master in de ergotherapeutische wetenschap · odisee, pxl, thomas more . 2 . 3 faculteit...
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Faculteit Geneeskunde en Gezondheidswetenschappen
The responsiveness of the Ghent Participation Scale (GPS) in an adult
population with locomotoric and/or neurological limitations
Lode Sabbe
Masterproef ingediend tot
het verkrijgen van de graad van Master of science in de ergotherapeutische wetenschap
Promotor: dr. Van de Velde
Co-promotoren: dr. Kristine Oostra dr. Vander Linden
Academiejaar 2014-2015
MASTER IN DE ERGOTHERAPEUTISCHE WETENSCHAP
Interuniversitaire master in samenwerking met:
UGent, KU Leuven, UHasselt, UAntwerpen,
Vives, HoGent, Arteveldehogeschool, AP Hogeschool Antwerpen, HoWest,
Odisee, PXL, Thomas More
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Faculteit Geneeskunde en Gezondheidswetenschappen
The responsiveness of the Ghent Participation Scale (GPS) in an adult
population with locomotoric and/or neurological limitations
Lode Sabbe
Masterproef ingediend tot
het verkrijgen van de graad van Master of science in de ergotherapeutische wetenschap
Promotor: dr. Van de Velde
Co-promotoren: dr. Kristine Oostra dr. Vander Linden
Academiejaar 2014-2015
MASTER IN DE ERGOTHERAPEUTISCHE WETENSCHAP
Interuniversitaire master in samenwerking met:
UGent, KU Leuven, UHasselt, UAntwerpen,
Vives, HoGent, Arteveldehogeschool, AP Hogeschool Antwerpen, HoWest,
Odisee, PXL, Thomas More
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Abstract Nederlands
Titel: De responsiviteit van de Gentse Participatieschaal (GPS) bij volwassenen met
motorische en/of neurologische beperkingen.
Achtergrond: Participatie wordt gezien als een positief beïnvloedende factor op de
algemene gezondheid en het algemeen welbevinden van ieder individu. Op die manier
is participatie ook een belangrijke uitkomstmaat binnen het revalidatiegebeuren. Maar
hoe omschrijven we het concept van participatie nu het best? En hoe moeten we nu of
iemand zijn participatie na verloop van tijd beter wordt of slechter?
Doel: Gezien de validiteit en betrouwbaarheid van de Gentse participatieschaal (GPS)
reeds in andere publicaties (artikel onder review in Europees tijdschrift) zijn onderzocht
is het de bedoeling om de responsiviteit van dit instrument na te gaan.
Methode: In een periode van drie maanden werden alle patiënten die op ontslag gingen
op twee revalidatieafdelingen in het Universitair Ziekenhuis Gent bevraagd om mee te
werken. Zij werden gevraagd om 2 online vragenlijsten in te vullen. Een eerste een
week na ontslag, een tweede drie maanden na de eerste bevraging. De onderzoekers
hadden van iedere respondent twee vragenlijsten nodig om deze zinvol statistisch te
kunnen verwerken in SPSS (Statistical Package for the Social Science). Uiteindelijk
werden 12 respondenten geïncludeerd in het onderzoek.
Resultaten: De “standardized response mean” (SRM) en “area under the receiver
operating characteristic curve” (AUC) voor de totale GPS score zijn respectievelijk 0.58
en 75%. De SRMs voor de individuele items van de GPS hebben een range tussen 0.16
en 0.44. De AUCs voor de individuele items situeren zich tussen 65% en 85%.
Conclusie: De GPS scores voor de onderdelen “zelf uitgevoerde activiteiten”,
“activiteiten volgens vooropgestelde keuzes en wensen”, “activiteiten die leiden tot
sociale waardering”en “gedelegeerde activiteiten” kunnen ideaal zijn om veranderingen
in iemand zijn participatie te meten. Vooral de GPS totaalscore kan een ultieme
uitkomstmaat zijn om iemand zijn graad van participatie (na revalidatie) in kaart te
brengen. Verder onderzoek is echter nodig gezien een aantal items van de GPS toch
duidelijk minder sensitief of minder accuraat blijken te zijn dan andere.
Trefwoorden: Gentse Participatieschaal (GPS), locomotorische beperkingen,
meetinstrument, neurologische beperkingen, participatie, responsiviteit, revalidatie,
volwassenen.
Aantal woorden masterproef: 5421
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Abstract English
Title: The responsiveness of the Ghent Participation Scale (GPS) in an adult population
with locomotoric and/or neurological limitations.
Background: Participation is considered to have a positive influence on health and well-
being and is vital for all humans. So participation is also an important outcome for
rehabilitation. The first question is how to determine the concept of participation itself.
The second question is how to measure more or less participation after rehabilitation.
Aim: As the Ghent Participation Scale (GPS) has been investigated in other research
with regard to reliability and validity (article under review for European journal) it is
our intention to investigate the responsiveness of the GPS.
Method: In a period of three months the researchers tried to include all clients that were
going on discharge in to rehabilitation wards within the University Hospital of Gent.
Patients were asked to fill in two electronic questionnaires after they left the
rehabilitation facility. First one a week after discharge, second one three months after
the first one. There was a need to have two completed questionnaires for each subject to
quantitatively research in SPSS (Statistical Package for the Social Science). Eventually
twelve subjects were included in the study.
Results: The standardized response mean (SRM) and area under the receiver operating
characteristic curve (AUC) for the total GPS score are 0.58 and 75%. The SRMs of the
individual items of the GPS ranged from 0.16 to 0.44. The AUCs for the individual
items ranged from 65% to 85%.
Conclusion: The scores on the GPS items addressing “self-performed activities”, “social
appreciation and acceptance, “preferred choice and wishes” and “delegated activities”
may be ideal to measure change in one’s participation. Especially the total GPS score
might be the ultimate outcome participation measure (in rehabilitation). More research
is needed on the GPS items because in the present study some items appeared to be less
sensitive or less accurate than others.
Keywords: adults, Ghent Participation Scale (GPS), locomotoric limitations,
neurological limitations, measurement, participation, rehabilitation, responsiveness.
Amount of words in master thesis: 5421
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Inhoud Introduction .................................................................................................................... 10
Methods .......................................................................................................................... 14
Study Population ......................................................................................................... 14
Methodology ............................................................................................................... 14
Measure ....................................................................................................................... 16
Statistical Analyses ..................................................................................................... 18
Results ............................................................................................................................ 20
Strenghts and weaknesses of this research ..................................................................... 22
Discussion ....................................................................................................................... 23
Conclusion ...................................................................................................................... 26
Bibliografie ..................................................................................................................... 27
Appendix A – The Ghent Participation Scale ................................................................ 34
Appendix B – Indices and algorithms to calculate the final score ................................. 35
Appendix D .................................................................................................................... 36
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Dankwoord Gezien wij al in een eerdere fase in de ontwikkeling van de Gentse Participatieschaal (GPS)
waren betrokken leek het ons niet meer dan logisch om opnieuw een bijdrage te leveren aan het
vervolgonderzoek in de verdere ontwikkeling van dit instrument.
Aanvankelijk was het woord “participatie” voor mij een soort van containerbegrip wat
afhankelijk van de context waarin het woord gebruikt wordt het iedere keer een andere
betekenis heeft. Nu echter hebben we de vele aspecten van participatie kunnen onderzoeken
alsook veel beter kunnen begrijpen.
De nodige inzichten voor dit onderzoek zou in niet gehad hebben zonder de feedback van mijn
promotor Dr. Van de Velde. Zonder zijn steun had ik deze vierjarige opleiding waarschijnlijk
niet tot een goed einde kunnen brengen.
Grote dank gaat ook uit naar mijn beide copromotoren; Dr. Vander Linden en Dr. Oostra. Uit
hun expertise kan ik al jaren putten voor mijn persoonlijke en professionele ontwikkeling. Ik
weet dat participatie ook voor hen een van de belangrijkste uitkomstmaten voor revalidatie is.
Zonder de medewerkingen van de patiënten had ik deze masterproef nooit tot een goed einde
kunnen brengen. Ook aan hen een welgemeende dank u, zeker diegenen die ik veelvuldig een
reminder mocht sturen om toch maar een vragenlijst in te vullen.
Ik ben er zeker van dat mijn echtgenote blij zal zijn als ik dit werkstuk tot een goed einde kan
brengen. Mijn dochters zullen dan weer tevreden zijn dat er meer tijd komt om alle klussen die
de laatste vier jaar blijven liggen zijn eindelijk terug af te werken. Dames, toch bedankt voor
jullie steun en aanmoediging de voorbije vier jaar. Spijtig genoeg voor Amber zat er geen
oudercontact inbegrepen in het lessenpakket .
Verder een speciale dank voor mijn ouders die ergens in een ver verleden toch de basis gelegd
hebben voor deze, weliswaar laattijdige, academische ontplooiing. Moeder, vader … merci.
Wie ik zeker niet mag vergeten zijn “de vijf musketiers” met wie ik vier jaar lief en leed kon
delen in deze opleiding. Soms zat de moed mij in de schoenen maar altijd was er wel iemand die
mij op gepaste momenten een por in de zij of een glaasje in de auto gaf zodat we weer verder
konden. Dames,… merci beaucoup!
Ook mijn vrienden wil ik bedanken voor hun steun. Soms was het wel eens lastig om een “M…
alarm” te moeten missen of wat “voorzichtig” te moeten zijn zodat we de dag nadien terug
konden werken “voor school”. Bedankt voor jullie steun hé moaten!
Als laatste wil ik ook mijn collega’s bedanken die rechtstreeks en onrechtstreeks ervoor gezorgd
hebben dat ik zoveel als mogelijk kon meepikken van deze waardevolle opleiding. Ik hoop dat
ik ook voor hen een bron van inspiratie kan zijn zodat ook zij zich persoonlijk en professioneel
verder kunnen blijven ontplooien.
Lode Sabbe, mei 2015.
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Introduction
The World Health Organization (WHO)’s definition in terms of participation is defined
as involvement in a life situation (World Health Organization, 2001). The domains for
participation component are given in a single list (combined with activity) that covers
the full range of life areas. See table 1:
Table 1: Domains of activities and participation (WHO,2001,p14).
Domains
d1 Learning and applying knowledge
d2 General tasks and demands
d3 Communication
d4 Mobility
d5 Self-Care
d6 Domestic Life
d7
Interpersonal interactions and
relationships
d8 Major life areas
d9 Community, socal and civic life
Participation is considered to have a positive influence on health and well-being and is
vital for all humans (Law, 2002). Participation is also considered to provide structure
and meaning to daily life (Ostir, Smith, & Ottenbacher, 2005; Mayo, Wood-Dauphinee,
Cote, Durcan, & Carlton, 2001; Gage, 1995; Cardol, de Jong, van den Bos, & de Groot,
2002) and leads to life satisfaction (Law, 2002). Hence, maximizing persons’
participation is seen as a goal for rehabilitation (Cardol, de Jong, van den Bos, & de
Groot, 2002; Gage, 1995).
In 1999 the Impact on Participation and Autonomy (IPA) questionnaire was developed
to assess the severity of restrictions in participation and individual needs related to
participation and autonomy. The IPA is a generic questionnaire that addresses two
different aspects of participation: perceived participation and the experience of
problems for every aspect of participation. In 2002 none of the questionnaires that were
available were suitable to assess participation from a patient point of view (Cardol, de
Jong, van den Bos, & de Groot, 2002).
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Table 2: Survey instruments to measure participation.
Instrument Abreviation Aspect of participation Measured Domains of the ICF(see table1)
1. Community Integration Measure
(McColl, Davies, Carlson, Johnston, & Minnes,
2001)
CIM Performance: alone, with someone
else, someone else
Not based on ICF domains
2. The Keel Assessment of Participation
(Wilkie, Peat, Thomas, Hooper, & Croft, 2005)
KAP Frequency all of the time, most of the
time, some of the time, little of the time,
none of the time
Five domains:
d4,d6,d7,d8,d9
3. Community Integration
Questionnaire – 2
(Johnstone, Goverover, & Dijkers, 2005)
CIQ-2 Performance: alon, with someone
else, someone else
Satisfaction: with an activity,the urge to
change an activity and the importance
of an activity
Not based on ICF domains
4. Impact on Participation and
Autonomy Questionnaire
(Cardol, de Haan, van den Bos, de Jong, & de
Groot, 1999)
IPA Autonomy, Choice and control: my
changes of (performing an activity)…
are very good, good, fair, poor, very
poor
Limitations: no problems, minor
problems, major problems
Not based on ICF domains
5. Late Life Function and Disability
Instrument
(Haley, Jette, Coster, Kooyoomjian, Levenson,
& Heeren, 2002)
LLFDI Frequency: of performing life tasks:
very often, often, once in a while,
almost never, never
Limitations: in daily routines: not at all,
a little, somewhat, a lot, completely
Not based on ICF domains
6. Measure of Home and Community
Participation
(Ostir, Granger, Black, Roberts, Burgos, &
Martinkewiz, 2006)
PAR-PRO Frequency: from did not participate in
this life situation to participated
daily/almost every day
Five domains:
d4,d6,d7,d8,d9
7. Participation Measure for Post-
Acute Care
(Gandek, Sinclair, Jette, & Ware, 2007)
PM-PAC Limitation: not at all limited, a little
limited, somewhat limited, very much
limited, extremely limited
Duration of activity: all of the time to
none of the time
Satisfaction: from very satisfied to very
dissatisfied
Eight domains:
d1,d3,d4,d5,d6,d7,d8,d9
8. Participation Objective,
Participation Subjective
(Brown, Dijkers, Gordon, Ashman, Charatz, &
Cheng, 2004)
POPS Frequency: how often in at typical
month do you …. ?
Satisfaction and importance: how
important is this to your wellbeing and
are you satisfied with your level of
participation
Five domains:
d4,d6,d7,d8,d9
9. Participation Survey/Mobility
(Gray, Hollingsworth, Stark, & Morgan, 2006)
PARTS/M Frequency: time spent in activities
Choice: to performe activities
Satisfaction and importance of the
performed activities
Six domains:
d4,d5,d6,d7,d8,d9
10. Participation Scale
(van Brakel, Anderson, Mutatkar, Bakirtzief,
Nicholls, & Raju, 2006)
P-Scale Limitations in participation: No
restriction, some restriction but no
problem, small problem, medium
problem, large problem
Eight domains:
d1,d3,d4,d5,d6,d7,d8,d9
11. The Utrecht Scale for Evaluation of
Rehabilitation-Participation (Post, van der Zee,
Hennink, Schafrat, Visser-Meily, & van
Berlekom, 2012)
USER-P Frequency of performing activities
Time spent in performing activities
Importance of activity to the client
Limitations experienced by the client
Not based on ICF domains
12. Ghent Participation Scale
(Van De Velde, Bracke, Van Hove, Viaene,
Coorevits, & Vanderstraeten, 2015)
GPS Frequency: time spent in activities
Importance: how important is the activity
to you?
Performance: with two components;
own choice of activity and social acceptance
Delegation of activities
Nine domains:
d1,d2,d3,d4,d5,d6,d7,d8,d9
Other important shortcomings of existing questionnaires are described in following
literature: at first there is ambiguity and vagueness about the term itself (Hammel,
Magasi, Heineman, Whiteneck, Bogner, & Rodriguez, 2008; Hemmingson & Jonsson,
2005; Ueda & Okawa, 2003), the subjective aspects of participation are missing
(Hemmingson & Jonsson, 2005; Borell, Asaba, Rosenberg, Schult, & Towsend, 2006;
Post, de Witte, Reichrath, Verdonschot, Wijlhuizen, & Perneboom, 2008; Poulin &
Desrosiers, 2009) and also the differentiating between activity and participation remains
12
unclear (Dijkers, 2010; Jette, Tao, & Haley, 2007; Johnston, Goverover, & Dijkers,
2005). That means that also the exiting measures fail in measuring the correct concept.
Furthermore one can say that outcome assessment is required to determine whether
treatment has been effective (i.e., whether the desired goals have been achieved). While
rehabilitation treatment ultimately aims at maximizing the participation and autonomy
of an individual with a disability. To obtain insight into the impact of a disease or
disability on a person’s life, assessment from the patient’s point of view is essential
because the patient’s assessment will differ from that of outsiders. Also because a
person with a chronic disabling condition faces the consequences of that illness or
disability for the rest of his/her life, rehabilitation assessment should always address
long-term outcomes in terms of participation (World Health Organization, 2001).
The reliability and validity of the outcome instruments in table 3 have been thoroughly
analysed, but their clinimetric value in terms of responsiveness often remains unknown.
Table 3: Psychometric properties of the selected measurement instruments.
Mea
surm
en
t
1 C
on
ten
t V
ali
dit
y
2 I
nte
rn
al
Co
nsi
sta
ncy
3 C
rite
riom
Va
lid
ity
4 C
on
stru
ct
Va
lid
ity
5 R
ep
ro
du
cib
ilit
y
Ag
ree
men
t
6 R
ep
ro
du
cib
ilit
y
Reli
ab
ilit
y
7 R
esp
on
siv
en
ess
8 F
loo
r-c
eili
ng
Eff
ects
9 I
nte
rp
reta
bil
ity
Ov
erall
Sco
re
CIM + + - - 0 - + + + 4
KAP ? na + na - 0 - + 2
CIQ-2 + + - - + + 0 + + 6
IPA + + - + + + + - + 7
LLFDI + + - 0 - + - - + 4
PAR-
PRO - + 0 - 0 0 0 + - 2
PM-PAC ? + - + + + + - + 6
POPS + 0 0 0 0 0 0 0 + 1
PARTS/
M + + ? - ? ? 0 0 - 2
P-Scale ? + 0 + + + + - + 6
USER-P + + + + + + - + 0 7
GPS + + + + + + 0 + + 8
1 +
A clear description is provided of the measurement aim, the target population, the concepts that are being measured, and th item selction AND target populatin and (investigators OR experts)
were involved in item selection;
? A clear decription of above mentioned aspects is lacking OR only target population involved OR doubtful design or method;
- No target population involvement;
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0 No information found on target population involvement;
2 + Factor analyses performed on adequate sample size (7*# items and >100) AND Cronbach's alpha's calculated per dimension AND Cronbach's Alpha(s) between 0.70 and 0.95;
? No factor analyses OR doubtful design or method;
- Cronbach(s) Alpha <0.70 or >0.95
0 No information found on internal consistency;
3 + convincing arguments that gold standard is "gold" AND correlation between gold standard is ≥0.70;
? No convincing arguments that gold standard is "gold" OR doubtful design or method;
- Correlation with gold standard < 0.70 despite adequate desing and method;
0 No information found on criterion validity;
4 + Specific hypotheses were formulated AND at least 75% of the results are in accordance with this hypotheses;
? Doubtful design or method (e.g. hypotheses);
- Less than 75% of hypotheses were confirmed, despite adequate design and methods;
0 No confirmation found on construct validity;
5 + MIC<SDC OR MIC outside the LOA OR convincing arguments that agreemant is acceptable;
? Doubtful design or method OR MIC not defined AND no convicing arguments that agreement is acceptable
- MC≥SDC OR MIC equals or inside LOA, despite adequate design or method;
0 No information found on agreement;
6 + ICC or weighted Kappa ≥0.70;
? Doubtful design or method (e.g. time interval not mentioned);
- ICC or weighted Kappa < 0.70, despite adequate design and method;
0 No information found on reliability;
7 + SDC or SDC<MIC OR MIC outside the LOA OR RR>1.96 or AUC≥0.70;
? Doubtful design or method;
- SDC or SDC≥MIC OR MIC equals or inside LOA OR RR≤1.96 OR AUC < 0.70 despite adequate methods;
0 No information found on responsiveness;
8 + ≤15% ot the respondents achieved the highest or lowest possible scores;
? Doubtful design or method;
- >15% of the respondents achieved the highest or lowest possible scores despite adequate design and methods;
0 No information found on interpretation
9 + Mean and SD scores presented of at least four relevant subgroups of patients and MIC defined;
? Doubtful Design or mehtod OR less than four subgroups OR no MIC defined;
0 No information found on interpretation
MIC= Minimal Important Change; SDC= Smallest Detectable Change; LOA = Limits of Agreement;
ICC= Intraclass Correlation; SD= Standard Deviation, na = non applicable
From several studies, however, including those available in the field of rehabilitation, it
is clear that responsiveness is a complex feature. Several strategies have been developed
to evaluate it (Deyo, Diehr, & Patrick,1991; Kazis, Anderson, & Meenan, 1989;Deyo &
Centor,1986; Guyatt, Deyo, Charlson, Levine, & Mitchell, 1989). Several
responsiveness indices provide different results, and even when the same indicators are
used, the responsiveness of well-known instruments like the Sickness Impact Profile
differs considerably among studies (Taylor, Taylor, Foy, & Fogg, 1999; Beaton, Hogg-
Johnson, & Bombardier, 1997; MacKenzie, Charlson, DiGioa, & Kelley, 1986). This
suggests that responsiveness is highly influenced by methodologic factors (size of the
study population, time between measurements, diagnosis, characteristics of the study
population) and the actual change in the phenomenon under study. Perhaps the most
common method to determine an instrument’s responsiveness is to compare scores of
the instrument under study before and after a treatment of known efficacy (Deyo, Diehr,
& Patrick,1991; Guyatt, Deyo, Charlson, Levine, & Mitchell, 1989).
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The Ghent Participation Scale (GPS) was developed between 2006 and 2014 (starting
with qualitative research for item derivation and ending in 2014 with a reliability and
validity study). The GPS focuses both on the objective as well as on the subjective
determinants of participation, including all domains of the ICF. Before an instrument
can be applied in rehabilitation practice or research the psychometric properties must be
known. An article about the psychometric properties of the GPS with regard to validity,
feasibility and the development of the instrument is under review in a European journal.
The aim of this study in the first place is to investigate the responsiveness of het GPS.
Methods
Study Population
Patients were recruited in two rehabilitation units within the University Hospital Ghent;
a large unit where clients are treated with neurological en motoric disabilities; Centre of
Locomotor and Neurological Rehabilitation (CLNR) and a smaller unit with only a
motoric rehabilitation program; Specialised Locomotor Rehabilitation Unit (SP) both in
the Ghent University Hospital . The major diagnostic groups within these facilities are:
Acquired brain injury
Spinal cord injury
Amputees
Polytrauma
Methodology
All clients on discharge were contacted personally in their last week on admission and
were asked if they wanted to enroll the study Clients were excluded when they were not
able to read or to write, had mild or major cognitive problems or who had behavioural
problems (established impairments by the multidisciplinary treatment team).
Respondents were invited to take part in 2 online assessments, 3 months apart. In their
last week of inpatient-rehabilitation all patients who were going on discharge were
contacted personally by the responsible occupational therapist (at the end of that
15
specific week). They were provided with oral and written information about the study.
Those who were interested to participate signed an informed consent.
Figure 1: Test protocol
At that time patients were also asked to give their e-mail address which was noted on a
separate list to insure confidentiality of results. For administrative reasons and to ensure
confidentiality a unique code was used. One week after discharge they received a mail
including a direct link to electronic questionnaire. The questionnaire was made in Lime
Survey (LimeSurvey, 2014). To log in they were provided with the unique password.
By using a unique password instead of their name the researchers guaranteed that the
results will be processed anonymously.
The second assessment took place 3 months after discharge, when a second e-mail with
a link to a second questionnaire was send. Additionally, patients were also requested to
fill in 4 extra questions. These questions are transition indices and were considered
necessary to check the increase or decrease of their participation level.
Because there is no golden standard yet to prove the efficacy of rehabilitation treatment
aimed at optimizing autonomy and participation, the present study uses external
standards to measure changes (transition indices) to compare with the GPS.
All transition indices consisted of a 1-item question with a 7-point ordinal scale.
Questions were: “With regard of my overall level of participation in daily life activities
my level of functioning is …. than three months ago.”, “ My feeling of social
appreciation at this moment is …. than three months ago.”, “Being able to choose my
activities at this moment is … than three months ago.”, “ Delegating activities to other
people is now … than when I had to delegate activities to others three months ago.”.
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Change was defined as “(much/slightly) worse”, “the same” or “(much/slightly) better”.
The first transition index concerned perceived change in general. The other three indices
concerned the three major factors which were determined elsewhere in research.
Prior inviting the patients to sign in for the study a test run of the questionnaires was
done with ten people (colleagues and family). Three of them could not continue with the
questionnaire because of system failure. All of them tried to open the questionnaire in
Explorer (Microsoft, 2015). On the other hand there were people who didn’t have any
troubles completing the questionnaire in that same browser. To be sure as many people
as possible participated in the study, there is explicitly mentioned that there might be a
problem using Explorer in the invitation mail. Two alternatives were recommended;
Mozilla Firefox (Mozilla, 2015) and Google Chrome (Google, 2015).
Because there was limited research time following methodology was applied to get as
many responses as possible. First all patients were contacted personally. The Theory of
Social Exchange states that personalizing messages and contacts increases perceived
rewards as participants in surveys consider their opinion an themselves to be important
and valuable for the researcher (Dillman, 2000). For the same reason it was stated in the
actual invitation by mail that the results of the questionnaire might influence the way
rehabilitation will be organised in the future in our rehabilitation facilities. These factors
can increase the probability of participation and therefore provide more fully finished
surveys (Heerwegh, Vanhove, Matthijs, & Loosveldt, 2005); (Joinson & Reips, 2007) .
One of the participants did ring us back to ask for more explanation about how to fill in
the questionnaire. If there had not been any personal contact in advance she probably
wouldn’t have done this extra effort.
Also found in literature is the fact that one can strongly influence the response rate by
using follow-up messages so one reminder was send after three days if the respondent
didn’t fill in the questionnaire. In that way the researchers wanted to raise the responses
with 25 to 30% as mentioned bij Kittelson in earlier studies (Kittelson, 1997).
Measure
The GPS is generic and pathology independent instrument that is based on the
subjective appraisal of activities. The instrument consists of 2 subscales: Subscale 1:
17
self-performed activities and subscale 2: delegated activities. Item derivation for the
different subscales of the GPS was based on qualitative research with patients in whom
the researchers assumed they experienced a loss of participation due to a sudden onset
of a disability (Terwee, et al., 2007). These items were checked by means of a follow up
qualitative research in people with a progressive disability and were related to existing
knowledge from similar research in people with disabilities in general (Hemmingsson &
Jonsson, 2005) , in people with an acquired brain injury (Van de Ven, Post, de W, & van
den Heuvel, 2008) , in elderly people (Van de Velde, Bracke, Van Hove, Josephsson, &
Vanderstraeten, 2010) and in people with chronic pain (Cardol, de Haan, de Jong, van
den Bos, & de Groot, 2001) . Fifteen subjective items were included in the GPS and 2
objective items were added: (1) the time spent in the self-performed activities and (2)
the number of delegated activities that the person wanted to perform himself. Whether
the items appeared to be measuring true variables of participation was reviewed by
experts from various fields: occupational therapy, rehabilitation medicine, sociology,
social sciences, consumers of rehabilitation treatment with varying disabilities and
healthy individuals. A factor analysis determined that the subscale of self-performed
activities could be divided in two separate subscales. Subscale 1a: activities according
to preferred choices and wishes and subscale 1b: activities leading to appreciation and
social acceptance. A sample item in subscale 1 is: “it was completely my choice to
engage in this activity”. A sample item for subscale 2 is “I experienced more control by
asking someone else to do this activity for me”. Each item is scored from 1 (I totally
disagree) to 5 (I totally agree). A total GPS score is calculated by the summation of (1)
the mean scores on the Likert scale of all the subjective determinants for the self-
performed activities multiplied by an index indicating the time spent in the activities
and (2) the means score on the Likert scale of all subjective determinants for the
delegated activities multiplied by an index indicating the number of delegated activities
that the individual wanted to perform himself, divided by the number of determinants.
See Appendix B for the algorithms and the indices. The rationale and the statistics for
using these algorithms and indices under review in another article (European
journal) The final score is recalculated in terms of a percentage. A higher percentage
indicating a higher perceived participation level and a lower percentage indicating a
lower perceived participation level. The degree to which one can assign a qualitative
18
meaning to these scores of the GPS is based on the ICF qualifiers scale. The used scale:
0, no participation problem (score on the GPS between 96-100%); 1, mild participation
problem (score on the GPS between 75-95%) 2, moderate participation problem (score
on the GPS between 50-75%); 3, severe participation problem (score on the GPS
between 5-50%); and 4, complete participation problem (score on the GPS between 4-
0%). Based on this anchor it is assumed that a clinical meaningful change is apparent
when someone reaches a higher score. Beside two percentages that indicate the
percepted grade of participation by the patient in the self-performed activities as well as
in the delegated activities the clinician gets a visual overview by means of a radar plot.
Figure 2: radar plot: final outcome GPS
Statistical Analyses
All data from the Lime Survey database (LimeSurvey, 2014) questionnaire were
extracted and loaded in to the program Statistical Package for the Social Science (SPSS)
19
(IBM, 2013). Participation scores were analysed in relation to the response to the
general transition index as well as the other three indices. Confidence intervals (Cis) for
the change were calculated. To provide a graphical insight into the shift of less or more
participation from baseline to follow-up, the data was inserted extracted into excel
(Microsoft, 2015) where first data cleaning took place.
In order to calculate the responsiveness to improvement of the GPS the standardized
respons mean (SRM) methodology was used. Just like the effect size, the SRM uses the
mean observed change as the numerator but divides it by the standard deviation (SD) of
the changed score. Criteria proposed by Cohen were used to interpret the SRMs, where
an SRM of 0.20 is considered to be small, an SRM of 0.50 indicates moderate
responsiveness, an SRM of 0.80 indicates substantial responsiveness (Cohen,1977;
Meenan, Kazis, Anthony, & Wallin, 1991).
In order to detect improvement according to an external criterion (transition indices)
receiver operating characteristic (ROC) curves were used (Deyo & Centor,1986; Sakett,
Haeynes, Guyatt, & Tugwell, 1991). Hereby one can calculate the area under curve
(AUC). Measurements can be viewed as diagnostic tests for discriminating between
improved and unimproved patients. In this way there will be a true-positive and false-
positive changes in GPS scores over time. The ROC curve depicts the true-positive rate
(sensitivity) versus the false-positive rate (specificity). An AUC of 50% would mean
that the GPS does not perform any better than chance, whereas an AUC of 100%
represents perfect accuracy in distinguishing improved from unimproved (Deyo &
Centor,1986).
20
Results
Figure 2: flowchart number of participants
In total sixty six possible participants were contacted. Forty-four persons dropped out
immediately of which four patients did not meet the exclusion criteria and eight possible
participants explicitly said they didn’t want to participate. The rest stated that they
didn’t have access to a computer or had a lack of computer skills. Twenty-four persons
were then enrolled the study. Of those, six did not fill in the first questionnaire after a
week not even after one reminder by mail. Eventually eighteen persons filled in the first
set of questions. After three months four other persons did not respond to the second
and last questionnaire. Fourteen participants filled in the two questionnaires. As two of
them did not fill in all questions in the second questionnaire only twelve patients were
selected . In total women (n= 9) outnumbered men (n= 3). Mean age was 51,57 where
the youngest participant was 21 years old, the oldest 66 years. Most participants had a
new disability. Some patients from the spinal cord group however had sustained their
lesion several years ago and are now treated for secondary problems to their initial
disability (n=2).
21
Table 4: Participants’ characteristics
Minimum Maximum Mean SD
Age male n=3 51 yrs 65 yrs 56,67 7,37
female n=9 22 yrs 66 yrs 49,89 18,19
Diagnositc group spinal cord
n=5 41%
acquired brain injury
n=4 33,33%
politrauma/amutation
n=3 25,67%
Table 5 presents the mean GPS item scores at baseline and follow-up with
corresponding change scores. The mean change scores indicate improvement on all
items of the GPS over a period of three months. The GPS total score did not show a
major evolution in change score (CS = - 0.4). The individual item scores show greater
change. The items “preferred choices and wishes” but also “delegated activities”
showed a lager improvement with a CS of -0.38 and -0.22. The largest change score
however was for the item of “self-performed activities” with a CS of -0.62.
Table 5: Mean GPS scores at baseline and at Follow-up with corresponding change scores (N=12)
Items of the GPS Baseline score Follow- up score Change score
GPS total score 1.94 ± 0.38 2.34 ± 0.70 -0.4
Self-performed activities 2.0 ± 0.68 2.62 ± 1.15 -0.62
Social appreciation and acceptance 2.82 ± 0.54 2.96 ± 0.92 -0.14
Preferred choice and wishes 2.94 ± 0.83 3.32 ± 0.92 -0.38
Delegated activities 1.33 ± 0.73 1.55 ± 1.07 -0.22
Change score = Baseline score – Follow-up score
Table 6 shows the SRMs and AUC for improvement in the GPS items. The GPS total
score shows an AUC of 75% which means the GPS has a good accuracy in
distinguishing improvement or unimprovement. A SRM score of 0.58 indicates an
adequate to strong responsiveness. . The items “social appreciation and acceptance” as
well as “preferred choice and wishes” both have AUGs of >0.70 which means they
have a strong accuracy in distinguishing improvement from unimprovement (Terwee, et
al., 2007). Both these GPS items however have low SRMs (0.16 and 0.32) which means
they have a small responsiveness.
22
Table 6: Mean Change Scores for improvement (N=17) and Responsiveness to improvement of the GPS items expressed in
SRM and AUC
Items of the GPS Change score for improvement Range SRM AUC (%)
GPS Total score 0.4 ± 0.68 -0.38 to 2.06 0.58 75
Self performed activities 0.61 ± 1.38 -1.81 to 2.61 0.44 65
Social appreciation and acceptance 0.14 ± 0.85 -1.39 to 1.15 0.16 77
Preferred choice and wishes 0.37 ± 1.15 -1.51 to 2.54 0.32 85
Delegated activities 0.21 ± 1.12 - 2.19 to 2.51 0.18 63
SRM≤0.20 = small responsiveness, SRM ≥0.50= moderate responsiveness, SRM≥0.80 = substantial responsiveness.
AUC≤50% = GPS does not perform better than chance, AUC=100% = GPS has perfect accuracy.
Strenghts and weaknesses of this research
It is not so easy to make conclusions about the responsiveness of the GPS in such a
short time window. Most studies with regard to this psychometric property have more
evaluation times than our two measuring points (one week and three months after
discharge). If an evaluation point at six months and at twelve months would be added
not only the results would be more accurate, the study would also have more
participants. (Askim, Morkved, Engen, Roos, Aas, & Indredavik, 2010; Kemp,
Bateham, Mulroy, Thompson, Adkins, & Kahan, 2011; Dattani, et al., 2013). This
would increase the power of this research. However, another way to indicate the quality
of a (web-) survey is to measure the response rate. Generally this is defined as the
number of completed units divided by the number of eligible units in the sample,
according to the American Association for Public Opinion Research. In the research by
Watt et al. (2002), the overall response rate for online surveys was 32.6%,while for
paper surveys it was 33.3% (Watt, Simpson, McKillop, & Nunn, 2002). Based on
research of Manfreda et al. in 2008 it is estimated that the response rate between web
surveys and other survey modes is on average approximately 11% lower than that of
other survey modes (Manfreda, Bosnjak, Berzelak, Haas, & Vehovar, 2008).
In an earlier version of the GPS it was not possible to go on with the survey unless
people gave exact five activities they have delegated to others. Also in the pilot study
respondents gave feedback that they didn’t complete the survey because they had only
three activities they had delegated to others. In that case the survey blocked. So the
researchers thought that they had to adjust the software so people could fill in less than
five activities and still get a reliable participation score.
Another weakness of this study might be the fact that the results of this study can be
biased because not all of possible respondents have access to internet. Perhaps in a
23
future long term study with regard of the responsiveness of the GPS different sampling
methods can be used. For example web based survey and oral surveys taken by an
interviewer at home with patients who do not have internet access or computer skills.
Only one reminder was send if a participant didn’t fill in the questionnaire after three
days. Although there is evidence that the number of filled in questionnaires increases
with the number of reminders the researchers in this study stopped after one . This
strategy was chosen because the researchers didn’t want to hurry our respondents to fill
in the questionnaire just to get rid of further notifications. Although this has not been
researched a lot in literature, as Diaz de Rada (2005), it was thought that more than one
reminder might influence the result of our study in a negative way by providing more
filled in questionnaires with poor quality.
Discussion
When Law talked about participation she talked about” Participation in everyday
occupations”. This construct incorporates the term “occupations”, which is defined as
groups of activities of everyday life that are given value and meaning by the individual
(Law,2002; Towsend & Polatajko, 2007).This is seen as a more specific part of
participation. In this paper when participation is mentioned it is used in a more general
way, not specific.
Adjusting the software so people did not have to fill in five activities (delegated or not)
to go on with the questionnaire was not such a good idea after all. Because people filled
in less than five activities the numbers used by the algorithm were underestimated. For
example, people with less than five delegated activities and who didn’t feel bad about
delegating activities got lower scores than people who did fill in five activities even
with the intention of doing the activities rather themselves than delegating them to
someone else. In the future if the GPS is used there should always be five activities
entered to become a correct final output.
If people don’t fill in five activities researchers my use another assessment method than
an electronic survey to get complete results. One might go over to the respondents
house to do an interview so missing data can be filled in. An interview by phone might
be another solution to expand the number of completed questionnaires.
24
Even with respondents who filled in all activities researchers noticed that the overall
score of the GPS is low. The highest score of total participation after three months is
60,72%. The rest of the participants had a total score under 51%. Looked at the sores on
an individual level one can see that especially the score of the delegated activities is
very low. This might mean that the index that is used to calculate the percentage of
participation in delegated activities is too heavy. Further research is needed to
investigate whether a lighter index would be more appropriate to use in the GPS.
In the Specialised Locomotor Rehabilitation Unit (SP) the largest number of patients
who explicitly refused to take part in this study (n=3) was encountered. In this service
there was also the largest population of people who didn’t have internet access or who
don’t have enough computer skills to participate in an online questionnaire(n=7). A
possible explanation may lay in the fact that patients in the SP-unit are generally older
than patients in the Centre of Locomotor and Neurological Rehabilitation (CLNR). In a
sample of December 2014 the average age of the SP-population was 70,75 years old
with a range from 42 to 86 years. In the CLNR however there was a range of 17 to 61
years old with an average of 44 years. Older people generally are less keen on
participating in studies and generally have less computer skills than younger people
which might explain the higher number of non-participants.
When evaluating rehabilitation interventions, responsiveness is a crucial property of an
outcome measurement (Fitspatrick, Ziebland, Jenkinson, & Mowat, 1992). With regard
to the GPS items, self-performed activities as well as delegated activities were less
responsive than the other items. The general responsiveness of the total GPS score
however was adequate to strong. The study sample was small, which implies that the
GPS responsiveness must be confirmed in a larger study population maybe with more
different diagnosegroups.
There is something to say about the methodology of this study. Although using
transition indices is a useful alternative when a treatment of know efficacy is missing,
Norman et all questioned the use of retrospective transitions ratings in 1997. Not only
because of the reliability and validity of transition indices are difficult to verify, it is
also difficult to judge change in a psychological way (Norman, Stratford, & Regehr,
1997). Patients must be able to quantify both their present state and their initial state and
25
then perform a mental substraction. Guyatt et al. suggest that the solution for this
dilemma lies in the previous responses of the subjects under study (Guyatt, Berman,
Towsend, & Taylor, 1985).
One mostly presumes that, when measuring change, the point of reference is fixed and
that an individual’s attitude toward illness and participation will remain stable (Allison,
Locker, & Feine, 1997). Attitudes are not stable; they vary with time and experience.
This is especially the case during rehabilitation treatment, when people have to find new
strategies to adapt to their illness. The use of clinical judgment of change is not likely to
avoid this bias because the clinician must use the patient as a major source of
information (Norman, Stratford, & Regehr, 1997).
Taken all these aspects into account one may say that the method used to evaluate the
responsiveness of the GPS was not the best way to make the evaluation. However, there
is no consensus on the best method to evaluate the responsiveness of a measure yet.
For example another way to measure responsiveness than described in this study, where
external criteria are used to measure change, is to relate the standard deviation change
(SDC) to the MIC (Gyatt, Walter, & Norman, 1987).
Recently some authors (Terluin, Eeckhout, Terwee, & de Vet, 2015) try to introduce a
new method to estimate a “minimal important change” (MIC) in an attempt to evaluate
health related quality of life scales (HRQLS). They found that mean HRQLS changes
may well reach statistical significance, whereas at the same time, the clinical relevance
might be limited, if not absolutely absent. Therefore they introduce an alternative to
ROC-based MIC (MICRoc), based on predictive modelling (MICPred) which is able to
overcome the drawbacks of the MICRoc.This new method uses logistic regression
analysis and identifies the change score associated with a likelihood ratio of 1 as the
MIC. In their research the authors found that the MICPred turned out to be more precise
than the MICRoc. These findings may increase statistical power in MIC studies.
26
Conclusion
The scores on the GPS items addressing self-performed activities, social appreciation
and acceptance, preferred choice and wishes and delegated activities may be ideal to
measure change in one’s participation. Especially the total GPS score might be the
ultimate outcome participation measure (in rehabilitation). More research is needed on
the GPS items because in the present study some items appeared to be less sensitive or
less accurate than others.
27
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Appendix A – The Ghent Participation Scale
Subscale 1: Self-performed activities (SPA):
1. What are the five most important activities that you have performed during the last week? (A1-A5)
2. How many time did you spent in these activities (one answer for each activity: TA1-TA5):
Response options for question 2: 1 = maximum 1 hour,
2 = more than 1 hour and less than half a day,
3 = half a day,
4 = a full day and
5 = more than 1 day
3. Subscale 1a: Activities according to preferred choices and wishes
Give an appreciation from 1 to 5 for the following statements (one answer for each activity: S1A1-
S5A5):
Response options for subscale 1a: 1: I totally disagree
2: I disagree
3: I doubt
4: Agree
5: Totally agree
S1: it was completely my choice to engage in this activity.
S2: I performed this activity (or I was part of it) completely as I wished.
S3: during this activity I was completely able to be myself.
S4: this activity was completely self-fulfilling.
S5: during this activity, I experienced a feeling of complete control.
4. Subscale 1b: Activities leading to appreciation and social acceptance
Give an appreciation from 1 to 5 for the following statements (one answer for each activity: S6A1-
S9A5):
S6: during this activity, I felt very safe.
S7: during this activity, I felt a strong appreciation.
S8: during this activity, it felt as if I was an important person.
S9: during this activity, I had a strong feeling to belong there (being part of the group).
Response option for subscale 1b: idem 1a
Subscale 2: Delegated activities (DA)
5. What are the five most important activities that you have delegated during the last week (D1-D5)?
6. How many of these activities would you have rather performed yourself (PD1-PD5)?
7. Give an appreciation from 1 to 5 for the following statements (one answer for each activity: S10D1-
S15D5):S10: it was completely my choice to let someone else perform this activity.
S11: I completely trusted the person(s) who performed this activity for me.
S12: I felt that the others loved to perform this activity for me.
S13: because others performed this activity, I didn’t worry about it anymore.
S14: I felt more safe by asking someone else to do this activity for me.
S15: I experienced more control by asking someone else to do this activity for me.
Response options for subscale 2: idem 1a and 1b
A: Activity – TA: Time spent in activity – S: Statement – D: delegated activity – PD: Activities rather performed self.
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Appendix B – Indices and algorithms to calculate the final score
1. The index and the underlying algorithm for ‘the mean amount of time spent in the five most
important activities’ (TA)
Algorithm Mean amount of time spent TA Index TA
∑ ( )
/5 Less than one hour ≤ 1 0.25
One hour, less than half a day >1 - ≤ 3 0.50
Half a day, less than one day > 3 - ≤ 4 0.75
More than half a day > 4 1
2. The index for ‘the number of activities the individual wanted to perform himself’ (PD)
Number of activities: PD Index PD
≥ 4 0.25
3 0.50
2 0.75
< 2 1
3. The algorithm to calculate the score for subscale 1 (SPA, self-performed activities)
∑ ∑ (
)
/45 x index TA
4. The algorithm to calculate the score for subscale 2 (DA, delegated activities)
∑ ∑ (
)
/30 x index PD
5. The algorithm to calculate the final participation score in percentage (GPS)
GPS = (SPA + DA)/2 x 20
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Appendix D
“De auteur en de promotor geven de toelating deze masterproef voor
consultatie
beschikbaar te stellen en delen ervan te kopiëren voor persoonlijk gebruik. Elk
ander gebruik valt onder de beperkingen van het auteursrecht, in het bijzonder
met betrekking tot de verplichting uitdrukkelijk de bron te vermelden bij het
aanhalen van resultaten uit deze masterproef.”
Datum
(handtekening student) (handtekening promotor)
Sabbe Lode Dr. Van de Velde D.