Sydney Psychosocial Reintegration Scale (SPRS-2): Meeting the Challenge of Measuring Participation in Neurological Conditions

Sydney Psychosocial Reintegration Scale (SPRS-2): Meeting theChallenge of Measuring Participation in Neurological Conditionsap_60 20..32

Robyn Tate,1,2 Grahame Simpson,1,3 Amanda Lane-Brown,1 Cheryl Soo,4 Annelies de Wolf,1 and Diane Whiting3

1Rehabilitation Studies Unit, Northern Clinical School, Sydney Medical School, University of Sydney, 2Royal Rehabilitation Centre Sydney, 3Brain Injury Reha-

bilitation Unit, Liverpool Hospital, and 4Australian Centre for Child Neuropsychology Studies, Murdoch Children’s Research Institute, Royal Children’s Hospital

This three-part article presents: (1) a review of the construct of participation; (2) an overview of the 12-item Sydney Psychosocial ReintegrationScale (SPRS) as a measure of participation and as a description of new developments resulting in its revision (SPRS-2); and (3) as an applicationin different neurological groups. Psychometrically, the SPRS performs very well. There are no significant floor or ceiling effects, and both FormA (change since injury) and Form B (current status) show excellent inter-rater and test–retest reliability. There is also substantial evidence for itsvalidity (concurrent, discriminant, and convergent/divergent), and it shows good fit to a Rasch model, providing evidence for its construct validity.Rasch logit scores are used to provide reliable change index values to determine whether an individual patient’s scores have improved ordeteriorated. In Part 3, three samples were compared: traumatic brain injury (TBI; n = 130), primary brain tumour (PBT; n = 54), and spinal cordinjury (SCI; n = 50) on the SPRS-2 Form B. The TBI sample performed more poorly than the PBT and SCI samples on the interpersonal relationshipsand occupational activity domains. On the living skills domain, the TBI and SCI groups both performed more poorly than the PBT sample. Thesedata demonstrate the differential levels of participation observed in different neurological groups.

Key words: assessment; brain injuries; community integration; participation; psychometric properties; Sydney Psychosocial ReintegrationScale.

Part 1: Assessing Participation afterTraumatic Brain Injury (TBI)—theBroader Context

Participation is a construct that has gained currency with theincreasing use of the International Classification of Functioning,Disability and Health (ICF; World Health Organization, 2001).It refers to “involvement in a life situation” (p. 10) and roughlycorresponds to constructs such as social role functioning, psy-chosocial functioning, and community integration. The livedexperience of people with chronic health conditions or disabili-ties is most frequently expressed in terms of the impact theseconditions have on participation (e.g., “I just want to get back towork”). Participation is of growing interest to health plannersand policymakers, both as a benchmark for service evaluationas well as a means to estimate the societal costs of chronic

health and other disabling conditions (Cameron, 2010; Magasi,Hammel, Heinemann, Whiteneck, & Bogner, 2009; Perenboom& Chorus, 2003). As a result, focus has increased on the mea-surement of participation.

TBI is a complex health condition that can have a significantdeleterious effect on participation. TBI results from an externalforce to the head of sufficient severity to cause disruption ofbrain function. Such disruption may be brief and mild to pro-longed and severe. Up to 80% of TBIs are mild, and most peoplesustaining mild TBI report transient symptoms that resolvewithin 3–6 months of injury (Carroll et al., 2004; Lundin, DeBousard, Edman, & Borg, 2006). The more severe degrees ofinjury, however, can cause significant lifelong morbidity, affect-ing body function, conduct of everyday activities, and resump-tion of social roles. TBI is important because it is the single mostcommon cause of acquired disability in previously healthy,young people (Thurman, Alverson, Dunn, Guerrero, & Sniezek,1999).

Yet, it is not only the heterogeneity of initial injury severityand longer-term outcome that makes TBI complex but also theclinical presentation of a person with TBI. In civilians, TBI mostcommonly occurs from road traffic crashes, assaults, and falls,causing acceleration-deceleration injury. The areas of the brainthat are particularly vulnerable to this type of injury are the

Correspondence: Robyn Tate, Rehabilitation Studies Unit, PO Box 6, Ryde,Sydney, NSW 1680, Australia. Fax: +61 29809 9037; email: [email protected]

Accepted for publication 21 November 2011

doi:10.1111/j.1742-9544.2011.00060.x

What is already known on this topic

1 Participation refers to involvement in a “life situation”.2 It is increasingly used in health research.3 The SPRS is a measure of participation designed for neurological

groups.

What this paper adds

1 Provides a taxonomy to classify scales of participation.2 Applies Rasch logit scores to calculate reliable change in an

individual’s SPRS scores.3 Compares SPRS performance in 3 different neurological

conditions.

Australian Psychologist 47 (2012) 20–32© 2012 The Australian Psychological Society

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frontal and temporal lobes that come into abrupt contact withthe sharp sphenoidal ridges of the skull resulting in contusions,along with nerve fibre damage (diffuse axonal injury) in thesubcortical white matter caused by the rotational and shearingforces associated with acceleration-deceleration injuries. Inturn, these neuropathologies are responsible for three hallmarkimpairments of TBI: executive/behaviour dysfunction related todisrupted functioning of the frontal lobes and their connections,memory/ learning impairments related to temporal lobe struc-tures, and slow-processing speed arising from subcortical whitematter damage. Thus, unlike many other disability groups, thecharacteristic type of disability after TBI is not physical, butrather neuropsychological, with the result that the person withTBI is not immediately identified as having a disability. It is theseneuropsychological sequelae that are, by and large, responsiblefor difficulties in social participation.

Historically, participation has been a relatively late addition tothe measurement of outcome and functional consequences ofacquired brain impairment (Tate, 2010). During the 1950s and1960s, initial standardised measures of activity limitations inolder people focused on basic activities of daily living for self-care activities and mobility. In the following decades, the focuswas expanded to include other components of functioningnecessary for independence, and consequently, during the1970s and 1980s, extended or instrumental activities of dailyliving were introduced, incorporating a broader item contentincluding domestic and occupational (particularly leisureoptions) activities. It was soon recognised that these instrumen-tal activities of daily living did not capture the types of func-tional disability experienced by some clinical groups, such asthose with TBI, and in the 1980s and 1990s, a spate of scalesassessing participation were published. Indeed, the nascentversion of the Sydney Psychosocial Reintegration Scale (SPRS),which originated as a semi-structured interview reporting onlong-term outcomes in a consecutive rehabilitation series (Tate,Lulham, Broe, Strettles, & Pfaff, 1989), was one of the first suchmeasures.

There is a growing number of measures of participation (seeMagasi & Post, 2010; Perenboom & Chorus, 2003; Resnik &Plow, 2009 for review), many of which are used for people withTBI (e.g., reviews by Reistetter & Abreu, 2005; Tate, 2010; Tate,in press). Assessing participation, however, is more complexthan evaluating relatively easily operationalised constructssuch as basic and instrumental activities of daily living. Asnoted elsewhere, although many participation instrumentscover similar content areas, they differ markedly with respect toconceptual perspectives and scoring procedures (Tate, in press).These differences are reflected in only modest correlation coef-ficients (in the order of r = 0.3-0.5) that sometimes have beenreported between different scales of participation in the same(TBI) clinical group,1 as well as between subscales examiningthe same domain.2

It is generally agreed that participation is a complex andmultidimensional construct, which is ideographic rather thannomothetic in nature. In other words, being ideographic, it isparticular to each individual and the unique combinations ofelements that might contribute to his or her sense of participa-tion. However, there are elements of participation that could beconsidered more nomothetic in character—certain benchmarks

including involvement in occupational activity (OA) and rela-tionships that are socially expected. Moreover, participation isnot a concrete entity that exists and can be directly observed.It is a latent construct, and as such, the nomothetic or societalelements do not constitute participation in and of themselves,although it is acknowledged that they are important constitu-ents of the domain of participation.

In addition, disagreement remains about how participationshould be measured and who is best placed to measure it (Tate,2010, in press). Assessment of participation is complicated whenthe familiar dichotomy of “subjective/objective” approachesto measurement is applied (e.g., Whiteneck & Dijkers, 2009).In relation to “subjective,” difficulties arise when “self-report”response formats are subsumed under the “subjective” category.Although it is true that self-report provides a unique window tothe interior life (thoughts, feelings) of the individual, people canalso provide self-reports on aspects of their lives that are verifi-able by others, such as the number of hours that they work. Thisthen leads to the consideration of “objective.” Frequency data,such as the number of hours that an individual works or thenumber of times in a week that family members are visited,provides certain verifiable data. Many measures of participationfocus on this type of information, including scales such as theCraig Handicap Assessment and Reporting Technique (CHART),Community Integration Questionnaire, and Brain InjuryCommunity Rehabilitation Outcomes. However, individualswith TBI and their family members/significant others find thatthe changes in the quality of relationships, work performance,and so forth, also occur, and these impacts are not necessarilycaptured by frequency data alone.

An alternative taxonomy that resolves these difficulties issuggested (see Figure 1; discussed in detail in Tate, in press). Itseeks to clarify the issues of what is being reported and whois doing the reporting, aiming to avoid the potential confusionthat can arise by applying the “subjective/objective” dichotomyto scales of participation. The “client-centred” aspect of parti-cipation refers to the perspective of the “disability insider, whoselife it is” (Brown et al., 2004). This can encompass the indivi-dual’s internal states, experience of satisfaction with the levelof participation, sense of autonomy, and the extent to whichthe person feels a sense of belongingness. These internal statescan only be given full expression by the person them-selves through their self-report. The Community IntegrationMeasure and the Impact on Participation and Autonomy Ques-tionnaire are examples of scales that seek to tap into thisperspective.

The term “exteriorised” refers to those dimensions of an indi-vidual’s life that can also be observed by others. Data aboutthese dimensions may include frequency data, as well as dataabout changes in quality of performance (e.g., in relationships,occupation). Although judgements about quality always involvea value evaluation, previous research employing the SPRS hasfound that agreement can be achieved with excellent inter-raterreliability in relation to these judgements of quality (Tate,Hodgkinson, Veerabangsa, & Maggiotto, 1999). These exterior-ised dimensions of participation can be rated by “others” or by“self-report.” As previously flagged, certain dimensions of the“exteriorised” data can then be compared against various typesof benchmarks or standards. These provide important yardsticks

R Tate et al. Sydney psychosocial reintegration scale


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against which the progress and situation of an individual can beevaluated.

With respect to scoring procedures, there is a wide variety ofreference standards used by scales adopting an exteriorised per-spective. They can be broadly classified into three types: (1)scales using normative data (e.g., CHART, Community Integra-tion Questionnaire, SPRS-Form B) in which functioning is com-pared with the general population; (2) scales using comparisonor reference data drawn from a clinical population (e.g., Mayo-Portland Adaptability Inventory) in which functioning is com-pared with the average person with a brain (or other) healthcondition; and (3) scales in which the person serves as his or herown control (e.g., SPRS-Form A) in which current functioningis compared with the person’s pre-injury level of function-ing. Different standards yield different types of information,although no single standard is inherently better than another.

Part 2: SPRS

The development and conceptual background of the SPRS arereviewed in Tate (2010). In brief, the SPRS was designed tomeasure psychosocial reintegration after TBI, targeting the threedomains in which the TBI population experience particulardifficulty: OA (both work and leisure), interpersonal relation-ships (IR), and independent living skills (LS). Originally, a semi-structured interview was used by experienced clinicians to obtainratings on the scale (Tate et al., 1989), but subsequently, the scalewas improved by developing a set of 12 items (see Appendix),with four items for each domain.3 Two forms of the SPRSmeasure “change since injury” (Form A; Tate et al., 1999) and“current status” (Form B; Tate, Pfaff, Veerabangsa, & Hodgkinson,2004). Although there are no hard and fast rules, it is suggestedthat Form B is used in situations where the injury occurred morethan a few years previously or in situations such as interventionstudies where the intention is to compare findings at two differ-ent points in time. For each form, there are three versions:clinician, self, and informant, each of which uses the same 12items but phrased as appropriate for the respondent.

The SPRS is available from the website of the RehabilitationStudies Unit (http://www.rehab.med.usyd.edu.au), and Form Ais reproduced in Tate (2010). Administration of the SPRS isgenerally completed interview-style with an informant/patient.Clinicians can also complete the scale independently, based onknowledge of the patient’s current level of functioning, andinformants or patients can also use this procedure. Self-completion of the SPRS is not recommended, however, forthose patients who experience functionally significant cognitiveimpairments in memory, judgement, or awareness, which maycompromise the validity of responses. Additionally, the SPRScan be completed online by clinicians, informants, or patients,this format also having automated chart-making facilities.Administration time is generally 15–20 min in interview-style,but the method of clinician-rating is much quicker (approxi-mately five minutes).

Originally, the SPRS used a 7-point rating scale, which hasbeen replaced by a 5-point scale, and is now referred to as theSPRS-2 (Tate, Simpson, Soo, & Lane-Brown, 2011). The changewas made in response to user feedback, with the aim of improv-ing ease of administration and completion. Each item is ratedfrom 0 (equivalent to “an extreme amount of change” on FormA or “extremely poor” on Form B) to 4 (equivalent to “nochange at all” on Form A or “very good” on Form B). Specificbehavioural descriptors are attached to response categories 0–3for each item. The total score ranges from 0 to 48 (0–16 for eachdomain), with higher scores representing better levels of psy-chosocial reintegration. The data from the original psychometricstudies using the 7-point scale were reanalysed with datarecoded to a 5-point scale and the patterns of psychometricproperties, including floor and ceiling effects, remained virtuallythe same (Tate et al., 2011) with excellent results (see the fol-lowing). Correlation coefficients between the original 7-pointand recoded 5-point scale were very high (total scores rs = 0.98,domains rs > 0.96, items rs > 0.94).

Tables of normative and TBI comparison data for Form A(change since injury) and Form B (current status) of the SPRSare available in Tate et al. (2011). Data for the community

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Exteriorised Client-centred

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(e.g., clinician, family member)

Self-report

Figure 1 A Taxonomy for Scales of Participation.

From Tate (in press).

Sydney psychosocial reintegration scale R Tate et al.


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samples are presented graphically in Figure 2, but in the previ-ous publication, the TBI groups are also stratified by post-traumatic amnesia (PTA) duration, as well as providing datafrom groups at rehabilitation discharge. Normative data forForm B (using a recoded 5-point SPRS) were derived from aconvenience sample of 105 healthy volunteers living in thecommunity who were recruited by newspaper advertisementsas part of another study. There was an even proportion of malesand females (n = 51 and n = 54, respectively), age range was16–76 years (M = 39.2, standard deviation (SD) = 16.68), andyears of education ranged from 6 to 22 years (M = 13.52,SD = 2.80). Comparative data for the TBI groups drew onsamples of participants who were all at least 12 months post-trauma and (mostly) living in the community. A clinician-ratedSPRS was used. Data from Form A (n = 201) were from previ-ously published studies with data recoded to a 5-point SPRS;data from Form B (n = 150) were from an independent sampleadministered the 5-point SPRS-2. Normative data were notrequired for Form A because by using comparison with thepremorbid state, the person serves as his/her own control.

Results of Mann–Whitney U-tests on Form B data docu-mented statistically significant differences between the norma-tive and TBI samples, both for the total score (z = -6.41,p = .000), as well as the OA (z = -8.48, p = .000), IR (z = -4.58,p = .000), and LS (z = -2.18, p = .03) domains (Tate et al., 2011).In the TBI samples, no significant floor or ceiling effects werepresent for the total score for either Form A (0% and 2.5%,respectively) or Form B (1.3% for both floor and ceiling). Foreach of the domains, both floor and ceiling effects were less thanthe stringent criterion of 15% (see Tate et al., 2011).

Psychometrically, the SPRS has been thoroughly examinedusing both classical test theory and rating scale analysis anddemonstrates very good measurement properties. Early psycho-metric studies using the 7-point scale documented that the SPRS

is a reliable scale for both Form A (change since injury; Tate et al.,1999) and Form B (current status; Tate et al., 2004). Morespecifically, inter-rater reliability is very high for Form A (Intra-class correlation coefficient (ICC) = 0.95) and Form B (ICC =0.84), as is temporal stability (ICC = 0.90 for both Form A(1 week) and Form B (1 month)). Responsiveness has beendocumented for Form A with large effect sizes (Simpson et al.,2004; Tate et al., 1999), although no information is yet availablefor Form B.

Validity of the SPRS has been examined from many perspec-tives. Both Form A (change since injury) and Form B (currentstatus) show good evidence of concurrent validity with theLondon Handicap Scale (rs = -0.85 and rs = -0.71, respectively;Tate et al., 1999, 2004). Discriminant validity was establishedfor both Forms A and B on the recoded 5-point scale showingsignificant differences between injury severity subgroups (Tateet al., 2011): those with duration of PTA less than 30 days hadhigher SPRS-2 scores (M = 32.98, SD = 11.22 and M = 33.27,SD = 9.62 on Forms A and B, respectively) than those with PTAduration between 1 and 3 months (M = 25.48, SD = 10.55 andM = 27.05, SD = 11.28, respectively), who in turn had higherSPRS-2 scores than those with PTA greater than 3 months(M = 14.70, SD = 9.47 and M = 13.97, SD = 8.80, respectively).Convergent and divergent validity were established with FormA of the original SPRS and the Sickness Impact Profile (SIP: Tateet al., 1999): the SPRS showed higher correlation coefficientswith hypothesised similar constructs (e.g., SPRS OA with SIPwork + recreation: rs = -0.72; SPRS IR with SIP psychosocial:rs = -0.76) and lower coefficients with hypothesised dissimilarconstructs (e.g., SPRS OA with SIP psychosocial: rs = -0.45;SPRS IR with SIP work + recreation: rs = -0.41).

Factor analysis of Form A (change since injury) of the origi-nal SPRS, using multidimensional scaling, was reported byKuipers, Kendall, Fleming, and Tate (2004). Two dimensions

Figure 2 SPRS Normative and TBI Compara-

tive Data.



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were identified: productivity/personal life and independent/dependent. We recognise that these dimensions differ from thethree domains of the SPRS as it is used clinically, but we opt toretain the latter for administration and scoring purposes becausepatients and clinicians alike readily relate to the structure ofoccupation, relationships, and LS.

A significant development in examining the measurementproperties of the SPRS-2 has been the application of Raschanalysis (Tate et al., 2011). The data used were those describedpreviously for the construction of TBI comparative data sets(Form A, n = 201; Form B, n = 150). Both SPRS forms metstandard criteria and showed good fit to a Rasch model. ForForm A, person separation was 3.36 (reliability 0.92) and itemseparation was 7.78 (reliability 0.98), with average infit statisticswithin the criterion range of 0.7–1.3 (persons 1.03, items 1.00).A single item (item 6—family) showed misfit (1.53), which wasdue to two misfitting persons, thereby lessening the likelihoodthat the misfit was due to a defect in the item. Results for FormB showed similar results with good person separation (3.03,reliability 0.90) and item separation (7.25, reliability 0.98), andaverage infit statistics in the criterion range (persons 1.04, items1.02). Two Form B items showed serious misfit (item4—organising work and leisure, 0.57; item 6—family, 1.88). Foritem 4, the misfit was explained by one or two outlying persons,although for item 6 the misfit for persons occurred across thelatent variable. We opted to retain the misfitting items in thescale because of their clinical relevance. The hierarchy of items

for each SPRS form was clinically meaningful, with work,leisure, and IR being more difficult than items for everydayactivity LS. The results of the Rasch analyses using the largersample sizes confirm the excellent reliability (internal consis-tency) and construct validity of the SPRS-2.

A distinct advantage of Rasch analysis is that the logit scoresproduced by the analysis represent interval level data. By usinga conversion table, it is therefore easy to translate the SPRS rawscores, which use ordinal data furnished from the Likert-type5-point rating scale to interval level data. Logit-based SPRSscores can then be used legitimately in parametric analyses.They can also be used at the individual patient level to deter-mine whether there has been a reliable change (improvementor deterioration) in a patient’s SPRS scores. This has enormousclinical benefit.

Calculation of the reliable change index for Form A (changesince injury) is described in detail in Tate et al. (2011). A con-version table of SPRS raw scores to logit values scaled from 0to 100 is provided in the SPRS-2 manual and is reproduced inTable 1. In brief, the formula described by Ley (1972; see Per-dices, 2005 for review of reliable change index formulae) wasapplied to the Rasch-derived logit scores for the SPRS-2. Theminimum difference of 8.23 logit scores is required to establishwhether a change in scores is reliable.4 The procedure is appliedas follows: first, convert the Time 1 SPRS-2 raw score to a logitvalue, using Table 1 and add the constant of 8.23. This new logitscore is the minimum score required to determine whether the

Table 1 Conversion table of SPRS-2 raw scores to Rasch logit scores scaled from 0 to 100

Form A Form B

Raw score Logit Raw score Logit Raw score Logit Raw score Logit

0 0 — — 0 0 — —

1 11.02 25 48.64 1 11.56 25 48.23

2 17.76 26 49.52 2 18.15 26 49.09

3 21.96 27 50.39 3 22.16 27 50.05

4 25.02 28 51.18 4 24.92 28 50.91

5 27.38 29 52.06 5 27.22 29 51.77

6 29.40 30 53.02 6 29.04 30 52.72

7 31.15 31 53.89 7 30.66 31 53.68

8 32.63 32 54.86 8 32.09 32 54.63

9 34.03 33 55.91 9 33.33 33 55.68

10 35.26 34 56.96 10 34.57 34 56.73

11 36.40 35 58.01 11 35.72 35 57.88

12 37.45 36 59.14 12 36.77 36 59.03

13 38.50 37 60.37 13 37.73 37 60.27

14 39.37 38 61.77 14 38.68 38 61.51

15 40.33 39 63.25 15 39.64 39 62.94

16 41.21 40 64.83 16 40.59 40 64.47

17 42.08 41 66.67 17 41.45 41 66.19

18 42.96 42 68.68 18 42.31 42 68.10

19 43.74 43 71.04 19 43.17 43 70.30

20 44.62 44 73.84 20 44.03 44 72.97

21 45.41 45 77.25 21 44.89 45 76.23

22 46.19 46 81.71 22 45.75 46 80.71

23 47.07 47 88.80 23 46.61 47 87.91

24 47.86 48 100 24 47.37 48 100



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change in score is reliable. Then, convert the new logit scoreback to a SPRS-2 raw score, using Table 1. This SPRS-2 scorerepresents the minimum SPRS-2 raw score required to deter-mine whether the change in score is reliable.

The following two examples demonstrate the application ofthe procedure. Example 1: At Time 1, Patient A has a SPRS-2total score of 28. Consulting Table 1, a SPRS-2 raw score of 28corresponds to 51.18 logits. When assessed on the SPRS-2 atTime 2, Patient A scored 35, corresponding to 58.01 logits.The required minimum score, however, is 59.41 logits (i.e.,51.18 + 8.23), and thus, we conclude that the SPRS-2 improve-ment of seven points was not a reliable change. Example 2: AtTime 1, Patient B has a SPRS-2 total score of 45, correspondingto 77.25 logits. At Time 2, Patient B scored 47, corresponding to88.8 logits. The required minimum difference is 85.48 logits(i.e., 77.25 + 8.23), and thus, we conclude that the improve-ment of two points was a reliable change.

Note that whereas the change score in logit values required todetermine the minimum difference is always constant (8.23 inthe case of the SPRS-2), the significance of the change in rawscore of the SPRS-2 differs according to its position in the scoredistribution—a smaller SPRS-2 raw score change is required atthe extremes of the distribution. Moreover, these two examplesdemonstrate the importance of using logit scores, which providean interval level of measurement—at the extremes of the scale,a smaller minimum difference of raw scores is required to dem-onstrate reliable change than in the mid ranges of the scale.Patient B who scored highly on the SPRS-2 at Time 1, with araw score of 45 (out of a possible 48), required a change of onlytwo SPRS-2 raw score points to meet requirements for reliablechange, but Patient A who scored in the mid range of the scaleat Time 1, with a raw score of 28, required a change of nineSPRS-2 raw scores to meet requirements. Thus, Patient B’sSPRS-2 raw score change of two was reliable, yet Patient A, whohad a numerically higher SPRS-2 raw score change of sevenpoints, did not demonstrate reliable change. Similar results havebeen found for other scales, such as the Functional Indepen-dence Measure when Rasch analysis has been applied (Linacre,Heinemann, Wright, Granger, & Hamilton, 1994).

In other applications of the SPRS in our clinical practice, weoften convert the total and domain scores back to the originaldescriptors, which enables the score to be more readily inter-preted, a procedure that Kervick and Kaemingk (2005) havealso used with the SPRS. For example, Patient A described in theforegoing had a total SPRS-2 score of 28/48, corresponding to amean score of 2.3/4 on the rating scale, which falls between “alittle” and “a moderate” degree of change. Additionally, in ourclinical and research work with Form A (Lammi, Smith, Tate, &Taylor, 2005), we have also grouped the total and domain scoresinto three broad bands. In the original 7-point scale, these bandscorrespond to the following scores: average scores 0–2 = majorchange (or poor outcome), average scores 3–4 = some change(or limited outcome), and average scores 5–6 = no significantchange (or good outcome). Using the SPRS-2, these groupingscorrespond to the following: average scores 0–1 = majorchange/poor outcome, average scores 2–3 = some change/limited outcome, and average score 4 = no significant change/good outcome. Thus, Patient A’s mean score of 2.3/4 on theSPRS-2 is equivalent to “some change” or “a limited outcome”.

Clinicians find such descriptors helpful in directly interpretingthe result; additionally, when a person is assessed on multipleoccasions, use of the reliable change index provides a rigoroustest of whether a change in scores is reliably different.

In addition to studies on the psychometric properties of theSPRS, our group has also used it as an outcome measure in alongitudinal study following up a consecutive series on average23 years post-trauma (Tate, Broe, Cameron, Hodgkinson,& Soo, 2005), as well as the follow-up of a statewide cohort(Harradine et al., 2004; Tate et al., 2006; Winstanley, Simpson,Tate, & Myles, 2006). It has also been use in correlational andintervention studies (Long, McDonald, Tate, Togher, & Born-hofen, 2008; McDonald et al., 2008; Togher, McDonald, Tate,Power, & Rietdijk, 2009).

Apart from the work of our own group, the SPRS is widely usedby other clinicians and researchers, particularly in Australia.A search of Medline and PsycINFO for “Sydney PsychosocialReintegration Scale” identified at least 20 original studies andreviews published by researchers other than the SPRS develop-ers. It has been commonly used as an outcome measure bygroups in Queensland and Victoria (Draper, Ponsford, & Schön-berger, 2007; Ownsworth & Shum, 2008; Ownsworth, Turpin,Carlson, & Brennan, 2004; Ownsworth et al., 2007; Turner,Fleming, Cornwell, Haines, & Ownsworth, 2009). Groups in NewSouth Wales and Queensland have used it in interventionresearch (Bornhofen & McDonald, 2008a, 2008b; Fleming,Kuipers, Foster, Smith, & Doig, 2009; Fleming, Shum, Strong, &Lightbody, 2005). Bornhofen and McDonald (2008a, 2008b)used a range of measures to assess the effect of a remediationprogramme for emotion perception deficits. The SPRS was usedas a generalisation measure, but treatment effect did not extendbeyond the specific target behaviour (emotion perception).Fleming et al. (2005) also used the SPRS as a generalisationmeasure to assess the effect of a treatment for prospectivememory deficits in a series of single-participant designs, with twoof the three participants showing improvement in SPRS totalscores following intervention. Fleming, Kuipers, et al. (2009)utilised the SPRS as an outcome measure, along with fourother measures, when evaluating a “Personal EnvironmentsEnhancing Rehabilitation” group intervention based on theICF “Environment” component for a (mainly) TBI population.A significant group-by-time interaction effect was found for theSPRS total score; the OA and LS scores improved significantlymore in the experimental treatment participants than in controlparticipants. The SPRS has also been used in correlational studies,both in Australia and elsewhere (Gould, Ponsford, Johnston, &Schönberger, 2011; Kervick & Kaemingk, 2005; Ownsworth &Fleming, 2005; Whelan-Goodinson, Ponsford, & Schönberger,2008; Wise, Ownsworth, & Fleming, 2005), predictive studies(Winkler, Unsworth, & Sloan, 2006), as well as psychometricstudies to validate a measure of prospective memory (Fleming,Kennedy, Fisher, Gill, Gullo, & Shum, 2009).

Although the development of and research using the SPRShas been conducted principally with adults of working age,more recent work has examined it in relation to adolescents andchildren. Anderson’s group in Victoria have adapted it for usein adolescents (Anderson, Brown, & Newitt, 2010; Anderson,Brown, Newitt, & Hoile, 2009, 2011; Muscara, Catroppa, &Anderson, 2008). Soo et al. (unpublished data) at the Royal



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Children’s Hospital in Melbourne have recently adapted theSPRS-2 for use with children, referred to as SPRS-C. This scaleis suitable for children between 5 and 16 years of age. Theadaptation focused on the Form B, with parent and self-reportversions available. As with the adult version, the scale includes12 items using a 5-point scale format. The process of adaptingthe scale comprised two distinct steps. First, each item wasreviewed by a multidisciplinary group of occupational therapistsand psychologists to assess its applicability to children, andchanges were made to account for developmental issues. Forexample, item 5 in the adult version “How do you rate yourrelationship with your spouse?” was replaced with “How do yourate your relationship with your parents/caregiver?” During thisprocess, it was clear that item 12 (accommodation) requireda substantial change in focus. In the adult version, item 12emphasises the ability of the person to live independently in thecommunity (i.e., “How do you rate your living situation?”).Given this would have limited applicability to children, item 12was replaced with a question in which the respondent rates thechild’s ability in everyday activities, such as performing ortaking on responsibility for chores (“How do you rate yourability to perform everyday activities?”). Second, the SPRS-Cwas changed so that each item is framed according to a devel-opmental criterion. Thus, for each item, the respondent is askedto rate current status compared with children of the same age.Normative data for the SPRS-C have been collected for theparent report version of Form B in approximately 200 childrenaged between 5 and 14 years.

Part 3: Using the SPRS with DifferentNeurological Groups

The SPRS had its genesis and long history of developmentwithin the field of TBI. However, the SPRS has been trialledin studies investigating other neurological populations. Forexample, the SPRS has been employed in a correlational studywith a mixed acquired brain injury sample (cerebrovascularaccidents, hypoxia, tumours; Ownsworth & Fleming, 2005). Ithas also been employed in studies of single diagnostic groupsincluding primary brain tumour (PBT; Whiting et al., 2010) andspinal cord injury (SCI; Cameron, Middleton, Quirk, De Wolf, &Murphy, 2007; De Wolf, Cameron, Middleton, & Quirk, 2008).Although the SPRS was specifically developed for use in theTBI population, neurological impairment, whatever the cause,can lead to challenges in the same key domains of occupation,relationships, and independent living. It is therefore of value toexamine the differential impact of various neurological condi-tions on participation as demonstrated by the SPRS. Applicationamong different neurological populations poses new challenges,however, because demographic features may differ (e.g., sex,age) and the characteristic neuropathology for each conditionvaries widely. These factors in combination will have flow-through effects in terms of the patterns of impairments, limita-tions on functioning, and subsequent levels of participation.

The spinal cord is part of the central nervous system. The twodefining features of SCI that distinguish it from TBI is the uni-versal presence of physical impairment and the absence of cog-nitive impairment (although up to 47% of people with SCI canhave a comorbid TBI; Hagen, Eide, Rekand, Gilhus, & Gronning,

2010). However, there are similarities between the two groupsin terms of their demographic profile and the typical cause ofinjury. PBT contrasts with TBI on three key accounts. First, thedemographic profile is different (usually older and a more bal-anced sex ratio). Second, the underlying neuropathology isoften more localised than the multifocal pattern of damageobserved in TBI, with some intracerebral tumours (e.g., of themeninges) not even directly damaging brain tissue. Finally, PBTscan be progressive, leading to worsening brain damage as thetumour grows, in contrast to a TBI, which is a nonprogressivecondition. However, fewer people with PBT display physicalimpairments, in contrast to SCI. Accordingly, the aim was toexamine the impact of different neurological conditions onparticipation using the SPRS.

Methods

Participants

Participants were convenience samples aggregated from threeprevious studies, which utilised the SPRS in three distinct neu-rological populations: PBT (Whiting et al., 2010), SCI (Cameronet al., 2007; De Wolf et al., 2008), and TBI (Simpson, 2010; Tateet al., 2011). The TBI group was that used in the Tate et al.(2011) article to provide comparative data and conduct theRasch analysis. To improve homogeneity of the groups withrespect to time post-injury/diagnosis, participants who weregreater than 10 years post-injury (n = 20, all TBI participants)were deleted from the sample, resulting in 130 of the original150 TBI participants being used in the current study. For thesame reason, the 2-year post-rehabilitation discharge time pointwas selected from the longitudinal SCI study. This resultedin 234 participants in total in the current study (TBI, n = 130;PBT, n = 54; SCI, n = 50). In order to have a common metric forinjury severity, measures of severity specific to each populationwere reclassified into “high” and “low” impairment categories.Criteria for the high impairment categories included PTA greaterthan 30 days (TBI, 57%), presence of high-grade tumour (PBT,39%), and tetraplegia with rating on the American Spinal InjuryAssociation Neurological Classification of Spinal Cord Injuryscale of sensory and motor functioning at the A, B, or C level(SCI, 22%).

Procedure

All three studies had been approved by the relevant Area HealthService Human Research Ethics Committees. The raw data fromthe three studies were aggregated into a single database. Evalu-ation of all participants with the SPRS used the clinician-ratedForm B (current status). There were some differences among thestudies in the method of data collection. First, in two of thesamples (SCI, PBT), the SPRS data were collected on the original7-point scale, and these were recoded to the 5-point revision ofthe SPRS (SPRS-2) following the procedure outlined by Tateet al. (2011). The TBI sample was collected using the 5-pointSPRS-2. Second, for the SCI sample, item 10 (personal habits)was answered from the perspective of whether or not the par-ticipant was able to complete self-care tasks either independentlyor by directing attendant carers; whereas in the TBI and PBT



26

samples, item 10 was rated strictly in terms of whether the personwas able to complete the task independent of another person’sinvolvement, whether for direct care, supervision, or prompt.The SPRS (and its revision, SPRS-2) has been extensively vali-dated with TBI populations (Tate et al., 1999, 2011) and morerecently for the SCI population (De Wolf, Lane-Brown, Tate,Middleton, & Cameron, 2010). However, it has not previouslybeen examined psychometrically for people with PBT. Therefore,some preliminary examination of the psychometric properties ofthe SPRS in the PBT sample was undertaken.

Statistical Analysis

To examine basic measurement properties of the SPRS-2 in thePBT data, internal consistency was evaluated using the Cron-bach’s alpha coefficient, and frequency data were examined forfloor and ceiling effects and item response restriction. Next,inspection was made of the SPRS score distributions for the totaland domain scores: OA, IR, and LS. Many scores were notnormally distributed, and therefore, non-parametric statisticalanalyses were conducted. A series of analyses examined varia-tions in demographic and injury/illness characteristics in thethree diagnostic groups using Mann–Whitney U-tests andKruskal–Wallis one-way analysis of variance (K-W ANOVA).Following this, the pattern of SPRS scores among the neurologi-cal populations was examined using the K-W ANOVA, with posthoc exploration undertaken using Mann–Whitney U-tests.Finally, differences in SPRS scores due to severity (high and low)were examined both within and among diagnostic categories.The within-neurological group analyses were conducted usingthe Mann–Whitney U-test. The patterns of SPRS scores wereexamined in diagnostic groups separately for high and lowlevels of impairment, because it was anticipated that partici-pation would differ depending on level of impairment. Thisbetween-group analysis was conducted using K-W ANOVA,with post hoc pairwise analyses using Mann–Whitney U-tests.Significant reported results met criteria for significance follow-ing the Bonferroni adjustment.

Results

Psychometric Properties of the SPRS inthe PBT Sample

Preliminary psychometric investigation of the SPRS for use inthe PBT population found high internal consistency (a = 0.87).Analysis of frequencies demonstrated that scores were distrib-uted throughout the range for the OA domain and the top twothirds for the total and other domain scores. There was a ceilingeffect on the LS domain with 28% achieving the highest scoreon this subscale. At the item level, analysis of the frequenciesfound that there was a spread of responses on all items;however, six items (items 5–10) showed ceiling effects withmore than 50% of the sample achieving the highest score.

SPRS Comparisons in the TBI, PBT,and SCI Samples

The 234 participants (130 TBI, 54 PBT, 50 SCI) were living inthe community and were between 1 and 10 years post-injury/

diagnosis. There were significant differences among the neuro-logical populations in the distribution of sex (c2 = 19.52,p = .00). In the TBI and SCI samples, the majority were males,whereas sex was more evenly distributed in the PBT sample (seeTable 2). Age profile at assessment was typical for the threegroups with the PBT sample being significantly older than theTBI and SCI samples (c2 = 32.66, p = .00; see Table 2). Thelength of time post-injury/diagnosis at assessment was signifi-cantly different across neurological populations (c2 = 30.87,p = .00). The PBT sample had been assessed on the SPRS atan earlier time point than the TBI and SCI populations (seeTable 2).

When examining SPRS total and domain scores among theneurological populations, there was a significant differenceamong the samples on all SPRS total and domain scores (seeTable 3). Post-hoc investigation demonstrated that the TBIsample had lower levels of psychosocial reintegration (total, OA,and IR scores) than the PBT and SCI populations, who did notdiffer significantly. For the LS domain, the PBT group performedsignificantly better than the TBI group, and there was no sig-nificant difference between TBI and SCI groups. There was noeffect of age or sex on the SPRS scores for any of the neurologi-cal populations, although there was a trend for an effect of agein the SCI group on the OA domain (z = -2.41, p = .016,a = 0.05/12 = 0.004), with older participants performing morepoorly.

The effect of severity of injury/illness on SPRS scores wasexamined first within each diagnostic group and then amongdiagnostic groups. For the within-group analyses, participantswith the more severe TBI demonstrated poorer SPRS total anddomain scores (total, z = -4.65, p = .00; OA, z = -3.7, p = .00; IR,z = -3.71, p = .00; LS, z = -5.30, p = .00) than those with PTAless than 30 days. Within the PBT sample, there were no sig-nificant differences in participation related to severity. A signifi-cant difference was observed between high and low impairment

Table 2 Demographic and Injury Variables in Neurological Populations

Variable TBI PBT SCI

(n = 130) (n = 54) (n = 50)

Age at assessment (years)

Mean (SD) 37.06 (14.07) 52.66 (16.12) 37.22 (14.93)

Median (IQR) 34.00 (25.0) 54.00 (20.0) 30.00 (27.0)

Sex, n (%)

Male 98 (75) 24 (44) 39 (78)

Female 32 (25) 30 (56) 11 (22)

Severity, n (%)

Low 56 (43) 33 (61) 31 (62)

High 74 (57) 21 (39) 19 (38)

Time post injury/diagnosis (years)

Mean (SD) 3.75 (2.48) 2.13 (1.86) 2.61 (0.27)

Median (IQR) 3.00 (3.0) 1.00 (1.5) 2.58 (0.4)

<2 years 20 33 0

2–5 years 83 15 50

>5 years 27 5 0

Note: There were small amounts of missing data for TBI (n = 3) and PBT

(n = 1). IQR, interquartile range.



27

SCI participants on LS (z = -3.6, p = .00), with the high impair-ment group performing more poorly, but no differences werefound for the total or other domain scores.

The final set of analyses examined the patterns of SPRS scoresamong neurological groups by impairment category. For the lowimpairment group, the only significant difference was seen inthe IR domain (c2 = 20.75, p = .00), in which the TBI populationperformed significantly worse than the PBT and SCI samples(see Figure 3). By contrast, for the high impairment group,overall analyses (K-W ANOVAs) found significant differences inall domains except LS (see Figure 4; total, c2 = 20.18, p = .001;OA, c2 = 11.47, p = .001; IR, c2 = 41.12, p = .001). Post hoc pair-wise comparisons (Mann–Whitney U-tests) found that the TBIgroup performed more poorly than the SCI group in the IR andOA domains, with no difference in the LS domain. The TBIgroup also performed more poorly than PBT sample in the IRand LS domains, with a trend towards performing more poorlyin the OA domain.

Discussion Relating toNeurological Groups

There were a number of demographic and injury differencesamong the neurological samples, but they were in line with the

epidemiologically expected variations in the populations: ThePBT sample is older and the sex ratio is more even than in theTBI and SCI population, who tend to be younger and includemore males. Despite these differences, analyses were conductedas planned because this demographic picture characterises thedifferences among the neurological populations.

We found that participants in the TBI sample had poorerpsychosocial reintegration than the SCI and PBT participants,even though the PBT participants were significantly earlier post-diagnosis than the TBI participants. This occurred on the SPRStotal, OA, and IR domain scores. In the LS domain, the SCIparticipants performed more closely to the TBI participants,with PBT participants obtaining higher scores than the twoother samples. Despite the physical limitations of the SCIparticipants, they performed at a very similar level to the TBIparticipants on the LS domain. This pattern of responses wasseen regardless of the level of impairment. It should be noted,however, that a caveat to this finding is the variation in the waythat item 10 (personal habits) was administered in the SCIsample, with the responses from the TBI population consideringthe need for attendant carers versus responses from the SCIpopulation focusing on the ability to direct personal care task,regardless of the need for attendant carers. If both these studieshad responded to item 10 from the perspective of completing

Table 3 SPRS Total and Domain Scores in Neurological Populations

TBI PBT SCI Kruskal–Wallis

comparison between

groups, chi-square, p

Pattern of significance

on post hoc analysesn = 130 n = 54 n = 50

Mean (SD),

median (IQR)

Mean (SD),

median (IQR)

Mean (SD),

median (IQR)

SPRS total score 27.25 (12.63) 37.09 (7.26) 36.22 (8.65) 34.32, p = .000 TBI < PBT and SCI

30.00 (21) 38.00 (10) 38.00 (11)a

SPRS OA 6.76 (4.69) 9.43 (4.31) 10.00 (4.25) 22.41, p = .000 TBI < PBT and SCI

7.00 (8) 9.00 (6) 10.50 (6)

SPRS IR 9.72 (4.45) 14.26 (1.51) 13.96 (2.65) 66.27, p = .000 TBI < PBT and SCI

11.00 (7) 15.00 (2) 15.00 (3)a

SPRS LS 10.78 (4.69) 13.41 (2.66) 12.26 (3.37) 12.71, p = .002 TBI and SCI < PBT

12.00 (7)a 14.00 (5) 13.00 (6)

Note: OA = occupational activity domain, IR = interpersonal relationships domain, LS = living skills domain; IQR, interquartile range.aNot normally distributed.

Figure 3 SPRS Mean Domain Scores for

Low Level Impairment across Neurological

Populations.



28

personal care tasks entirely independently, without the assis-tance of attendant carers, it is anticipated that performance onthe LS domain would be poorer for the high impairment SCIsample than the TBI sample.

Psychometrically, the SPRS performed reasonably well in thePBT population, particularly considering it was developed as acondition-specific measure for use in the TBI population. Inter-nal consistency was high, item responses were not restricted,and scores were spread across most of the range of the scale.However, there was a ceiling effect on the LS domain with 28%of participants scoring the highest score, which is above the levelconsidered acceptable by the Andresen (2000) criteria. Theeffects of demographic and injury differences between the TBIand PBT groups were reflected in this ceiling effect and patternof responses, which suggested that the PBT sample had consis-tently better reintegration than the TBI group in terms of socialskills, personal habits, ability to get around the community, andliving situation. In fact, when SPRS scores from this PBT sampleare compared with the healthy sample reported in Tate et al.(2011), both samples perform at a similar level on the LSdomain.

The SPRS was previously evaluated psychometrically in a SCIpopulation (De Wolf et al., 2010), using the same sample asin the present report. It showed excellent measurement pro-perties in comparison with CHART (a well-established outcomemeasure that assesses participation in the SCI population; Whit-eneck, Charlifue, Gerhart, Drew, & Richardson, 1992). TheSPRS was found to be highly internally consistent (Cronbach’sa = 0.80), sensitive to change over time, and valid in terms ofconvergent validity with CHART (r = 0.72). In addition, withrespect to convergent/divergent validity, it showed hypo-thesised relationships with similar and dissimilar constructsof CHART domains. For example SPRS OA correlated higherwith CHART occupation (r = 0.57) than with CHART physical(r = 0.34), and SPRS LS correlated higher with CHART physical(r = 0.70) than with CHART occupation (r = 0.50). The SPRStotal score was found not to discriminate between high andlow impairment at 1-year post-SCI, but domain scores were nottested.

Extending the use of the SPRS beyond TBI has shown someinteresting differences in participation among the neurological

samples which seem to reflect the differences in impairment.The results highlight some of the challenges in applying acondition-specific measure beyond its original parameters, asillustrated by the ceiling effects observed in the PBT sample.When reviewing these results, caution should be exercisedbecause these samples were convenience samples, and peoplewith advanced, high-grade tumours and those with the mostsevere TBI were not involved in these studies. Thus, the sug-gested pattern of SPRS scores in the neurological samples needsto be examined in further research.

Concluding Comments

This article has presented a conceptual framework for the mea-surement of participation and reviewed the development andpsychometric studies of the participation measure developed byour group, the SPRS (and its revision as SPRS-2). Psychometri-cally, the SPRS has been comprehensively evaluated and per-forms very strongly on all fronts. When benchmarked againstthe set of 11 clinical and psychometric criteria proposed byAndresen (2000), the SPRS meets seven criteria at level A (reli-ability, validity, responsiveness, measurement model in terms offloor/ceiling effects, administrative burden, respondent burden,normative and comparative data), two criteria at level B (con-ceptual framework and item/instrument bias in terms of factoranalysis), and two criteria were at level C (availability of alter-nate forms and cultural adaptations). The widespread use of theSPRS, both by our own group as well as other clinical andresearch teams is evident, with its application in almost 40 fullpublications. We are now moving into new territory in extend-ing application of the SPRS to children and different neurolo-gical groups, and initial results, as reported in this article, arepromising.

Acknowledgements

Studies from which data were drawn for the present article werefunded by the Motor Accidents Authority of New South Walesand the New South Wales Cancer Institute.

Figure 4 SPRS Mean Domain Scores for High

Impairment across Neurological Populations.



29

Notes

1. For example, both McColl, Davies, Carlson, Johnston, andMinnes (2001) and Reistetter, Spencer, Trujillo, and Abreu(2005) found a correlation coefficient of r = 0.34 between theCommunity Integration Measure and the Community Integra-tion Questionnaire.2. For example, Willer, Rosenthal, Kreutzer, Gordon, andRempel (1993) reported a correlation coefficient of r = 0.25between social domains of the Community Integration Question-naire and the Craig Handicap Assessment and Reporting Tech-nique; Kuipers et al. (2004) found a correlation coefficient ofr = 0.41 between the respective productive/occupationaldomains of the Community Integration Questionnaire and SPRS.3. Factual background data on the three SPRS domains isrecorded using an additional 15 items, but this information isnot scored for the purposes of the scale.4. Tate et al. (2011) also suggest using the minimum differenceof 8.23 logit scores for Form B, even though we do not have thetest–retest data on the Form B sample (n = 150) to calculate theactual minimum difference. We consider that using the logitvalue of 8.23 will provide a close approximation for a reliablechange index for the following reasons: (1) the logit scoresfor Form A and Form B show very close correspondence; and(2) the test–retest correlation coefficient for the original psy-chometric studies on Forms A and B were high and identical(ICC = 0.90; Tate et al., 1999, 2004). Clearly, however, thissuggestion requires verification.

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Appendix: Item Description of the SPRS

Work and Leisure

1 Hours of work (or study) or type of work (or study)2 Work skills3 Number or type of leisure activities or interests4 Organising work and leisure activities

Interpersonal Relationships

5 Relationship with your partner or spouse6 Relationships with other family members (except partner)7 Relationships with other people outside family (such as

close friends, work mates, neighbours)8 Communication skills (i.e., talking with other people and

understanding what they say)

Living Skills

9 Social skills and behaviour in public10 Personal habits (e.g., care in cleanliness, dressing and

tidiness)11 Use of transport and travel around the community12 Accommodation (living situation)



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Documents

Sydney Psychosocial Reintegration Scale (SPRS-2): Meeting the Challenge of Measuring Participation in Neurological Conditions