Objective

This study assesses the psychometric properties of Ward's seven-subtest short form (SF) for WAIS-IV in a sample of adults with schizophrenia (SZ) and schizoaffective disorder.

Method

Seventy patients diagnosed with schizophrenia or schizoaffective disorder were administered the full version of the WAIS-IV. Four different versions of the Ward's SF were then calculated. The subtests used were: Similarities, Digit Span, Arithmetic, Information, Coding, Picture Completion, and Block Design (BD version) or Matrix Reasoning (MR version). Prorated and regression-based formulae were assessed for each version.

Results

The actual and estimated factorial indexes reflected the typical pattern observed in schizophrenia. The four SFs correlated significantly with their full-version counterparts, but the Perceptual Reasoning Index (PRI) correlated below the acceptance threshold for all four versions. The regression-derived estimates showed larger differences compared to the full form. The four forms revealed comparable but generally low clinical category agreement rates for factor indexes. All SFs showed an acceptable reliability, but they were not correlated with clinical outcomes.

Conclusions

The WAIS-IV SF offers a good estimate of WAIS-IV intelligence quotient, which is consistent with previous results. Although the overall scores are comparable between the four versions, the prorated forms provided a better estimation of almost all indexes. MR can be used as an alternative for BD without substantially changing the psychometric properties of the SF. However, we recommend a cautious use of these abbreviated forms when it is necessary to estimate the factor index scores, especially PRI, and Processing Speed Index.

Introduction

Mental, neurological, and substance-use (MNS) disorders constitute 13% of the global disease burden, surpassing both cardiovascular disease and cancer (Collins et al., 2011; Wittchen et al., 2011). MNS reduces the ability to adapt to a variety of real-life contexts. Wechsler defined intelligence as “the aggregate or global capacity of the individual to act purposefully, to think rationally and to deal effectively with his environment” (1939). A careful assessment of the abilities that enable the subject to adapt to his or her environment has been increasingly developed in the last few decades. As intellectual ability is no longer considered a single entity, but rather, a multifactorial construct covering multiple cognitive areas, the full assessment of cognitive functioning requires time and the selection of adapted tools.

Cognition largely contributes to functional outcome in terms of professional insertion, community functioning, ability to acquire new skills and to manage everyday activities (Green & Harvey, 2014). In patients with schizophrenia (SZ), the Intellectual Quotient (IQ) has been shown a more sensitive and reliable predictor of functional outcome than specific cognitive measures (Leeson, Barnes, Hutton, Ron, & Joyce, 2009). Full-Scale IQ (FSIQ) is strongly associated with educational attainment, occupational level, and school achievement (Wechsler, 2008). An association between premorbid impaired IQ and the subsequent onset of psychosis has also been described (David, Malmberg, Brandt, Allebeck, & Lewis, 1997) which supports the neurodevelopmental contribution to schizophrenia. Cognitive functioning was suggested to be more accurate than neurobiology in differentiating SZ patients from healthy controls (Heinrichs, 2005). Systematic assessment of IQ has, therefore, been recommended in SZ by some authors (Harrison-Read, 2008).

The Wechsler Adult Intelligence Scale (WAIS) is one of the most commonly used cognitive batteries designed to assess subject's IQ, a proxy of general cognitive functioning. Beyond the traditional dichotomic “verbal versus performance” intelligence distinction (Wechsler, 2008), the current version of the WAIS (WAIS-IV) is based on four major components: the Verbal Comprehension Index (VCI), the Perceptual Reasoning Index (PRI), the Working Memory Index (WMI) and the Processing Speed Index (PSI). FSIQ and General Ability Index (GAI) can be generated from these scores. Overall, the WAIS-IV includes 10 core subtests and 5 supplemental subtests. A typical pattern of performance among patients with SZ can be observed across the WAIS subscales. Tasks involving processing speed display the largest group differences, followed by working memory, and perceptual organization. The least impaired factor is verbal comprehension (Michel et al., 2013).

Although in-depth assessment can certainly increase the understanding a of patient's cognitive profile and is a prerequisite for cognitive rehabilitation, in the context of efforts to decrease reimbursed assessment time for clinicians and researchers, the use of well-established abbreviated forms of the Wechsler scale may be helpful. The time savings could leave room for a more specific neuropsychological assessment. The mean administration time to obtain the FSIQ with the 4th edition (Wechsler, 2008) is estimated around 67 min, which is 13 min shorter than that of the WAIS-III (Sattler & Ryan, 2009). However, according to Ryan et al. (1998), the administration time may be increased by 50%–80% in patients suffering from neurological conditions. Schizophrenic patients may experience similar difficulties due to broad cognitive impairment (Heinrichs & Zakzanis, 1998), motivational problems, and low processing speed leading to fatigability.

To this end, different short forms (SFs) of the Wechsler Scales have been developed. One of the most widely used was published by Ward (1990). This seven-subtest SF initially conceived for the Wechsler Adult Intelligence Scale-Revised (WAIS-R) includes Block Design (BD), Similarities (SI), Digit Span (DS), Arithmetic (AR), Information (IN), Coding (CD), and Picture Completion (PC) subtests. Each test is administered in original form according to the manual's instructions. The scaled scores are then weighted: Verbal IQ (VIQ) raw = 2 ×  (IN + SI) + (DS + AR); Performance IQ (PIQ) raw = 2 × (PC + BD) + (CD); FSIQ raw is the sum of the VIQ raw and the PIQ raw. IQ scores are obtained from the usual conversion tables from the manual.

The administration time for this abbreviated form is estimated to be 46 min (Ryan et al., 1998). This SF offered a good estimation of FSIQ, VIQ and PIQ composite factors, as well as an excellent reliability (Axelrod, Woodard, Schretlen, & Benedict, 1996). Pilgrim, Meyers, Bayless, and Whetstone (1999) reported equivalent psychometric properties of the SF of the WAIS-III. The correlations found were 0.95 for PIQ, 0.97 for VIQ, and 0.98 for FSIQ. FSIQ and VIQ maintained good reliability with the full-version scores in both 2nd and 3rd editions (Axelrod & Paolo, 1998; Axelrod, Ryan, & Ward, 2001). The psychometric properties of this SF are conserved in other populations, such as traumatic brain injury patients (Guilmette, Dabrowski, Kennedy, & Gnys, 1999). These authors underlined the superiority of this version over other SF based on an absolute mean of differences between predicted and effective scores.

Ryan and Ward (1999) published an alternative form that substitutes MR for BD. The MR form (7MRsf, as opposed to 7BDsf for “BD” version) was less time consuming, had a good reliability, and showed a high correlation with the initial form. Moreover, the 7MRsf seemed to slightly improve the accuracy of PIQ (Axelrod et al., 2001).

Despite brief administration time and independent standardization of shorter instruments, such as WASI (Wechsler, 1999), the estimation of intellectual functioning reduced to very few scores provides less information about specific cognitive abilities and may lead to a lower validity of the estimation (Wymer, Rayls, & Wagner, 2003). More detailed information about underlying cognitive domains is often relevant in the context of the neuropsychological evaluation.

Ward's SF was studied in a sample of 304 psychiatric inpatients (Benedict, Schretlen, & Bobholz, 1992). The results showed smaller errors in predicted IQ compared to two other SF and a better predictive power for the Ward's SF. Another study conducted in a mixed psychiatric sample confirmed the superiority of the Ward SF over shorter instruments in terms of reliability and validity (Abraham, Axelrod, & Paolo, 1997).

Allen et al. (1997) assessed nine different SF in patients diagnosed with SZ. Compared to other SFs (Kaufman, Ishikuma, & Kaufman-Packer, 1991), the Ward's seven-subtest SF showed the lowest misclassification rate, lower difference from the full-version IQ and the best correlation with the FSIQ. The authors advocate the use of Ward SF in schizophrenia when assessment time is not limited.

Later, Ryan, Weilage, and Spaulding (1999) examined the accuracy of the SF for predicting IQs of 73 SZ inpatients. Results indicated that 93% of the estimated FSIQs were within ±5 points of their actual scores. The authors suggested using the SF with schizophrenic patients when only general estimates of intellectual functioning are required which is consistent with previous findings (Iverson, Guirguis, & Green, 1998).

More recently, based on WAIS-IV, Meyers, Zellinger, Kockler, Wagner, and Miller (2013) examined 7BDsf properties in a sample of 102 subjects with different neurological, psychiatric, and somatic conditions. The authors compared two different methods to estimate FSIQ and index scores based on Ward's seven subtests: (i) the original method based on prorated scores and (ii) a regression-based method. Both methods were stable and adequately predictive of their full-version counterparts. The FSIQ was best predicted by the prorated scores method which is also easier to use in clinical practice. If index scores are also needed, the prorated score was more accurate for the VCI and nearly as accurate for the PRI. The PSI prediction showed better accuracy with the weighted regression. To date, no studies have been conducted to assess Ward's SF of the latest edition of the Wechsler scale in schizophrenia.

The objective of this study was, therefore, to assess the properties of Ward's seven-subtest SF for WAIS-IV in a sample of patients diagnosed with SZ. We examined four different SF calculation algorithms to determine the most suitable one.

Methods

Study Sample

Seventy outpatients with a diagnosis of schizophrenia or schizoaffective disorder, according to DSM-5 (American Psychiatric Association, 2013) criteria were consecutively assessed in a university-affiliated hospital (Cognitive and Social Rehabilitation Centre, Psychiatry Department, Hôpitaux Universitaires Henri Mondor, Assistance Publique des Hôpitaux de Paris (AP-HP)). The collected data were a part of a regular care process. A psychiatric interview was conducted with every participant by two experienced psychiatrists to confirm the diagnosis of schizophrenia or schizoaffective disorder and to ensure that patients were in clinical remission according to the remission criteria of Andreasen et al. (2014). All subjects were French-native speakers. Patients with a history of central nervous system disorder (including epilepsy, brain injury, and neurological disorders), uncorrected perceptive disorders affecting the understanding of oral and written instructions, a substance or alcohol disorder in the 6 months prior to participation, an electroconvulsive therapy treatment during the 12 months prior to participation, or a current depressive or manic episode were not included in the study. Socio-demographic data were collected. The sample characteristics are described in Table 1 and show no significant differences between patients with SZ and schizoaffective disorder.

Table 1.

Social, demographic, and cognitive characteristics of the study sample

 Whole sample Schizophrenia Schizoaffective disorder Sig. (2-sided) 
N 70 49 (70%) 21 (30%)  
Sex, % male 56 (80%) 38 (77.6%) 18 (85.7%) p = .43 
Age, mean (SD) 31.0 (9.6) 31.0 (10.0) 30.9 (9.0) p = .89 
Handedness, % right handed 63 (90%) 46 (93.9%) 17 (81.0%) p = .23 
Education level    p = .44 
 Education class 1 17 (24%) 14 (28.6%) 3 (14.3%)  
 Education class 2 21 (30%) 14 (28.6%) 7 (33.3%)  
 Education class 3 32 (46%) 21 (42.9%) 11 (52.4%)  
Illness duration, years, mean (SD) 7.5 (5.9) 7.43 (6.7) 7.76 (3.4) p = .14 
Functional outcome*, mean (SD) 45.81 (16.4) 47.73 (17.1) 41.26 (13.8) p = .15 
WAIS-IV, mean (SD)    
 FSIQ 81.1 (15.5) 83.0 (15.3) 76.7 (15.4) p = .12 
   VCI 88.9 (17.1) 90.0 (15.4) 86.3 (20.8) p = .48 
 PRI 84.3 (15.4) 86.5 (15.7) 79.1 (13.8) p = .07 
 WMI 83.9 (14.1) 85.7 (14.4) 79.7 (12.6) p = .10 
 PSI 80.9 (14.3) 81.9 (14.8) 78.5 (13.0) p = .37 
 Whole sample Schizophrenia Schizoaffective disorder Sig. (2-sided) 
N 70 49 (70%) 21 (30%)  
Sex, % male 56 (80%) 38 (77.6%) 18 (85.7%) p = .43 
Age, mean (SD) 31.0 (9.6) 31.0 (10.0) 30.9 (9.0) p = .89 
Handedness, % right handed 63 (90%) 46 (93.9%) 17 (81.0%) p = .23 
Education level    p = .44 
 Education class 1 17 (24%) 14 (28.6%) 3 (14.3%)  
 Education class 2 21 (30%) 14 (28.6%) 7 (33.3%)  
 Education class 3 32 (46%) 21 (42.9%) 11 (52.4%)  
Illness duration, years, mean (SD) 7.5 (5.9) 7.43 (6.7) 7.76 (3.4) p = .14 
Functional outcome*, mean (SD) 45.81 (16.4) 47.73 (17.1) 41.26 (13.8) p = .15 
WAIS-IV, mean (SD)    
 FSIQ 81.1 (15.5) 83.0 (15.3) 76.7 (15.4) p = .12 
   VCI 88.9 (17.1) 90.0 (15.4) 86.3 (20.8) p = .48 
 PRI 84.3 (15.4) 86.5 (15.7) 79.1 (13.8) p = .07 
 WMI 83.9 (14.1) 85.7 (14.4) 79.7 (12.6) p = .10 
 PSI 80.9 (14.3) 81.9 (14.8) 78.5 (13.0) p = .37 

*Total score on Social Autonomy Scale. WAIS-IV, Wechsler Adult Intelligence Scale-IV; FSIQ, Full Scale Intellectual Quotient; VCI, Verbal Comprehension Index; PRI, Perceptive Reasoning Index; WMI, Working Memory Index; PSI, Processing Speed Index.

Ethical Agreement

This study involved data from regular care, no written consent was therefore required. Each patient was informed about a possible use of their data for research purpose and their ability to oppose this use at any time in which case patient's data were excluded from the analysis. A non-opposition form was signed by all participants. All data were collected and made anonymous. The study was carried out in accordance with ethical principles for medical research involving humans (WMA, Declaration of Helsinki).

Measurements

The neuropsychological assessment was conducted by a trained neuropsychologist and included WAIS–4th edition. All participants received a full version of WAIS-IV including all core subtests and the optional picture completion subtest that is necessary to calculate the SF.

Functional outcome was assessed by a trained psychiatric nurse using the Social Autonomy Scale (SAS) (Leguay et al., 1998). This hetero-assessment instrument investigates the self-sufficiency level of the persons who suffer from chronic psychiatric conditions and measures subjects abilities to face up to tangible problems in everyday life.

Data Analysis

Based on the full WAIS-IV, four index scores (VCI, PRI, WMI, and PSI) and FSIQ composite score were generated.

Descriptive statistics were computed for the demographic and neuropsychological measures (Table 1). Educational level was defined as the highest completed school grade and recorded as a trichotomous variable: (i) no formal education or uncompleted primary, completed primary, and uncompleted lower secondary; (ii) uncompleted secondary or any other case between (i) and (iii); (iii) at least some secondary education completed (Pichot, Lebeaux, Penhouët, & Simon, 1993).

The data were examined for normal distribution (skewness, kurtosis, and outliers analysis). A preliminary analysis of the standard FSIQ and factor indexes was performed in order to compare the WAIS-IV profile in SZ patients with normative data issued from standardization subsample (Wechsler, 2008) using one sample t-tests.

Ward's SF estimated indexes were calculated for each participant, using (i) prorated scores method and (ii) regression-based method, for both ‘BD’ (7BDsf) (Meyers et al., 2013) and “Matrix Reasoning” (7MRsf) (Meyers, personal communication) versions. Table 2 summarizes the formulae used to calculate the four SF. The prorated formulae were used to obtain the raw indexes that were then transformed according to conversion tables from the manual. The regression-based formulae directly provided the estimated values.

Table 2.

SF calculation algorithms using prorated scores and regression formulae*

 7BDsf 7MRsf 
Prorated formulae 
FSIQ ((IN + SI + BD + PC + DS + AR + CD) × 10)/7 ((IN + SI + MR + PC + DS + AR + CD) × 10)/7 
VCI ((IN + SI) × 3)/2 ((IN + SI) ×3)/2 
PRI ((BD + PC) × 3)/2 ((MR + PC) × 3)/2 
WMI DS + AR DS + AR 
PSI CD × 2 CD × 2 
Regression-based formulae 
FSIQ 0.941(SI) + 1.144(BD) + 1.148(IN) + 0.859(DS) + 0.997(CD) + 0.877(AR) + 0.868(PC) + 32.148 1.102(SI) + 0.928(MR) + 1.156(IN) + 0.875(DS) + 1.084(CD) + 0.74(AR) + 0.995(PC) + 31.709 
VCI 2.937(SI) + 2.835(IN) + 43.53 2.989(SI) + 2.782(IN) + 43.195 
PRI 2.794(BD) + 0.778(AR) + 1.913(PC) + 45.279 3.014(MR) + 2.218(PC) + 47.415 
WMI 2.835(DS) + 2.783(AR) + 43.7 2.793(AR) + 2.819(DS) + 43.712 
PSI 0.921(BD) + 4.063(CD) + 49.402 4.691(CD) + 53.325 
 7BDsf 7MRsf 
Prorated formulae 
FSIQ ((IN + SI + BD + PC + DS + AR + CD) × 10)/7 ((IN + SI + MR + PC + DS + AR + CD) × 10)/7 
VCI ((IN + SI) × 3)/2 ((IN + SI) ×3)/2 
PRI ((BD + PC) × 3)/2 ((MR + PC) × 3)/2 
WMI DS + AR DS + AR 
PSI CD × 2 CD × 2 
Regression-based formulae 
FSIQ 0.941(SI) + 1.144(BD) + 1.148(IN) + 0.859(DS) + 0.997(CD) + 0.877(AR) + 0.868(PC) + 32.148 1.102(SI) + 0.928(MR) + 1.156(IN) + 0.875(DS) + 1.084(CD) + 0.74(AR) + 0.995(PC) + 31.709 
VCI 2.937(SI) + 2.835(IN) + 43.53 2.989(SI) + 2.782(IN) + 43.195 
PRI 2.794(BD) + 0.778(AR) + 1.913(PC) + 45.279 3.014(MR) + 2.218(PC) + 47.415 
WMI 2.835(DS) + 2.783(AR) + 43.7 2.793(AR) + 2.819(DS) + 43.712 
PSI 0.921(BD) + 4.063(CD) + 49.402 4.691(CD) + 53.325 

*7BDsf, Ward's seven-subtest SF (BD version); 7MRsf, Ward's seven-subtest SF (MR version); FSIQ, Full-Scale Intelligence Quotient; VCI, Verbal Comprehension Index; PRI, Perceptual Reasoning Index; WMI, Working Memory Index; PSI, Processing Speed Index; IN, Information; SI, Similarities; BD,  Block Design; PC, Picture Completion; DS, Digit Span; AR, Arithmetic; CD, Coding; MR, Matrix Reasoning.

The four SF formulae were evaluated following nine different criteria found in the literature (Donders & Axlerod, 2002; Iverson, Myers, & Adams, 1997; Meyers et al., 2013; Ryan et al., 1999): (i) correlation coefficients, (ii) mean comparison, (iii) difference scores, (iv) category agreement, (v) band of error analysis, (vi) clinical accuracy, (vii) time savings, (viii) internal consistency reliability, and (ix) criterion validity.

The SF scores were compared to the full-version scores through correlation analysis and comparison of means. As the comparisons between SF and full-form indexes were derived from the same administration of the WAIS-IV, which may lead to inflated Spearman correlations, we designated correlations above 0.90 as sufficiently accurate for clinical practice (Iverson et al., 1998).

Dependent-sample t-tests were run to assess differences between SF and full-form scores. In case of normality violation, additional Wilcoxon tests were performed to confirm the result. The magnitude of the difference was estimated using Cohen's d in order to determine whether the difference between the actual and the estimated scores was clinically relevant. Cohen's d for within-subjects studies was corrected by the correlation between the means (Morris & DeShon, 2002). Mean score differences (Δ = Full version – Short version) were provided.

Next, each composite score (FSIQ, VCI, PRI, WMI, and PSI) was sorted on the basis of Wechsler's intelligence classification (manual) into seven groups: Extremely low, Borderline, Low Average, Average, High Average, Superior, Very superior, in order to perform a category agreement analysis (Iverson et al., 1997). We set an 80% agreement threshold to consider a SF clinically acceptable.

A band of error analysis consisting of identification of cases within 2 SEM of the full WAIS-IV score was then conducted. According to the WAIS-IV technical manual, the SEM values are as follows: FSIQ = 2.56, VCI = 3.6, PRI = 3.48, WMI = 3.94, PSI = 5.26 (Manual, French edition, page 35, Table 4.3). We calculated the percentage of subjects scoring within 2 SEMs on the four SF compared to their actual scores. The criterion was met if at least 80% of cases fell in the same diagnostic category. We then determined the percentage of subjects who met either clinical classification or band of error criteria. If both criteria were violated at the same time, the SF was considered clinically inaccurate (Iverson et al., 1997).

For information purpose, we estimated time savings for each SF, based on previous WAIS-III research (Ryan et al., 1998). To the best of our knowledge, no studies assessed the WAIS-IV separate subtests administration time in detail.

Finally, reliability was measured to evaluate the internal consistency of each form. Along with Donders and Axlerod (2002), we set a minimum reliability threshold of 0.90. Criterion validity assessed the ability of each SF to predict functional outcome (Social Autonomy Scale) and illness duration.

The “best methods” were discussed following the above-mentioned decision criteria.

All statistical analyses were performed with SPSS (IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp.). All statistical tests were two-tailed. Given that multiple tests were computed, familywise error was adjusted by applying a Bonferroni correction to the alpha level (i.e., 4 forms × 5 indexes: α = 0.05/(4 × 5)). As such, the revised alpha was set at 0.003.

Results

Compared to the standardization sample (data issued from the manual), SZ patients obtained significantly worse scores on all measures (t-test, p ≤ 0.0001). The average FSIQ was 81.1 (SD = 15.5). VCI mean score was the highest factor score (88.9 ± 17.1), while PSI was the lowest (80.9 ± 14.3). The PRI and WMI scores were, respectively, 84.3 ± 15.4 and 83.9 ± 14.1. The patterns of performance on the different composite scores are illustrated in Fig. 1. The mean comparison did not reveal sex-related differences of the WAIS-IV scores (independent samples t-test, p > .05).

Fig. 1.

Composite scores estimated by the four Short forms and the full Wechsler Adult Intelligence Scale-IV in patients with schizophrenia.

Fig. 1.

Composite scores estimated by the four Short forms and the full Wechsler Adult Intelligence Scale-IV in patients with schizophrenia.

Means and SD for the estimated IQ and Index scores following the four SF formulae are presented in Table 3.

Table 3.

Estimated IQ and Index scores (N = 70)*

 7BDsf PRO 7MRsf PRO 7BDsf REG 7MRsf REG 
FSIQ 81.39 (±15.00) 81.46 (±14.97) 82.92 (±14.38) 83.08 (±14.49) 
VCI 89.76 (±17.23) 89.76 (±17.23) 91.08 (±17.04) 90.79 (±17.07) 
PRI 85.81 (±16.21) 86.04 (±15.18) 86.55 (±14.21) 87.42 (±13.29) 
WMI 83.91 (±14.05) 83.91 (±14.05) 84.24 (±13.82) 84.20 (±13.81) 
PSI 77.07 (±14.98) 77.07 (±14.98) 80.22 (±12.29) 81.00 (±12.56) 
 7BDsf PRO 7MRsf PRO 7BDsf REG 7MRsf REG 
FSIQ 81.39 (±15.00) 81.46 (±14.97) 82.92 (±14.38) 83.08 (±14.49) 
VCI 89.76 (±17.23) 89.76 (±17.23) 91.08 (±17.04) 90.79 (±17.07) 
PRI 85.81 (±16.21) 86.04 (±15.18) 86.55 (±14.21) 87.42 (±13.29) 
WMI 83.91 (±14.05) 83.91 (±14.05) 84.24 (±13.82) 84.20 (±13.81) 
PSI 77.07 (±14.98) 77.07 (±14.98) 80.22 (±12.29) 81.00 (±12.56) 

*7BDsf, Ward's seven-subtest SF (BD version); 7MRsf, Ward's seven-subtest SF (MR version); PRO, prorated scores version; REG, regression-based version; FSIQ, Full-Scale Intelligence Quotient; VCI, Verbal Comprehension Index; PRI, Perceptual Reasoning Index; WMI, Working Memory Index; PSI, Processing Speed Index.

The comparison of the four SF is detailed in Table 4. The Spearman correlation coefficients with the full versions were high and comparable across the four SF. Except PRI ranging from 0.84 to 0.89, all other coefficients were above the 0.90 threshold (all p ≤ 0.0001, two-tailed). When analyzed separately in the two diagnostic groups, PRI correlation with the full-form counterparts was systematically lower in patients with schizoaffective disorder (Spearman's rho ranging from 0.67 to 0.76) compared to SZ patients (Spearman's rho ranging from 0.85 to 0.90). Other index correlations were comparable in both diagnostic groups.

Table 4.

Comparison of the four SF with the full-version counterparts in patients with schizophrenia (N = 70)*

 7BDsf PRO 7MRsf PRO 7BDsf REG 7MRsf REG 
I—Spearman correlation coefficients (all p < .001, 2-tailed) 
FSIQ 0.98 0.97 0.98 0.97 
VCI 0.97 0.97 0.97 1.00 
PRI 0.85 0.84 0.89 0.85 
WMI 1.00 1.00 1.00 1.00 
PSI 0.92 0.92 0.93 0.92 
II—Mean comparison (paired samples t-tests, 2-tailed, Cohen's d
FSIQ t(69) = −0.662, p = .510 (d = 0.09) t(69) = −0.776, p = .440 (= 0.10) t(69) = −4.650, p < .001 (d = 0.58) t(69) = −4.498, p < .001 (d = 0.57) 
VCI t(69) = −1.565, p = .122 (d = 0.20) t(69) = −1.565, p = .122 (d = 0.20) t(69) = −3.978, p < .001 (= 0.51) t(69) = −3.453, p = .001 (d = 0.44) 
PRI t(69) = −1.456, p = .150 (d = 0.18) t(69) = −1.673, p = .099 (d = 0.20) t(69) = −2.621, = .011 (d = 0.32) t(69) = −3.259, p = .002 (d = 0.40) 
WMI — — t(69) = −6.826, p < .001 (d = 0.39) t(69) = −6.002, p < .001 (d = 0.34) 
PSI t(69) = 4.904, p < .001 (d = −0.66) t(69) = 4.904, p < .001 (d = −0.66) t(69) = 0.921, p = .360 (d = −0.14) t(69) = −0.197, p = .844 (d = 0.02) 
III—Difference scores compared to the full-version counterparts (mean, SD
FSIQ −0.26 (±3.25) −0.33 (±3.64) −1.80 (±3.24) −1.96 (±3.64) 
VCI 0.87 (±4.66) −0.87 (±4.66) −2.19 (±4.61) −1.90 (±4.61) 
PRI −1.53 (±8.78) −1.76 (±8.79) −2.26 (±7.21) −3.14 (±8.06) 
WMI 0.00 (±0.00) 0.00 (±0.00) −3.32 (±0.39) −0.29 (±0.40) 
PSI 3.79 (±6.46) 3.80 (±6.46) 0.64 (±5.83) −0.14 (±6.15) 
IV—IQ category agreement (% cases falling in the same diagnostic category as in the full version) 
FSIQ 81% 83% 80% 77% 
VCI 73% 73% 71% 71% 
PRI 57% 54% 59% 54% 
WMI 100% 100% 100% 99% 
PSI 61% 63% 64% 64% 
V—Band of error (% cases falling within 2 SEMs from the actual IQ) 
FSIQ 91% 86% 81% 76% 
VCI 89% 89% 81% 81% 
PRI 57% 51% 59% 50% 
WMI 100% 100% 100% 100% 
PSI 84% 84% 93% 90% 
VI—Clinical accuracy (% cases with either 4 or 5 met) 
FSIQ 94% 91% 91% 89% 
VCI 90% 90% 86% 87% 
PRI 70% 69% 71% 64% 
WMI 100% 100% 100% 100% 
PSI 90% 91% 94% 96% 
VII—Estimated time savings 
 49% 54% 49% 54% 
VIII—Internal consistency reliability 
 r = 0.90 r = 0.90 r = 0.93 r = 0.91 
IX—Criterion validity (Spearman's rho, p
Clinical remission −0.09 (p = .48) −0.09 (p = .48) −0.08 (p = .54) −0.07 (p = .60) 
Illness duration 0.11 (p = .37) 0.11 (p = .39) 0.10 (p = .43) 0.10 (p = .43) 
 7BDsf PRO 7MRsf PRO 7BDsf REG 7MRsf REG 
I—Spearman correlation coefficients (all p < .001, 2-tailed) 
FSIQ 0.98 0.97 0.98 0.97 
VCI 0.97 0.97 0.97 1.00 
PRI 0.85 0.84 0.89 0.85 
WMI 1.00 1.00 1.00 1.00 
PSI 0.92 0.92 0.93 0.92 
II—Mean comparison (paired samples t-tests, 2-tailed, Cohen's d
FSIQ t(69) = −0.662, p = .510 (d = 0.09) t(69) = −0.776, p = .440 (= 0.10) t(69) = −4.650, p < .001 (d = 0.58) t(69) = −4.498, p < .001 (d = 0.57) 
VCI t(69) = −1.565, p = .122 (d = 0.20) t(69) = −1.565, p = .122 (d = 0.20) t(69) = −3.978, p < .001 (= 0.51) t(69) = −3.453, p = .001 (d = 0.44) 
PRI t(69) = −1.456, p = .150 (d = 0.18) t(69) = −1.673, p = .099 (d = 0.20) t(69) = −2.621, = .011 (d = 0.32) t(69) = −3.259, p = .002 (d = 0.40) 
WMI — — t(69) = −6.826, p < .001 (d = 0.39) t(69) = −6.002, p < .001 (d = 0.34) 
PSI t(69) = 4.904, p < .001 (d = −0.66) t(69) = 4.904, p < .001 (d = −0.66) t(69) = 0.921, p = .360 (d = −0.14) t(69) = −0.197, p = .844 (d = 0.02) 
III—Difference scores compared to the full-version counterparts (mean, SD
FSIQ −0.26 (±3.25) −0.33 (±3.64) −1.80 (±3.24) −1.96 (±3.64) 
VCI 0.87 (±4.66) −0.87 (±4.66) −2.19 (±4.61) −1.90 (±4.61) 
PRI −1.53 (±8.78) −1.76 (±8.79) −2.26 (±7.21) −3.14 (±8.06) 
WMI 0.00 (±0.00) 0.00 (±0.00) −3.32 (±0.39) −0.29 (±0.40) 
PSI 3.79 (±6.46) 3.80 (±6.46) 0.64 (±5.83) −0.14 (±6.15) 
IV—IQ category agreement (% cases falling in the same diagnostic category as in the full version) 
FSIQ 81% 83% 80% 77% 
VCI 73% 73% 71% 71% 
PRI 57% 54% 59% 54% 
WMI 100% 100% 100% 99% 
PSI 61% 63% 64% 64% 
V—Band of error (% cases falling within 2 SEMs from the actual IQ) 
FSIQ 91% 86% 81% 76% 
VCI 89% 89% 81% 81% 
PRI 57% 51% 59% 50% 
WMI 100% 100% 100% 100% 
PSI 84% 84% 93% 90% 
VI—Clinical accuracy (% cases with either 4 or 5 met) 
FSIQ 94% 91% 91% 89% 
VCI 90% 90% 86% 87% 
PRI 70% 69% 71% 64% 
WMI 100% 100% 100% 100% 
PSI 90% 91% 94% 96% 
VII—Estimated time savings 
 49% 54% 49% 54% 
VIII—Internal consistency reliability 
 r = 0.90 r = 0.90 r = 0.93 r = 0.91 
IX—Criterion validity (Spearman's rho, p
Clinical remission −0.09 (p = .48) −0.09 (p = .48) −0.08 (p = .54) −0.07 (p = .60) 
Illness duration 0.11 (p = .37) 0.11 (p = .39) 0.10 (p = .43) 0.10 (p = .43) 

*7BDsf, Ward's seven-subtest SF (BD version); 7MRsf, Ward's seven-subtest SF (MR version); PRO, prorated scores version; REG, regression-based version; FSIQ, Full-Scale Intelligence Quotient; VCI, Verbal Comprehension Index; PRI, Perceptual Reasoning Index; WMI, Working Memory Index; PSI, Processing Speed Index.

Analyses of the mean differences between SF and original scores showed that some SF scores, especially when derived from the regression-based versions, differed from the full-version scores (Cohen's d for dependent samples were “negligible” to “small” for prorated forms and mostly “medium” for the regression-based forms, see Table 4). Of note, WMI was not included in the mean comparison for the prorated versions, given the fact that all the subtests necessary to calculate the full form are included in the SF. The scores are thus identical to the full-version counterparts.

Category agreement was comparable for all four SF, the percentage of cases falling into the same diagnostic category (compared to the full form) was systematically lower for PRI (54%–59%), PSI (61%–64%), and VCI (71–73%) indexes, all methods taken together. None of the SF showed an acceptable agreement on these dimensions. The general agreement ranged from 77% to 83% for the FSIQ.

The band of error analysis showed generally higher misclassification rates for PRI index (all forms confounded). Only a half of the patients fell within the 2 SEM band for PRI when MR forms were used. 7MRsf REG was the least accurate of the four SF. The two BD forms showed slightly better accuracy for this criterion. Combining the two last decision criteria did not reveal any superiority among the four methods, but again PRI index showed the least accurate scores.

When analyzed separately, PSI, and PRI indexes show noticeable differences in category agreement across diagnostic groups. Although preliminary and based on a small sample, the results show a very low category agreement (43%–48%) in patients with schizoaffective disorder.

An additional analysis of agreement rates was performed. The sample was split into four quartiles following initial scores obtained with the full version of the WAIS-IV. FSIQ and WMI agreement rates did not differ across the groups. Instead, we observed differential agreement rates relative to the initial IQ on other indexes. PRI showed better agreement rates in subjects with higher IQ. PSI showed better agreement rates in subjects with lower IQ. VCI agreement rates were higher in persons within the percentiles 25 and 75; instead, more extreme values of VCI obtained slightly lower clinical agreement.

The estimated time savings were slightly higher for the ‘MR’ versions (54% vs. 49%).

Criterion validity analysis did not reveal any significant correlation between WAIS-IV variables (both full and SF) and functional outcome and illness duration. Internal consistency estimates were assessed using Spearman–Brown corrected split-half or coefficient alpha methods for each form. The results were satisfactory and are presented in the Table 4. Cronbach's alpha/split-half reliability coefficients for subtests in the WAIS-IV ranged from 0.90 to 0.93.

Discussion

We assessed seven-subtest SF of the WAIS-IV in a sample of SZ patients. We studied four different versions of the Ward's  SF (Ward, 1990): BD (7BDsf) and MR (7MRsf) forms, both calculated following the prorated scores method (PRO) and regression-based method (REG).

WAIS-IV Score Pattern in Schizophrenia

The full WAIS-IV factor index scores presented the typical pattern of performance in SZ (Michel et al., 2013). This pattern was maintained in each of the four SF. This confirms a relative preservation of verbal comprehension and perceptual abilities, along with a more pronounced working memory and processing speed impairment in SZ. As expected, all scores were found significantly lower compared to the standardization sample (Michel et al., 2013).

Clinical decision rules should be clearly stated to reliably predict SF accuracy and help clinicians choose the appropriate form. For this reason, we analyzed the four SF algorithms following nine decision criteria found in literature with a priori set acceptance thresholds.

Criterion 1: Correlations

In terms of correlation with the full version, the four SF were fairly comparable. All correlation coefficients ranged from 0.84 to 1.0 Only PRI did not meet the acceptance criterion (r ≥ 0.90) but the lower correlations were mainly observed in patients with schizoaffective disorder. While PRI scores showed no statistical difference between the diagnostic groups, there was a slight trend toward lower scores in schizoaffective patients (t-test, 2-tailed, p = .07). This is surprising in the light of previous studies showing more pronounced cognitive impairment in patients with SZ compared to schizoaffective disorder (Bora, Yucel, & Pantelis, 2009). Future studies are needed to explore this dimension in detail. For these reasons, we recommend a cautious use of the SF when estimating PRI.

Criteria 2 & 3: Mean Scores Comparison

Our results show that the regression-based SF tend to slightly overestimate the FSIQ, VCI, PRI, and WMI, while PSI is underestimated by the prorated methods (effect size ranged from small to medium) and thus led us to consider both regression-based forms less suitable when used with patients with schizophrenia. Meyer's regression formulae were issued from a heterogeneous clinical sample and their use should be careful when assessing SZ patients.

Although regression approach is widely used in literature, it is highly sample-related. Consequently, the regression equations issued from a previous study (Meyers et al., 2013, Meyers, personal communication) should be used with caution when assessing patients with SZ or schizoaffective disorder. To address this question, a linear regression was calculated using the age-scaled scores from the seven subtests to predict the FSIQ and the index scores within this diagnostic group (Table 5). Further research is therefore needed to assess the reliability of these algorithms in an independent sample of SZ patients.

Table 5.

Regression equations for the FSIQ and index scores derived from the sample of patients with schizophrenia and schizoaffective disorder*

 7BDsf 7MRsf 
FSIQ 1.071(SI) + 1.201(BD) + 1.273(IN) + 1.644(DS) + 1.185(CD) + 0.52(AR) + 0.46(PC) + 26.705 1.021(SI) + 1.027(MR) + 1.106(IN) + 1.349(DS) + 1.219(CD) + 0.87(AR) + 0.671(PC) + 27.441 
VCI 2.909(SI) + 2.655(IN) + 42.973 2.909(SI) + 2.655(IN) + 42.973 
PRI 3.343(BD) + 1.459(DS) + 0.809(PC) + 42.455 3.175(MR) + 1.237(PC) + 1.079(AR) + 43.07 
WMI 2.866(DS) + 2.844(AR) + 42.719 2.866(DS) + 2.844(AR) + 42.719 
PSI 1.02(DS) + 4.46(CD) + 47.086 1.02(DS) + 4.46(CD) + 47.086 
 7BDsf 7MRsf 
FSIQ 1.071(SI) + 1.201(BD) + 1.273(IN) + 1.644(DS) + 1.185(CD) + 0.52(AR) + 0.46(PC) + 26.705 1.021(SI) + 1.027(MR) + 1.106(IN) + 1.349(DS) + 1.219(CD) + 0.87(AR) + 0.671(PC) + 27.441 
VCI 2.909(SI) + 2.655(IN) + 42.973 2.909(SI) + 2.655(IN) + 42.973 
PRI 3.343(BD) + 1.459(DS) + 0.809(PC) + 42.455 3.175(MR) + 1.237(PC) + 1.079(AR) + 43.07 
WMI 2.866(DS) + 2.844(AR) + 42.719 2.866(DS) + 2.844(AR) + 42.719 
PSI 1.02(DS) + 4.46(CD) + 47.086 1.02(DS) + 4.46(CD) + 47.086 

*7BDsf, Ward's seven-subtest SF (BD version); 7MRsf, Ward's seven-subtest SF (MR version); FSIQ, Full-Scale Intelligence Quotient; VCI, Verbal Comprehension Index; PRI, Perceptual Reasoning Index; WMI, Working Memory Index; PSI, Processing Speed Index; IN, Information; SI, Similarities; BD, Block Design; PC, Picture Completion; DS, Digit Span; AR, Arithmetic; CD, Coding; MR, Matrix Reasoning.

Criteria 4, 5 & 6: Category Agreement, Band of Error Analysis, and Clinical Accuracy

The four forms revealed comparable but generally low category agreement rates. We found a noticeable change in clinical classification for PRI, PSI, and VCI scores across all methods. The band of error analysis showed inadequate estimates of PRI and more generally the MR forms. PRI indexes showed even lower agreement rates in schizoaffective patients, while PSI was more heterogeneous in SZ patients.

One of the sources of PRI bias is certainly the fact that the latest edition of the WAIS does not require the Picture Completion subtest to calculate the original scores. If these were calculated using Picture Completion substitution (e.g., replacing the Visual Puzzle subtest, which is not included in either of the SF), the correlation coefficients and mean comparison would logically reveal a closer association between the full and SF, especially on the PRI index, which regularly shows lower rates of association with the full version on the different decision criteria. An additional analysis (using full-scale IQ recalculated with this optional subtest), might be conducted to confirm this point, but this is beyond the scope of this article. Future studies should investigate the utility of an alternative SF to replace this optional subtest with one of the core subtests. However, Michel et al. (2013) showed that WAIS-IV subtests that best differentiate SZ patients from controls (p = .001) include Picture Completion (along with Symbol search, CD, Cancellation, and Comprehension subtests).

However, in the three out of four forms, PSI was estimated based on one subtest only. This index generally tends to be the least reliable, for this reason using subtest dyads to provide estimates has been advocated (Christensen, Girard, & Bagby, 2007; Donders & Axlerod, 2002). This may explain the observed lower accuracy and led us to question the clinical advantage of these forms when estimating processing speed.

Both category agreement and band of error analysis show a slightly better fit for prorated versions as far as FSIQ and VCI are concerned. PSI tends to be better predicted by the regression forms. On this point, our results are comparable with those published by Meyers et al., (2013).

Finally, category agreement tends to be higher in subjects with higher IQ for PRI, lower IQ for PSI and the IQ between 25th and 75th percentiles for VCI.

Overall, the low category agreement raises question of the ability of the Ward's SF to estimate the factor indexes and this point should be taken into account while interpreting clinical data. While WMI is measured in its full form, and VCI offers agreement rates in the low 70s, the only factor with at least 80% of clinical agreement was FSIQ. The results seem even more compromised in patients with schizoaffective disorder.

Criterion 7: Time Savings

We found no substantial difference between the “MR” and “BD” versions which is consistent with Ryan and Ward (1999). The clinician may thus want to select the appropriate form to match clinical hypotheses and requirements. The “MR” versions offer slightly better time savings and an additional abstract reasoning assessment. Visuo-construction will be better assessed with the BD version. Of note, when administered WAIS-IV, SZ patients tend to differ from the control group on BD, while this difference is not statistically significant on MR test (Michel et al., 2013).

Criteria 8 & 9: Internal Consistency and Criterion Validity

The four SF showed a good reliability. Instead, neither the full WAIS-IV nor any of the SF estimates was related to meaningful outcomes in terms of everyday autonomy or illness duration.

Limits

The limitations of our study include an unbalanced sex-ratio with a majority of male participants. This could be explained by the classical difference in severity of the disease between men and women (Aleman, Kahn, & Selten, 2003). Our study was conducted on a consecutive sample of patients recruited in a day care centre, where male patients are overrepresented due to a relatively higher severity of psychotic symptoms and a larger number of hospitalizations. Some studies suggest that patients with schizophrenia display gender differences on cognitive variables. Men tend to suffer from more pronounced cognitive impairments (Sota & Heinrichs, 2003). This was not supported by our findings. None of the WAIS-IV index scores differed according to sex and thus we considered this confound negligible.

Second, low category agreement across the factor indexes (except WMI measured in its full form) questions the clinical utility of the Ward's SF when estimating cognitive performance in a more detailed way. To address this issue, we suggested alternative regression equations built on our sample. These require further assessment within an independent sample of SZ subjects.

Third, another possible source of lower factor estimates and biased validity estimates may be related to suboptimal effort. Motivational factors can play a role in QI assessment, especially in patients with schizophrenia. Poor mental effort might be considered a core symptom of schizophrenia, representing an executive, monitoring, or motivational problem (Gorissen, Sanz, & Schmand, 2005). While SFs delivered independently can sometimes yield better estimates of performance as they are potentially less susceptible to fatigue, in the current case, with SF scores derived from the full administration, motivation may not explain differences between SF and full-scale scores, but it may contribute to error variance and decrease reliability, which in turn affects validity estimates.

Fourth, this study raises concern about the ability of SF scales to predict outcome measures. Neither SF estimates nor full WAIS-IV IQ assessment did show any significant correlation with functional outcome and illness duration. This finding underlines the question of ecological validity of WAIS-IV as a complement to clinical assessment in schizophrenia.

Finally, this study was carried out on a French speaking sample which may potentially affect the generalizability of our conclusions. Further research is needed to draw more general conclusions about the clinical advantages of the present SF.

Strengths

This study offers clear strengths: (i) a relatively large and homogenous sample of clinically stable SZ or schizoaffective patients, (ii) the parallel analysis of four different versions derived from the original SF, and (iii) the use of nine different comparison criteria.

Conclusion

In conclusion, our results provide strong support for using the Ward seven-subtest SF (Ward, 1990) of the WAIS-IV in patients with SZ or schizoaffective disorders when FSIQ estimate is needed. If factor indexes are required, the Ward's SF seems less appropriate and clinical conclusions should be drawn with caution, given the low clinical agreement rates. We recommend the use of the prorated forms in SZ given their better psychometric properties. Our study did not support the use of Ward's SF when estimating PRI in schizophrenia or schizoaffective disorder.

Funding

No funding sources had any role in study design, in the collection, analysis, and interpretation of data, in the writing of the report, or in the decision to submit the paper for publication.

Acknowledgements

We thank Mary Beth Spitznagel from Research and Editing Consulting Program (RECP) for her assistance in editing this manuscript. We thank Monik Graziani for her logistic assistance.

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