A Haptic Nonverbal Cognitive Test for Children and Adolescents With Visual Impairment

Abstract

Introduction: The objective of the current study was to design and pilot-test a nonverbal intelligence test for children and adolescents with visual impairment (i.e., blindness and low vision) aged 10 to 16 years. Method: A three-dimensional haptic matrix test of nonverbal cognitive abilities (3-DHMT-CA), initially developed for adults with visual impairment, was adapted and administered to 25 juveniles with severe low vision or blindness and 25 sighted peers. The test consisted of 22 tactual matrices with a missing element, and juveniles were asked to understand the logical scheme underlying each matrix and to complete it. Convergent validity was assessed in the sighted group with the Standard Progressive Matrices. Divergent validity was measured with the Verbal Comprehension Index (VCI) and the Working Memory Index (WMI) of the Italian version of the Wechsler Intelligence Scale for Children–Fourth Edition. Between-group differences were analyzed with Student’s t-test and ANOVA. Results: Results show a high correlation with the convergent measure (with the Standard Progressive Matrices), and the moderate correlations with divergent measures (VCI and WMI). Between-group differences showed significantly higher scores for sighted peers than juveniles with visual impairment at 3-DHMT-CA, and non-significant differences at VCI and WMI. Discussion: This haptic nonverbal cognitive test showed good psychometric properties, but it needs to be validated in a larger sample with a qualitative analysis of solution strategies because juveniles with visual impairment seem to use different verbal and working memory strategies. Implications for Practitioners: The 3-DHMT-CA and the haptic two-hands modality seem to be suitable to test nonverbal cognitive abilities in juveniles with visual impairment. Practitioners should focus on empowering verbal and working memory abilities, since they may affect nonverbal cognitive abilities as well.

Keywords

visual impairment blindness children adolescents cognitive test haptic test assessment

Cognitive assessment is very important to guide rehabilitation, professional orientation, and educational programming for people with disabilities, including visual impairment (i.e., blindness and low vision). According to Leung (1993), examiners should gather information from many sources and methods in order to achieve a comprehensive cognitive evaluation in accordance with the R.I.O.T. model (review records, interview key informants, observe students, and administer tests). Unfortunately, most of the available cognitive tests rely heavily on vision (e.g., Wechsler Scales, Standard Progressive Matrices, Kohs Block Design Test, and Wisconsin Card Sorting Test) and, therefore, they are inaccessible to people with visual impairment. There are two different approaches to solve this problem: to use standard cognitive tests, omitting visual items (Miller & Skillman, 2003); or to offer a vision-independent cognitive test. The first option allows easy administration by clinicians because these tests are popular and widely distributed and for the most part they refer to the Cattell-Horn-Carroll (CHC) theory of cognitive abilities, which is the most comprehensive and empirically supported psychometric theory of the structure of cognitive abilities to date (Flanagan & Harrison, 2012). The CHC model includes several broad cognitive abilities such as: crystallized intelligence (Gc), fluid intelligence (Gf), quantitative knowledge (Gq), reading and writing skills (Grw), short-term memory (Gsm), processing speed (Gs), visual processing (Gv), long-term storage and recall (Glr), auditory processing (Ga), and decision speed or reaction time (Gt). The CHC theory–based cross-battery evaluation approach can be used to assess these broad abilities, but for the population with visual impairment, only verbal or tactile tests may be considered. For example, the fluid reasoning (Gf in CHC theory) can be measured using solely auditory means with RIAS-2 Guess What and Verbal Reasoning subtest, the WJ-IV ECAD Verbal Analogies subtest, the DAS-II Verbal Similarities subtest, the CELF-5 Word Classes and Semantic Relationships subtest, the WISC-V Arithmetic, D-KEFS Word Context Test, and KABC-II NU Riddles subtest. The short-term memory (Gsm) or long-term storage and recall (Glr) or auditory processing (Ga), but of verbal type can be measured, for example, with the WAIS-IV and WISC-IV Digit Span and Letter-Number Sequencing subtest, the DAS-II Recall of Digits Backwards or the WJ-IV Verbal Attention, Numbers Reversed, and Object-Number Sequencing subtest, the NEPSY-II Word List Interference, the TAPS-4 Number Memory Reversed, and the WRAML2 Verbal Working Memory.

However, by examining only verbal subtests, we lose information relative to nonverbal fluid intelligence (Gf) that refers to mental operations that an individual uses when faced with a relatively novel task that cannot be performed automatically. Inductive and deductive reasoning are generally considered to be the hallmark narrow ability indicators of Gf. They are skills that are typically solved in tasks such as Raven's Matrices, the WISC-IV and WAIS-IV Matrix reasoning and Figure Weight. Therefore, nonverbal cognitive abilities are left out of assessment altogether (Atkins et al., 2011; Morash & McKerracher, 2017).

Some research has been conducted to develop adjusted cognitive measures and there are some useful psychometric scales available to measure cognitive functioning, and especially nonverbal abilities, for adults with visual impairment. Most of them are haptic adaptations of tests that were originally developed and standardized for sighted people and later adapted for people with visual impairment. Nelson and colleagues (2002) developed the Cognitive Test for the Blind, which investigates both verbal and nonverbal abilities by means of 10 subtests adapted from the Wechsler Adult Intelligence Scales. Another important test is the Kohs Block Design Test (Kohs, 1923), which consists of arranging 3D textured blocks in accordance with a given pattern. Several adaptations of this test for individuals with visual impairment were made (Reid, 2002; Suinn et al., 1966; Thiebaut et al., 2002). Beauvais and colleagues (2004) developed a tactile version of the Wisconsin Card Sorting Test (Grant & Berg, 1948) to assess executive functions. Each card has a different 2D shape and texture and the examinee is asked to find rules for matching the cards with given key cards. Other tests are derived from the Standard Progressive Matrices (Raven, 1941): Raven’s Tactual Progressive Matrices (Rich & Anderson, 1965) and the Three-Dimensional Haptic Matrix Test of Non-Verbal Abilities (3-DHM, Miller et al., 2007). The latter (3-DHM) was pilot-tested on 21 adults with visual impairment. The matrix provided a range of tasks similar to those of the Cognitive Test for the Blind but according to participants it was more pleasant and less frustrating to interact with. Due to such positive feedback, and the small size of the pilot group, it would be interesting to evaluate on a larger group whether the 3-DHM could be a suitable test for individuals with visual impairment.

The common point of all the mentioned tests is the use of haptic modality instead of vision (Mazella et al., 2014). Haptic modality plays an important role in the cognitive development of individuals with visual impairment. More specifically, most cognitive tests, based on haptic modality, use 3D objects rather than 2D. According to Klatzky and colleagues (1993), when using only haptic modality, it is easier to identify 3D objects than 2D. In addition, some haptic tests have to be realized with a single index finger or one hand only, and others require both hands. Morash and colleagues (2014) found that adults with visual impairment have a perceptual advantage using both hands rather than one finger or one hand in haptic tasks.

Most of the mentioned studies originated in the United States, or were standardized in the English language, with no transcultural standardization. Furthermore, many of them did not include any control group with sighted peers and, therefore, data on differences between two populations are missing (Mazella et al., 2014).

Also, there are only few studies on cognitive testing in children and adolescents with visual impairment. It is difficult to find a large and representative sample of such population, because visual impairment is a rare and heterogeneous condition that is often associated with other disabilities. Some tests were available in the past, but normative data are now obsolete (Dekker, 1993; Newland, 1979; Paknikar, 1981). More recently, two haptic batteries were developed to assess children’s cognitive and perceptual abilities in processing information. The haptic test battery (Ballesteros et al., 2005) presents the examinee with 2D and 3D shapes; the Haptic-2D (Mazella et al., 2016) only 2D raised lines and shapes. In many subtests, the examinee is asked to discriminate between haptic stimuli, distinguishing different types of fabric, materials, objects, or shapes. Such an assessment may depend on the inter-correlations between perceptual haptic abilities and cognitive abilities, possibly over-focusing on haptic discrimination.

To summarize, scientific literature on cognitive assessment of adults with visual impairment is more developed than for children and adolescents (Cassar & Lucchese, 2016; Mazella et al., 2014) and can be considered the base for further research aiming at reducing the gap.

The purpose of the current study is to provide a pilot-test of a new cognitive nonverbal scale for children and adolescents with visual impairment. One haptic matrix test is proposed, in which the examinee is asked to understand the logical pattern underlying different haptic stimuli (3D objects with easily distinguishable shapes and sizes) using both hands. Results are expected to depend less on the perceptual haptic abilities and more on the cognitive abilities. A sighted control group is provided to study differences between subjects with or without visual impairment in nonverbal reasoning through haptic modality. In accordance with Miller et al. (2007), performances are expected to be related to visual experience: examinees who are able to generate a visual imagery of the matrix (i.e., participants who are sighted or with less severe low vision) are expected to score higher than others. Our aim is to evaluate the psychometric properties of this new test. It is expected to have a high reliability and to correlate more with same measures of cognitive nonverbal abilities and less with different measures of verbal and working memory abilities.

Method

Participants and Procedures

Twenty-five (16 boys and 9 girls) Italian participants with visual impairment aged 10–16 years, and 25 sighted control participants took part in the study. The experimental group was recruited from rehabilitation centers for people with visual impairment. The subjects of the control group were taken from scout groups and were matched for age, gender, and school experience. The experimental group comprised 13 individuals with blindness and 12 with severe vision impairment, according to the International Classification of Disease 11^th Revision categorization system (World Health Organization, 2018), without other physical or psychological disabilities as reported by the psychologists working at the center. Vision impairment was congenital for 19 children and adolescents, and for the others (6) it was acquired during infancy. Participants from both groups were blindfolded (unless they were totally blind) and never saw the instruments until the end of the test. Assent was given by subjects, and their parents provided informed written consent. The study was conducted according to the International Ethical Guidelines and Declaration of Helsinki.

Instruments

Three-Dimensional Haptic Matrix Test for Children and Adolescents (3-DHMT-CA)

The 3-DHMT-CA is a test of nonverbal reasoning that was originally developed for adults with vision impairment (Miller et al., 2007), and was adapted for children and adolescents in the present study. Test materials consist of wooden boards and beads. Two boards were prepared, sized 30 cm × 30 cm, with vertical rods 10 cm high, with 7 mm diameter. One board featured 4 rods, the other featured 9 rods, both organized in a square grid (2 × 2 and 3 × 3, respectively). The beads were prepared in two shapes and two sizes: cubic (with sides 1.5 cm and 2.5 cm) and spherical (with diameters 1.3 cm and 1.8 cm). All beads were drilled through, in order to be easily stacked on the rods.

The test was simplified with respect to Miller et al. (2007) in order to be more suitable for children and adolescents: only two sizes of cubes were available instead of three, and the matrices were generally simpler. Different beads were clearly distinguishable (big or small, cubes or spheres): the purpose was to assess cognitive nonverbal abilities, rather than perceptual abilities. According to McGrew and Flanagan (1998) and to Carpenter and colleagues (1990), matrix tasks are highly correlated with general intelligence and are good indicators of executive functioning, abstract reasoning, and induction.

The test is composed of 22 items, all original work of the authors (see Figure 1), and it takes 40 minutes to administer. In each item, the examinee was asked to solve a logical puzzle: he or she was presented with a matrix, consisting of beads with different shapes and sizes stacked on rods. The last element of the matrix was missing: the last rod had no beads. A compartmented box was beside the board; each compartment contained beads of the same shape and size.

The examinee had to identify the logical pattern represented by the matrix, then complete it by picking up the appropriate beads from the box and inserting them on the last rod. Items were designed in accordance with the logic underlying the Standard Progressive Matrices (Raven, 1941): repetition of a pattern, change of size, inversion of a pattern, removal of an element, addition of elements, and rotation of elements. Items were organized in pairs requiring the same kind of reasoning. The “odd form” of the test was the set of the odd-numbered items; the “even form” was the set of the even-numbered items. Each element of the even form thus requires the same kind of reasoning than the corresponding item from odd form.

Some help could be provided to the subject if he or she was not able to solve the task on his or her own. The help consisted of saying: "Place your hands on two rods of the same line. Could you tell the difference between the two? Please, try to repeat the same logic on the last rod." The score was from 0 to 2, in which 0 was assigned to those who had failed to perform the task, 1 to those who had succeeded only with some help, and 2 to those who had succeeded autonomously without help.

Wechsler Intelligence Scale for Children- Fourth Edition (WISC-IV)

The verbal subtest of the Italian version of the Wechsler Intelligence Scale for Children–Fourth Edition (WISC-IV, Wechsler, 2003; Wechsler et al., 2012) were administered to both groups. The score of analogies, vocabulary, and comprehension subtests are necessary for the determination of the Verbal Comprehension Index (VCI), while the score of the Digit Span and Letter-Number Sequencing subtests are necessary for the computation of the Working Memory Index (WMI).

Standard Progressive Matrices

The Standard Progressive Matrices (Raven, 1941; Picone et al., 2016) were administered to the matched paired control-group, in order to measure convergent validity. The test consists of 60 visual matrices with a missing element and the examinee was asked to understand the logical scheme underlying each matrix and to complete it.

Data Analysis

The reliability of 3-DHMT-CA was evaluated using split-half method: the Pearson correlation between the scorings obtained at the odd and the even items, by all participants with or without visual impairment, were corrected using the Spearman–Brown prophecy formula to estimate the full test reliability.

A Student’s t-test was applied to verify the significance level of the means difference between the odd form and the even form performances of all subjects. Convergent and divergent validities were assessed using Pearson’s correlation coefficients. Student’s t-tests and ANOVA tests were applied in order to analyze differences between groups.

Results

According to guidelines of Nunnally and Bernstein (1994), the split-half reliability between the odd and even item of the 3-DHMT-CA was very high (r = .96, p < 0.001).

In order to study the 3DHMT-CA convergent validity, Standard Progressive Matrices were administered to the control group. Raw scores were considered, not converted to age equivalent, as the 3DHMT-CA scores are also not age equivalent. Convergent validity, as calculated in this way, was high for each 3DHMT-CA score (see Table 1). In particular, the lowest correlation was with the even-numbered form (r = .53, p < 0.001), which could be due to a training effect of the odd-numbered form.

Table 1.

Convergent and Divergent Validity of the 3DHMT-CA: Correlations with Standard Progressive Matrices, Verbal Comprehension Index, and Working Memory Index.

	3-DHMT-CA
	All subjects			Control group			Experimental group
	Odd form	Even form	Tot Odd+Even	Odd form	Even form	Tot Odd+Even	Odd form	Even form	Tot Odd+Even
SPM				.704***	.5354**	.641**
VCI	.531***	.463***	.511***	−.131	.031	−.043	.678***	.596**	.651***
WMI	.361*	.229	.304*	−.195	−.121	−.162	.616**	.463*	.555**

Note. 3-DHMT-CA: Tridimensional Haptic Matrix Test for Children and Adolescents; SPM: Standard Progressive Matrices; VCI: Verbal Comprehension Index; WMI: Working Memory Index.*** p< .001; **p< .01; *p < .05

Correlations on divergent validity are reported in Table 1. A moderate correlation between 3-DHMT-CA and two verbal measures of WISC-IV (Verbal Comprehension Index and Working Memory Index) emerged. However, considering only the control group, these correlations were not significant. Correlations were still significant only considering the experimental group.

In addition, children and adolescents with visual impairment obtained significantly lower scores than their peers in the 3-DHMT-CA with a large effect size (Cohen’s d = .77) (see Table 2).

Table 2.

Differences Between Experimental Group and Control Group in the 3-DHMT-CA.

	Control group (n = 25)	Experimental group (n = 25)
3-DHMT-CA	mean (sd)	mean (sd)	t (48)	p	Cohen’s d
Odd form	17.00 (1.98)	14.84 (3.56)	2.65	< .05	0.75
Even form	18.04 (2.46)	16.00 (3.06)	2.60	< .05	0.74
Total	35.04 (4.23)	30.84 (6.5)	2.71	< .001	0.77

Note. 3-DHMT-CA: Tridimensional Haptic Matrix Test for Children and Adolescents.

For the interpretation of Cohen’s d there is: small effect if d = .20; medium effect if d = .50; and large effect if d = .80.

We also analyzed separately the subjects with blindness versus those with severe low vision versus those without low vision (see Table 3) and we found that the ANOVA showed a significant difference only between juveniles with blindness and their sighted peers (p < 0.05) with a large effect size (η² = .15).

Table 3.

Differences Between Subjects With Blindness, Those With Severe Low Vision, and Sighted Peers in the 3-DHMT-CA.

3-DHMT-CA	Sighted peers (n = 25)	Subjects with severe low vision (n = 12)	Subjects with blindness (n = 13)				Sighted vs. low vision df b = 1 df w = 35	Sighted vs.blind df b =1 df w = 36	Low vision vs. blind df b = 1df w = 23
3-DHMT-CA	mean (sd)	mean (sd)	mean (sd)	F	p	η²	Sighted vs. low vision df b = 1 df w = 35	Sighted vs.blind df b =1 df w = 36	Low vision vs. blind df b = 1df w = 23
Odd form	17.00 (1.98)	15.42 (3.03)	14.31 (4.03)	3.98	.025	.14	p = .372d = .67	p = .026d = .95	p = 1.000d = .31
Even form	18.04 (2.46)	16.67 (2.90)	15.38 (3.18)	4.08	.023	.15	p = .491d = .53	p = .022d = .98	p = .757d = .42
Total	35.04 (4.23)	32.08 (5.79)	29.69 (7.12)	4.28	.020	.15	p = .392d = .62	p = .019d = 1.00	p = .841d = .37

Note. 3-DHMT-CA: Three Dimensional Haptic Matrix Test for Children and Adolescents; For interpretation of η² there is: small effect if η² = .01; moderate effect if η² = .06; and large effect if η² = .14.

For the interpretation of Cohen’s d there is: small effect if d = .20; medium effect if d = .50; and large effect if d = .80.

Concerning WISC-IV indices, no significant differences were found between the experimental group and the control-group (see Table 4). However, a small effect (see Cohen’s d) emerged in the Verbal Comprehension Index.

Table 4.

Differences Between Experimental Group and Control Group in the VCI and in the WMI.

	Group	mean (sd)	t(48)	p	Cohen’s d
VCI	Experimental	115.8 (21.3)	1.63	.111	.46
VCI	Control	123.3 (11.3)	1.63	.111	.46
WMI	Experimental	111.3 (26.4)	.45	.652	.13
WMI	Control	108.5 (15.9)	.45	.652	.13

Note. VCI: Verbal Comprehension Index; WMI: Working Memory Index.

For the interpretation of Cohen’s d there is: small effect if d = .20; medium effect if d = .50; and large effect if d = .80.

Discussion and Conclusion

The aim of the present study was to design and pilot-test a new, nonverbal cognitive test for juveniles with vision impairment aged 10 to 16 years. This study has several strengths. It is the first tridimensional haptic matrix test of nonverbal cognitive abilities for children and adolescents with visual impairment, it showed good psychometric properties of reliability, convergent and divergent validity, and it properly assesses nonverbal cognitive abilities. The haptic modality relying on the use of two hands is confirmed to be reliable and suitable to evaluate nonverbal reasoning abilities in individuals with vision impairment. It is interesting that sighted peers may not be disadvantaged using this modality.

Results indicated that juveniles with and without visual impairment may adopt different cognitive strategies solving the 3-DHMT-CA tasks. Correlations between 3-DHMT-CA performances and both Wechsler Indexes were significant only in the experimental group and not in the control group. It is possible that when executing 3-DHMT-CA tasks, children and adolescents with visual impairment adopted different strategies than their sighted peers, leveraging verbal and working memory abilities. According to Röder et al. (1999), individuals with visual impairment compensate lack of vision enhancing their auditory and verbal abilities on the spatial tuning. Cornoldi et al. (2009) found that individuals with visual impairment benefit more from verbal strategies (e.g., counting and naming directions) on spatial tasks than their sighted peers.

On the other hand, the control group scored significantly higher than the experimental group on the 3-DHMT-CA. These findings seem to be consistent with Miller et al. (2007): participants who were able to visually describe the items and the solutions exhibited better performances. Miller et al. (2007) suggested that performances on their haptic matrix test (3-DHM) could be related to mental imagery abilities. Interestingly, visual impairment, and specifically congenital blindness, does not prevent one from generating mental images, but it can affect the way mental images are processed and used. Individuals who are congenitally blind show some limitations in specific mental imagery tasks (Renzi et al., 2013). It is possible that 3-DHMT-CA is sensitive to mental imagery abilities, and therefore scores differences between the control and experimental groups were related to these abilities. If 3-DHMT-CA performance was related to mental imagery abilities, this test could also predict such abilities in juveniles with or without visual impairment regardless of visual perception. Mental imagery abilities are indeed critical for many cognitive processes (Pearson et al., 2008).

Verbal Comprehension Index results showed no significant differences between the experimental and the control group; however, there was a small or moderate effect size. It is possible that, in a larger sample, sighted participants could score significantly higher than peers with visual impairment. Though a p-value can determine whether an effect exists, it will not reveal the effect’s size. The effect’s size provides information regarding its practical significance, whereas the p-value does not assess practical significance. Knowing an effect’s magnitude allows one to ascertain the practical significance of statistical significance. Even a large effect may not be statistically significant if the sample size is too small.

Thus, differences between groups on 3-DHMT-CA may have been due to verbal skills. Unfortunately, literature does not provide clear data on verbal abilities differences between juveniles with and without visual impairment.

Limitations

This study has some limitations. The small sample size is not sufficient to provide normative data. Indeed, vision impairment is a rare condition that is very frequently accompanied by other physical or mental disabilities (Atkins et al., 2011). Moreover, there is no other equivalent cognitive test for this target population, so the convergent validity was measured only with sighted subjects. In addition, the VCI of both groups was well above the mean of the normative data, and the control group was in the very high average range for the WISC-IV, which makes the sample unusual and it is harder to interpret the meaning of the findings.

Further research is necessary to validate the 3-DHMT-CA in a larger and transcultural sample and to add a qualitative analysis of solution strategies, in order to verify the hypothesis of a difference between children and adolescents with and without vision impairment. A larger sample could also allow researchers to study differences between individuals with congenital and adventitious vision impairment. Additional studies could better clarify which type of ability (induction, quantitative reasoning, or deductive reasoning) are assessed by the 3-DHMT-CA. Executive functions and mental imagery abilities tests would be important to determine any correlations with 3-DHMT-CA performances. A longitudinal study is required to evaluate whether 3-DHMT-CA can predict learning abilities, academic success, and rehabilitation outcomes.

Implications for Practitioners

The 3-DHMT-CA for juveniles could fill a gap in the literature and in the assessment of children and adolescents with vision impairment. The haptic two-hands modality seems to be suitable to test nonverbal cognitive abilities, not only in adults with visual impairment, but also in juveniles who are visually impaired. The 3-DHMT-CA could be a valid assessment tool for making comprehensive cognitive evaluations, together with the tests, records reviews, interviews, observation, rating scales, and checklists guiding rehabilitation processes and educational programming.

Also, the present study highlights possible different verbal and working memory compensation strategies used by juveniles with vision impairment. Education and rehabilitation professionals could focus on empowering verbal and working memory abilities because they may affect other cognitive abilities as well.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and publication of this article: National Institute for Health Research (NIHR) Research Professorship to Professor Andrea Cipriani, Grant RP-2017-08-ST2-006, NIHR Oxford Health Biomedical Research Centre, Grant BRC-1215-20005.

ORCID iD

Carolina Cassar

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