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

2

3

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

4

5

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

6

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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8

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

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1 C

on

ten

t V

ali

dit

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2 I

nte

rn

al

Co

nsi

sta

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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;

13

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).

14

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.”.

16

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.

35

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

36

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.