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SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4 1
INTEGRATING INJURY SCREENING WITH
MEASUREMENT AND MONITORING:
ACONCEPTUAL APPROACH USING APATIENT
GLOBAL ASSESSMENT OF BODY AND LIMBS SCALE
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INTRODUCTION / PURPOSE
The purpose of this paper is to introduce
a new conceptual model for compensable
or third party insurance patients with
musculoskeletal injuries. This model
integrates two essential areas of manage-
ment: prospective injury screening and
outcome measurement and monitoring.
Musculoskeletal medicine has embraced
the concept of Evidence Based Practice
(EBP) and its three essential criteria:
external clinical evidence from systematic
research, clinical expertise and a patient-
centred focus (Sackett et al 1996). This
concept, in particular, is emphasised in
the management of compensable/insured
musculoskeletal patients. Evidence is
advocated through the use of a stan-
dardised systematic approach (APA 2003)
which encourages the measurement
and monitoring of patients by means of
recognised Self Report Outcome
Measures (SROMs). These reflect all
three components of the EBP definition
(Herbert et al 2005; Stratford and Riddle
2005) by quantifying the patient’s sta-
tus and any change over time. A more
recent complementary trend has seen
the introduction of prospective screen-
ing using a biopsychosocial approach
(Linton and Boersma 2003; WC-NSW
2006). This can determine the potential
risk of chronicity and assist early identi-
fication of patients likely to have
increased absenteeism and a delayed
return to work; factors that can lead to
increased total medical, rehabilitation
ABSTRACT: Purpose: To develop a conceptual model for patients with
musculoskeletal injuries that relates Injury Screening to Measurement and
Monitoring (ISMAM). Screening scores would predict quantifiable outcomes
on a proposed Global Assessment of Body And Limbs (GABAL) composite
scale. The scale would define status as a percentage of pre-injury capacity
using quantitative and qualitative self report outcome measures combined
with work and life status data.
Background: Screening questionnaires use psychosocial yellow flags and
activity limitation to identify potential chronic patients. Outcome measures
provide clinical evidence by establishing patient status and assessing intervening change. Independently developed,
definitive statistical links between these established concepts are yet to be determined.
Description: The ISMAM components are integrated using a graph of time versus score on the GABAL-scale with
initial screening predicting recovery time to a designated pre-injury percentage level. Actual status would be assessed
through initial then subsequent sequential measurements with GABAL-scale scores enabling trendline analysis to
verify if the rate of actual recovery coincides with that predicted by screening.
Observations: Face and content validity are apparent because validated screening tools are available and the required
components for the GABAL-scale would be existing validated outcome measures and quantifiable data.
Conclusions: This model should provide a practical method of integrating screening and global measurement that
facilitates communication across agencies and professions. A clinical research trial to validate the ISMAM concept
has been initiated.
KEY WORDS: EVIDENCE BASED PRACTICE, OUTCOME MEASURES, MUSCULOSKELETAL, ASSESSMENT.
Philip Gabel, MSc1,
Lynn Bardin, MSc2,
Brendan Burkett, PhD1,
Anne Neller, PhD1
1University of the Sunshine Coast, Queensland,
Australia.
2University of Melbourne, Victoria, Australia.
CORRESPONDENCE TO:
Philip Gabel
University of the Sunshine Coast,
Queensland, Australia
PO Box 760 Coolum Qld 4573
Tel: 61 (0) 7 5446 4444;
Fax: 61 (0) 7 5446 3344
Email: cp.gabel@bigpond.com
LIST OF ABBREVIATIONS:
EBP - Evidence Based Practice
GABAL - Global Assessment of Body And Limbs
ICF - International Classification of Functioning, Disability and Health
ISMAM - Injury Screening to Measurement and Monitoring
LBP - Low Back Pain
OMPQ - Orebro Musculoskeletal Pain Questionnaire
SROM - Self Report Outcome Measure
WHO - World Health Organisation
2 SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4
and workers compensation costs (Hurley
et al 2001; Linton and Boersma 2003).
Alogical progression is the integra-
tion of the screening and measurement
concepts to relate ‘Injury Screening’
to ‘Measurement And Monitoring’
(ISMAM). Theoretically, a definitive
relationship should exist between the
two components whereby screening
would provide a quantifiable prediction
of the eventual outcome measurement.
This could be a specific value, a per-
centage of pre-injury status or the time
required to reach either of these levels.
However, for this to occur the existing
SROM scales of regional, quantitative
and qualitative status alone would not
suffice. A new SROM scale would be
required that demonstrates a Global
Assessment of Body And Limbs
(GABAL) and integrates both existing
qualitative and quantitative measures
and specific levels of work or activities
of daily living. To facilitate peer accep-
tance and ensure face and content vali-
dity, this GABAL-scale would need to
be a composite of existing validated
quantitative and qualitative SROMs.
Existing measures would need to be
progressed, supplement and integrated
into a single tool that would also include
quantification of work and life attri-
butes that are of critical importance to
patients (Sackett et al 1996), professional
groups (APA 2003) and insurers
(WC-NSW 2006). The final validated
GABAL-scale would be a SROM that
exhibits simplicity for patient comple-
tion, therapist scoring and case manager
interpretation.
This paper proposes five specific
components as the preliminary basis of
the GABAL-scale. Recommended indi-
vidual variables are selected based on
current models of Australian insurer
and professional organisations accepted
outcome criteria (APA 2003; WC-NSW
2006) and on key recommendations
from reviews on the use of outcome
measures and patient management
(Ritchie 2001; Rossignol 2003; Stratford
and Riddle 2005). The proposed five
key indices are: 1) quantitative: self
report status; 2) qualitative: self report
status; 3) hours of work or daily routine;
4) salary, earnings or satisfaction
recompense and 5) duties or activities
performed. The three latter components
would each be quantified as a propor-
tional percentage of their preinjury
level. Whether these five composite
components truly reflect global status is
currently unknown, however they would
be clarified through further clinical
research. This would provide justification
for adding different components and
retaining or removing those proposed.
The specific ratio or weighting of the
individual component scores to form the
final composite total similarly will require
validation through further research. The
final components of such a composite
GABAL-scale will reflect a means by
which the injured individual’s status
would be defined in a global manner as
a proportion of their pre-injury status. A
global assessment measurement scale
has the potential to meet the demands
of government and corporate health
services by documenting the outcome of
clinical care (APA 2003). It provides
external objective measures to substan-
tiate clinical rationale (Ritchie 2001;
Bardin 2003) and justify intervention.
BACKGROUND
The provision of EBP through the use of
outcome measures as advocated by
insurers, third party payers and profes-
sional organisations enables the clini-
cian, case manager and potentially any
external auditor to rapidly quantify and
establish an individual patient’s status.
In this way the outcome of any interven-
tion can be assessed with a view to
justification of its use and evaluating the
costs involved (Ritchie 2001; Bardin
2003). It is accepted that SROMs mea-
sure outcomes and the change in status
that has occurred in the subsequent
interval between measures. Such change
is not the result of an isolated interven-
tion, but rather related to a multiplicity
of factors that can include the conditions
natural course, placebo effect and other
components (Herbert et al 2005). The
effectiveness of interventions in an
interim period can best be determined
and justified by the use of SROMs
(Stratford and Riddle 2005; Campbell et
al 2006). These tools enable the mea-
surement of multi-factorial changes
relevant to the chosen intervention and
provide evidence and accountability for
treatment and standards of care (Ritchie
2001; APA 2003; Bardin 2003). Outcome
measures provide objective evidence
that is clinically significant and patient-
centred as well as being impartial, valid,
reliable and responsive (Bardin 2003;
Herbert et al 2005). Furthermore, such
evidence is becoming an integral part of
responsible clinical management and
is advocated by professional groups,
insurers, governmental bodies and third
party payers.
By contrast, the use of screening
questionnaires seeks to determine psycho-
social yellow flag signs and, with the
combined presence of physical function
limitations, to identify the potential risk
of chronicity (Linton and Boersma
2003). Their use has gained increased
popularity as a means of early identifi-
cation of patients likely to require longer
recovery time, ongoing treatment and
higher costs. At present the focus of
screening tool development and valida-
tion has been in low back pain (LBP)
populations with tools such as the
Orebro Musculoskeleatal Pain Question-
naire (OMPQ) (Linton and Boersma
2003) being shown to have predictive
capacity in both workers compensation
and national health patient groups
(Hurley et al 2001; Linton and Boersma
2003). However, only limited work
has been performed to validate a modi-
fied OMPQ tool in populations that
encompass all musculoskeletal injuries
(Dunstan et al 2005).
The two concepts of screening and
measurement have been developed inde-
pendently and a definitive statistical link
between them has yet to be established.
This integration would be simplified if
consistency was present in the format of
existing SROMs. Despite the advances
within SROM research, most tools have
been developed in relative isolation.
This is demonstrated when existing
functional assessment tools from dif-
ferent body regions are compared.
Examples include spinal SROMs such
as the Oswestry, Roland Morris, Neck
Disability Index or Functional Rater
Index and extremity tools such as the
Lower Extremity Functional Scale or
the Upper Limb Functional Index and
Disability Arm Shoulder and Hand.
When compared, these tools show mini-
SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4 3
mal consistency in item variables and
limited continuity in tool format pre-
venting integration into a single holistic
patient-focused system. An alternative
to these quantitative tools with pre-
selected item constructs are qualitative
measures such as the Patient Specific
Functional Scale (Stratford and Riddle
2005) and derivations of this concept
like the Patient Specific Index (Gabel et
al 2006). Tools with this validated
concept use item variables determined
by the patient to enable functional
assessment in all regions. The concept
is well received and endorsed by both
professional, peer and governmental
organisations such as Veterans Affairs
agencies and Workers Compensation
groups (APA 2003; WC-NSW 2006).
Because these tools are ‘patient specific’,
the selected item variables cannot be
used for comparison between patients or
across patient populations (Stratford and
Riddle 2005). To overcome this diffi-
culty, different research groups have
pursued the development and validation
of a series of quantitative tools with
consistency of format and item variables
across the three primary areas of the
limbs and spine. These have included
the work by Stratford and colleagues
who developed the Upper and Lower
Extremity and Back Pain Functional
Scales (Stratford and Riddle 2005) and
by Gabel and colleagues who developed
the Upper and Lower Limb and Spinal
Functional Index tools (Gabel et al
2006). Such tools with item and format
consistency enable direct comparison
between patients and across different
population groups.
The ISMAM model emphasises the
need to demonstrate that beneficial out-
comes are due to the therapeutic
intervention itself or the natural progres-
sion of injury, not chance or other coin-
cidental occurrences (Ritchie 2001;
Stratford and Riddle 2005; Gabel et al
2006). It supports scientific evaluation
through objective, patient-provided cri-
teria (Sackett et al 1996; Herbert et al
2005). It is important however, that the
patient be considered holistically, as
injury affects both body and mind.
Consequently, any tool for prediction or
measurement of health status must
consider essential domains that describe
health and function within a multi-
disciplinary approach for individuals
of all ages. It must be consistent with
the World Health Organisation’s (WHO)
‘International Classification of Func-
tioning’ (ICF) whose domains include
impairment, activity limitation, partici-
pation restriction, wellbeing and distress
(WHO 2001). This is achieved through
the selection of SROMs that have
demonstrated these criteria either through
research findings or within the context
of ‘health related quality of life’ during
their initial development and validation
process and still reflect these findings in
their final scoring methodology (Stratford
and Riddle 2005; Gabel et al 2006).
DESCRIPTION
The ISMAM concept ensures that initial
screening is cross referenced with
concurrent then subsequent outcome
measurements. These measures indicate
status on a common GABAL-scale
expressed as a percentage measure of the
patient’s pre-injury capacity (Figure 1).
It is a proactive individualised approach
with initial one-off use of a stand-
alone generic screening tool that would
indicate the risk of chronicity using
Figure 1: Overview Algorhithm of the Process of ISMAM.
The patient at initial assessment completes 3 components:
1) Screening: a single use item assessing the risk of chronicity and predicting either impairment level or time to reach it.
2) SROMs: quantitative and qualitative SROMs providing functional scores which contribute to a composite GABAL-scale.
3) Work / Life status data: measures of current levels of performance of normal daily or work related activities, such as hours, duties
or salary, measured as a percentage of pre-injury status and contribute to a composite GABAL-scale.
Measurement assessments would be repeated at 1, 2 or 4 weekly intervals for SROM and Work / Life data to provide their
individual component scores and contribution to the composite GABAL-scale score.
Patient Assessment
Has 3 Components
1.
Musculoskeletal Screening
(Psychosocial & Physical)
2.
SROMs
(Quantitative & Qualitative)
3.
Work &/or Life Status
(eg. Hous, Duties & Salary)
Risk of
Chronicity
Functional
Impairment
GABAL Score
Status as a % of
Pre-injury Capacity
4 SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4
continuous data. Concurrently, additional
information from repeated measures of
qualitative and quantitative outcome
tools would provide ordinal data which
would then be combined with work and
life status measures, such as hours,
duties and salary. Together these vari-
ables would provide the score on the
composite GABAL-scale. Component
variables would be represented in
percentage values of the individual
patient’s normal pre-injury capacity
with their ratios being determined by
research and statistical analysis. This
would provide a single generic value on
the GABAL-scale that reflects global
status as a percentage of pre-injury
capacity. This score would be measured
every one to two weeks in the initial
acute stage as change in this period due
to treatment and natural healing is more
rapid. Once the sub-acute to chronic
stage is reached, where change is antici-
pated to be slower, then repeated
GABAL-scale measures would be every
two to four weeks until discharge.
The flow of the ISMAM concept and
its sequencing is shown in the algorithm
in Figure 2. The screening score predicts
future recovery time to a designated pre-
injury status level whilst the GABAL-
scale score quantifies measurement
of the existing status. With repeated
outcome measures a graphical sequen-
tial representation of this status can be
produced with the horizontal axis repre-
senting time and the vertical axis the
‘GABAL-scale’ which indicates the
global preinjury capacity. A hypothetical
example using monthly measures and
both linear and logarithmic trendlines to
forecast potential progress is shown in
Figure 3. A trendline can be established
by the third measurement that will pre-
dict an individual clinical pathway and
anticipated progress. It would also pro-
pose an expected point of recovery to a
designated pre-injury capacity.
It is hypothesised that a link will be
found between the scores on a suitable
screening tool and the time taken to
achieve the level indicated. The trend-
line extrapolation from the actual mea-
sures would indicate if actual recovery
time and status would coincide with the
specified level initially predicted by the
screening tool. Using logarithmic trend
extrapolation in Figure 3, the anticipated
95% level of pre-injury capacity is 7.5
months - an estimate reinforced by the
fourth and fifth measure. Other predes-
ignated levels, for example 90%, could
be similarly used in which case the
prediction time of 6.75 months would be
found. By contrast, if a linear trendline
were used then the 95% and 90% recovery
levels would be 5.75 and 5.48 months
respectively. It is anticipated that future
research will determine the critical
GABAL-scale score that shows a statis-
tical link with the initial screening score
and whether linear, logarithmic or some
other calculated trendline provides the
best predictive model. Once that link is
determined then it will enable a target
prediction recovery level to be placed on
the graph as a reference and comparative
point for the trendline extrapolation.
This process enables the recovery time
to a designated level to be estimated and
the progress pathway to be continuously
Figure 2: Detailed Algorithm for the process of Injury Screening Measurement and
Monitoring (ISMAM).
Injury to Individual
Completion of:
- Relevant statutory documents
- Workers Compensation forms
- Incident report
ISMAM
- Completion of Generic Screening Tool
- Completion of initial Self Report Outcome Measure (SROM)
- Completion of Work / Life Status Data
Screening determines risk (single use)
- value and level provided
SROM determines functional status (repeated use)
- value and normative level provided
Work / Life Status Data
- nominal percentage values to combine with SROM
Work and Life Status Data
Additional Patient specific status data is obtained
From employer
From worker
From Insurer or statutory body
- combines with SROM Score to provide a Generic Value
Numeric quantification of information
ie Generic Score is Represented on a GABAL-Scale
(Global Assessment of Body And Limbs)
Review and repeat analysis at specific time intervals
Acute (Up to 3 months): 1 - 2 weekly;
Chronic (from 3 months) till Discharge: 2 - 4 weekly
SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4 5
monitored. Subsequently, the estimated
costs of the recovery (based on the
known weekly salary and medical
expenditure) can be anticipated and
determined from the graphical extrapo-
lation and compared to that predicted
from screening.
Acase study that illustrates the
ISMAM concept, using a modified-
OMPQ and the GABAL-scale for a
distal radius fracture, is provided
(Figure 4). This patient was involved
in a motor accident and initially placed
in an Intensive Care Unit (ICU).
Measurements were made at weekly to
fortnightly intervals over the initial two
months and then reduced to monthly
until discharge. Screening with the
modified-OMPQ tool (Dunstan et al
2005) provided a score of 128 points
which predicted more than 28 days off
work (Linton and Boersma 2003;
Dunstan et al 2005). The GABAL-scale
was constructed using the Upper Limb
Functional Index and Patient Specific
Index (Gabel et al 2006) and patient
reported percentage values for work
hours, salary and duties compared to
pre-injury levels. These were combined
in at an arbitrary ratio of 40:15:15:15:15
respectively for the five values to pro-
vide the composite score. A consistent
improvement over the first four weeks is
shown with a rapid improvement on
return to work at five weeks, then a
gradual palteauing over the subsequent
eight weeks. Intuitively this visualised
progress illustrates the anticipated clini-
cal recovery from such an injury
(Stratford and Riddle 2005; Gabel et al
2006). As a case example the concept is
demonstrated. It is anticipated that
future research will determine the rela-
tionship between screening scores, such
as 128 in this example, and if it will
equate to a specified score range on the
GABAL-scale, such as 90 or 95%.
Alternatively it may predict the time
required to reach these levels - such as
13 weeks to the 90% level.
The ISMAM model may offer an
objective standard utilising validated
assessment tools which is in contrast to
most medical models currently used in
the various compensable systems
(Ritchie 2001; Bardin 2003; Linton
and Boersma 2003; Rossignol 2003).
Furthermore, the ISMAM model may
also provide a prospective predictive
assessment of risk and recovery that is
continuously and individually quantified
and adjusted throughout the recovery
period from initial presentation through
X Axis = Time in months with repeated measures, initially at baseline, then monthly;
Y Axis = A composite GABAL-scale representing the patient as a percentage of their
pre-injury capacity.
Composite GABAL components are assumed as being 100% values at their pre-injury
level.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
12345678 9
Time - Months Post Injury
% of Preinjury
Sample ISMAM
Anticipated Recovery to 95% Preinjury
May 16
June 16
Jul 16 Aug 16
Sept 16
Nov30
Logarithmic Trend
Linear Trend
Figure 3: Sample ISMAM chart illustrating format and prediction through the
use of trendlines.
X Axis = Time in weeks with repeated measures at baseline, then week 2, 3, 4, 5, 7,
11 and 13;
Y Axis = GABAL-Scale: a representation of the patient as a percentage of pre-injury
capacity.
Pre-injury capacity is assumed as 100% or with only maximum values in each of the
5 contributing components.
Patient returned to work on 14.7.04.
100
95
90
85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
9/06/2004
16/06/2004
23/06/2004
30/06/2004
7/07/2004
14/07/2004
21/07/2004
28/07/2004
4/08/2004
11/08/2004
18/08/2004
25/08/2004
1/09/2004
8/09/2004
15/09/2004
22/09/2004
GABAL
Figure 4: Case Example using an ISMAM Chart for the upper limb of a motor
accident patient initially in ICU.
Modified-OMPQ Score = 128: Predictive of > 28 days off work
6SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4
to final discharge. The use of screening
and measurement SROMs provides a
two-stage process with separate values
for musculoskeletal injury prediction
and assessment. The former will alert
those involved in the patient’s manage-
ment to the potential risk of chronicity
whilst the latter will provide a consistent
global and regional picture of the injured
individual’s qualitative and quantita-
tive status when compared to their
pre-injury level.
OBSERVATIONS
Critical to any new concept and scale is
its validity. In the development and
theoretical stage it is important that face
and content validity be apparent whilst
construct and criterion validity, along with
the practical characteristics - such as
completion and scoring time and psycho-
metric properties - such as reliability,
error range, responsiveness, are esta-
blished through clinical research. With
the ISMAM concept, face and content
validity appear evident as all existing
SROM tools required would be validated
measures and additional data relating
to work or daily duties is rapidly quan-
tifiable from the patient (Dawson et al
2002). In this way the GABAL-scale
would similarly exhibit face validity as
it would be a measure of global status
(Rossignol 2003; Gabel et al 2006). Its
content, such as the five proposed com-
ponents, would demonstrate content
validity as they each portray the con-
structs of interest and have been inde-
pendently validated through existing
research (Stratford and Riddle 2005).
The proposed individual components
that form this new scale may be con-
tentious. Included variables and their
specific weighting ratio to each other
will require validation through clinical
research. It may be argued that the pro-
posed five selected composite variables
are not representative of a global score
as not all aspects of recognised general
health scales, such as the SF-36 or the
subcomponents of the WHO ICF (WHO
2001) are included. Such criticism
might be valid, however should not
detract from the merits of the concept.
There is currently significant evidence
and literature support for the view that
quantitative regional SROMs are the
most specific and relevant measurement
for determining regional impairment
status and that they reflect HRQOL and
holistic functional activity (Rossignol
2003; Stratford and Riddle 2005;
Campbell et al 2006; Gabel et al 2006).
In addition there is ample scope for spe-
cific individual expression within the
proposed GABAL-scale through the use
of the qualitative tool aspects. The data
of hours, duties and recompense are
considered three essential criteria for
return to work capacity by the insurance
industry (WC-NSW 2006). This view is
supported by occupational assessment
standards (Dawson et al 2002) and
review publications (Rossignol 2003).
Consideration of the algorithm
(Figure 2) and components of the
ISMAM concept (Figure 1) enable the
potential demonstration of several out-
comes and forms of external evidence.
These include: the stand alone scores
from the screening tool and both the
qualitative and quantitative outcome
tools; their composite GABAL-scale
score; the measured values and the
extrapolation trend-graphing for clinical
pathways. This extrapolation would
enable costing to be estimated by using
known weekly expenses (including
employer, medical and rehabilitation
costs) multiplied by the predicted num-
ber of weeks to the designated recovery
level. The predictive capacity of screen-
ing tools has been demonstrated in LBP
populations by several authors over
recent years with an integrated consis-
tency between screening and various
outcomes including absenteeism (Linton
and Boersma 2003) and failure to return
to work at 6 months post injury (Hurley
et al 2001). Further research has devel-
oped this through the investigation of
any musculoskeletal injury population
(Dunstan et al 2005). This predictive
capacity of screening will have signi-
ficant implications for the management
of compensable patients. It will also
become a critical area in future inves-
tigative research for strategies in com-
pensable injury claims management and
early intervention.
To validate a final scale any argument
for inclusion, exclusion or the weighting
ratio of composite variables will require
support from investigative patient-
specific research trials. This paper and
the case examples presented (Figures 3
and 4) propose and illustrate the concept
of the model, the specific content will
evolve with further research. It is anti-
cipated that the ISMAM concept, using
a composite GABAL-scale, will possess
the essential psychometric properties
required for demonstration of a robust
and valid model.
CONCLUSIONS
This model provides a simple, clinician-
friendly method of integrating screening
with global status measurement. It has
the potential to facilitate communication
between agencies and health professions.
Demands for evidence from insurer,
government agency, professional and
patient groups continue to increase.
These demands can best be met with a
comprehensive integrated approach that
provides prediction, outcome measure-
ment, costing and accountability. The
conceptual ISMAM model would satisfy
these requirements as it is a proactive
approach with patient focus and fulfil-
ment of EBP requirements. It demon-
strates risk and the generalised overall
status of the injured individual by
summarising current functional status,
related capacity and predicting recovery
time and subsequent costs. The model
can be further developed and researched
to provide a means of patient assessment
and monitoring that is simple, effective
and acceptable to all stakeholders. A
clinical research trial to determine the
model’s viability has been initiated by
the Centre for Healthy Activity Sport
and Exercise at the University of the
Sunshine Coast in Australia.
REFERENCES
APA: Australian Physiotherapy Association
2003: Policy on outcome measures and treat-
ment justification. Melbourne:. http://apa.
advsol.com.au/members/documents.
Bardin LD 2003. “Physiotherapy and low
back pain - Part III: Outcomes research uti-
lising the biopsychosocial model: psychoso-
cial outcomes.” South African Journal of
Physiotherapy 59(2): 16-24.
SA JOURNAL OF PHYSIOTHERAPY 2006 VOL 62 NO4 7
Campbell H, Rivero-Arias O, Johnston K,
Gray A, Fairbank J, Frost H and UK MRC
SST 2006. “Responsiveness of objective, dis-
ease-specific, and generic outcome measures
in patients with chronic low back pain: an
assessment for improving, stable, and deterio-
rating patients.” Spine 31(7): 815-22.
Dawson EG, Kanim LE, Sra P, Dorey FJ,
Goldstein TB, Delamarter RB and Sandhu HS
2002. “Low back pain recollection versus
concurrent accounts: outcomes analysis.”
Spine 27(9): 984-93.
Dunstan D, Covic T, Tyson GA and Lennie IG
2005. “Does the Orebro Musculoskeletal
Pain Questionnaire predict outcomes following
a work-related compensable injury?” Inter-
national Journal of Rehabilitation Research
28(4): 369-70.
Gabel CP, Michener L, Burkett B and Neller A
2006. “The Upper Limb Functional Index
(ULFI): Development and Determination of
Reliability, Validity and Responsiveness.”
Journal of Hand Therapy 19(3): In Press.
Herbert RD, Jamtvedt G, Mead J and Hagen
KB 2005. “Outcome measures measure out-
comes, not effects of intervention.” Australian
Journal of Physiotherapy 51(1): 3-4.
Hurley DA, Dusoir TE, M. MS, Moore APand
Baxter GD 2001. “How effective is the acute low
back pain screening questionnaire for predicting
1-year followup in patients with low back pain?”
Clinical Journal of Pain 17(3): 256-263.
Linton SJ and Boersma K 2003. “Early iden-
tification of patients at risk of developing
a persistent back problem: the predictive vali-
dity of the Orebro Musculoskeletal Pain
Questionnaire.” Clinical Journal of Pain 19(2):
80-86.
Ritchie JE 2001. “Case series research: a case
for qualitative method in assembling evidence.”
Physiotherapy Theory and Practice 17(3):
127-135.
Rossignol M 2003. “The management of low
back pain.” Occupational Environmental
Medicine 60(9): 617.
Sackett DL, Rosenberg W, Muir Gray JA,
Haynes RB and Richardson WS 1996.
“Evidence based medicine: what it is and what
it isn’t.” British Medical Journal 312: 71-72.
Stratford PW and Riddle DL 2005. “Assessing
sensitivity to change: choosing the appropriate
change coefficient.” Health and Quality of
Life Outcomes 3(23): 23.
WC-NSW: Workers Compensation Authority
of New South Wales - Australia 2006. Manage-
ment of Soft Tissue Injuries: Clinical
Guideline - Electronic Website Report.
Sydney: Motor Accident Authority; 1.3.06.
http://www.workcover.nsw.gov.au/MediaReso
urces/MediaReleases/2006/270206.htmNew.
WHO: World Health Organisation: 2001. “ICF
- International Classification of Functioning,
Disability and Health.” www.who.int/classifi-
cations/en/WHOFICFamily.pdf
