95% of the differences within 95% LoA (Figures 2-5) which implies normal

distribution during the last 2 attempts (Bland and Altman, 1986). Only LHROM during

SKE maintained rejected normal distribution over the 3 attempts (Figure 3).

The large SD’s and variability of normality of the data over the 3 attempts indicated

that reliability analysis was required. Due to the rejected normality non-parametric data

analysis was performed i.e. Spearman’s rank correlation coefficient (rho).

Key: MCD; Motor Control Dysfunction, WB; Waiters Bow, SKE; Seated Knee Extension, SFL; Sitting Forward Lean, RBFPK; Rocking Back in Four Point Kneeling, ROM;

Range of Movement, EG; Electrogoniometry, KROM; Knee ROM, HROM; Hip ROM, LSROMLOC; Lumbar Spine ROM to the point of Loss of Control, TLSROM; Total

Lumbar Spine ROM, LHROM; Lateral Hip ROM, LLSROM; Lateral Lumbar Spine ROM. 34

Table 7. Summary of Descriptive Data for Lumbar Flexion Control Test ROM (Attempts 1 -3)

Test Outcome Variable

Mean (Degrees)

Standard Deviation

(SD) (Degrees)

95% confidence interval (Degrees)

Lower Upper

Range (Min, Max) (Degrees)

Standard Error

(Degrees)

Coefficient of Skewness (p value)

Coefficient of

Kurtosis (p value)

Normality (p value)

WB KROM 2.06 3.51 0.42 3.70 -2.4, 10.37 0.78 1.23 (0.02) 0.62 (0.41) 0.05 (r)

HROM 16.06 9.47 11.63 20.49 3, 35.03 2.12 0.52 (0.29) -0.43 (0.76) 0.55

LSROMLOC 5.57 0.97 5.12 6.03 3.9, 8 0.22 0.86 (0.09) 0.73 (0.36) 0.16

TLSROM 29.73 17.21 21.67 37.78 4.37, 59.73 3.85 -0.04 (0.94) -1.24 (0.07) 0.19

LHROM 2.06 4.58 -0.08 4.21 7.77, 11.53 1.02 -0.08 (0.87) 0.32 (0.58) 0.85

LLSROM 0.17 2.11 -0.82 1.16 -3.3, 3.3 0.47 -0.09 (0.85) -1.38 (0.03) 0.09

SKE KROM 65.09 10.66 60.10 70.08 44.2, 82 2.38 -0.07 (0.89) -0.81 (0.37) 0.66

HROM -0.72 3.74 -2.47 1.03 7.53, 6 0.84 -0.44 (0.37) -0.47 (0.72) 0.63

LSROMLOC 4.28 1.15 3.74 4.82 2.1, 6.7 0.26 0.06 (0.90) 0.13 (0.71) 0.93

TLSROM 6.33 2.83 5 7.65 2.43, 12.77 0.63 0.84 (0.10) 1.13 (0.23) 0.12

LHROM 4.76 4.18 2.80 6.71 3.57, 16.17 0.93 0.86 (0.09) 2.37 (0.06) 0.04 (r)

LLSROM -1.53 1.79 -2.36 -0.69 -4.53, 1.53 0.4 0.24 (0.62) -0.85 (0.34) 0.56

SFL KROM 0.12 1.35 -0.51 0.75 -2.43, 2.37 0.3 -0.15 (0.75) -0.82 (0.37) 0.63

HROM 15.35 7.10 12.02 18.67 3.17, 33.83 1.59 0.64 (0.20) 1.10 (0.24) 0.22

LSROMLOC 5.60 1.36 4.96 6.23 2.6, 8.8 0.3 0.79 (0.12) 2.60 (0.04) 0.04 (r)

TLSROM 21.20 10.22 16.41 25.98 6.43, 40.8 2.28 0.44 (0.37) -0.90 (0.29) 0.38

LHROM 5.59 7.50 2.08 9.10 4.13, 24.73 1.68 1.27 (0.02) 1.38 (0.17) 0.02 (r)

LLSROM -1.47 2.17 -2.48 -0.45 -6, 1.93 0.48 -0.39 (0.42) -0.41 (0.79) 0.70

RBFPK KROM 23.71 7.57 20.17 27.26 7.87, 34 1.69 -0.64 (0.20) -0.34 (0.86) 0.43

HROM 19.68 9.48 15.24 24.12 5.1, 36.9 2.12 0.38 (0.44) -0.68 (0.51) 0.60

LSROMLOC 5.03 0.87 4.62 5.44 2.83, 6.13 0.19 -1.40 (0.01) 1.91 (0.09) 0.01 (r)

TLSROM 16.37 7.60 12.82 19.93 6.47, 30.9 1.70 0.30 (0.54) -1.22 (0.08) 0.18

LHROM 4.02 7.18 0.66 7.38 -12.37, 23.27

1.61 0.55 (0.27) 2.60 (0.04) 0.07

LLSROM 0.22 1.30 -0.39 0.83 -3.37, 3.23 0.29 -0.41 (0.41) 3.13 (0.03) 0.06

[Normality; D'Agostino-Pearson test for normal distribution (r = reject normality). Significant finding; P<0.05]

35

HIP ROM KNEE ROM TOTAL LUMBAR SPINE ROM

LATERAL LUMBAR SPINE ROM LATERAL HIP ROM LUMBAR SPINE ROM TO LOSS OF CONTROL

FIGURE 2. Waiters Bow Bland-Altman Plots (Attempt 2 and 3)

0 10 20 30 40

-25

-20

-15

-10

-5

0

5

10

15

20

25

Average of Attempt 2 and Attempt 3

Attem

pt 2 -

Attem

pt 3

Mean

2.6

-1.96 SD

-14.8

+1.96 SD

20.1

-2 0 2 4 6 8 10 12 14

-8

-6

-4

-2

0

2

4

Average of Attempt 2 and Attempt_3

Attem

pt 2 -

Attem

pt_

3

Mean

-1.0

-1.96 SD

-5.1

+1.96 SD

3.2

0 10 20 30 40 50 60 70

-25

-20

-15

-10

-5

0

5

10

15

20


Attem

pt 2 -

Attem

pt 3

Mean

-0.7

-1.96 SD

-18.5

+1.96 SD

17.0

-4 -2 0 2 4 6

-8

-6

-4

-2

0

2

4

6


Attem

pt 2 -

Attem

pt 3

Mean

0.2

-1.96 SD

-3.9

+1.96 SD

4.2

-10 -5 0 5 10 15

-10

-8

-6

-4

-2

0

2

4

6

8


Attem

pt 2 -

Attem

pt 3

Mean

-0.5

-1.96 SD

-7.6

+1.96 SD

6.6

2 3 4 5 6 7 8 9

-6

-4

-2

0

2

4

6

8


Attem

pt 2 -

Attem

pt 3

Mean

0.5

-1.96 SD

-3.7

+1.96 SD

4.7

36



FIGURE 3. Seated Knee Extension Bland-Altman Plots (Attempts 2 and 3)

-10 -5 0 5 10

-6

-4

-2

0

2

4


Att

em

pt

2 -

Att

em

pt

3

Mean

-0.3

-1.96 SD

-3.8

+1.96 SD

3.1

40 50 60 70 80 90

-15

-10

-5

0

5

10

15

20


Att

em

pt

2 -

Att

em

pt_

3Mean

0.8

-1.96 SD

-10.0

+1.96 SD

11.7

2 4 6 8 10 12 14 16

-6

-4

-2

0

2

4

6

Average of Attmept 2 and Attempt 3

Att

me

pt

2 -

Att

em

pt

3

Mean

-0.1

-1.96 SD

-4.9

+1.96 SD

4.7

-6 -4 -2 0 2 4

-3

-2

-1

0

1

2

3


Att

em

pt

2 -

Att

em

pt

3

Mean

0.1

-1.96 SD

-2.0

+1.96 SD

2.2

-10 -5 0 5 10 15

-20

-15

-10

-5

0

5

10

15


Att

em

pt

2 -

Att

em

pt

3

Mean

1.0

-1.96 SD

-10.3

+1.96 SD

12.4

2 3 4 5 6 7 8

-8

-6

-4

-2

0

2

4

6


Att

em

pt

2 -

Att

em

pt

3

Mean

0.4

-1.96 SD

-3.7

+1.96 SD

4.5

37



FIGURE 4. Sitting Forward Lean Bland-Altman Plots (Attempts 2 and 3)

0 5 10 15 20 25 30 35

-10

-5

0

5

10

15


Att

em

pt

2 -

Att

em

pt

3

Mean

0.9

-1.96 SD

-8.2

+1.96 SD

10.0

-3 -2 -1 0 1 2 3 4

-4

-3

-2

-1

0

1

2

3

4

5

6


Att

em

pt

2 -

Att

em

pt

3

Mean

0.4

-1.96 SD

-2.6

+1.96 SD

3.4

0 10 20 30 40 50

-10

-5

0

5

10

15


Atte

mp

t 2

- A

tte

mp

t 3

Mean

1.3

-1.96 SD

-8.2

+1.96 SD

10.9

-6 -4 -2 0 2 4

-6

-4

-2

0

2

4

6


Att

em

pt

2 -

Att

em

pt

3

Mean

-0.2

-1.96 SD

-4.1

+1.96 SD

3.7

-10 0 10 20 30 40

-20

-15

-10

-5

0

5

10

15


Att

em

pt

2 -

Att

em

pt

3

Mean

-0.5

-1.96 SD

-10.7

+1.96 SD

9.7

0 2 4 6 8 10

-4

-3

-2

-1

0

1

2

3

4

5


Att

em

pt

2 -

Att

em

pt

3

Mean

0.3

-1.96 SD

-3.3

+1.96 SD

4.0

38



FIGURE 5. Rocking Backwards in Four Point Kneeling Bland-Altman Plots (Attempts 2 and 3)

0 10 20 30 40 50

-30

-20

-10

0

10

20

30


Att

em

pt

2 -

Att

em

pt_

3

Mean

0.6

-1.96 SD

-19.7

+1.96 SD

21.0

5 10 15 20 25 30 35 40

-40

-30

-20

-10

0

10

20

30

40


Atte

mp

t 2

- A

tte

mp

t 3

Mean

1.5

-1.96 SD

-25.2

+1.96 SD

28.2

5 10 15 20 25 30 35 40

-10

-8

-6

-4

-2

0

2

4

6

8


Att

em

pt

2 -

Att

em

pt

3

Mean

-1.4

-1.96 SD

-7.9

+1.96 SD

5.1

-6 -4 -2 0 2 4

-3

-2

-1

0

1

2

3

4

5


Att

em

pt

2 -

Att

em

pt

3

Mean

0.9

-1.96 SD

-1.9

+1.96 SD

3.8

-20 -10 0 10 20 30

-15

-10

-5

0

5

10

15


Atte

mp

t 2

- A

tte

mp

t 3

Mean

1.3

-1.96 SD

-8.5

+1.96 SD

11.2

2 3 4 5 6 7

-3

-2

-1

0

1

2

3

4


Atte

mp

t 2

- A

tte

mp

t 3

Mean

-0.1

-1.96 SD

-2.6

+1.96 SD

2.4

Key: MCD; Motor Control Dysfunction, WB; Waiters Bow, SKE; Seated Knee Extension, SFL; Sitting Forward Lean, RBFPK; Rocking Back in Four Point Kneeling, ROM;

Range of Movement, EG; Electrogoniometry, KROM; Knee ROM, HROM; Hip ROM, LSROMLOC; Lumbar Spine ROM to the point of Loss of Control, TLSROM; Total

Lumbar Spine ROM, LHROM; Lateral Hip ROM, LLSROM; Lateral Lumbar Spine ROM. 39

Table 8. Summary of Intra-measure Data for Lumbar Flexion Control Tests (Attempts 2-3)

Test Outcome Variable Spearmans Coefficient Correlation (rho)

rho (p value) 95% Confidence Interval

rho (p value) 95% CI

Mean Difference (SD) LOA (95%) SEM MDC

WB KROM 0.59 (0.01) 0.20 to 0.82 1 (2.12) -3.16 to 5.15 1.50 4.16

HROM 0.78 (0.00) 0.52 to 0.91 -2.64 (8.89) -20.06 to 14.78 6.31 17.50

LSROMLOC 0.07 (0.77) -0.38 to 0.50 -0.48 (2.15) -4.68 to 3.73 1.53 4.24

TLSROM 0.88 (0.00) 0.71 to 0.95 0.75 (9.05) -16.99 to 18.48 6.42 17.80

LHROM 0.81 (0.00) 0.57 to 0.92 0.51 (3.62) -4.22 to 3.86 2.57 7.12

LLSROM 0.73 (0.00) 0.42 to 0.88 -0.18 (2.06) -6.58 to 7.61 1.46 4.05

Mean 0.64 0.34 to 0.83

SKE KROM 0.85 (0.00) 0.66 to 0.94 -1.96 (7.31) -16.29 to 12.36 10.34 20.27

HROM 0.83 (0.00) 0.61 to 0.93 0.20 (2.39) -4.48 to 4.88 3.38 6.63

LSROMLOC 0.56 (0.01) 0.16 to 0.80 -0.13 (1.23) -2.55 to 2.28 1.74 3.41

TLSROM 0.70 (0.00) 0.36 to 0.87 0.85 (2.27) -3.60 to 5.30 3.21 6.29

LHROM 0.68 (0.00) 0.34 to 0.86 1.41 (5.47) -9.33 to 12.14 7.34 14.39

LLSROM 0.46 (0.04) 0.03 to 0.75 -0.54 (2.01) -4.48 to 3.41 2.84 5.57

Mean 0.68 0.36 to 0.86

SFL KROM 0.63 (0.00) 0.25 to 0.84 -0.38 (1.54) -3.40 to 2.64 1.09 3.02

HROM 0.61 (0.01) 0.22 to 0.83 0.54 (4.31) -7.92 to 8.99 3.05 8.45

LSROMLOC 0.22 (0.34) -0.24 to 0.61 -0.33 (1.86) -3.98 to 3.32 1.32 3.66

TLSROM 0.92 (0.00) 0.81 to 0.97 -1.33 (4.89) -10.91 to 8.24 3.46 9.59

LHROM 0.80 (0.00) 0.55 to 0.92 0.54 (5.20) -9.65 to 10.74 3.68 10.20

LLSROM 0.72 (0.00) 0.41 to 0.88 0.22 (2.00) -3.69 to 4.14 1.41 3.91

Mean 0.65 0.33 to 0.84

RBFPK KROM 0.17 (0.46) -0.29 to 0.57 -1.51 (13.61) -28.18 to 25.17 9.62 26.67

HROM 0.48 (0.03) 0.05 to 0.76 -0.62 (10.39) -20.98 to 19.74 7.35 20.37

LSROMLOC 0.41 (0.08) -0.05 to 0.72 0.07 (1.28) -2.45 to 2.58 0.91 2.52

TLSROM 0.94 (0.00) 0.85 to 0.98 1.41 (3.33) -5.12 to 7.94 2.36 6.54

LHROM 0.65 (0.00) 0.29 to 0.85 -1.33 (5.01) -11.15 to 8.48 3.54 9.81

LLSROM 0.32 (0.17) -1.41 to 0.67 -0.95 (1.45) -3.80 to 1.90 1.03 2.86

Mean 0.50 0.39 to 0.76

[95% Confidence Interval for rho (95% CI), Standard Deviation of the Difference (SD), Limits of Agreement 95% (LOA 95%), Standard error of Measurement (SEM),

Minimal Detectable Change (MDC)]





Lumbar Spine ROM.

40 Chapter 3

3.2 Intra-measure Repeatability

Minimal detectable change (MDC) is defined as “the minimal change that falls outside

the measurement error in the score of an instrument used to measure a symptom”

(Kovacs et al. 2008). The results in Table 8 indicate that the MDC between attempts 2-3

ranged from approx. 2.1° to 26.7°, depending upon the ROM variable. Meaning that in

order to detect a real difference between the attempts that is not due to measurement

error the ROM must reach at least these differences (Damstra et al. 2011). Therefore,

the higher results such as KROM during RBFPK (26.7°), HROM during RBFPK (20.4°)

and KROM during SKE (20.3°) indicate that a large difference in ROM must be made

between attempts 2-3 to be sure of a change. This coincides with the large standard

error mean (SEM) for the same ROM variables between attempts 2-3 (i.e. 9.62°, 7.35°

and 10.34° respectively). The low MDC results (i.e. 2.52°) also mean that only small

differences have to be made to be sure of a real change not due to error. These low

values are seen mainly in the lumbar spine results (Table 8) which ideally should be low

due to the small amount of movement expected to be made in this area. The variation

between the two measures from large to small shows that certain tests may be more

accurate than others (i.e. SFL overall had smaller MDC results than any other test).

Large SEM and MDC coincided with the mean difference (bias) results between

attempts 2-3 (i.e. large SEM and MDC meant a large bias; Table 8). The mean

differences are shown to have be different (over ±0.50°) from zero in a number of the

ROM results, which Bland and Altman (1986) stated should not happen if the results are

repeated measures. All of the mean differences for lateral hip ROM are shown to be

greater than ±0.50° (WB: 0.51, SKE: 1.41, SFL: 0.54, RBFPK: -1.33) and the RBFPK

test in particular has all ROM variables except LSROMLOC mean difference results

above ±0.50° (HROM: -0.62, KROM: -1.51, LSROME: -1.44, LHROM: -1.33, LLSROM: -

0.95). The largest mean bias were seen in HROM during the WB (-2.64), KROM during





Lumbar Spine ROM.

41 Chapter 3

SKE (-1.96) and KROM during RBFPK (-1.51), indicating that on average attempt 3 was

lower than attempt 2 in these variables. This indicates that the repeated ROM results

were not 100% accurate due to the bias in the measurements caused by measurement

errors (Challis, 2008).

The Bland-Altman plots and Table 8 show that there were some large limits of

agreement (LoA) (95%) up to -28° to 25° (KROMRBFPK), which represents the

absolute differences in measurements in relation to the mean of the measurements

(Enoch et al. 2011). However, the majority of the differences were within a smaller inner

range for each test then the LoA (95%); SKE (±1°-±5°) and SFL (±2°-±5°), WB (±3°-

±10°) and RBFPK (±2°-±10°). Therefore, the large variations in the differences and the

outliers of up to ±30° (RBFPK) created the large LoA (95%).

Altman and Bland (1983) stated that the definition of a repeatability coefficient, as

adopted by the British Standards Institution, is that 95% of the differences should be

less than ±2SD (or 95% LoA). They also stated that if the differences are normally

distributed then 95% of the differences will be within the LoA (95%). The Bland-Altman

plots (Figures 2-5) showed that 90-100% of all the differences between attempts 2 and

3 for all 4 tests were within the LoA (95%). SFL was the only test to have 95% or more

of all the ROM differences within the LoA (95%), with the other tests showing variable

distribution. In particular the RBFPK test had 90% of the differences within LoA (95%)

for 5 of the 6 ROM variables. The only ROM variable to have an average of 95% of all

the differences within the LoA (95%) in each test was the LLSROM. Therefore, the

Bland-Altman data suggests that between attempts 2-3 SFL was the only normally

distributed test and LLSROM was consistently normally distributed. However, the other

tests had varied distribution normality and the results from all 3 attempts (Table 7) show

that several of the ROM variables are not normally distributed and therefore non-

parametric analysis was performed.





Lumbar Spine ROM.

42 Chapter 3

The majority of the spearman’s correlation coefficient (rho) results showed fair (0.22)

to almost perfect (0.95) agreement in ROM between individual attempts (2-3). However,

two of the ROM variables had poor correlation; LSROMLOC during the WB (0.07) and

KROM during RBFPK (0.17). The KROM result during RBFPK (rho = 0.17) can be

rounded up to fair correlation (0.2). Whereas LSROMLOC during the WB is closer to

zero than 0.2, which meant that attempt’s 2-3 definitely had poor correlation. The

LSROMLOC spearman results for each of the tests had the worst agreement (i.e. poor;

0.07 to moderate; 0.56), which coincided with the variation in LSLOCROM from 5° in all

3 attempts seen in Table 7 (i.e. 5.57°, 4.28°, 5.03°, 5.60°). This indicated that the

LSLOCROM did not always start at 0° (LSN), as all of the ROM values were taken from

5° of lumbar flexion on the Biometrics software (i.e. -0.57° starting point would equal

5.57° LSROMLOC).

Overall, the mean intra-measure agreement rho results for the ROM variables were

moderately correlated (>0.4) for all of the lumbar flexion tests. As described above the

individual ROM variables showed fair to almost perfect correlation for all ROM variables,

with the exception of one ROM variable. However, several of the results were also

variable depending on the test (i.e. LSROMLOC; WB 0.07, SKE 0.56, SFL 0.22, RBFPK

0.41). TLSROM rho results were the most consistent throughout the tests, with strong

(0.70) to almost perfect (0.94) intra-measure agreement.





Lumbar Spine ROM.

43 Chapter 3

3.3 Inter-Rater Agreement

Table 9. Inter-Rater ROM Agreement for Lumbar Flexion Tests (attempts 1-3)

KROM kappa (CI)

HROM kappa (CI)

LSROMLOC kappa (CI)

TLSROM kappa (CI)

LHROM kappa (CI)

LLSROM kappa (CI)

Mean kappa (CI)

WB 0.64

(0.51 to 0.77)

0.64 (0.51 to

0.77)

0.67 (0.53 to

0.80)

0.64 (0.51 to

0.77)

0.64 (0.51 to

0.77)

0.64 (0.51 to

0.77)

0.65 (0.51 to

0.77

SKE 0.30

(-0.15 to 0.76)

0.64 (0.51 to

0.77)

0.63 (0.51 to

0.77)

0.48 (0.17 to

0.78)

0.46 (0.22 to

0.69)

0.30 (0.07 to

0.53)

0.47 (0.22 to

0.72)

SFL 0.67

(0.53 to 0.80)

0.46 (0.08 to

0.83)

0.64 (0.51 to

0.77)

0.52 (0.32 to

0.73)

0.48 (0.17 to

0.78)

0.46 (0.04 to

0.87)

0.54 (0.28 to

0.80)

RBFPK 0.64

(0.51 to 0.77)

0.46 (0.16 to

0.75)

0.64 (0.51 to

0.77)

0.64 (0.51 to

0.77)

0.64 (0.51 to

0.77)

0.70 (0.50 to

0.91)

0.62 (0.45 to

0.79) [95 % Confidence interval (CI), Weighted Kappa Correlation (kappa)]

Table 9 shows that the attained inter-rater agreement on the ROM results ranged from

fair (k = 0.30) to strong (k = 0.70). All of the correlations are positive which means that

when one judges ROM score increased so did the other judges; therefore agreement

was made on the ROM variable. Overall, the mean inter-rater agreement results were

moderately correlated (k = 0.47 – 0.65).

The best inter-rater agreement was shown in the WB test, with moderate correlation (k

>0.60) for each ROM variable. The LLSROM during RBFPK had the highest correlation

(0.70) and both LLSROM and KROM during the SKE had the lowest correlation (0.30)

between judges. The ROM variable LSROMLOC was the most consistent variable

throughout the tests (k > 0.60). This is due to the data analysis protocol involving taking

the ROM values from 5° of lumbar flexion (point of loss of control), which should be the

same or a similar point for both judges.





Lumbar Spine ROM.

44 Chapter 3

3.4 Association of Other Parameters

The electrodes were placed on the left side of each individual’s body was tested due to

limitations of the equipment (i.e. not enough electrode attachments) and for

consistency. Therefore a comparison of the LKEA and joint ROM was made rather than

RKEA. Table 10 shows this comparison along with BMI, and age correlations, which

have been associated with influencing lumbar spine ROM. The rho results demonstrate

that for the majority of the test ROM variables there is poor (0-0.2) to fair (0.2-0.4)

positive or negative correlation, but several of the results show moderate (rho 0.4-0.7)

to almost perfect (rho >0.8) correlation (Table 10, Appendix 7.0).

There were two almost perfect correlations (rho >80) seen in the female participants;

between LKEA and LSROMLOC (rho = -0.94) during the RBFPK test, and BMI and

KROM (rho = 0.81) during the SFL test. There were also four strong correlations (0.7-

0.8) seen in the female participants between age and TLSROM during both the WB test

(rho -0.78) and SFL (rho -0.72), and LHROM (rho 0.78) during the RBFPK test.

TLSROM also had strong correlation with BMI (rho 0.76) during the SKE test in the

female participants. The female participants had many moderate or above correlations

related to lumbar spine movement (Table 10). Female subjects had increased lumbar

spine ROM with increased BMI (LSROMLOC during RBFPK; rho 0.59, TLSROM during

SKE; rho 0.76), but generally female lumbar spine ROM decreased with age (TLSROM

during WB; -0.78, TLSROM during SFL; -0.72, TLSROM during RBFPK; -0.46).

However, during the SKE female subjects had increased lumbar spine ROM with

increased age (TLSROM; rho 0.44), which could be due to many participants not

reaching 5° of lumbar flexion.





Lumbar Spine ROM.

45 Chapter 3

Table 10. Spearman’s Correlation Coefficient (rho) for Hamstring Length (via

LKEA), Body Mass Index (BMI), Age and Joint ROM (Attempts 1-3)

Test Outcome Variable

(Joint

ROM)

Spearman’s Correlation Coefficient (rho)

Male LKEA (p value)

Female LKEA

(p value)

Male BMI (p value)

Female BMI

(p value)

Male Age (p value)

Female Age

(p value)

WB KROM 0.64 (0.05) -0.57 (0.09) 0.61 (0.06) 0.40 (0.25) 0.18 (0.63) -0.03 (0.95)

HROM 0.59 (0.07) 0.55 (0.10) 0.39 (0.26) -0.32 (0.37) 0.49 (0.15) -0.37 (0.29)

LSROMLOC 0.24 (0.51) 0.43 (0.12) -0.29 (0.43) -0.24 (0.50) -0.48 (0.16) 0.28 (0.43)

TLSROM -0.21 (0.56) 0.07 (0.85) -0.31 (0.39) -0.30 (0.41) -0.53 (0.12) -0.78 (0.01)

LHROM 0.49 (0.15) 0.22 (0.54) 0.07 (0.86) -0.07 (0.86) 0.39 (0.27) -0.04 (0.91)

LLSROM 0.02 (0.96) 0.15 (0.69) -0.19 (0.60) -0.10 (0.78) 0.36 (0.31) -0.43 (0.21)

SKE KROM 0.39 (0.26) 0.10 (0.79) 0.37 (0.29) -0.10 (0.78) -0.45 (0.19) 0.01 (0.99)

HROM -0.08 (0.83) 0.50 (0.15) 0.26 (0.47) -0.27 (0.44) -0.35 (0.33) -0.28 (0.43)

LSROMLOC 0.47 (0.17) -0.14 (0.70) -0.09 (0.80) 0.34 (0.34) -0.14 (0.71) 0.28 (0.43)

TLSROM 0.25 (0.49) -0.38 (0.28) -0.09 (0.80) 0.76 (0.01) -0.14 (0.71) 0.44 (0.20)

LHROM -0.36 (0.31) 0.30 (0.40) -0.33 (0.35) 0.03 (0.93) 0.35 (0.32) -0.26 (0.47)

LLSROM -0.10 (0.78) 0.05 (0.89) 0.02 (0.95) 0.02 (0.96) 0.55 (0.10) -0.14 (0.70)

SFL KROM -0.20 (0.58) -0.57 (0.08) -0.44 (0.20) 0.81 (0.01) -0.24 (0.50) 0.53 (0.12)

HROM -0.47 (0.17) 0.34 (0.34) -0.07 (0.86) 0.16 (0.65) -0.05 (0.90) -0.23 (0.52)

LSROMLOC -0.21 (0.56) 0.25 (0.49) 0.35 (0.33) -0.34 (0.34) 0.13 (0.73) 0.14 (0.70)

TLSROM -0.04 (0.91) 0.08 (0.83) 0.15 (0.68) -0.39 (0.26) -0.56 (0.09) -0.72 (0.02)

LHROM -0.36 (0.31) 0.37 (0.29) 0.08 (0.83) -0.06 (0.88) 0.13 (0.73) 0.33 (0.36)

LLSROM 0.09 (0.80) -0.33 (0.35) 0.41 (0.24) 0.14 (0.70) 0.44 (0.20) 0.25 (0.48)

RBFPK KROM -0.09 (0.80) 0.15 (0.68) 0.12 (0.75) -0.08 (0.83) -0.68 (0.03) 0.03 (0.93)

HROM -0.36 (0.31) 0.46 (0.19) 0.19 (0.60) -0.36 (0.31) -0.61 (0.06) -0.62 (0.06)

LSROMLOC 0.06 (0.88) -0.94 (0.00) -0.27 (0.45) 0.59 (0.07) 0.15 (0.69) 0.28 (0.44)

TLSROM -0.60 (0.07) 0.15 (0.69) 0.16 (0.65) -0.32 (0.37) 0.10 (0.79) -0.46 (0.19)

LHROM -0.09 (0.80) -0.20 (0.59) 0.14 (0.70) 0.50 (0.14) -0.57 (0.09) 0.78 (0.01)

LLSROM 0.02 (0.96) 0.43 (0.22) -0.38 (0.28) -0.53 (0.12) 0.39 (0.27) -0.57 (0.08)

Several of the ROM variables and associated factors had positive moderate

correlation for both male and female participants. HROM during the WB and hamstring

tightness (via LKEA) had moderate correlation in both the male (rho 0.59) and female

(rho 0.55) subjects, which indicated that subjects with tight hamstrings had increased

hip ROM. KROM during the WB and BMI also had moderate correlation for both male

(rho 0.61) and female (rho 0.40) subjects, which indicated that higher BMI lead to

increased knee flexion during the WB test.

Correlation:

Poor [0.0-0.2] Fair [0.2-0.4] Moderate [0.4-0.7] Strong [0.7-0.8] Almost Perfect [>0.8]





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46 Chapter 3

Table 10 also shows that for several of the ROM variables age was negatively

correlated for both male and female subjects, indicating that with increasing age there

was decreased ROM at certain joints. Total lumbar spine ROM (TLSROM) during both

the WB and SFL tests was shown to decrease with increased age in male and female

subjects. Hip ROM was also decreased in older subjects during the RBFPK test in both

male (rho 0.61) and female (rho 0.62) subjects.

3.4.1 Lumbar Spine Movement

FIGURE 6. Lumbar Spine ROM during Flexion Control Tests

Figure 6 demonstrates that lumbar spine loss of control (5° LS flexion) occurs at a

variety of percentages of total LS ROM during the different tests (i.e. 31.4%, 73.7%,

34.9%, 38.2%). With some of the participants not loosing control of their LS during the

SKE test (i.e. average of 4.28°, Table 7), the average percentage of movement to loss

of control was high (73.7%). However, the other three tests showed that LS flexion

occurred at below 40% of the total LS movement for the majority of the flexion control

tests.

0

5

10

15

20

25

30

35

WB SKE SFL RBFPK

LSROMLOC

Total LS ROM

73.71%

34.85%

38.18%

31.41%





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47 Chapter 4

4 Chapter 4

Discussion

4.1 Normative Range of Movement

Motor control is an area of interest in LBP research, as maladaptive motor control can

compromise lumbar stability and can perpetuate LBP (Barr et al. 2005, Luomajoki et al.

2008). In the past, biomechanical movement pattern assessment of the low back has

been investigated for reliability and validity, with clear differences between patients with

or without LBP during motor control tests (Luomajoki et al. 2008). However, the majority

of the previous studies relied on qualitative data (i.e. subjective observations) and many

assessed diagnostic reliability based on a whole battery of tests. Of the motor control

tests involved no studies have provided evidence-based ‘normative’ ROM values or

used biomechanical monitoring devices. To the knowledge of the researchers involved

this is only the second study to utilize a quantitative method for analyzing lumbar motor

control tests, secondary to Enoch et al. (2011). Thus no previous studies are directly

comparable with the methodology in this study.

The accuracy of ‘normative’ ROM values has been reported to be important in human

spinal movement assessment, as interventions are provided to individuals who fall

outside the ‘normative’ boundaries (Comerford and Mottram 2001a, b). Luomajoki et al.

(2007) and Enoch et al. (2011) stated that normative ROM values for correctly

performed MCD tests require establishment, as on review of the previous research on

MCD it is clear that there has been little to no evidence to support the previously

reported ROM values (Table 1). Therefore, no clear consensus has been made for

‘normative’ ROM values. The findings of this study show that the previously reported

‘normative’ ROM variables may not be accurate when measured by a quantitative

methodology. Table 7 demonstrates that the average evidence-based ROM values





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48 Chapter 4

were shown to be 10-15° less than the previously reported values (Table 1). However,

the limitations of the methodology influenced the reliability of the evidence-based

‘normative’ ROM values. Therefore, the reliability and limitations of the methodology will

be the focus of this section.

4.2 Methodological Reliability

The methodological reliability is important, as with a reliable data collection and

analysis method ‘normative’ ROM values can be determined. To evaluate reliability this

study included intra-measure and inter-rater agreement. It also included standard error

of measurement (SEM) and minimal detectable change (MDC). The MDC results

provide practitioners with an estimate for the acceptable variations between two

attempts (attempts 2-3) and may indicate the accuracy of certain tests and ROM

variables. However, MDC computation relies on the assumption of data being drawn

from a normally distributed population (Kovacs et al. 2008). In this study the data was

not normally distributed, therefore SEM and MDC are presented in the results for clinical

practice and comparison with other work.

The principle findings of this study were that the majority of the lumbar flexion test

ROM variables had moderate or above (>0.4) correlation for both intra-measure and

inter-rater agreement. However, four of the ROM variables (LSROMLOC WB,

LSROMLOC SFL, KROM RBFPK and LLSROM RBFPK; Table 8) had poor (rho <0.2)

to fair (>0.2 – 0.4) intra-measure agreement and the SKE test had fair (k = 0.30) inter-

rater agreement for two of the ROM variables. Previous researchers in the area of

motor control tests for LBP have accepted that intra and inter agreement results above

moderate correlation (>0.4) are clinically relevant and reliable (Paatelma et al. 2010,

Luomajoki et al. 2007). Only 1 of the 4 tests (SKE) had moderate or above (rho >0.4)





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49 Chapter 4

intra-measure agreement for all of the ROM variables (Table 8) and only 1 of the 4 tests

(SFL) had moderate or above (k >0.4) inter-rater agreement (Table 9). The spearman’s

correlation coefficient results indicated that there was variability in the method used, but

on average the tests had moderate intra and inter reliability (>0.4, Tables 8, 9). The

poor to fair results during the WB, SKE and RBFPK (Table 8) testing could have been

due to a number of issues within the methodology. Therefore, modifications to the

methodology of the study could improve the level of agreement during all of the tests

involved.

The spearman correlation coefficients (rho) used for reliability could easily disguise

large differences in the ROM measurements (Enoch et al. 2011) therefore this study

also utilized Bland-Altman plots. Bland-Altman plots demonstrate the true differences

between two individual measures (Altman and Bland, 1983). Enoch et al. (2011)

showed that Bland-Altman plots for MCD tests had the majority of the differences within

a smaller range than the limits of agreement (LoA). With the LBP group values being at

the outer range of the LoA even though the correlation coefficient results were the same

for subjects with and without LBP. This study had similar results, with the majority of the

differences being within a smaller range (i.e. from ±1° to ±10°) for all of the ROM

variables during all of the tests (Figures 2-5). However, even though only non-LBP

subjects were used there were still large variations between some of the single

measures up to approx. ±20° - 30° and large LoA, which had moderate to almost

perfect correlation coefficients (Table 8, Figures 2-5). Therefore, the Bland-Altman plots

demonstrate that there was a true variation between certain single measures (attempts

2 and 3) of up to approx. ±30° by a single examiner, which should be used as a

supplement to the correlation coefficients. Many of the ROM variables had differences

within a smaller range therefore it is possible that the outliers may be accounted for by





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50 Chapter 4

the study limitations and could be improved with further adjustments to the protocols

involved.

4.3 Novice-Expert Variation

It is worth commenting that for the therapists involved in this study better protocol

training could have been performed beforehand. Dankearts et al. (2006) stated that

increased familiarity with the motor control tests can increase reliability, which may be

the same for this studies data collection and analysis process. Enoch et al. (2011),

Henry et al. (2012) and Dankearts et al. (2006) all reported that a specific training phase

can improve agreement between practitioners. Training could be useful as O’Sullivan et

al. (2010) reported that reliability may vary according to experience of those involved.

Within this study the main researcher was a novice physiotherapist, but there was also

a secondary experienced physiotherapist involved in the data analysis. During the data

analysis process there was fair (k = 0.30) to strong (k = 0.70) agreement between the

novice and expert practitioners (Table 9). This is much less than the almost perfect (k =

0.90, CI 0.74-1.04) agreement between novice practitioners Henry et al. (2012) found in

motor control tests. However, the ‘novices’ in the study by Henry et al. (2012)

underwent a training period prior to the assessments. The variation between novice and

expert practitioners in this study was similar to the research of Dankearts et al. (2006),

Enoch et al. (2011) and Luomajoki et al. (2007) who all demonstrated that

inexperienced practitioners had poor agreement with experts, due to the reliance on

‘expert opinion’ in the testing. However, the standardized data analysis protocol used in

this study (Appendix 3.0) allowed the two practitioners to on average reach moderate

agreement (k = 0.47 to 0.65), which is a step in the right direction for the methodology

being of use in a clinical or research setting (Dankearts et al. 2006).





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51 Chapter 4

The novice practitioner performed the data collection which involved teaching the

tests; however their inexperience influenced participant performance of the tests. As

previously stated the researcher involved in the data collection was a novice practitioner

who had little training in the use of MCD testing. This influenced the reliability of the

testing, as the average number of attempts that had to be made by each subject to

proficiently perform the WB was shown to approximately 7 (i.e. 4 practice with the

researcher giving feedback and 3 recorded with no feedback) and the other tests had

an average of 5-6 attempts (Table 6). The protocol initially stated that 5 attempts would

be adequate (i.e. 2 practice attempts with feedback and 3 recorded attempts with no

feedback), which was underestimated by the researcher. Although, Comerford and

Mottram (2012) reported that 3-8 repetitions should be sufficient for teaching, learning

and familiarization of the test movements. This indicated that a higher level of expertise

may be required in order to help the participants perform MCD tests correctly within 3-5

attempts, which could be achieved via a training period (Enoch et al. 2011, Dankearts et

al. 2006, O’Sullivan et al. 2010). Alternatively more teaching repetitions (i.e. 8+) could

have been performed with feedback before 3 attempts without feedback, as Comerford

and Mottram (2012) stated that the test should involve reproducing the movement

without feedback. Improvement in reliability would be due to the test being tested and

not the practitioners’ ability to instruct the test (Comerford and Mottram, 2012).

4.4 Feed-Forward and Feed-Back Mechanisms

The worst reliability for both intra and inter-agreement was during the WB, where the

lumbar spine range of movement to the point of loss of control (LSROMLOC) variable

had poor correlation (rho 0.07). However, the inter-rater agreement for the WB was

shown to be moderately (k >0.6) correlated for all of the ROM variables. The intra-





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52 Chapter 4

measure agreement during the WB (i.e. agreement between single measures) was

shown to have moderate (rho 0.59) to almost perfect (rho 0.88) agreement for all ROM

variables with the exception of LSROMLOC. Similarly, the intra-measure agreement

result for LSROMLOC during the SFL test had fair (rho 0.22) correlation, whereas the

other ROM variables all had moderate (rho 0.61) to almost perfect (rho 0.92)

correlation. This demonstrates that there was some intra-measure variability within the

LSROMLOC variable during these two tests and potentially the other tests (SKE; rho

0.56, RBFPK; rho 0.41).

The ROM variables were all taken at 5° of lumbar flexion (LSROMLOC) which means

that the average LSROMLOC should have been 5° (i.e. start at 0° and end at the point

of loss of control at 5°). In the view of Tidstrand and Horneij (2009) the poor to fair

agreement may be accounted for by differences in starting position of the lumbar spine

between individual attempts. The average ROM to the point of loss of control was

variable for all of the tests (WB 5.57°, SKE 4.28°, SFL 5.60°, RBFPK 5.03°; Table 7).

This indicated that on average the subjects began in a LS extended position for the WB,

SFL, RBFPK (-0.57°, -0.60°, -0.3°) tests and in a flexed position during the SKE (0.72°)

test. The EG device was used by the researcher to set the subjects in neutral (‘0°’), with

the researcher providing feedback to assist the subjects in assuming the neutral

posture. However, there was no data collected until the researcher moved away from

the subject to activate the Biometrics software, taking away the feedback. The lack of

feedback could have allowed the subjects to move prior to the collection or testing

period, as O’Sullivan et al. (2010) stated that healthy subjects have difficulty assuming a

neutral LS posture without feedback.

The MCD tests are movements which were unfamiliar to the subjects, as MCD

procedures involve the control of one body segment while moving another which may





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53 Chapter 4

not regularly done in daily activities (Sahrmann, 2002, Comerford and Mottram, 2012).

Therefore, the external tactile and auditory feedback given by the researcher may also

have been a factor in the subjects’ ability to perform the tests, as during the recorded

attempts there was no feedback. O’Sullivan et al. (2010) reported that even subjects

without LBP find it difficult to assume postural positions with no feedback. Studies

involving local segmental muscle control state that feedback via tactile, verbal and

visual means is a critically important to aid patient performance (Hides, Richardson and

Hodges, 2004, Herbert, Heiss and Basso, 2008). Radebold et al. (2001) and Lee et al.

(2012) reported that LBP patients performed postural control tests worse with their eyes

closed, which they believed was due to proprioception damage leading to increased

reliance on visual feedback. Feedback therefore is a key factor to correct performance

of the motor control tests involved in this study in both healthy and LBP subjects. Wand

et al. (2012) demonstrated that visualization can also improve performance of repeated

spinal movements. Mirror visual feedback could have been utilised during test

performance to allow patients to visualize their movement (Wand et al. 2012).

The movement prior to the subject performing the test may also have been due to

feed-forward anticipatory movement once the feed-back had been removed (Zeinali-

Davarani, et al. 2008, Brumagne et al. 2008). The change in pressure on inter-vertebral

discs (i.e. 100% pressure is normal standing; 150% standing flexion; 140% normal

sitting; 185% sitting flexion) could have triggered an initial feed-forward response

(Norris, 2000, Indahl, Holm and Bogduk, 2009). After performing several of the test

movements prior to recording the data pre-programmed feed-forward adjustments, firing

patterns, amplitudes of activation and re-organisation of trunk muscle representation at

the motor cortex would have been made by the participants (Muthukrishnan et al. 2010,

Hodges, 2004). These short-term motor memory factors become predictable and





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54 Chapter 4

possibly led to feed-forward anticipatory activation of deep local (e.g. deep multifidus,

transverse abdominals) and superficial global muscles (e.g. erector spinae, latissimuss

dorsi, gluetius maximus), with movement being made in advance of the imposed forces

(Gill and Callaghan, 1998, Hodges, 2004). However, anticipatory adjustments are based

on a prediction and are therefore suboptimal (Latash, 2012). Anticipation (e.g. hip

strategy) in this study was a subjective observation, as no data was collected while the

subject was positioned into neutral or before voluntary movement occurred. Anticipatory

adjustments usually occur at 100ms prior to muscle activation whereas voluntary task

specific corrections in posture occur after 150ms (Latash, 2012). Therefore with no

electrogoniometry (EG) or electromyography (EMG) activity recorded it is difficult to

definitively comment on this issue. Gill and Callaghan (1998) showed that there was no

difference in short-term motor memory between subjects with or without LBP; therefore

altered muscle activation, feed-forward mechanisms and difficulty in performing the

tests would be the same for LBP groups.

4.5 Skin Movement

During the RBFPK, SFL and WB tests several ROM variables showed poor (rho >0.2)

to fair (rho <0.2 – 0.4) intra-measure agreement (Table 8), which indicated that there

were issues with the reliability of the data collection. The low agreement could be

accounted for by skin movement during the attempts, which has not been reported in

other low back motor control studies. Skin movement was the main limitation of this

study and was observed during all of the MCD tests and meant that true angles could

not be assessed (Appendix 3.0), therefore knee, hip and lumbar spine ROM made

during the tests was analyzed. This has implications on the tests themselves as skin





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55 Chapter 4

movement can adversely affect findings when measured with skin mounted devices

(Chockalingam et al. 2002).

Skin movement creates electrode displacement, which is an issue because the

measurement of a joint ROM by electrogoniometry (EG) depends on a change in

voltage between the two end blocks of each electrode. Kiran et al. (2010) reported that

skin movement during flexion of the knee and hip interferes with the change in voltage

between the two blocks and alters the ROM values obtained. Similarly, Rowe et al.

(2001) stated when using EG as much as 20° of movement can be made purely from

skin movement during flexion or extension. Therefore, in order to reduce the movement

of the electrodes Rowe et al. (2001) used long plastic strips attached to the EG and to

the lateral borders of the skin. They also utilized stiff foam blocks under the electrodes

to account for abduction or adduction due to body shape and elastic straps to apply

pressure on the electrodes. However, Piriyaprasarth et al. (2008) stated that the use of

the adaptations Rowe et al. (2001) still encounter inaccuracies due to skin slippage. The

foam blocks actually increased skin movement causing substantial errors in abduction

and adduction. Although, Rowe et al. (2001) overall reported reduced measurement

error they still found 1°-2° variation between 3D Vicon system and EG. However,

Pomeroy et al. (2006) demonstrated that these two devices are not interchangeable

measures of ROM. Therefore, accurate attachment of the EG electrodes is vital in order

to obtain valid measurements of ROM (Piriyaprasarth et al. 2008).

Skin movement is affected by BMI (Table 9); larger BMI may cause larger skin

movement error (Kuo, Tully and Galea, 2008). Larger BMI in the female group was

shown to have moderate to almost perfect correlation with increased ROM in several of

the ROM variables (e.g. LSROMLOC; 0.59, LHROM; 0.50 during RBFPK, KROM; 0.81

during SFL, TLSROM; 0.76 during SKE and KROM; 0.40 during WB in the females).





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56 Chapter 4

Only two ROM variables were increased with larger BMI in the male group (e.g. KROM;

0.61 during WB and LLSROM; 0.41 during SFL). In particular, during the WB (rho 0.61,

0.40) and SFL (rho -0.44, 0.81) tests skin movement due to larger BMI may have

affected the KROM results for both males and females. Previous studies which have

utilized EG to measure knee flexion and extension have shown that skin movement can

adversely affect results. Cappozzo et al. (1996) reported that lateral femoral epicondyle

markers can be displaced posteriorly up to 4 cm during knee flexion. Similarly a study

by Kiran et al. (2010) showed that EG analysis of the knee joint can be adversely

affected by skin distraction during flexion and extension activities. Kuo, Tully and Galea

(2008) also reported that lateral thigh skin markers can be displaced during hip and

knee flexion, which could account for the deviations in the WB, SFL and RBFPK results

(Appendix 6.0).

With increased age there was decreased TLSROM in the WB (male; -0.53, female; -

0.78), SFL (male; -0.56, female; -0.72) and RBFPK (female; -0.46) tests. This agreed

with previous research that has shown that LS ROM decreases with age (Intolo et al.

2009). However, the age of the participants had moderate to strong positive (rho 0.4>)

or negative (rho <-0.4) correlation with many of the other ROM variables (Table 10)

indicating that ROM increased or decreased with increased age at certain joints. This

could be due to older aged participants having looser, softer skin creating skin

movement (Kuo, Tully and Galea, 2008). The affected ROM values were at known

areas of displacement; the lateral thigh, knee and lumbar spine (Table 10) (Kuo, Tully

and Galea, 2008). However, there was a lack of variation in age due to the small

sample size (n=20) and convenience of the sample, therefore this study is unable to

make definitive conclusions about the influence of age on the ROM variables.





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57 Chapter 4

In the view of Rowe et al. (2001) due to skin movement the results of this study may

be invalid measures of the ROM of the underlying structures. Therefore, other

biomechanical devices may be more accurate when monitoring ROM during motor

control tests; such as the 3D Vicon system, skeletal mounted devices, magnetic

resonance imaging (MRI) etc. However, these devices are invasive, costly, require more

time and could not be easily used in a clinical setting by physiotherapists, but could be

used in future studies to establish ‘normative’ ROM values (O’Sullivan et al. 2010,

Paatelma, Karvonen and Heinonen, 2010, Borghuis, Hof and Lemmink, 2008, Fritz,

Erhard and Hagen, 1998).

4.6 Fasciae Influence on Range of Movement

The LS ROM measurements were potentially influenced by feed-forward mechanisms

tensioning the fasciae of the lumbar region. In the view of Chen et al. (2012) and

Alexander (2007) passive treatments such as fascial taping and massage work to

reduce pain because underlying fasciae and skin are interconnected, which can

influence skin movement (Tozzi, Bongiorno and Vitturini, 2012). The thoraco-lumbar

fasciae (TLF) encloses the muscles of the lumbar spine and has three sections;

posterior, anterior and middle (Gilchrist et al. 2003). Fascial tension in these sections

contributes to spinal stability, but there remains debate on its possible influences on

spinal control (Hodges, 2004b). TLF is influenced by proprioception (Barker and Briggs,

2007) which causes activation of muscles. Findley and Schleip (2007) stated that

lumbar fasciae transmits tension between trunk and leg muscles (i.e. latissimus dorsi on

one side and gluteus maximus on the other side), which possibly influenced the LS

ROM results. Feed-forward early activation of muscles can tension fascia and stimulate

connected muscles prior to voluntary muscle contraction during test performance (Tesh





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58 Chapter 4

et al., 1987), which could alter skin position. This could have contributed to the variation

in lumbar spine ROM during the MCD tests.

The posterior layer of the TLF regulates tension between both local (i.e. internal and

external obliques) and global muscles (i.e. latissimuss dorsi and gluetius maximus), as it

has extensive muscular attachments (Stevens et al. 2007). However, the transverse

abdominals (TrA) may have had the largest influence on tensioning fascia due to its

extensive attachments and known feed-forward anticipatory activation during trunk

movements in healthy subjects (Massé-Alarie et al. 2012, Hodges, 2004a, b).

Anticipatory activation of TrA maintains fascial influence on segmental neutral zone

motion (Barker and Briggs, 2007). Tension in the TrA aponeurosis occurs during spinal

flexion and is transmitted to the vertebrae via the posterior lumbar fasciae (PLF), which

indicates that PLF has a role in spinal control (Barker et al., 2004, Barker et al. 2006).

Therefore, tension of the PLF influences movement and produces extension moments,

which could account for the extended lumbar starting positions for several of the tests

(Table 7; WB -0.57°, SFL -0.60°, RBFPK, -0.3°) (Barker et al. 2006, Tesh et al. 1987,

Hodges and Richardson, 1997). When tension is applied by the TrA and latissimus

dorsi, 50% of the force passes transversely in the PLF (Barker et al. 2004). This could

account for the variable intra (rho 0.32-0.73) and inter (k = 0.30-0.70) agreement in

lateral lumbar spine movement (Table 8, 9). In combination the multifidus (MF) may

have also been activated, as several studies have shown that TrA and MF activation is

linked to form a ‘corset’ around the waist to stabilize the spine (Kavcic, Grenier and

McGill, 2004, Danneels et al. 2001, Hides et al. 2001). Therefore, the use of

electromyography (EMG) on key muscles (e.g. TrA, MF, Latissimus dorsi, internal and

external obliques etc.) during the tests could be used to assess their influence on

lumbar spine ROM.






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59 Chapter 4

4.7 Lumbar Spine Neutral Zone Range of Movement

Lumbar spine ROM to the point of loss of control was variable depending on the test

(i.e. WB; 31.4%, SKE; 73.7%, SFL; 34.85% and RBFPK; 38.18%; Figure 6). Grauer et

al. (2000) reported that the lumbar spine (LS) neutral zone ROM is usually around 25%

of total LS ROM in human subjects. Although, the LS neutral zone according to Panjabi

(1992b) involves inter-vertebral motion where little resistance is offered by the passive

spinal column when muscular and neurological factors are removed (Tidstrand and

Horneij, 2009). Therefore, it is not accurate to simply assume that 25% of spinal

movement during these tests is NZ, as all of the tests involve muscular and neurological

control.

The results of the lumbar percentage ROM to loss of control indicated that some tests

may be easier to pass than others. Several of the subjects were able to complete the

SKE test without failing (i.e. flexion of spine passed 5°), which was demonstrated by the

mean LSROMLOC result being below 5° (i.e. 4.28°; Table 7). This increased the

percentage of lumbar movement to the point of loss of control to 73.7%, which

coincided with the SKE test to be the only test to have moderate or above intra-measure

correlation for all ROM variables (Table 8). Whereas, during other tests such as the

RBFPK test the average percentage LS ROM (38.18%) would be classed as

dysfunctional by Sarhmann (2002) who stated that lumbar spine flexion should occur

after 50% of full lumbar spine movement during the RBFPK test. After observation of

the RBFPK tests Sahrmann (2002) would provide an intervention to reduce pain and

faulty movement (i.e. reducing lumbar flexion and increasing hip flexion). However, due

to the limitations previously discussed in this section (i.e. skin movement, fasciae

tensioning etc.) the accuracy of the percentage of LS ROM to loss of control (5°) may

have been influenced. The variation in percentage of movement to loss of control also





Lumbar Spine ROM.

60 Chapter 4

indicated that the subjects’ possibly compensated for lack of movement at certain joints

with increased movement at other joints (i.e. HROM or LSROMLOC compensated by

KROM or Thoracic spine ROM) or muscular activation to control movement (i.e. stiff LS

or hip extensors during forward bending) (Sahrmann, 2002).

4.8 Associated and Compensatory Factors

The ROM variables were also influenced by hamstring length measured via left knee

extension angle (LKEA). Hamstring length had moderate (rho >0.4) to almost perfect

(rho >0.8) correlation for several ROM variables (Table 10, Appendix 7.0). Kendall et al.

(2005) and Sahrmann (2002) have both reported that hamstring tightness and lumbar

flexion are associated. Richardson (2004) stated that hamstring tightness is one of the

most common findings in LBP, as shortened hamstrings prevent physiologic pelvic

flexion over the hips during any forward bending, which produces excessive kyphotic

force on the LS. Hamstring tightness is associated with decreased flexion ROM of the

hip and LS and increased thoracic spine flexion (Frank, 2010, López-Mi˜narro and

Alacid, 2010). This was the case in both the SFL and RBFPK tests, which had

negatively correlated LKEA and HROM, TLSROM and LSROMLOC in the male group

and LSROMLOC during RBFPK was also negatively correlated (rho -0.94) in the female

group (Table 10).In contrast with the previous research during the WB, SKE and

RBFPK tests there was moderate positive correlation between LKEA and HROM in

either female or male participants (Table 10), meaning subjects with tight hamstrings

had increased hip flexion during the tests (i.e. WB, SFL, RBFPK).





Lumbar Spine ROM.

61 Chapter 4

Knee flexion by the male subjects and possibly increased thoracic spine flexion by the

female subjects may have compensated for hamstring tightness in the WB and RBFPK

tests. Male KROM during the WB (rho 0.64) had a moderate correlation with LKEA,

which meant that males flexed their knees with their hips during the WB. Sahrmann

(2002) stated knee flexion is important in male subjects in order to prevent faulty

hamstring strategy. Sahrmann (2002) believed that males should simultaneously flex

their hips and knees during any forward bending due to the increased load of their

upper body. Increased load was demonstrated in the increased knee ROM in higher

BMI subjects during the WB test (rho 0.64). Sahrmann (2002) also stated that for many

males it is not an issue of hamstring length but rather a motor control issue of the trunk

and pelvis, due to the large upper body which increases the activity of the hamstrings.

Increased activity of the hamstrings was likely to have occurred in a feed-forward

manner within the asymptomatic participants, but may be delayed in LBP patients

(Richardson, 2004). However, hamstring activity was not recorded and should be

included in any future studies.

Female LSROMLOC during the WB (rho 0.43) test also had a moderate correlation

with LKEA, which indicated that participants with tight hamstrings had larger lumbar

Figure 7 – Example of Lumbar Spine Electrode Placement

Sacrum

Lumbar

spine

Thoracic

spine





Lumbar Spine ROM.

62 Chapter 4

flexion ROM to the point of loss of control (5°). On average the female group had

smaller height than the male group, which has implications with the Biometrics device

used. The Lumbar spine EG skin marker used was place with one electrode on the first

sacral vertebra and one in a longitudinal line on the spine (Figure 7). However, with a lot

of the participants, especially the shorter females, the 2nd electrode was placed either

on first lumbar vertebra or into the thoracic spine (Figure 7). Lumbar pelvic rhythm

during trunk flexion involves the co-ordination of lumbar and thoracic flexion with

anterior pelvic tilt. To control this co-ordination the thoracic spine can increase in flexion

to compensate for tight hamstrings (López-Mi˜narro and Alacid, 2010). Therefore,

participants with tight hamstrings may have had increased thoracic spine flexion and

this was recorded rather than increased LS ROM, which would have affected ROM

acquired.

4.9 Recommendations for Future Studies

This study was unable to meet its overall aims, as there was some variation in the

reliability of the testing. However several aspects have been discussed in this section

which require consideration and analysis in the future. Ideally future studies should use

other more accurate biomechanical devices (i.e. 3D Vicon system, magnetic resonance

imaging (MRI), skeletal markers etc.) to develop ‘normative’ ROM values for lumbar

flexion control tests. However, this study informs modifications for future work using the

methodology involved in this study to accurately provide normative ROM values using

electrongoniometry (EG). This would allow inexperienced practitioners to utilise EG in a

clinical setting and potentially improve the accuracy of MCD assessment.

Recommendations for modifications include utilising a similar protocol to Rowe et al.

(2001) to prevent electrode slippage and reduce skin movement errors. Other





Lumbar Spine ROM.

63 Chapter 4

recommendations involve a training period being performed prior to the testing, with

both the expert and novice practitioners being involved in the testing for comparison.

Due to feed-forward anticipatory responses occurring prior to recorded test movement,

data recording should begin before the subjects are set into a neutral posture.

Feedback from the practitioner (i.e. tactile, verbal or visual) and from visual devices (i.e.

ultrasound, video or mirror) is also important for each subject to perform each test

optimally. During each test Electromyography is required on key local (e.g. TrA, MF

etc.) and global (e.g. erector spinae, hamstrings etc.) muscles to assess their activation

patterns and influence on ROM.

Test validity was not assessed in this or other recent studies, which needs

establishment in order to provide accurate clinical assessments (Enoch et al. 2011,

Luomajoki et al. 2007, 2008). Validity is important as the test movements involve many

other factors such as skin movement, fascial tensioning, hamstring tightness and

muscle activity etc. which need to be investigated in future validity studies possibly

utilizing functional MRI, ultrasound or the 3D Vicon system (Hidalgo et al. 2012).





Lumbar Spine ROM.

64 Chapter 5

5 Chapter 5

Conclusions

The overall aim of this study was to create a ‘normative’ data set for ROM variables

during lumbar flexion control tests. However, this study was not able to provide accurate

‘normative’ ROM values due to the limitations within the methodology i.e. skin

movement etc. The studies limitations adversely affected the reliability of the ROM

results, however the majority of the results had moderate or above reliability. Only four

of the ROM variables had below moderate reliability. Therefore, the conclusion of this

study was that the MCD testing methodology is feasible but requires modifications in

future studies.

The modifications required involve a more rigorous data collection protocol, which will

allow for testing accuracy. Specific recommendations for further study included rigorous

attachment of surface electrodes, increased training for both the practitioners involved

and the subjects, feedback to participants during testing, recording of data prior to test

performance and the use of electromyography on key muscles. However, these

modifications need to take into account other influences on lumbar ROM and overall

study reliability.

Subsequent studies need to have larger cohorts of subjects, as this was a pilot study

and that the overall study limitations may not be an issue in larger studies. The small

number of participants (n=20) may have affected the level of correlation between some

of the results i.e. over or under estimation. However, the number of non-LBP

participants was similar to previous MCD research (Luomajoki et al. 2007, Enoch et al.

2011, Roussel et al. 2009a, Paatelma, Karvonen and Heinonen, 2010). With larger

studies age and socioeconomic background diversity is required as lumbar ROM control

may differ across age groups, whereas this study consisted mainly of university





Lumbar Spine ROM.

65 Chapter 5

students. The participants also had to volunteer for the study which may not represent a

true normal population sample.

Acknowledgements

The author would like to thank all the volunteers involved in the study and to the people

who provided support throughout the project.

66 Chapter 5

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84 Chapter 5

Appendix 1 Data Collection Protocol

1. Baseline measurements: age, weight, gender, knee extension angle.

2. Laser spirit level: placed on flat table and used to find horizontal and vertical and

mark on subject.

3. Use lines to mark (with removable pen) place on subject where EG electrodes

are to be placed:

1st EG fixed to the exposed lateral femoral condyle and tibial anatomical bony

landmarks.

2nd EG fixed to exposed greater trochanter and along a longitudinal axis on the

trunk.

3rd EG fixed to first sacrum and to spine along a longitudinal axis.

4. Tape electrodes to patient, with adequate tension; there are no fixed rules

governing which size of sensor is most suitable for a particular joint; this depends

on the size of the subject. The sensor must be capable of reaching across the

joint so that the two end blocks can be mounted where least movement occurs

between the skin and underlying skeletal structure.

Electrodes will be labelled with their appropriate location.

5. Twin axis electrodes are to be used for lumbar spine and hip, whereas a single

axis electrode will be used for knee. They will be attached on the dorsal surface

using double sided tape, while the joint is in a neutral position at the start of each

test.

The “SG” series twin axis goniometers simultaneously measure angles in up to

two planes of movement. The goniometer has two separate output connectors,

which measure in two separate planes of movement. When used to measure a

single axis joint such as the knee or elbow, or when measuring a single plane of

a twin axis joint, simply connect one channel, the other remains redundant. All

85 Chapter 5

twin axis SG series goniometers function the same way, the difference being

physical size.

knee SG150 flexion/extension, valgus/varus

hip SG150 flexion/extension, abduction/adduction

back SG150B flexion/extension, lateral flexion

6. Connect electrodes to Biometrics kit and laptop.

7. Ideally 5 performances of the four tests involved but have to make sure

participant is relatively competent; with the last 3 recordings of each test for each

participant: average of the 3. First attempts are adjusted by the practitioner and

feedback is verbally and proprioceptively given via manual handling.

8. Record data on software; setting alarm for 5° of lumbar flexion from neutral

position (loss of control) so that marker can be placed at this point. Reset neutral

for lumbar spine just prior to each individual attempt.

9. Record the degrees at which the lumbar spine leaves neutral at the hip, knee and

lumbar spine; in notebook and transfer to Excel/SPSS spreadsheet.

10. Excel/SPSS spreadsheet used to show descriptive statistics.

86 Chapter 5

Appendix 2 Data Collection Sheet

Participant number................

Age

Gender

Height

Weight

BMI

KEA

Work Y/N or Student (Circle)

ROM Attempt 1 Attempt 2 Attempt 3 Average

KROMWB

HROMWB

LSROMLOCWB

LSROMEWB

LHROMWB

LLSROMWB

KROMSKE

HROMSKE

LSROMLOCSKE

LSROMESKE

LHROMSKE

LLSROMSKE

KROMSFL

HROMSFL

LSROMLOCSFL

LSROMESFL

LHROMSFL

LLSROMSFL

KROMRBFPK

HROMRBFPK

LSROMLOCRBFPK

LSROMERBFPK

LHROMRBFPK

LLSROMRBFPK

87 Chapter 5

Appendix 3 Data Analysis Protocol

1. Biometrics Datalog software used to get raw data from electrogoniometry device.

2. There should be 3 Attempts for each flexion control movement, which should

have knee (pink), hip (blue), lumbar spine (green), lateral hip (organge) and

lateral lumbar spine angles (red).

3. In order to view the point where we know that the lumbar spine has gone into a

flexion range of movement, select the lumbar spine trace on the Axis/Markers

Key.

4. Then follow the LS trace to the first point that the trace goes to 5° or above (i.e.

5.1°). This entails zooming in on the trace and finding a positive fluctuation in the

trace, which will be an average of 2 blocks of time due to the software (between

0.00.002 and 0.00.006 of a second).

[5° was used as a loss of flexion control indicator on this Biometrics system as

Panjabi (1992b) showed that the neutral zone (NZ) for lumbar flexion was 1.5°

and the elastic zone (EZ) was 6.1° and the overall range of movement (ROM)

was 7.6°. Also, between L5 and S1 the flexion results were; NZ 3°, EZ 7° and

ROM 10°. We attached the EG electrodes to S1 and L1/T12. The Biometrics

system has a margin of error of ± 2°, therefore looking for 5° will allow us to find

the point where the spine is either out of the neutral zone (3°-5°) or out of the

elastic zone (5°-7°) and starting to go into a flexion ROM (7°+)]

5. Then zoom back out once this has been marked to check that the overall lumbar

spine trace has gone into flexion (i.e. positive increase/moment close to event

marker trace), if it has not then go to the next point where a flexion angle of 5° or

more has been made and repeat steps 4 and 5.

6. Then note down on a spreadsheet the knee, hip, lumbar spine (5 or 5.1°), lateral

hip and lateral lumbar spine angles.

7. Next, zoom into the first 2 blocks of time on the trace in order to get an average

of the two blocks for each trace. Note down the knee, hip, lumbar spine (should

ideally be 0, but can fluctuate due to pre-emptive movement), lateral hip and

lateral lumbar spine angles.

88 Chapter 5

Example of Full Electrogoniometer Trace for RBFPK (Participant 1)

Example of Zoomed in RBFPK Trace to View Loss of Control (Praticipant 1)

Lu

mb

ar s

pin

e R

OM

0:00.000 0:02.000 0:04.000 0:06.000 0:08.000 0:10.000 0:12.000

180

-180

-150

-100

-50

(deg) 0

50

100

150

Lu

mb

ar s

pin

e R

OM

0:06.400 0:06.600 0:06.800 0:07.000 0:07.200 0:07.400 0:07.600 0:07.800 0:08.000 0:08.200

180

-180

-150

-100

-50

(deg) 0

50

100

150

Lumbar spine ROMLumbar spine ROMHip ROMHip ROMKnee ROM

Graph Key (degrees)

Lumbar spine ROMLumbar spine ROMHip ROMHip ROMKnee ROM

Graph Key (degrees)

5°

5°

89

8. Next, take all the individual angles noted down from the 5° of flexion point away from the start angles and this will give you the range of

movement for each trace/marker.

9. Also, as a final ROM marker, note down the maximal Lumbar Spine flexion angle and take this away from the starting angle to get the

overall lumbar spine flexion ROM.

10. Repeat the above steps for all 3 of the traces for each attempt and each test subject. Once all 3 ROM values for each axis/marker have

been found, take an average of the 3. This will be the average range of movement.

Example of the Raw Data Analysis Table

Knee range of movement rocking backwards in four point kneeling (KROMRBFPK), Hip range of movement rocking backwards in four point kneeling (HROMRBFPK), Lumbar spine range of movement to loss of

flexion control rocking backwards in four point kneeling (LSROMLOCRBFPK), Lateral hip range of movement rocking backwards in four point kneeling (LHROMRBFPK), Lateral lumbar spine range of movement

rocking backwards in four point kneeling (LLSROMRBFPK), Total lumbar spine range of movement into flexion (TLSROM)

Saggital ROM

Lateral ROM

KROM RBFPK

HROM RBFPK

LSROMLOCRBFPK

TLSROM RBFPK

LHROM RBFPK

LLSROM RBFPK

Participant start Loss of

LSN ROM start Loss of

LSN ROM start Loss of

LSN ROM End LS total

LSROM Start Loss of

LSN ROM Start Loss of

LSN ROM

1 91.8 126.4 34.6 66.4 102.8 36.4 4 5.1 1.1 15.6 11.6 -23 -8.5 14.5 -0.5 -0.9 -0.4

94.3 127 32.7 68.4 103.1 34.7 0.9 5 4.1 11.5 10.6 -25.1 -11.9 13.2 -0.9 -0.9 0

93.4 124.1 30.7 69 100.3 31.3 1.8 5.1 3.3 11.6 9.8 -24.2 -13 11.2 -1.7 -1.5 0.2

32.666

67

34.13333

2.833333

10.66666667

12.96667 -0.06667

90 Chapter 5

Appendix 4 Baseline Measures Raw Data

Participant Gender Age Height Weight BMI LKEA RKEA

1 m 24 188 82 23.2 18 20

2 m 25 185 64 18.7 21 19

3 f 44 157 64 25.96 7 5

4 m 45 175 70 22.86 9 8

5 f 24 152 54 23.37 19 7

6 m 24 183 78 23.29 15 12

7 m 24 175 71 23.18 16 12

8 m 25 178 87 27.46 35 33

9 f 23 160 53 20.7 30 28

10 m 25 188 85 24.05 39 42

11 f 27 172 76 25.69 6 30

12 f 21 162 59 22.48 14 17

13 f 22 169 58.5 20.48 28 33

14 f 22 170 58.7 20.31 45 38

15 f 22 164 69 25.65 35 8

16 f 23 163 54.5 20.51 45 48

17 m 24 170 66.5 23.01 6 18

18 m 24 187 76 21.73 13 15

19 m 18 184 69 20.38 25 26

20 f 29 167 58.5 20.98 40 29

Mean

25.8 172.5 67.7 22.7 23.3 22.4

SD

6.8 10.9 10.4 2.3 13.1 12.4

91

Appendix 5. Inter-Rater Agreement Raw Data

WB KROM HROM LSROMLOC TLSROM LHROM LLSROM

KROM2 HROM2 LSROMLOC2 TLSROM2 LHROM2 LLSROM2

9 -1.8 13.36667 5.733333333 41.73333 5.233333 -3.46667

-2.4 12.43 5.83 42.66667 5.8 -3.3

10 7.8 33 4.766666667 12.46667 8.1 -0.5

8.4 34.2 4.83 13.16667 8.93 -0.53

18 -0.56667 4.533333 6.866666667 45.06667 -1.2 -0.26667

-0.46667 5.766667 6.966666667 45.43333 -1.03333 -0.36667

19 0.466667 6.1 6.366666667 35.76667 1.066667 1.533333

0.866667 6.233333 6.366666667 36.1 1 1.7

SKE KROM HROM LSROMLOC TLSROM LHROM LLSROM


9 -45.5667 6.433333 3.966666667 6.733333 0.066667 -1.9

-44.2 6 4 7.033333 1.4 -2.8

10 -68.4 -6.83333 4.766666667 6.7 2.166667 -1.96667

-68.33 -7 4.63 6.8 2.33 -1.9

18 -80.0333 -7.36667 3.033333333 2.8 5.6 -3.7

-80.1667 -7.53333 3.066666667 3.066667 6.033333 -3.66667

19 -80.2667 -6.1 4.866666667 10.97 1.666667 -3.23333

-51.3 -1.06667 6.7 12.76667 0.733333 -3.83333

SFL KROM HROM LSROMLOC TLSROM LHROM LLSROM


9 -3.03333 1.933333 5.9 33.9 0.266667 -2.2

-2.43333 6.3 6.1 34.63333 0.533333 -2.13333

10 -0.83333 12.6 4.4 13.53333 11.66667 1

-0.83333 12.46667 4.366666667 13.8 11.63333 1.233333

18 -1.2 21.33333 5.3 13.53333 1.966667 -5.23333

-0.96667 21.8 5.333333333 13.9 2.3 -5.16667

19 2.1 12.56667 4.633333333 23.26667 1.633333 -0.7

2.366667 12.73333 4.733333333 23.63333 2.033333 -2.76667

RBFPK KROM HROM LSROMLOC TLSROM LHROM LLSROM


9 20.33333 15.16667 5.433333333 11.66667 -0.3 -0.46667

20 14.53333 5.533333333 12.26667 -0.2 -0.53333

10 11.3 9.266667 5.233333333 14.8 0.966667 -0.16667

10.46667 8.2 5.4 15.5 3.633333 -0.13333

18 18.76667 17.16667 4.766666667 26.13333 8.266667 1.833333

19 17.26667 4.8 26.43333 8.2 1.833333

19 29.83333 17.33333 5.1 8.666667 7.533333 0.5

29.43333 16.83333 5.166666667 7.35 7.466667 0.133333

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Appendix 6.0 Electorgoniometry Kit and Placement Examples

Joint Electrode placement

Knee 1st EG electrode fixed to the exposed lateral femoral condyle and tibial

anatomical bony landmarks (Szulc, Lewandowski and Marecki, 2000).

Example of WB Knee EG Electrode Placement

Hip 2nd EG electrode fixed to exposed greater trochanter and along a

longitudinal axis on the trunk (Mayhew, Norton and Sahrmann, 1983).

Example of Hip Electrode Placement During RBFPK Test

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Example of SFL Hip Example of Hip WB EG

EG Electrode Placement Electrode Placement

Lumbar

spine

3rd EG electrode fixed to first sacrum and to spine along a longitudinal

axis (Marras and Wongsam, 1986).

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Example of Lumbar Spine EG Electrode Placement

Example of EG Computer set up

Example of EG kit set up

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Appendix 7.0 Other Associated Parameters (LKEA, BMI, Age and Joint ROM)

7.1 LKEA correlation with Joint ROM

FIGURE 8. Correlation between KROM during WB and LKEA

Figure 8 shows that male KROM and LKEA had a high moderate positive correlaton

during the WB test, meaning that when KROM increased so did LKEA. Figure 6 also

shows that female KROM and LKEA had moderately negative correlation during the WB

test, which means that when LKEA increased KROM decreased.

FIGURE 9. Correlation between HROM during WB and LKEA

rho = 0.59

(p = 0.07)

rho = 0.55

(p = 0.10)

rho = -0.57 (p = 0.09)

rho = 0.64

(p = 0.05)

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Figure 9 shows that male and female HROM during the WB and LKEA had a high

moderate positive correlation, which means that as LKEA increased so did HROM

during the WB.

FIGURE 10. Correlation between Female HROM during SFL and LKEA

Figure 10 shows that during the SFL, HROM and LKEA had a high moderate positive

correlation. Therefore as LKEA increased so did HROM during the SFL test.

FIGURE 11. Correlation between Female LSROMLOC during RBFPK and LKEA

Figure 11 shows that LSROMLOC had almost perfect negative correlation with LKEA,

which means that when LKEA increased LSROMLOC decreased.

0

10

20

30

40

50

0 5 10 15 20 25

LKEA

HROM SFL

Female

Female

Linear (Female)

0

10

20

30

40

50

60

0 2 4 6 8

LKEA

LSROMLOC RBFPK

Female

Female

Linear (Female)

rho = -0.94 (p = >0.0001)

rho = 0.59 (p = 0.07)

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FIGURE 12. Correlation between TLSROM during RBFPK and LKEA

Figure 12 shows that TLSROM during RBFPK and LKEA had a high moderate

negative correlation, which means that as LKEA increased TLSROM during RBFPK

decreased.

7.2 BMI Correlation with Joint ROM

Figure 13. Correlation between Male KROM during WB and BMI

Figure 13 shows that in KROM during the WB test had a high moderate positive

correlation with BMI in the male participants. Therefore, during the WB test the male

0

5

10

15

20

25

30

35

40

45

0 5 10 15 20 25 30

LKEA

TLSROM RBFPK

Male

Male

Linear (Male )

18

19

20

21

22

23

24

25

26

27

28

-1 0 1 2 3 4 5 6 7 8 9

BM

I

KROM WB

Male

Male

Linear (Male)

rho = -0.60 (p = 0.07)

rho = 0.64 (p = 0.05)

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participants with higher BMI flexed their knees more. Several participants are also

shown to have hyperextended their knees during the WB test.

Figure 14. Correlation between Female LSROMLOC during SKE and BMI

Figure 14 shows that there was a strong positive correlation between LSROMLOC

during SKE and BMI in the female participants. This means that with higher BMI the

female participants had greater ROM to loss of control (5° of lumbar flexion). Therefore,

the female participants with higher BMI’s must have been starting the SKE test in an

extended position and not neutral (i.e. 7° LSROMLOC would mean a starting position of

-2° of lumbar flexion or 2° of lumbar extension).

Figure 15. Correlation between Female KROM during SFL and BMI

18

20

22

24

26

28

0 1 2 3 4 5 6 7 8

BM

I

LSROMLOC SKE

Female

Female

Linear (Female)

18

20

22

24

26

28

-3 -2 -1 0 1 2 3

BM

I (w

eig

ht/

he

igh

t²)

KROM SFL (Degrees)

Female

Female

Linear (Female)

rho = 0.76 (p = 0.01)

rho = 0.81 (p = 0.01)

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Figure 15 shows that there was an almost perfect positive correlation between KROM

during the SKE test and BMI in the female participants. This demonstrates that the

female participants with high BMI’s flexed their knees during the test, while the females

with low BMI’s extended their knees.

Figure 16. Correlation between Female LSROMLOC during RBFPK and BMI

Figure 16 demonstrates that there was a high moderate positive correlation between

LSROMLOC and BMI during the RBFPK test in the female participants. This means that

the females with higher BMI’s began the test in an extended position (1-2° extension

which would equal 6-7° ROM to 5° of lumbar flexion), whereas the females with low

BMI’s started in a neutral or slightly flexed position (i.e. 1° of flexion equals 4° ROM).

Therefore, many of the female participants did not start at the neutral (‘0°’) position they

were put into by the researcher using the EG before the test began to be recorded.

15

20

25

30

35

40

45

50

4 4.5 5 5.5 6 6.5

Age

(ye

ars)

LSROMLOC RBFPK (Degrees)

Female

Female

Linear (Female)

rho = 0.59 (p = 0.07)

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Figure 17. Correlation between Female LHROM during RBFPK and BMI

Figure 17 shows that LHROM during RBFPK had a high moderate positive correlation

with BMI, which means that males with higher BMI had increased LHROM during the

RBFPK test.

Figure 18. Correlation between Female LLSROM during RBFPK and BMI

Figure 18 shows that there was a high moderate negative correlation between

LLSROM during RBFPK and BMI in female participants. Therefore, the females with

high BMI had less LLSROM during RBFPK.

7.3 Age Correlation with Joint ROM

18

20

22

24

26

28

-5 0 5 10 15

BM

I (w

eig

ht/

he

igh

t²)

LHROM RBFPK (Degrees)

Female

Female

Linear (Female)

18

20

22

24

26

28

-1 0 1 2 3 4

BM

I (w

eig

ht/

he

igh

t²)

LLSROM RBFPK (Degrees)

Female

Female

Linear (Female)

rho = 0.50 (p = 0.14)

rho = -0.53 (p = 0.12)

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Figure 19. Correlation between Female TLSROM during WB and Participant Age

Figure 19 demonstrates that there was a strong negative correlation between female

participant age and the TLSROM during the WB. Therefore, the younger females had

more lumbar spine ROM than the older females during the test.

Figure 20. Correlation between Male TLSROM during WB and Participant Age

Figure 20 demonstrates that during the WB male TLSROM had high moderate

correlation with the participants age. Meaning that the olderthe participant was the less

total lumbar flexion ROM they achieved during the WB test.

15

20

25

30

35

40

45

50

0 20 40 60

Age

(ye

ars)

TLSROM WB (Degrees)

Female

Female

Linear (Female)

15

20

25

30

35

40

45

50

0 20 40 60 80

Age

(ye

ars)

TLSROM WB (Degrees)

Male

Male

Linear (Male)

rho = -0.78 (p = 0.01)

rho = -0.53 (p = 0.12)

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Figure 21. Correlation between Male LLSROM during SKE and Participant Age

Figure 21 shows that there was a high moderate positive correlation between male

age and LLSROM during SKE. This indicates that increased age lead to lumbar spine

movement to the right, as negative ROM was movement to the left and positive was

movement to the right.

Figure 22. Correlation between Male TLSROM during SFL and Participant Age

Figure 22 shows that there was a high moderate negative correlation between male

participant age and TLSROM during SFL test. This indicates that the younger

participants were able to flex their lumbar spine further than older participants.

15

20

25

30

35

40

45

50

-5 -4 -3 -2 -1 0 1 2

Age

(ye

ars)

LLSROM SKE (Degrees)

Male

Male

Linear (Male)

15

20

25

30

35

40

45

50

0 5 10 15 20 25

Age

(ye

ars)

TLSROM SFL (Degrees)

Male

Male

Linear (Male)

rho = 0.55 (p = 0.10)

rho = -0.56 (p = 0.09)

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Figure 23. Correlation between Female TLSROM during SFL and Participant Age

Figure 23 demonstrates that there was a borderline strong negative correlation

between female age and TLSROM during the SFL test. Which indicates the same result

as the male participants; that older females had lower TLSROM and vice versa.

Figure 24. Correlation between Female KROM during SFL and Participant Age

Figure 24 demonstrates that there was a high moderate positive correlation between

female participant age and KROM during the SFL test. This indicated that older females

flexed there knees during the SFL test and vice versa.

15

20

25

30

35

40

45

50

0 10 20 30 40 50

Age

(ye

ars)

TLSROM SFL (Degrees)

Female

Female

Linear (Female)

15

20

25

30

35

40

45

50

-3 -2 -1 0 1 2 3

Age

(ye

ars)

KROM SFL (Degrees)

Female

Female

Linear (Female)

rho = -0.68 (p = 0.03)

rho = 0.53 (p = 0.12)

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Figure 25. Correlation between Male LHROM during RBFPK and Participant Age

Figure 25 indicates that there was a high moderate negative correlation between male

participant age and LHROM during the RBFPK test. This indicated that older males had

less LHROM than younger male participants.

Figure 26. Correlation between Male HROM during RBFPK and Participant Age

Figure 26 demonstrates that there was a high moderate negative correlation between

male participants age and HROM during the RBFPK test. This indicated that older male

participants had lower HROM to the point of loss of lumbar flexion control during the

RBFPK test and vice versa.

15

20

25

30

35

40

45

50

-20 -10 0 10 20 30

Age

(ye

ars)


Male

Male

Linear (Male)

15

20

25

30

35

40

45

50

0 10 20 30 40

Age

(ye

ars)

HROM RBFPK (Degrees)

Male

Male

Linear (Male)

rho = -0.57 (p = 0.09)

rho = -0.62 (p = 0.06)

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Figure 27. Correlation between Male KROM during RBFPK and Participant Age

Figure 27 demonstrates that there was a strong negative correlation between male

participant age and KROM during the RBFPK test. This indicated that older male

participants had less KROM than younger males to the point of loss of lumbar flexion

control and vice versa.

Figure 28. Correlation between Female HROM during RBFPK and Participant Age

Figure 28 shows that the female participant age had a high moderate negative

correlation with HROM during the RBFPK test. This indicated that older females had

less HROM at the point of loss of control that the younger females.

15

25

35

45

55

0 10 20 30 40

Age

(ye

ars)

KROM RBFPK (Degrees)

Male

Male

Linear (Male)

15

20

25

30

35

40

45

50

0 10 20 30 40

Age

(ye

ars)

HROM RBFPK (Degrees)

Female

Female

Linear (Female)

rho = -0.72 (p = 0.02)

rho = -0.62 (p = 0.06)

106 Chapter 5

Figure 29. Correlation between Female LHROM during RBFPK and Participant

Age

Figure 29 shows that there was a borderline strong positive correlation between

female participant age and LHROM during the RBFPK test. This indicated that younger

female participants had less LHROM at the point of loss of control during the RBFPK

test than the older females.

Figure 30. Correlation between Female LLSROM during RBFPK and Participant

Age

Figure 30 demonstrates that there was a high moderate negative correlation between

female participant age and LLSROM during the RBFPK test. This indicated that younger

female participants had more LLSROM to the right (positive ROM value) at the point of

15

25

35

45

55

-5 0 5 10 15

Age

(ye

ars)


Female

Female

Linear (Female)

15

25

35

45

55

-1 0 1 2 3 4

Age

(ye

ars)

LLSROM RBFPK (Degrees)

Female

Female

Linear (Female)

rho = 0.78 (p = 0.01)

rho = -0.57 (p = 0.08)

107 Chapter 5

loss of lumbar flexion control. Whereas the older female participants had more LLSROM

to the left (negative ROM value) at the point of loss of flexion control.

108 Chapter 5

Evidence-Based Normative Data in Lumbar Flexion Control Tests; a Pilot Study

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