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Journal of Psychiatric Research 47 (2013) 1403e1408

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Journal of Psychiatric Research

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Comparison of generic and disease-specific measures of quality of lifein first-episode psychosis

Laoise Renwick a,*, John Lyne a, Elizabeth Owens a, Brian O’ Donoghue a, Kevin Madigan a,Niall Turner a, Jonathan Drennan c, Ann Sheridan c, Anthony Kinsella a, Mary Clarke a,b,Eadbhard O’ Callaghan a,b,1

aDETECT Early Psychosis Service, Block 5, Blackrock Business Park, Blackrock, Dublin, Irelandb School of Medicine, University College Dublin, Irelandc School of Nursing, Midwifery & Health Systems, University College Dublin, Ireland

a r t i c l e i n f o

Article history:Received 18 May 2012Received in revised form28 April 2013Accepted 3 June 2013

Keywords:Quality of lifeFirst-episode psychosisGeneric measuresDisease-specific measures

* Corresponding author. Tel.: þ353 12791700; fax:E-mail address: Laoise.renwick@sjog.ie (L. Renwic

1 Deceased.

0022-3956/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.jpsychires.2013.06.001

a b s t r a c t

Background: Quality of life (QOL) is now recognised as an important measure of outcome that couldpotentially influence clinical decision-making for those with a first-episode psychosis (FEP). A number ofQOL instruments are available however; many differ in their conceptual orientation which may haveserious implications for the outcome of QOL studies, interpretation of findings and clinical utility. Weaimed to compare two commonly used tools representing both generic and disease-specific constructs toexamine whether both tools appraise the same underlying QOL traits and also whether disease-specifictools retain their psychometric properties when used in FEP groups.Methods: We assessed 159 consecutive individuals presenting with FEP in a defined catchment area withtwo commonly used QOL tools and examined the findings using the multi-trait multi-method matrix.Results: Similarly named domains of QOL between both tools (Psychological Wellbeing, Physical Health,Social Relations) showed good convergent validity using confirmatory factor analysis. However,discriminant validity was not established given that domains loading onto their indicated latent factorswere more strongly correlated with their non-corresponding latent factors.Conclusions: A major consideration in undertaking the present study was to assess the extent to whichthe outcome of QOL studies in FEP were valid and that systematic error did not provide another plausibleexplanation for findings. Establishing convergent validity demonstrates that either tool could be usedsatisfactorily to measure the QOL construct identified however; we did not establish discriminant val-idity. Doing so would have demonstrated that QOL domains are substantively different in that theycontain some unique piece of information determining clinical utility. These findings are important forour understanding of multi-dimensional models of QOL.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Quality of life (QOL) is now recognized as an important outcomemeasure, used in the evaluation of both pharmacological and psy-chosocial treatments during a first episode of psychosis (FEP)(Thorup et al., 2010; Ho et al., 2000). The QOL concept aspires totake a step beyond traditional indicators of outcome, such as hos-pital recidivism and symptom remission, by reflecting patient-levelconcerns about their well-being that are recognized as increasingly

þ353 12791799.k).

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important in clinical decision-making (Cotton et al., 2010; Mallaand Payne, 2005). Indeed, the widespread availability of QOL in-struments suggests they are popular in both research and in clinicaluse. Even still, disagreement among experts persists regarding auniversal definition of QOL, the perspective fromwhich it should beviewed and its constituent parts. Consequently, measuring clini-cally meaningful improvement in the quality of patient’s lives ishindered by the lack of consensus on a gold standard approach.

Instruments differ in their orientation towards subjective orobjective perspectives of QOL (Malla and Payne, 2005), whetherQOL comprises a unitary measure or multiple life domains (Awadand Voruganti, 2000) or whether it should reflect the life do-mains of generic populations or be specific to the influence ofspecific illnesses on the quality of people’s lives (Melle et al., 2005).

L. Renwick et al. / Journal of Psychiatric Research 47 (2013) 1403e14081404

As a result, it seems possible that the use of a particular QOLmeasure may have serious implications for the outcome and toolsoriented towards different perspectives may be non-equivalent orbiased (Shadish et al., 2002). Inaccurately estimating the quality ofpeople’s lives makes comparison between studies challenging andimportantly, has wider implications for the interpretation andapplication of findings in clinical practice.

Multi-trait multi-method matrices (MMTM) are routinely usedto evaluate construct validity and the extent to which reliablevariance on a measure is due to the method of assessment (Eidet al., 2009; Podsakoff et al., 2003; Campbell and Fiske, 1959).This method requires an examination of all possible correlationsbetween two or more traits that are measured by two or moremeasures (Schmitt, 1978). Ideally, tests will show that similar traitsthat are measured by different methods will be correlated stronglyand also that different traits measured by either method will notcorrelate significantly (Walters, 2009). The aim of the present studywas to establish and compare the psychometric properties of twofrequently used QOL tools in FEP, namely the WHOQOL-Bref (TheWhoqol Group, 1998) and the WQLI-Client Version (Becker et al.,1993). Although both instruments endorse the QOL construct asthe subjective appraisal of participant with multiple dimensions oflife, the former is a generic instrument and the latter is a diseasespecific instrument. In theory, there should be substantive differ-ences between each tool due to this conceptual distinction inaddition to similarities such as, the ability of multidimensionalmodels of QOL to derive clinically relevant results (Ruggeri et al.,2005; Sainfort et al., 1996).

A major problem noted with respect to analysing Campbell &Fiske’s criteria for convergent and discriminant validity is thesubjectivity in visually inspecting matrices to arrive at valid con-clusions (Schmitt, 1978). Thus, several analytic procedures havebeen utilized with confirmatory factor analysis believed to be mostadvantageous (Hadorn and Hays, 1991; Kenny and Kashy, 1992). Akey aspect of this study was to employ the criteria of Campbell &Fiske in examining the convergent and discriminant validity of QOLtools using confirmatory factor analytic techniques.

2. Methods

2.1. Subjects

Between February 2009 and April 2011, we assessed 159consecutive individuals presenting with FEP aged between 17 and65 years within a geographically defined catchment area (popula-tion approx. 375,000). Participants were excluded if they had priortreatment with anti-psychotic medication for more than 30 days,had an existing learning disability, or had psychosis deemed to bethe result of a general medical condition. Individuals satisfyingDSM-IV criteria for psychotic disorder diagnoses, primary psychoticdisorder (n ¼ 66) or primary mood disorder (n ¼ 20), who reportedon their QOL were included in this study.

2.2. Measures

Participants’ diagnoses were established using the StructuredClinical Interview for DSM-IV (Association, 2000) and comprisedthose with both affective and non-affective psychoses at firsttreatment for psychotic illness. Having a first episode of psychosisreferred to patients who were largely untreated within secondaryservices, however, there may be unsuccessful attempts at gainingentry or attempting to engage a person in treatment. Given this, ifthey had been prescribed pharmacological treatment for a psy-chotic illness by a primary care physician for more than 30 daysprior to presentation for treatment, they were deemed not suitable

for the study. Onset was denoted by the first noted psychoticsymptoms (reality distortion, disorganised speech) by eitherretrospective assessment with the participant, family or priorhealthcare records. Both pharmacological and psychosocial treat-ments were offered at inception into the clinical service denotingadequate treatment availability as the offset of psychosis. As such,we defined first episode psychosis as the first presentation withpsychotic symptoms to secondary mental health services where anadequate trial of pharmacological treatment has not been admin-istered prior to presentation. Given that there are several diffi-culties in establishing the boundaries of first-episode psychosis andin attempting to ensure that participants are relatively homoge-nous and representative of the sample from which they weredrawn, these operational definitions were utilised in conjunctionwith weekly consensus meetings chaired by the Professor of Psy-chiatry or designated equivalent. QOL was assessed using theWHOQOL-Bref and WQLI-Client which are described in the sectionbelow.

2.3. Description of QOL instruments

Both QOL instruments have been detailed elsewhere and havereported good reliability and validity (Skevington et al., 2004;Becker et al., 1993). See Table 1 for a descriptive comparison ofQOL definitions, constructs and operationalisation in bothinstruments.

2.4. Procedures

Data were collected as part of a larger observational studydetermining outcomes of an epidemiological cohort of participantswith FEP. The study raters (post-membership registrars in psychi-atry and clinical nurse specialists in psychosis) received training inthe use of instruments and were subject to inter-rater reliabilitytesting. Concordance in diagnosing patients with the SCID inter-viewwas minimum 90%. Assessments typically commenced within48 h of receipt of referral for assessment and treatment of FEP, andwere conducted sequentially with interviewer assessments first,then self-reported assessments. Self-report assessments wereadministered after a level of clinical stability had been achieved.Informed consent and ascent was obtained at entry into the studyand ethical approval was granted by the St John of God HospitallerServices Provincial Ethics Committee.

2.5. Statistical analysis

MMTM was used to test hypotheses regarding convergent anddiscriminant validity (Campbell and Fiske, 1959) by assessingvariance due to measurement method. As before, using thisapproach, the domains of QOL are considered traits and the in-struments are considered methods and when combined allow forconsideration of validity. Convergent validity, defined as the degreeof shared variance between indicators of latent constructs, isestablished by examining the validity diagonals and the columnsand rows of the heterotrait-heteromethod triangles. Correlations inthe validity diagonal should be significantly different from zero andshould be higher than the correlation coefficients in the columnsand rows of the corresponding triangles thus indicating a level ofagreement between rating similar concepts using differentmethods (Campbell and Fiske, 1959). In this study, the validity di-agonal refers to psychological well-being, physical health and socialrelations. Conversely, discriminant validity, defined as the extent towhich a construct is truly distinct from other constructs (Hair et al.,2010), is established by ascertaining correlation coefficients withinthe heterotrait-heteromethod triangles show a pattern of inter-

Table 1Descriptive comparison of QOL tools.

WQLI-Client version WHOQOL-Bref

QOL definition ‘a person’s sense of well-being that stems from satisfactionor dissatisfaction with the areas of life that are importantto him/her.’

‘individuals perceptions of their position in lifein the context of their culture and value systemsin which they live and in relation to their goals,expectations, standards and concerns’

Conceptualisation Complex, multi-dimensional construct incorporatingobjective indices and subjective evaluations of same

Subjective satisfaction of several life domainsthat are cross-culturally sensitive

Orientation Disease-specific GenericNo of domains and items 8 Domains 4 Domains

2 Overall QOL Domains(1 weighted for importance)

1 Overall QOL Domain (summation of QOL uniscaleand satisfaction with health status)

117 items 26 itemsDomains of QOL General Satisfaction

OccupationPsychological Well-beingPhysical HealthSymptoms/OutlookSocial RelationsMoneyActivities of Daily LivingGoal Attainment

Physical HealthPsychologicalSocial RelationshipsEnvironment

Completion time& type of questionnaire

20e30 min 10e15 minSelf-administered Self-administered

Frame of reference Four weeks Two weeksScoring Items within domains rescaled and aggregated

to produce domains scores (�3 to þ3, positivescoring indicating better QOL)

Mean score of items within each domain producesa domain score (0e100, higher scores indicate greatersatisfaction in domain being evaluated)

L. Renwick et al. / Journal of Psychiatric Research 47 (2013) 1403e1408 1405

relationships that are weaker than those for traits that areconsidered to be similar. The heterotrait-heteromethod trianglescontain all other QOL domains assessed by either instrument thatshould display a pattern of relationships that discriminate betweentraits (QOL domains). Univariate and bivariate data analyses wereconducted using PASW 20.

Confirmatory factor analysis was conducted to test thehypothesised structure of comparative QOL methods usingmaximum likelihood estimation in AMOS 20. The proposed modelfor examining MMTM, comprising latent variables representingboth methods and traits, resulted in an unidentified model or‘Heywood Case’ where the model failed to converge (Kenny andKashy, 1992; Blunch, 2013). A series of models were thereforehypothesised to examine three traits measured by two separatemethods (Eid et al., 2003). Model 1 to 3 were single-group MMTMdesigns with each method observed variable loading onto itsrespective latent factor constituting an attempt to establishconvergent validity e.g. psychological well-being in each tool wasan indicator (observed variable) of the latent variable psychologicalwell-being. Discriminant validity was determined by replications ofthis model with successive iterations loading the non-corresponding QOL domains onto each of the hypothesised traitsi.e. latent factors. The final model contained no variables that didnot correspond with the three latent QOL factors identified in bothtools. A necessity prior to model specification and identificationand to ensure an unbiased dataset (Schumacker and Lomax, 2004),missing values were imputed having established these data weremissing completely at random (MCAR X2 ¼ 104.48, df ¼ 102,p ¼ .413). The fully observed dataset in this instance accounted for88% of the data thus few imputations were necessary.

There are several goodness of fit indices available for eachmodelbut commonly reported indices include Chi-square (X2), Compar-ative Fit Index (CFI), Root Mean Square Error of Approximation(RMSEA) and Akaike Information Criterion (AIC), all of which pro-vide global fit measures (Schreiber et al., 2006). To ascertain thereliability and validity, the output also yields information onConstruct Reliability (CR) with a value above .7 indicating scalereliability. Estimates of Average Variance Extracted (AVE) and

Maximum and Average Shared Squared Variance (MVA & ASV) arecomputed to establish convergent and discriminant validity. Evi-dence of convergent validity is established when CR is greater thanAVE and the AVE is above .5, indicating that observed variableswithin a latent factor explain an acceptable average variance. Evi-dence of discriminant validity is established when both MSV andASV are less than AVE, indicating that the latent factor is explainedby hypothesised observed variables better than observed variableshypothesised to relate to another latent factor.

3. Results

At study entry, there were completed clinician interviews ofclinical status for 159 participants and a subgroup had completeinformation on QOL; WQLI (n ¼ 86) and WHOQOL-Bref (n ¼ 68).There were 66 participants with ratings of QOL on both generic anddisease-specific measures comprising the complete sample ana-lysed here and there were no differences in sample characteristicsbetween respondents and non-respondents (Table 2).

3.1. Construct reliability

As a measure of internal consistency, analysis provided twoseparate sets of reliability coefficients for QOL domains measuredby each method and latent constructs; Cronbach’sf in MMTM andCR in CFA. Reliabilities in the former set of estimates for theWHOQOL domain scores ranged from .76 to .89 and were between.73 and .85 for the WQLI subscales. Estimates above .7 indicate anacceptable level of internal consistency (Cronbach, 1951). The CRvalues for each of the latent constructs in the four CFA models areall within acceptable limits (Hair et al., 2010).

3.2. Convergent and discriminant validity

As before, convergent validity is derived from the AVE of theindicators of a specific construct. In Model 1 through 3, the AVE isbelow the recommended level of .5 for each of the latent constructswhen additional QOL domains are loaded onto the respective factor.

Table 4Goodness of fit indices of multi-method models of QOL.

Models Fit indices

X2 df p CFI RMSEA [90%CI] AIC

PW 94.54 51 .001 .90 .11 [.077e.148] 172.54PH 96.27 51 .001 .90 .12 [.079e.150] 174.27SR 95.65 51 .001 .90 .11 [.078e.149] 173.65ALL 8.60 6 .197 8.60 .08 [.000e.191] 50.60

Note 2: SR¼ Social Relations; PW¼ PsychologicalWell-being; PH¼ Physical Health;Model 1 Non-corresponding QOL domains loaded onto PW; Model 2 non-corresponding QOL domains loaded onto PH; Model 3 non-corresponding QOLdomains loaded onto SR.

Table 2Sample characteristics.

Mean (SD)

Age at presentation 35.1 (11.9)n, (%)

Marital statusNot married 49 (74)Married 17 (26)

EmployedYes 24 (36)No 42 (64)

DiagnosisSchizophrenia spectrum 50 (76)Depression with psychosis 7 (10)Mania with psychosis 9 (14)

Admission statusIn-patient 41 (62)Out-patient 25 (38)Involuntary admission 16 (39)Voluntary admission 25 (61)

Medication prescribed (n [ 63)Yes 51 (77)No 12 (18)

Administered > 2/52 (n [ 62)Yes 9 (14)No 53 (80)

Global assessment of functioning 32.7 (11.3)Duration of untreated psychosis (months) 26.6 (72.7)Length of unemployment (months, n [ 57) 57.9 (84.6)Positive symptoms (SAPS global score) 6.9 (2.8)Negative symptoms (SANS global score) 4.5 (4.4)Depressive symptoms (CDSS total score) 5.0 (6.0)

L. Renwick et al. / Journal of Psychiatric Research 47 (2013) 1403e14081406

Conversely, when the additional domains are excluded the AVE iswithin acceptable limits thus establishing convergent validity foreach of the traits measured by different methods (Tables 3 and 4).

As observed in the MMTM, the correlations between corre-sponding QOL domains measuring the same hypothesized traits arenot greater than correlations between non-corresponding traitsmeasured by any method. This indicates that discriminant validityhas not been established, a finding reproduced in confirmatoryfactor analysis. Table 5 details test statistics to establish discrimi-nant validity. As can be seen, in Models 1 through 4, the square rootof the AVE is less than one the absolute correlations with otherfactors indicating that domains loading onto their indicated latentfactors are more strongly correlated with non-corresponding latentfactors. In all Models the AVE is less than themaximum and averagesquare root of the shared variance indicating variance could befurther explained by domains not corresponding to their identified

Table 3Multimethod multitrait correlation matrix and Cronbach’s alpha reliability coefficients f

WHOQOL-Bref WQLI

PW PH SR EN GS

WHOQOL-Bref PW .898PH .751 .795SR .747 .678 .767EN .628 .607 .585 .862

WQLI-Client GS .647 .567 .760 .662 .851OC .521 .551 .472 .394 .453PW .653 .574 .535 .440 .326PH .429 .532 .395 .373 .272SR .630 .341 .709 .460 .606SX .626 .341 .470 .314 .414M .465 .527 .375 .524 .468ADL .494 .526 .376 .251 .245

Note 1: PW ¼ Psychological Well-being; PH ¼ Physical Health; SR ¼ Social Relations; ENDaily Living. Correlation coefficients in bold italics indicate stronger relationships for nobeen established.

latent factor. There is one exception in Model 4 where the averagesquared variance is not greater than the AVE but the maximumshared variance remains above the AVE thus discriminant validitycannot be established.

4. Discussion

A major consideration in undertaking the present study was toassess the extent to which the outcome of QOL studies in FEP maybe partially dependent upon the instrument that is chosen for thetask. As such, the study was conducted primarily to assess whetherany systematic measurement error provides a plausible alternativeexplanation for observed relationships in QOL studies in FEP todate. In particular, we aimed to compare two commonly used toolsrepresenting both generic and disease-specific constructs toexamine whether both tools appraise the same underlying QOLtraits and also whether disease-specific tools retain their psycho-metric properties when used in FEP groups (Melle et al., 2005). Asecondary aim was to establish whether scores on QOL domains ineither tool were substantively different indicating that, althoughrelated by comprising an element of the QOL construct, each wouldcontain some unique piece of information that would produceclinically useful data upon which to base clinical judgements.

On the first point, we examined the convergent validity of threecorresponding domains in both tools. As a precursory measure,examining the internal consistency of all QOL domains wasnecessary. With the exception of the occupation domain, co-efficients in all domains were above the advised .7 (Cronbach,1951)and were comparable with previously reported data (Diaz et al.,1999). Weaker internal consistency in the occupation domaincould possibly be explained by summing fewer items than otherdomains but could also be explained by divergence between

or the WHOQOL-Bref and the WQLI-Client.

-Client

OC PW PH SR SX M ADL

.588

.481 .756

.348 .493 .794

.345 .404 .312 .732

.381 .655 .393 .380 .740

.433 .298 .298 .298 .262 .770

.390 .373 .470 .272 .414 .269 797

¼ Environment; OC ¼ Occupation; SX ¼ Symptoms; M ¼Money; ADL ¼ Activities ofn-corresponding traits than corresponding traits thus discriminant validity has not

Table 5Convergent and discriminant validity statistics of multi-method models of QOL.

Models CR AVE MSV ASV

Model 1SR .838 .722 .861 .754PW .871 .466 .861 .845PH .726 .581 .828 .737Model 2SR .838 .722 .817 .811PW .807 .680 .906 .858PH .857 .434 .906 .862Model 3SR .873 .471 .867 .789PW .808 .682 .867 .818PH .732 .590 .769 .740Model 4SR .838 .722 .794 .704PW .810 .685 .794 .768PH .737 .597 .741 .678

Note 3: SR¼ Social Relations; PW¼ PsychologicalWell-being; PH¼ Physical Health;Model 1 Non-corresponding QOL domains loaded onto PW; Model 2 non-corresponding QOL domains loaded onto PH; Model 3 non-corresponding QOLdomains loaded onto SR.

L. Renwick et al. / Journal of Psychiatric Research 47 (2013) 1403e1408 1407

objective and subjective QOL (Melle et al., 2005) and patient’ssatisfaction being less consistent with their level of participation inactivities. Nonetheless, it can be deduced that there is substantiveevidence of reasonable convergent validity among each of the threeQOL domains with correspondingmeasures and that either methodcould be used to assess patients subjective QOL in these areas.

On the latter point, this study also aimed to establish discrimi-nant validity between multiple QOL domains in each tool. Indeed,multi-dimensional models of QOL have been accepted as necessary(Testa, 2000) and tested as clinically valid by ascertaining logicalclinical relationships between QOL domains and clinical variablesgiven their usefulness in planning interventions and assessing acomprehensive range of patient outcomes. However, demon-strating that QOL domains can, to a degree, discriminate betweeneach other is also crucial for establishing the clinical validity ofmulti-dimensional models of QOL (Katschnig et al., 2006). Thisstudy did not confirm that QOL domains in either tool were satis-factorily able to distinguish from each other. Specifically, somedomains displayed stronger associations with non-correspondingdomains than with their corresponding domains. For example,the social relations domains of the WHOQOL was strongly corre-lated with its counterpart in the WQLI but was more stronglycorrelated with the general satisfaction subscale of the WQLI thanits counterpart in the WQLI.

To our knowledge, this is the first study to assess method vari-ance in QOL assessments in FEP. Research has primarily focused onprogramme evaluation (Addington et al., 2003; Cotton et al., 2010;Larsen et al., 2011; Malla et al., 2001) and prospectively assessingthe determinants of QOL (Gorna et al., 2008; Browne et al., 2000;Malla et al., 2004; Whitty et al., 2004) and have produced incon-sistent findings (Renwick et al., 2012; Malla and Payne, 2005).Specifically, comparison across studies has been difficult due toinconsistent findings between studies, although within studies thefinding that general psychopathology has been correlatedwith QOLdomains without distinction has been replicated with more con-sistency (Malla and Payne, 2005; Renwick et al., 2011). Whilst in-consistencies and consistencies may largely be due tomethodological nuances between studies, the prospect of utilizingdifferent conceptualizations of QOL that are ill-equipped to provideclinically meaningful information must be considered a possibleexplanation for these findings.

In terms of advancing research on QOL in FEP, Campbell andFiske (1959) advise that examination of the MMTM will indicatewhether methods should be discarded or replaced or whether

concepts should be sharpened in definition to produce a moreclinically relevant method of measure a given concept. This isproposed when convergent validity has not been established,however, no similar recommendation has been made to deal withdiscriminant validity. Hammond et al. (1986) suggest an approachto assessing criterion-related clinical importance, as an extension ofthe Campbell & Fiske model, to combine convergent and discrim-inant validity in MMTMwith evaluation of differential prediction ofclinical variables thus further establishing clinical validity. Thiswould extend this work and assist in establishing much-needed,clinically valid conceptualizations of QOL in the FEP group toadequately assess the psychosocial impact of FEP on QOL.

There are obvious limitations to this study, namely, high attri-tion rates and the use of cross-sectional data which limits the in-ferences that can be made. Nonetheless, the results of this studyindicate that the usefulness and clinical value of multi-dimensionalassessments of QOL for FEP merits more detailed consideration.Whilst not detracting from the importance of assessing QOL in FEP,instruments used during the acute phase of the illness may be illequipped to provide precise information about multiple domains ofQOL for targeted interventions. A further consideration is thebenefits of QOL assessment for programme evaluation and clinicaldecision-making in the absence of concurrence on the domainsthat constitute QOL and an adequate concept that is fit for purpose.

Contributors

Laoise Renwick is the first author who initiated the study ofquality of life in firat episode psychosis and was responsible writingthe manuscript. Brian O’Donoghue, Elizabeth Owens, John Lyne,Niall Turner and Kevin Madigan were responsible for data collec-tion, reviewing themanuscript and contributing to ideas within themanuscript. Anthony Kinsella provided statistical advice on theresearch. Jonathan Drennan and Ann Sheridan supervised theresearch on quality of life in first-episode psychosis and MaryClarke is responsible for the design of the DETECT project research.Eadbhard O’Callaghan was the founder of the DETECT project andsupervised the research in DETECT. All authors have contributed toand approved the final manuscript.

Statement of funding

The early psychosis service is funded by the Health Service Exec-utive and formerly St JohnofGodHospitaller Services. Thefirst authoris funded by a Nursing and Midwifery fellowship from the HealthResearch Board of Ireland. The authors have no ties with industry.

Conflict of interest

The authors have not ties with industry.

Acknowledgements

The authors thank all of the people, both clients and clinicians,who participated in this study for generously giving their time.

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