The Assessment of Perceptual Therapy Study (APTS)

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Henry Patterson

Graduate Program in Vision Science

The Ohio State University

2011

Master's Examination Committee:

Marjean T. Kulp, Advisor; Michael J. Earley; and Jeffrey J. Walline

Henry Daniel Patterson

2011

Abstract

Purpose: The purpose of this study was to determine if using the Perceptual Therapy

System II: PTS II iNet (PTS II), a computerized visual perception therapy program, would improve performance on standardized tests of visual perception and decrease the frequency of any reported problem behaviors. Methods: We recruited children ages 6 to

13 with below age-level performance on a standardized test of visual perception (the

Beery-Buktenica Developmental Test of Visual Motor Integration, 5th Edition [VMI], the

Beery VMI supplemental test of Visual Perception [VP], or the Test of Visual Perceptual

Skills, 3rd Edition [TVPS-3]). Children who scored 80 or below on the Kaufman Brief

Intelligence Test, 2nd edition (KBIT-2) were excluded. All patients were given the PTS II software and prescribed 16 weeks of home therapy. Baseline and outcome testing included the VMI, the VP, the TVPS-3 (Visual Discrimination, Visual Memory and

Visual Sequential Memory), the Cognitive Assessment System (CAS) Figure Memory subtest and the Conners’ Parental Rating Scales-Revised (S) (Conners’). One sample t- tests were performed to compare the scores of participating children to normative values.

Mann-Whitney analysis was used to compare scores at baseline to those at outcome. A multiple linear regression controlling for age, compliance and baseline score was used to evaluate whether there was a relation between change in test score and compliance.

Results: Twenty children enrolled and sixteen children (mean age = 9.6 years) completed the study. At baseline, children scored on average significantly above the mean ii

(indicating a higher frequency of problem behaviors) on the Conners’ (Cognitive

Problems/Inattention scale, Hyperactivity scale, and ADHD Index) (p ≤ 0.03 for all analyses) and significantly below the mean for all visual perceptual tests (p ≤ 0.03 for all analyses) except the TVPS-3 Visual Memory (p = 0.28) and the CAS Figure Memory (p

= 0.13). Children also scored below the mean on the KBIT-2 Non-verbal at baseline.

Overall, excluding those who did not finish the study, the children completed an average of 59.5 sessions (range: 10.8 to 99.0 sessions). The outcome exam occurred on average at 19.5 weeks (range: 15.6 to 28.1 weeks). The frequency of problem behaviors as reported by the Conners’ decreased significantly from baseline to outcome: Oppositional

(p=0.04); Cognitive Problems/Inattention (p = 0.001); and ADHD Index (p = 0.002). No significant changes in visual perceptual skill were found. Conclusion: The use of the PTS

II resulted in a decreased frequency of parent-reported problem behaviors as measured by the Conners’. Further research with a larger sample size and a control group is needed.

iii

Dedication

Dedicated to my wife for her endless support and patience

Acknowledgments

Thanks are due to the tireless encouragement and assistance of my advisor, Marjean T.

Kulp and the willingness of my thesis defense committee, Drs. Michael J. Earley and

Jeffrey J. Walline, who were willing to read through this thesis at a time when they had much more to do. Also, much thanks for the hard work of my co-investigator, Linda

Nguyen. All of this would not have been possible without the facilities and referrals provided by the Ohio State University College of Optometry and for the quality referrals from Dr. Mattson.

Vita

1997...... Castro Valley High School

2005...... B.A. Music, Brigham Young University

Fields of Study

Professional Studies: Optometry

Graduate Studies: Vision Science

Table of Contents

Abstract ...... ii

Dedication ...... iv

Acknowledgments...... v

Vita ...... vi

List of Tables ...... ix

List of Figures ...... x

Chapter 1: Historical Review ...... 1

What is Visual Perception? ...... 1

Why is Visual Perception Important? ...... 2

Visual Perception and Academic Performance ...... 3

Visual Perceptual Significance at Earlier Grades ...... 8

Persistence of Visual Perception problems ...... 9

Poor correlation between visual perception and academics ...... 10

Support for a Multi-disciplinary Approach ...... 14

Can visual perception be improved? ...... 17

How are Visual Perceptual Deficits Treated? ...... 20

vii

Chapter 2: Materials and Methods ...... 24

Subjects ...... 24

Procedures for Baseline and Eligibility Testing ...... 25

The Test of Visual Perceptual Skills ...... 25

The Beery-Buktenica Developmental Test of Visual Motor Integration ...... 26

Conners’ Parent Rating Scale – Revised (S) ...... 27

Therapy Procedures ...... 28

Procedures for outcome testing ...... 42

Statistical Analysis ...... 42

Chapter 3: Results ...... 44

Subjects ...... 44

Software Issues ...... 54

Chapter 4: Discussion ...... 55

Chapter 5: Conclusions ...... 59

References ...... 60

viii

List of Tables

Table 1 Correlation between visual perception and academic achievement ...... 7

Table 2 Visual perception significance at earlier grade levels ...... 9

Table 3 Poor relationships between visual perception and academic performance...... 13

Table 4 Academic achievement correlates with multiple factors ...... 16

Table 5 Improvement of visual perceptual skill with therapy ...... 20

Table 6 Perceptual testing used to validate the PTS II ...... 23

Table 7 The PTS II program elements as they relate to various perceptual areas...... 42

Table 8 Comparison of baseline scores between complete and incomplete groups ...... 45

Table 9 Baseline testing values ...... 47

Table 10 Baseline data compared to normative values ...... 48

Table 11 Outcome testing values ...... 49

Table 12 Outcome data compared to normative values ...... 50

Table 13 Improvement with Conners' behavioral testing ...... 51

Table 14 Linear relationship between test scores and compliance ...... 53

List of Figures

Figure 1 Visual Sequencing ...... 30

Figure 2 Visual Span ...... 31

Figure 3 Visual Scan ...... 32

Figure 4 Visual Sequential Processing ...... 33

Figure 5 Visual Search ...... 34

Figure 6 Tachistoscope ...... 35

Figure 7 Visual-visual Integration ...... 36

Figure 8 Parafoveal stimulation ...... 37

Figure 9 Visual Closure ...... 38

Figure 10 Visual Concentration ...... 39

Figure 11 Visual-motor Integration ...... 40

Chapter 1: Historical Review

What is Visual Perception?

Groffman defines perception as the active process of locating and extracting information from the environment (Groffman 2006). Visual perception focuses on visual input from one’s environment but includes interactions between other senses and higher cortical functioning. Solan suggested that perceptions, which are more complex than sensations, may also be the product of previous organization, experience, and elaboration of the nervous system(Solan and Ciner 1989). According to the AOA Guidelines, the major elements of visual perception include visual spatial orientation skills, visual analysis skills, visual memory, auditory-visual integration, visual-motor integration, and rapid naming (Garzia, Borsting et al. 2000). Visual spatial orientation is defined as the ability to perceive relative position of one’s self to objects located in one’s surrounding environment. Visual analysis is defined as the ability to visually manipulate an object in one’s mind and to break it down into smaller more manageable parts. Visual memory is the ability to remember detail of images previously seen. Auditory-visual integration incorporates hearing and vision allowing for a connection of spoken phonemes and written graphemes and may assist in locating the cause of an auditory stimulus(Maier and

Groh 2009). Visual-motor integration incorporates vision with motor ability allowing for 1 efficient and accurate interaction with objects in one’s environment such as guiding one’s hand to draw a picture, or guiding arm movements to strike a ball with a bat.

Theoretically each part can be addressed individually; however, visual perception in our daily lives never separates itself in neat components. Visual perception incorporates all parts simultaneously and allows for proper functioning and interaction in daily tasks such as learning, motility, communication and social interaction.

Why is Visual Perception Important?

Visual perception has been shown to correlate with academic performance, especially in younger children (Coleman 1972; Kavale 1982; Feagans and Merriwether 1990; Taylor

Kulp 1999; Sortor and Kulp 2003; Goldstand, Koslowe et al. 2005). For example, some studies have found visual motor integration testing to be predictive of future academic achievement (Keogh and Smith 1967; Fowler and Cross 1986; Kulp and Schmidt 1996;

Taylor Kulp 1999; Sortor and Kulp 2003). Conceptually it is understandable that good visual discrimination and visual analysis (i.e., the ability to judge differences in symbols and break them down into smaller parts) should help a child perform better academically, as it requires the ability to correctly perceive the letter or symbol and to organize it in one’s mind (Kulp, Earley et al. 2004). It has been stated that, “The treatment of underlying perceptual deficits complements the educational process by improving visual organization, attention and information processing in those children who manifest difficulties in these attributes” (Scheiman and Rouse 2006). This suggests that improving

2 visual perception at earlier ages could benefit children by helping them create building blocks for future academic success.

Visual Perception and Academic Performance

Supporting the idea that visual perception plays an integral part in learning, many studies have found significant relationships between visual perception and academic performance in mathematics, reading, writing and/or spelling (Coleman 1972; Kavale

1982; Feagans and Merriwether 1990; Taylor Kulp 1999; Sortor and Kulp 2003;

Goldstand, Koslowe et al. 2005).

An early pilot study by Starnes tested the perceptual skills of 18 children (8 good readers and 10 poor readers) chosen subjectively by the school principal, using a variety of non- standardized perceptual tests (Six-figure Form Board, Winter Haven Visual Forms,

Tactual Forms, Circus form board, and Key Form Board). Although IQ was not controlled, good readers performed better than the poor readers on every perceptual test except the Key Form Board (Starnes 1969).

Keogh and Smith also examined the relationship between visual perception (as tested by the Bender Gestalt test of visual perception [a copying test using black and white figures]), and school achievement, as measured by the reading and spelling sections of the California Achievement Tests at 3rd grade and the Iowa Test of Basic Skills at 6th grade. The study authors followed 221 children from Kindergarten to 3rd grade and to 6th

3 grade (K=221; 3rd=127; 6th=73). Although most of the original sample was lost, they found that consistently scoring 1 standard deviation above or below the mean on the

Bender Gestalt significantly predicted good or poor reading achievement, respectively.

The Bender Gestalt test of visual perception was determined to be a useful predictor of academic achievement (Keogh and Smith 1967).

Coleman conducted a study, in West Warwick, Rhode Island, which evaluated the effect of a largely motor-based, modified teaching technique on academic achievement. The modified teaching technique involved a standard classroom curriculum augmented with visual, auditory, kinesthetic and tactile activities. Students in the pilot treatment class engaged in one-on-one remedial language therapy for reading and spelling. They also participated in extensive physical education, including spatial orientation, balance, eye- hand coordination, and visual tracking using balance beams, high bars, tilt boards and a trampoline. The study was conducted over two years each with a pilot class with a matching control (n=14, n=14 respectively). After the first year of the program, all pilot program children demonstrated improved scores as measured by the Wechsler

Intelligence Scale for Children (WISC), while controls only maintained or decreased their full scale score. The second year program incorporated pre- and post-testing using the

WISC, an unspecified visual-perceptual-motor test, motor abilities, and two tests of academic achievement (Metropolitan Readiness, and the Stanford Achievement Test).

The study showed statistically significant improvement (p < 0.01) in reading, writing and spelling (Stanford Achievement Test) and concurrent improvement on a test of visual-

4 perceptual-motor skills (p < 0.05) (Coleman 1972). Although the WISC was used to measure intelligence, the author did not control for IQ in the statistical analysis.

Kulp studied the relationship between visual motor integration, as measured with the

VMI, and academic performance as measured by teachers’ ratings (1–5) in 191 children in grades K-3. Cognitive ability was partially controlled for using the Otis-Lennon

School Ability Test non-verbal cluster (OLSAT). Overall significance was found (p ≤

0.012) between teachers’ ratings (reading, writing, math, and spelling) and the VMI scores. Teachers were masked from knowing VMI scores. The 7-year-olds showed significant correlations (p < 0.001) between all teachers’ ratings, except for spelling (p =

0.053), and VMI scores. Eight-year-olds showed significant correlations (p < 0.040) between all teachers’ ratings and VMI scores. And 9-year-olds showed significant correlations (p <0.016) between all teachers’ ratings and the VMI scores, except with reading (p = 0.057) (Taylor Kulp 1999).

Kulp and Edwards also investigated the relationship between performance on a test of visual memory (Test of Visual Perceptual Skills subtest) and academic achievement as measured by the Stanford Achievement Test in 155 children in grades 2-4. They found that poor visual memory ability was significantly related to below-average reading decoding, math, and overall academic achievement (Stanford Achievement Test) while controlling for age and verbal ability (Kulp, Edwards et al. 2002).

Sortor and Kulp conducted a study of 155 children, from grades 2-4 comparing visual motor integration, as measured by the VMI and its supplemental tests, and academic achievement, as measured by the Otis –Lennon School Ability Test and the Stanford

Achievement Test. They found a significant difference between the VMI standard scores, the VP standard scores, and the motor coordination supplement standard scores when compared to the upper and lower quartiles scorers in reading and math achievement, as measured by the Stanford Achievement Test (p ≤ 0.027 for all analyses). The VMI standard score correlated significantly with the Stanford math score (p = 0.001). Both the visual perception and motor coordination supplemental tests demonstrated a significant relationship to the Stanford math and reading scores (p ≤ 0.027 for all analyses). The data suggested that a correlation between low visual perceptual ability and poor math and reading achievement may exist. Therefore, the authors suggested the need for visual perceptual assessment in children who score poorly in math or reading (Sortor and Kulp

2003).

In another study, poor visual perceptual skill, as measured by a newly developed test of

Visual Sequential Memory (involving remembering the order of a sequence of visual images) and the Beery VMI supplemental test of Visual Perception (VP), was significantly related to poor mathematics ability as measured by the California

Achievement Test-5. However, after logistic analysis in a single model, only Visual

Sequential Memory remained significant, suggesting that the newly developed test was

more significantly related to poor mathematic skills than was the VP (Kulp, Earley et al.

2004).

Investigator Year Population Conclusions Additional

Starnes 1969 N=8 good Perceptual tests had a Non-standardized readers direct relationship to tests used. N=10 poor reading ability. Potential for bias in readers subject selection. Grade 3 No control for IQ Keogh and 1967 N=73 Bender-Gestalt predictive Smith Grades K, and of academic achievement. 3–6 Coleman 1972 N=14 Improvement in Visual- IQ not controlled. Control N=14 perceptual-motor skills (p < 0.5) and visual-motor Grades K-6 skills (p<0.1)

Taylor 1999 N=191; VMI and academics Controlled for IQ Kulp Grades K-3 correlated significantly Kulp and 2002 N=155 Poor visual memory Edwards Grades 2-4 correlated with reading et al. decoding, math and academic achievement Kulp and 2003 N=155; VMI, VP and Motor Sortor Grades 2-4 Coordination show significant differences (p ≤ 0.027) between upper and lower quartile scorers in the Stanford reading and math tests. Kulp and 2004 N=171 Poor visual perception Earley, et Grades 2-6 and math performance al. correlated with new test of Visual Sequential Memory when compared with the VP. Table 1 Correlation between visual perception and academic achievement 7

Visual Perceptual Significance at Earlier Grades

Multiple studies have found that the link between visual perception and academic performance occurs in earlier grades. In fact, a meta-analysis of 161 studies involving the study of visual perception, Kavale found that visual memory and visual discrimination were significantly correlated with reading skills (explaining 16-30% of variance) in preschool and primary grade levels (grades K-6). However, no significance was found at the intermediate grade level, supporting the idea that visual perception has a more important role in reading ability at earlier grade levels (Kavale 1982).

Solan et al. conducted a double blind study of 144 normal children in grades K-2 (48=K,

49=1st, 47=2nd) comparing learning readiness and reading ability with perceptual-motor skills. Learning readiness and reading ability were evaluated using the S.R.A. Primary

Mental Abilities Test-Readiness Level scores in kindergarten and the Gates-MacGinitie

Reading Test-Levels A and B in first and second grade, respectively. Perceptual-motor skills were evaluated using the Tachistoscopic Exposure Test, the Grooved Peg Board, the Divided Form Board and the Auditory Visual integration test (AVIT). Correlations were shown to be significant (p < 0.05) in all grade levels studied and with all tests evaluated except for the AVIT which only showed significant correlations in grades one and two. A stronger correlation was observed in kindergarten (r2 = 12.1–28.8) and grade one (r2 = 5.6–30.7) than what was found in grade two (r2=7.6–16.2). The authors also concluded that visual perception may have a significant role in learning readiness and reading ability especially at earlier stages of development (Solan, Mozlin et al. 1985).

The greater impact of visual perception on learning ability in primary levels of schooling

(Kavale 1982; Solan, Mozlin et al. 1985) may be due to the development of a visual word form area (VWFA), an area of the temporal occipital lobe which responds directly to visual representations of words and letters, in children as young as 6 years old when learning to read (Dehaene, Pegado et al. 2010).

Investigator Year Population Conclusions Additional

Kavale 1982 Meta- Visual memory and No significance analysis of visual discrimination found at intermediate 161 prior were shown to correlate grade levels visual 16-30% with reading suggesting a more perceptual achievement in important role at studies. preschool and primary earlier grade levels. grade levels. Solan 1985 Grade Reading readiness Norms established K=48 correlated with for 4 tests of Grade perceptual-motor perception. 1=49 testing; explaining 54% Grade of the variance. 2=47 Table 2 Visual perception significance at earlier grade levels

Persistence of Visual Perception problems

Despite the reportedly greater impact of visual perceptual problems in earlier grades, one study found that visual perception problems can persist through elementary school and lead to the persistence of academic problems. Feagans conducted a study involving 66 learning disabled children, 6-7 years of age. The children were followed for 3 years after 9 evaluating their visual discrimination deficits using a Gibson letter-like visual discrimination task. The Gibson task consisted of an array of 11 forms some of which had been transformed by rotation, reversal, or adding breaks, closes or curve changes. The child needed to identify the standard forms from the transformed forms. The children were grouped into 4 groups for analysis: low and high error learning disabled (LD) groups and a low and high error non-learning disabled (NLD) groups. Achievement was measured each year by three subtests (reading recognition, reading comprehension, and mathematics) of the Peabody Individualized Achievement Test (PIAT). Year-by-year analyses comparing the 4 groups showed large group differences which were maintained throughout the 3 years on all the tests of academic achievement (F > 17.44; p < 0.0001 for all tests). Those in the high error LD group consistently performed worse on the PIAT subtests than those in the low error LD group and both consistently performed worse than those in the NLD groups. The authors concluded that visual discrimination problems are found in some but not all poor readers, and these discrimination issues can persist and lead to consistently poor achievement throughout elementary school (Feagans and

Merriwether 1990).

Poor correlation between visual perception and academics

Although many studies have shown correlation between visual perception testing and academic achievement, it is not without some controversy. A few studies have found a lack of correlation when comparing visual perception and academic achievement.

Giebink and Birch evaluated 142 children in 2nd grade using the Bender Gestalt test and reading achievement assessment using the California Achievement Test (CAT) and found an inadequate correlation for predicting academic achievement (Giebink and Birch 1970).

Du Bois evaluated a randomly chosen group of 60 children from grades 2 and 4 to determine if positive correlations existed between the Frostig Test of Visual Perception,

Bender-Gestalt test, Auditory-Visual Integration Test (AVIT), the Gates MacGinitie

Reading Survey, the Peabody Picture Vocabulary Test and the Stanford Binet Vocabulary subtest. The only correlations found were between the Frostig and the Gates MacGinitie

Reading tests but after controlling for vocabulary performance no significant correlation was found. The author concluded that relying on visual testing alone would not be wise when considering reading remediation, a conclusion which agrees with other studies supporting the relationship between visual perception and academic performance (Du

Bois 1973).

Helveston compared academic achievement with visual function in 1,910 children in grades 1-3. Academic performance was evaluated using the Metropolitan Readiness

Test, the Cognitive Abilities Test, the Iowa Test of Basic Skills, and the individual teacher's assessment of reading level (above average, average, below average). Visual function was evaluated using visual acuity, muscle balance, preferred eye and hand, color vision, refraction, sensory and motor function, and a simple writing and drawing task (i.e.

“draw a clock” and “draw a bicycle” test). The author concluded that there was no

11 positive relationship between visual function and academic achievement, although significant differences were reported between reading groups and performance on the

“draw a bicycle” test (p < 0.001) (Helveston, Weber et al. 1985). Stolzberg criticized the study stating that the prevalence of visual problems found in the study was lower than average and the criteria for placing children in reading groups was too simplified and subjective (Stolzberg 1986).

Goldstein and Britt evaluated the relationship between visual-motor coordination using three visual-motor tests (The Developmental Test of Visual-Motor Integration, the Test of Visual-Motor skills, and the Bender-Gestalt) and academic achievement using the

Woodcock-Johnson Battery Test of Achievement. They tested a group of 44 children from the ages of 6-12 years who were referred to their clinic for suspected learning disabilities. Fifteen of the children were learning disabled, eight of the children were mildly retarded, and the other 21 children had borderline or low intelligence without a specified learning disability. Although significant correlation (p<.01 for all tests) was found when comparing academic achievement to each visual-motor test, the effect was no longer significant after controlling for IQ except between mathematics and the Test of

Visual-motor Skills (p = .02).However, this only explained a small amount of the variance (7.5%). The author suggested further exploration in the area of mathematics and visual perception in order to determine if the remaining effect continued to be robust

Although some studies have found poor correlation between visual perception and academic achievement a large body of literature reported a significant relationship between visual perception and academic achievement. Regardless, the need for a more inter-disciplinary approach when evaluating and remediating academic achievement has been largely accepted.

Investigator Year Population Conclusions Additional

Giebink and 1970 N=142 Bender Gestalt Test was Birch Grade 2 a poor predictor of reading achievement.

DuBois 1973 N=60 No significant Grades 2, 4 correlations found between various tests of visual and auditory perception and reading/vocabulary testing. Helveston et. 1985 N=1,910 No positive relationship Teachers al Grades 1-3 between visual function subjectively placed and academic children in above, performance. below or average However, a significant groups. difference among reading groups using the “draw a bicycle test” (p<.001). Goldstein 1994 N=44 Poor correlation with Small sample size, and Britt Ages 6-12 visual motor coordination large age range and academic may give a small achievement when effect. controlling for IQ Table 3 Poor relationships between visual perception and academic performance.

Support for a Multi-disciplinary Approach

Although studies have suggested that visual perception had a greater role in the development of learning abilities, multiple studies have found that visual perception is only one of the variables contributing to academic achievement.

Johnston and Anderson evaluated both visual and auditory perception as it related to reading performance in 20 poor readers compared to 20 reading age normal controls and

20 chronological age controls while controlling for IQ. The 20 poor readers were of an average age of 10.7 years (average reading age equivalent of 7.7 years). Visual perceptual testing included the Mooney Test, a test of visual closure, and the Children’s Embedded

Figures Test (a figure ground test). Auditory perceptual testing used included a test of auditory segmentation, which consisted of picking a word that did not belong from a set of four words, and an auditory memory pre-test, which consisted of repeating a series of four words presented orally. Both visual and auditory perceptual performance correlated with poor reading performance in both the poor readers and the controls. However, the performance on the Mooney test only correlated with poor readers but not the controls.

This suggested that auditory and visual perceptual skills were both important in the development of reading skills (Johnston, Anderson et al. 1990).

Solan and Ficarra compared scores of 51 reading disabled children to average normal scores on a battery of 14 tests which assessed verbal, perceptual, spatial, and motor skills.

All children were determined to have normal IQ using the WISC-R. They reported a

14 significant correlation between reading comprehension and 3 perceptual tests (King-

Devick, Auditory-Visual integration Test (AVIT), and the grooved peg-board test) and 2 verbal tests (Digit Span Backwards, and the Token Test). Thirty-eight percent of the variance was explained by the three perceptual tests together and 40% of variance was explained by all 5 tests together. However, 28% of the variance was explained by the

King-Devick eye movement test alone. The authors concluded that the results suggested a strong eye movement component and that reading and reading comprehension difficulties often cannot be explained by only one variable alone, requiring a more inter- disciplinary approach to be taken when attempting to improve reading problems (Solan and Ficarra 1990).

In an attempt to determine the risk that a given preschooler might have of failing a grade,

Fowler and Cross longitudinally compared the Beery-Buktenica Developmental Test of

Visual Motor Integration (VMI) with reading and math achievement scores, maternal education, and the Sprigle School Readiness Screening Test (SSRST). Reading and math achievement scores, as tested with the California Achievement test, correlated significantly with VMI performance (r2=0.05 with mathematics; r2=0.03 with reading achievement). However, achievement scores also correlated with the Sprigle School

Readiness Screening Test (SSRST) (r2=0.26 with reading achievement), and increased maternal education (r2=0.05 with mathematics; r2=0.07 with reading achievement).

Combining all significant variables demonstrated a much greater correlation (r2=0.35 with mathematics; r2=0.42 with reading achievement). Therefore, it was determined that

15 using the VMI or SSRST alone was not as beneficial in predicting grade failure as a more multi-factorial approach (Fowler and Cross 1986).

Overall, it has been largely accepted that many factors, including visual perception contribute to poor academic achievement. Thus, when attempting to remediate reading performance or other poor academic performance it has been suggested to involve a more inter-disciplinary approach.

Investigator Year Population Conclusions Additional

Johnston 1990 N=20 poor Visual perceptual testing Mooney visual and readers and auditory perceptual closure testing only Anderson, et Control = testing correlated with correlated with al. 40 normal poor reading reading scores of Mean age: performance. poor readers but not 10.7 with controls. Solan and 1990 N=51 Perceptual skills Auditory, motor and Ficarra reading accounted for 38% of visual elements were disabled variance in reading included in the Grades 4-6 comprehension. perceptual skills testing. Fowler and 1986 N=210 VMI correlated (r2=0.03 Correlations reported Cross Pre K to 0.05) when predicting for reading grade failure. A multi- achievement and factorial assessment mathematics correlated more (r2=0.35 respectively. to 0.42) than with the VMI alone. Table 4 Academic achievement correlates with multiple factors

Can visual perception be improved?

Several studies have supported the idea that training visual perception can have a positive effect on academic performance.

Two case studies reported that effective training of visual perceptual skills increased academic performance. Seiderman and Solan reported a single case of a 5 year 9 month child who failed the 1st grade due to reported hyperactivity, a short attention span and repeated poor performance. At initial testing a normal IQ of 101 was noted with considerable deficits in a variety of perceptual skills categorized into visual, auditory, form, right-left and large/small motor subgroups. A marked improvement to or above age-expected levels was noted in all perceptual areas after a 10 month individualized treatment plan. The case study did not detail the treatment prescribed over the 10 month period but rather stressed the importance an individualized perceptual vision therapy plan can have for certain children (Solan and Seiderman 1970).

Rosner and Rosner published a case report addressing the appropriate treatment of a visual perceptual deficit. Their case addressed a 6 year, 3 month old who near the end of his kindergarten year displayed difficulty in completing paper/pencil tasks and remembering directions. He also was described as being unable to carry out multiple step activities in an organized way. He did well in reading and had no visual or binocular problems. However, he tested at a 5 year, 1 month level when testing visual motor integration with the VMI. He was diagnosed with a lag in visual perceptual skills development and the author worked with the school to have the child use the Test of

Visual Analysis Skills (T.V.A.S) program, a visual perceptual program which teaches how to analyze patterns and trains the understanding of spatial relationships. Within 3 months of initiating treatment, the child performed at age expected levels on the VMI and continued to perform well through the 2nd grade at which point the article was written (Rosner 1986).

Seiderman conducted a study, which included 36 learning disabled children who showed sub-normal performance on perceptual-motor tasks (form matching, copying, figure ground and alternate hopping and bouncing) and binocular vision testing

(fusional vergence ranges, and accommodation). The group was divided in half with the control group receiving art or music courses while the experimental group received individualized visual or perceptual therapy for a period of nine months. Both groups received daily specialized reading training. Significant gains in the experimental group were noted particularly in the area of reading (Stanford Achievement Test) when compared to the control group. In an analysis of covariance, significance (p < 0.05) was found with two of the seven visual perceptual tests: the divided form board (Getman) and the Perceptual Constancy sub-test of the Frostig. Also, convergence break and recovery values at both distance and near showed significant improvement when compared to the control. Details of each individualized therapy were not described.

These findings suggested that individualized treatment plans involving visual perception and vision therapy can be used to improve visual perceptual and reading skills of a

18 learning disabled population (Seiderman 1980). A major drawback of the study included not isolating perceptual problems from binocular vision problems.

In another study, Halliwell and Solan evaluated the effect of a supplemental visual perceptual program on 35 children, as compared to an alternative reading therapy group

(n=35) and a control group (n=35). All study participants were reported to be at risk of being poor readers according to scores obtained with the Metropolitan Readiness Test.

Each group was age and sex matched. All groups received regular reading training in the normal school program. Experimental I Group received an additional 45 minutes of perceptual training 2 days per week for 7 months. The perceptual training consisted of sensory and inter-sensory processing, fine and gross motor development, and laterality and directionality tasks. Specific activities included tachistoscopic training, figure ground and form constancy training (Frostig), visual motor development training

(Winterhaven Templates), visual motor training with a chalkboard, and visual tracking.

Experimental II Group received additional training for the same time as Experimental I

Group. However, they received only additional reading assistance which included exercises in word recognition, phonetic training, reading comprehension listening, and choral poetry. The control group received no additional assistance. At the completion of the study, reading comprehension was tested using the Metropolitan Achievement Test,

Primary I Battery. Regression analysis revealed no statistically significant difference between Groups I and II, and Group II and the control. However, Group I performed better than the control group overall and with respect to boys alone (p < 0.05 both

19 analyses). The authors suggested that adding a supplemental perceptual training program in addition to reading assistance was beneficial in improving the children’s reading skills (Halliwell and Solan 1972).

Investigator Year Population Conclusions Additional

Solan and 1970 N= 1 Case report detailing Seiderman Grade 1 improvement in sensory processing, self-concept and academics Halliwell and 1972 N=140 Increase in reading scores with a Small Solan Grade 1 supplemental perceptual training Group program. sample size (n=35) Seiderman 1980 N=36 Learning disabled children and Ages 7-12 children with perceptual lags showed improvement with reading scores. Rosner and 1986 N=1; Case reporting a child with visual Rosner Age 6 perception deficit successfully treated with the T.V.A.S. program. Table 5 Improvement of visual perceptual skill with therapy

How are Visual Perceptual Deficits Treated?

Guidelines for treating visual perceptual deficits have been outlined in Optometric

Management of Learning-Related Vision Problems (Scheiman and Rouse 2006).

Therapy may be office- or home-based. Office-based therapy involves regular (e.g.

20 weekly) visits with a therapist who uses a wide variety of procedures to engage the child and improve the specified visual perceptual skill. Overall, the goal of therapy is often to improve a child’s visual perceptual skills to an adequate level to become adept in the classroom and ultimately to learn quickly and efficiently. Tools used in visual perceptual therapy may include using parquetry blocks (i.e. wood blocks of varying shapes, colors and sizes), geoboards (i.e. a board with a grid of pegs that can hold rubber bands to design geometric shapes), word searches, visual tracings, hidden pictures, memory card games, bean bag games, a marsden ball (a plastic ball with printed letters which is suspended from the ceiling which aids in training visual tracking and visual-motor integration), pegboard games, or bead stringing. The in-office therapist will continually seek to increase the complexity and difficulty of the task while attempting to maintain the child’s interest in the therapy.

It has been postulated that web-based programs may help improve compliance with therapy. As poor compliance often impedes success with therapy, computer therapy may improve compliance and thus improve the outcome of the therapy (Scheiman and Rouse

2006). Children are often the focus of visual perceptual therapy and are not only more familiar with computers but also enjoy computer games which may keep their attention for longer than the traditional approaches to therapy (Scheiman and Rouse 2006).

Computerized therapy can also aid the therapist with tools the therapist may not have previously had, such as the ability to change difficulty levels quickly or remotely, to present challenging stimuli that otherwise could not have been presented. Although it has

21 been suggested that computer therapy should be used as an adjunct to office-based therapy rather than to replace traditional therapy (Scheiman and Rouse 2006), standalone home-based computer therapy is often prescribed. One commonly used, commercially available, program is the PTS II.

Groffman studied the effect of home-based computer therapy on 14 children ages 7.5–

11.8 years in an unpublished validation study of the PTS II (Groffman 2001). He administered 13 tests/subtests at baseline and he classified the outcome as assessments of simultaneous processing, sequential processing or perceptual speed. On average, scores were below average at baseline. Simultaneous Processing testing included the VMI; the

Primary Mental Abilities (PMA) Spatial Relations test; the Detroit Test of Learning

Aptitude (DTLA) Symbolic Relations test; the Test of Memory and Learning (TOMAL)

Spatial Memory test; and the Kaufman Assessment Battery for Children (KABC) Gestalt

Closure test. Sequential Processing testing included the DTLA Digits Forward, Word

Sequences and Design Sequence tests; the Visual Span test; and the KABC Hand

Movements test. Perceptual Speed testing included the Woodcock Johnson test of

Cognitive Ability Perceptual Speed test and the Tachistoscope (see Table 6). Groffman reported significant increases in simultaneous processing (p < 0.01), sequential processing (p < 0.01), and perceptual speed (p < 0.001) at outcome after completion of an average of 37 sessions.

Perceptual Test Skill Simultaneous VMI Processing Primary Mental Abilities (PMA): Spatial Relations test Detroit Test of Learning Aptitude (DTLA): Symbolic Relations Test Test of Memory and Learning (TOMAL): Spatial Memory Test Kaufman Assessment Battery for Children (KABC): Gestalt Closure Test Sequential DTLA: Digits Forward Processing DTLA: Word Sequences DTLA: Design Sequence Test Visual Span Test KABC: Hand Movements Test Perceptual Woodcock Johnson test of Cognitive Ability: Perceptual Speed Speed Tachistoscope Table 6 Perceptual testing used to validate the PTS II

As the PTS II is commonly prescribed for the remediation of visual perceptual deficits, and as previous literature has not evaluated the use of home visual perceptual therapy, the purpose of this thesis was to determine if using the PTS II would improve performance on standardized tests of visual perception in children who initially performed below age-level on the same standardized visual perception tests. This study also sought to determine if the children tested would also show a decrease in the frequency of any problem behaviors as reported with the Conners’ Parental Rating

Scales-Revised (S) (Conners’), a standardized parent rating scale.

Chapter 2: Materials and Methods

Subjects

Children between the ages of 6-17 were recruited from the Pediatrics Service at The

Ohio State University College of Optometry and from referrals from local optometrists, and other professionals (e.g. other eye care practitioners and school personnel) in the

Columbus, Ohio area. Study information was provided to families of children who performed poorly on standardized visual perceptual tests which are routinely administered during comprehensive pediatric vision examination. Eligibility criteria included below age-level performance (one half standard deviation or more below the mean) on at least one of the following standardized tests of visual perception: the Test of Visual Perceptual Skills, 3rd Edition (TVPS-3), the Beery-Buktenica Developmental

Test of Visual Motor Integration, 5th ed. (VMI), or the Beery VMI Visual Perception supplemental test (VP). Exclusion criteria included a score of 80 or below on the

Kaufman Brief Intelligence Test, 2nd Edition (KBIT-2) and best corrected visual acuity of 20/30 or worse. All children needing spectacle correction agreed to wear their correction while using the prescribed home therapy software.

Procedures for Baseline and Eligibility Testing

Parental permission, the child’s assent, and HIPAA disclosure were obtained prior to performing any study-related testing. Standardized tests of visual perception were administered in the following order: TVPS-3 (Visual Discrimination, Visual Memory, and Visual Sequential Memory subtests only), VMI and VP. The KBIT-2 was also administered at the eligibility exam. The KBIT-2 is a standardized, normalized test often used for screening intelligence. The KBIT-2 includes 3 subtests (Verbal Knowledge,

Matrices, and Riddles) and provides a verbal, non-verbal and composite IQ score

(Kaufman and Kaufman). Testing was performed according to the published directions for all tests. The parent completed the Conners’ questionnaire while waiting for the child to finish testing.

The Test of Visual Perceptual Skills

The TVPS-3 was chosen for use in this study because it is a commonly used, commercially available standardized test which assesses specific areas of visual perception such as visual discrimination, visual sequential memory and visual memory with little motor involvement. Visual sequential memory and visual memory are both trained in the PTS II and the TVPS-3 Visual Memory subtest has been shown to be predictive of academic performance (Kulp, Edwards et al. 2002). The TVPS-3 consists of black and white test stimuli presented in a multiple choice format. The TVPS-3 has been normalized nationally using scores from 2,008 children ages 4-18 years old.

Demographics were moderately representative of the 2000 U.S. Census. According to the

25 test manual, test-retest correlation was reported to be 0.97 overall with individual subtest correlations ranging from 0.34 to 0.81. Criterion-related validity was met showing a moderately strong correlation of 0.67 when comparing the TVPS-3 overall score with the

VP. Construct validity was verified by demonstrating that the TVPS-3 consistently improved with age. It was also shown that a learning disabled population and an

Attention Deficit Disorder population consistently performed lower than age matched means.

The Beery-Buktenica Developmental Test of Visual Motor Integration

The VMI has been a widely used, standardized test of visual perception and motor integration used by psychologists, learning disabilities specialists and eye care professionals. The VMI full test involves copying black and white line figures with a pencil and the VP involves multiple-choice matching of figures incorporating distracters such as size differences, flipped images or detail changes. The 5th edition was normed in

2003 on an overall sample size totaling 10,950 children from 2–18 years old which spanned 4 major census regions in the United States and was representative of the 2000

U.S. Census (Beery and Beery). Norms have been consistent over time and location according to data published in the VMI 5th edition manual (Beery and Beery). The test has also been normed internationally (Webb and Abe 1984; Webb 1985). Because of the detailed scoring criteria, reliability has remained high for the VMI and the VP. The test manual reports test-retest coefficients of 0.89 for the VMI and 0.85 for the VP. Inter- scorer reliability was reported to be 0.92 for the VMI and 0.98 for the VP.

Validity has been shown to be strong on many levels. The VMI and its supplemental tests have correlated highly with chronological age. It was determined that the VMI and its supplemental tests have moderately correlated more with non-verbal intelligence than verbal intelligence. A moderately high correlation of 0.63 between the Comprehensive

Test of Basic Skills (CTBS) and the VMI was found and suggested a moderately strong relation to academic achievement. The VMI has been found to be predictive of reading readiness and academic achievement (Fowler and Cross 1986; Taylor Kulp 1999; Sortor and Kulp 2003). No gender bias has been found.

Conners’ Parent Rating Scale – Revised (S)

The Conners’, a normalized behavioral questionnaire, was completed by the parent who brought the child. The Conners’ is a questionnaire consisting of 27 questions concerning the child’s behavior in the past 30 days with responses ranging from 0 (not true at all) to

3 (very much true). Answers were totaled and summed into four scales: Oppositional,

Cognitive Problems/Inattention, Hyperactivity, and ADHD Index. Each scale has been described as follows (Conners 2001).

1. Oppositional: The child tends to break rules and to have problems with authority.

2. Cognitive Problems/Inattention: The child may be inattentive or struggle

academically, and may have poor organizational skills and long-term focusing

problems.

3. Hyperactivity: The child may have difficulty sitting still, difficulty focusing for

extended periods and may show signs of restlessness or impulsiveness.

4. ADHD Index: A proprietary assessment to identify children who may be at risk

for ADHD.

Therapy Procedures

Upon qualifying for the study, parents were given a copy of the PTS II and a printed copy of the patient manual which is also digitally contained within the program disk. They were instructed to choose the “internet option” upon installation. Children and parents were instructed that the child should perform 5 sessions per week for 16 weeks on the

PTS II. Each session lasted approximately 20 minutes. According to the doctor’s manual provided with the PTS II, most children would need to complete 70-80 sessions to finish the Auto Mode protocol. The parent and child were given the co-investigator’s cell phone number and email address in case they encountered problems or questions concerning the study. The software was kept in its automatic setting, which sets the target levels for each individual exercise according to the age of the child.

The PTS II tracked the individual progress of each child and automatically increased the level of difficulty as the child’s performance improved. Child performance and compliance were monitored remotely by a co-investigator through a database maintained by Home Vision Therapy, the PTS II manufacturer. Compliance was evaluated by total number of sessions (one session equal to 4 exercises) completed by the child. All children were contacted weekly by email or phone by a co-investigator to help motivate the child

28 and encourage continuing compliance. Issues regarding software installation or compatibility were referred to the software company for technical assistance.

In order to understand what is contained in the program, detailed descriptions of each task have been included below with an example of each visual perceptual therapy exercise.

Visual Sequencing: The child is required to find specific stimuli (lower or upper case letters, numbers or any combination of both) in the order that they appear at the top of the screen, choosing them out of a string of randomized characters. The child moves a yellow box with the right arrow key and selects the desired letter with the spacebar. If the child makes an error they are sent back to the last correct response and continue until the task is completed. To advance to the next level the child must make, on average, fewer than 2.5 errors during the exercise. In order to increase difficulty, the target type may involve numbers, letters or both. The target sequence may be presented in random order (e.g. 523023) or sequentially (e.g. 123456). The length of the target sequence may vary from 5–26 characters in length. The number of randomized strings of characters on the screen can vary from 40–300 (see Figure 1).

Figure 1 Visual Sequencing

Visual Span: Children are shown a series of stimuli (upper or lower case letters, numbers or any combination of both) one at a time. The child is then required to remember the sequence presented and enter it in using the keyboard. To increase difficulty, the child may be required to wait while a distracting animation (a moving bird, balloon or fish) is presented before inputting the response. The sequence length may be range from 2 to 6 characters and the stimulus size may be large to medium. The child must answer correctly 70% of the time in order to advance to the next level (see

Figure 2).

Figure 2 Visual Span

Visual Scan: Children are to select a symbol (letter, number or symbol) of one type found in an array of randomly placed characters or symbols. To advance to the next level, the child must make fewer than 4 errors per trial in less than 3-4 minutes. More time is allowed for smaller sized targets (e.g. large, 3 min; medium, 3.5 min; and small,

4 min). Complexity can be increased by varying the type of stimuli presented (e.g. all lower or upper case letters, all numbers, all symbols, or any combination of letters, numbers and symbols). The number of targets to be found can be increased and the target size can be decreased from large to small (see Figure 3).

Figure 3 Visual Scan

Visual Sequential Processing: Children are briefly shown a stimulus (a picture, an upper or lower case letter or a number) in a blue box at the center of the screen. The child then attempts to count how many times that particular stimulus is presented as random stimuli are flashed on the screen one at a time. The child must count only the number of times her specified stimulus was shown. The child waits until all stimuli are presented, then enters her total using the keyboard. The child needs to answer correctly 70% of the time in order to advance to the next level. Complexity can vary by stimulus size

(medium or large), speed of presentation (7 speeds, slow to fast), number of stimuli presented (20–60), or stimuli placement patterns (fixed location or random location)

(see Figure 4).

Figure 4 Visual Sequential Processing

Visual Search: The child is presented with a list of randomized sequences and is instructed to locate only those sequences that exactly match a given sequence of letters, numbers, symbols, or codes (any combination of numbers, letters, and symbols). The child attempts to find every presentation of the given sequence and is allowed up to 3 misses per exercise in order to advance to the next level. In order to increase complexity, stimulus type can include any number, letter or symbol contained on the keyboard. The length of the sequence can vary from 2–6 characters and the list of randomized sequences can range from as few as 15 to as many as 140 (see Figure 5).

Figure 5 Visual Search

Tachistoscope: A string of random letters is flashed for 0.5 seconds. Children are required to look at all the letters or numbers and replicate the sequence after the stimuli have been removed from the screen. To advance to the next level, the child needs to enter correct responses 70% of the time. The exercise can be varied by presenting upper and lower case letters, numbers and codes (any combination of letters and numbers). In order to increase complexity of the task, stimuli can vary between medium and large sizes. The length of the stimulus can consist of 1–6 characters. Presentation speed can be increased to 0.25 seconds. And, a moving distracter (bird, balloon or fish) may be presented between the time the stimulus is presented and the time the child is allowed to enter his/her answer (see Figure 6).

Figure 6 Tachistoscope

Visual-visual integration: The child is required to memorize a dot and/or dash sequence presented on the screen one dot or dash at a time. At the end of the presented stimuli, the child is required to identify a comparable pattern displayed in a multiple choice format.

The child advances to the next level when she correctly identifies the sequence 70% of the time. The difficulty of the task can vary by increasing the number of stimuli presented, the groupings in which they are presented (e.g. a sequence can be composed of 3 groupings of stimuli with a pause between each group) and the number of multiple choice answers offered (up to 8 choices) (see figure 7).

Figure 7 Visual-visual Integration

Parafoveal stimulation: Using a working distance equivalent to the distance between the child’s elbow and knuckles known as the Harmon distance, the child attempts to identify pairs of letters flashed on the screen while focusing on a central red dot. The dot is randomly presented on left and right inner walls of a central blue box. The child follows the dot by responding with the corresponding right and left arrow keys. At random intervals, a pair of letters is flashed on the screen, one letter inside the box and one just to the right of the box. If the letters match, the child presses the spacebar, if not, the child presses nothing. The child advances to the next level when 70% of stimuli pairs are correctly identified and 70% of fixation targets are correctly entered. Stimuli can vary between upper and lower case letters. Target size can vary between large, medium and small. Presentation speed can vary from 15/60th of a second, to 10/60th of a second, or 5/60th of a second (see Figure 8).

Figure 8 Parafoveal stimulation

Visual Closure: The child attempts to identify incomplete stimuli (line drawings, photographs, upper and lower case letters, or numbers) as quickly as possible. The stimulus is revealed progressively in block segments from 1% to 100% completeness.

However, to advanced to the next level, the child must correctly respond before more than 30% (small blocks setting) is revealed in order to obtain a correct response.

Overall, the child must correctly respond 70% of the time. Block size also can be varied.

The maximum percentage that may be revealed in order for a response to be counted as correct varies with block size (e.g. small = 30%; medium = 40%, and large = 50%).

Stimuli are varied as described above. The child can respond in a multiple choice format

(with answers presented at once or sequentially) or by typing the answer on the keyboard (e.g. upper or lower case letters or numbers) (see Figure 9).

Figure 9 Visual Closure

Visual Concentration: The child attempts to tie or beat the computer by correctly matching hidden pictures which are revealed one at a time. The child chooses a square in the grid and clicks on it revealing the picture underneath. The child then chooses another square in the grid. If both pictures match, the child receives one point. If they do not match, the squares are again hidden and the computer then chooses two tiles to attempt a match. Play proceeds from computer to child until all matches are made. If the child has more points or ties the computer then she wins that round. Difficulty can be varied with grid size (total number of boxes in grid range from 6–40), by computer skill level (average or above average) and by stimulus option (pictures, upper and lower case letters, numbers, and symbols). The child must win 70% of the games played to advance to the next level (see Figure 10).

Figure 10 Visual Concentration

Visual Motor integration: Children are trained by moving a slider at the bottom of the screen to hit a moving ball which descends diagonally from the top of the screen and bounces off walls and other distracting objects like spaceships and satellites. The slider is controlled by right and left movements of the mouse. The ball speed can vary, and distracting elements (e.g. moving objects, fixed objects, or a moving wall) can be added to increase complexity of the task. The slider can also vary in size (4 sizes from small to very large). The goal of the exercise is to hit the ball as many times as possible, hitting the moving ball with the slider at least 30 times in an exercise to advance to the next level (see Figure 11).

Figure 11 Visual-motor Integration

The PTS II, according to the author, has been based on the percepto-cognitive theory developed by Alexander Luria and Naglieri and Das. This theory suggested that visual information processing generally is divided into two major elements: sequential processing and simultaneous processing. Simultaneous processing involves a perception of things as a whole as they exist in space at one moment. Whereas, sequential processing involves a perception of things through time as they relate in a stepwise fashion.

Groffman suggested a simple analogy to clarify these concepts (Scheiman and Rouse

2006): locating and identifying the spatial configuration of the Big Dipper as it relates to the observer in the sky would demonstrate simultaneous processing. Whereas the process of counting the stars in the constellation in order one by one requires sequential processing.

Additional aspects of perception, namely temporal vision perceptual processing and rapid automatized naming (RAN), have also been addressed within the PTS II. It has been theorized that temporal vision perceptual processing helps with reading by maintaining accurate visual perception even as one’s eyes move rapidly from word to word allowing the reader to be both attentive to the next word on the page as well as accurately perceive the symbols on the page and understand their meaning. The importance of speed in processing has been based upon Rapid Automatized Naming (RAN) research with regard to dyslexia. This research has suggested that the more automatic our perception of simpler segments of data like letters or phonemes the faster our reading and comprehension can be. Each PTS procedure has been designed to address one or more of these areas of perception (see Table 7).

Visual Temporal Speed RAN Processing Processing Processing Parafoveal Stimulation X X

Tachistoscope X X X

Visual closure X

Visual Concentration X

Visual Scan X X X

Visual Search X X X

Visual Sequencing X X X X Visual Sequential Processing X X X X Visual Span X X

Visual-Motor Integration X X

Visual-visual Integration X X

Table 7 The PTS II program elements as they relate to various perceptual areas.

Procedures for outcome testing

At the completion of the therapy, children returned to complete final testing which included the same battery of visual perceptual tests presented at the baseline visit. Parents were again given the Conners’ questionnaire test to complete.

Statistical Analysis

All statistics were generated with SPSS Statistics 17.0 for Windows. Means, standard deviations, and medians for baseline and outcome testing were generated. Standard, t- scores, or scaled scores were used in all analyses. An alpha of 0.05 was used as the level of significance for all tests. A Mann-Whitney nonparametric test was run to compare the

42 median baseline score of children who completed therapy to the median score of children who did not complete the therapy. One-sample t-tests were performed to compare the baseline and outcome scores of participating children to normative values. A Wilcoxon

Signed-Rank test, using exact testing, was performed to evaluate change between baseline testing and outcome testing. A multilinear regression was performed as a secondary analysis to determine whether the change in test scores was related to compliance while controlling for age and baseline testing.

Chapter 3: Results

Subjects

Twenty children were recruited and enrolled (mean age 9.7 years) from the Pediatrics

Service at The Ohio State University College of Optometry and from referrals from local optometrists. Sixteen children (75%), (9 females [56.25%], 7 males [43.75%]) with a mean age of 9.6 years old (range: 6. 7 – 12.9 years), completed the study. Even though children who performed poorly on the VMI alone were not excluded specifically

(suggesting a motor deficit), no child demonstrated such a deficit. Two children, whose parents reported difficulty motivating their child, withdrew from the study. An additional two children failed to return for outcome testing and were lost to follow up.

The median baseline score of children who completed therapy (n=16) was similar to the median score of children who did not (n=4) (Mann-Whitney, p ≥ 0.12 for all comparisons) (see Table 8). Although there were no statistically significant differences between those who completed the study and those who did not, the Conners’

Hyperactivity scale scores were more than one standard deviation higher in children who did not complete the study (indicating a greater frequency of hyperactive behaviors). However, parents of children who did not complete the study also reported fewer oppositional behaviors. In addition, children who did not complete the study

44 scored, on average, one standard deviation lower on the TVPS-3 Visual Memory subtest but one standard deviation higher on the TVPS-3 Visual Sequential Memory subtest.

Median at Baseline Mann- Children Children Exact Sig. Variable IQR Whitney Completed Lost (2-tailed) (n=20) U (n=16) (n=4) Age 9.8 10.6 4.0 26.0 .617 Conners' Oppositional 55.0 43.5 20.8 20.0 .280 (T-scores) Conners' Cognitive Problems/Inattention 67.5 72.0 13.3 23.0 .420 (T-scores) Conners' Hyperactivity 52.5 65.5 19.8 26.5 .631 (T-scores) Conners' ADHD Index 68.0 70.0 21.8 28.5 .769 (T-scores) VMI 88.0 90.0 12.5 29.0 .800 (Standard Scores) VP 96.0 89.0 9.5 15.0 .115 (Standard Scores) TVPS-3 Visual Discrimination 82.5 82.5 17.5 27.0 .667 (Standard Scores) TVPS-3 Visual Memory 95.0 80.0 35.0 23.5 .447 (Standard Scores) TVPS-3 Visual Sequential 87.5 102.5 25.0 22.5 .399 Memory (Standard Scores) CAS Figure Memory 9.0 8.0 3.8 24.0 .497 (Scaled Score) KBIT-2 Verbal Score 95.0 99.5 10.5 22.5 .396 (Standard Scores) KBIT-2 Non-verbal Score 91.5 93.0 16.5 32.0 1.000 (Standard Scores) IQR = Interquartile Range Table 8 Comparison of baseline scores between complete and incomplete groups

Baseline and outcome data are presented in tables 9 and 11 respectively. At baseline, children scored, on average, significantly above the mean on the Conners’ Cognitive

Problems/Inattention scale (p = .000002), Hyperactivity scale (p = 0.03), and ADHD

Index (p = .00001), indicating a higher frequency of problem behaviors. Children scored significantly below the mean on all visual perceptual tests (p ≤ 0.03 for all analyses) except the TVPS-3 Visual Memory subtest (p = 0.28) and the Cognitive Assessment

System (CAS) Figure Memory subtest (p = 0.13). Children also scored below the mean on the KBIT-2 Non-verbal (p = 0.06) at baseline (see Table 10). Overall, excluding those who did not finish the study, the children completed an average of 59.5 sessions (one session equal to 4 exercises) (range: 10.8 – 99.0 sessions). The outcome exam occurred on average at 19.5 weeks (range: 15.6 to 28.1 weeks). Twelve of the children had the same parent complete both baseline and outcome Conners’ questionnaires. The other four children had both parents participate at baseline and then only one parent at outcome testing. At outcome testing, scores remained, on average, significantly above the mean on the Conners’ Cognitive Problems/Inattention scale and ADHD Index (p = .0007 for both analyses) and significantly below the mean for the VMI, VP and TVPS-3 Visual

Sequential Memory subtest (p ≤ 0.02 for all analyses) (see Table 12).

Conner’s Beery TVPS KBIT CAS (T score) (Std Score) (Std Score) (Std Score) (Scale) Age Opp Cog Hyper ADHD VMI VP VD VM VSM Verb NV FM 1 46 56 44 55 91 97 125 75 115 114 54 13 7.8 2 59 77 73 76 88 104 120 65 80 108 110 10 9.8 3 71 70 66 68 77 95 100 95 70 103 119 8 7.5 4 69 72 65 64 104 97 100 90 80 95 87 9 10.3 5 44 56 45 68 80 98 90 90 105 101 91 11 9.8 6 61 64 50 55 86 98 80 105 85 89 116 11 11.0 7 44 73 45 76 105 93 85 120 80 93 81 9 10.1 8 64 65 48 74 88 93 80 110 95 97 93 10 12.9 9 68 75 46 77 79 78 70 55 55 94 68 8 12.1 10 40 62 50 52 90 80 90 70 55 95 92 6 8.1 11 44 76 64 77 87 98 80 125 90 96 101 7 10.0 12 40 65 52 65 100 108 70 90 95 106 98 11 12.6 13 51 55 58 53 86 94 60 95 55 92 84 5 7.1 14 45 56 53 53 90 100 80 115 110 77 100 8 9.4 15 61 77 63 71 76 88 85 110 115 88 85 4 7.8 16 68 86 72 81 106 90 70 100 110 86 87 13 6.7 Mean 54.6 67.8 55.9 66.6 89.6 94.4 86.6 94.4 87.2 95.9 91.6 8.9 9.6 SD 11.5 9.4 10.0 10.1 9.7 7.8 17.7 20.2 21.0 9.1 16.6 2.6 2.0 S Score = Standard Score; FM = Figure Memory; Scale = Scaled Score; Opp = Oppositional; Cog = Cognitive Problems/Inattention; Hyper = Hyperactivity; VMI = Visual-motor Integration; VP = Visual Perception; VD = Visual Discrimination; VM = Visual Memory; VSM = Visual Sequential Memory; Verb = Verbal; NV = Non-verbal; SD = Standard Deviation; Table 9 Baseline testing values

Variable Mean SD Norm Significance Conners' Oppositional 54.7 11.5 50 0.12 (T-scores) Conners' Cognitive Problems/Inattention 67.8 9.4 50 0.000002* (T-scores) Conners' Hyperactivity 55.9 10.0 50 0.03* (T-scores) Conners' ADHD Index 66.6 10.1 50 0.00001* (T-scores) VMI 89.6 9.7 100 0.0006* (Standard Scores) VP 94.4 7.8 100 0.01* (Standard Scores) TVPS-3 Visual Discrimination 86.6 17.7 100 0.008* (Standard Scores) TVPS-3 Visual Memory 94.4 20.2 100 0.28 (Standard Scores) TVPS-3 Visual Sequential Memory 87.2 21.0 100 0.03* (Standard Scores) CAS Figure Memory 8.9 2.6 10 0.13 (Scaled Scores) KBIT-2 Verbal Score 95.9 9.1 100 0.09 (Standard Scores) KBIT-2 Non-verbal Score 91.6 16.6 100 0.06** (Standard Scores) SD = Standard Deviation; Norm = Normative mean; *significance p ≤ 0.05 **trend toward significance Table 10 Baseline data compared to normative values

Conner’s Beery TVPS Compliance CAS (No. (T Score) (S Score) (S Score) (Scale) Sessions) Opp Cog Hyper ADHD VMI VP VD VM VSM FM 1 93.5 40 47 47 48 92 85 95 115 75 10 2 56.8 61 65 82 68 84 93 125 80 95 13 3 99.0 65 68 61 64 97 93 90 95 65 5 4 57.0 72 73 67 69 102 98 110 100 95 13 5 48.0 41 47 50 53 85 71 95 100 85 12 6 28.0 55 53 45 52 96 110 80 85 120 14 7 61.5 41 70 50 65 97 99 85 70 90 10 8 58.8 56 69 52 72 85 72 100 100 85 11 9 70.3 59 64 46 66 90 86 80 90 60 7 10 30.8 40 59 50 55 106 70 80 80 55 9 11 77.3 55 61 60 65 90 93 80 110 90 4 12 71.0 43 53 59 59 94 97 95 100 100 7 13 10.8 48 46 45 42 82 100 75 110 105 5 14 60.0 42 56 44 55 96 104 130 105 70 9 15 51.5 52 56 60 55 75 80 75 75 90 5 16 78.5 52 59 47 55 119 89 75 90 60 14 Mean 59.5 51.4 59.1 54.1 58.9 93.1 90.0 91.9 94.1 83.8 9.25 SD 23.2 9.8 8.6 10.2 8.4 10.5 12.0 17.2 13.3 18.2 3.4 S Score = Standard Score; FM = Figure Memory; Scale = Scaled Score; Opp = Oppositional; Cog = Cognitive Problems/Inattention; Hyper = Hyperactivity; VMI = Visual-motor Integration; VP = Visual Perception; VD = Visual Discrimination; VM = Visual Memory; VSM = Visual Sequential Memory; Verb = Verbal; NV = Non-verbal; SD = Standard Deviation; Table 11 Outcome testing values

Variable Mean SD Norm Significance

Conners' Oppositional 51.4 9.8 50 0.58 (T-scores) Conners' Cognitive Problems/Inattention 59.1 8.6 50 0.0007* (T-scores) Conners' Hyperactivity 54.1 10.3 50 0.13 (T-scores) Conners' ADHD Index 58.9 8.4 50 0.0007* (T-scores) VMI 93.1 10.5 100 0.02* (Standard Scores) VP 90.0 12.0 100 0.004* (Standard Scores) TVPS-3 Visual Discrimination 91.9 17.2 100 0.08 (Standard Scores) TVPS-3 Visual Memory 94.1 13.3 100 0.09 (Standard Scores) TVPS-3 Visual Sequential Memory 83.8 18.2 100 0.003* (Standard Scores) CAS Figure Memory 9.3 3.4 10 0.40 (Scaled Scores) SD = Standard Deviation; Norm = Normative mean; *significance p ≤ 0.05 Table 12 Outcome data compared to normative values

In order to determine if any significant changes occurred between baseline and outcome testing, a Wilcoxon Signed-Rank test, using exact testing, was performed. A significant improvement, as demonstrated by a reduction in score levels, was noted in the Conners’

Oppositional scale (p = 0.04), the Conners’ Cognitive Problems/Inattention scale (p = 50

0.001) and the Conners’ ADHD Index (p = 0.002). No other significant changes were found (see Table 13).

Mean at Mean at Z - Exact Sig. Variable Baseline Outcome statistic (2-tailed) Conners' Oppositional 54.69 51.38 -2.061a 0.04* (T-scores) Conners' Cognitive Problems/Inattention 67.81 59.13 -3.071a 0.001* (T-scores) Conners' Hyperactivity 55.88 54.06 -.504a .637 (T-scores) Conners' ADHD Index 66.56 58.94 -2.950a 0.002* (T-scores) VMI 89.56 93.13 -1.319b .198 (Standard Scores) VP 94.44 90.00 -1.423a .163 (Standard Scores) TVPS-3 Visual Discrimination 86.56 91.88 -1.091b .299 (Standard Scores) TVPS-3 Visual Memory 94.38 94.06 -1.158b .270 (Standard Scores) TVPS-3 Visual Sequential Memory 87.19 83.75 -.472a .656 (Standard Scores) CAS Figure Memory 8.94 9.25 -.579b .583 (Scaled Score) *significance p ≤ 0.05 a Based on negative ranks b Based on positive ranks Table 13 Improvement with Conners' behavioral testing

Compliance was evaluated weekly by totaling the number of sessions (four exercises per session) completed each week. This evaluation was the most accurate manner in which to measure compliance, as the PTS II administers all exercises in subsequent therapy sessions even if a session is interrupted prematurely. Generally, a child with good or poor compliance in the first two weeks of therapy demonstrated similar compliance throughout the study. All children displayed a tapering of compliance after approximately 7 to 20 weeks. Because compliance varied, a multilinear regression was performed to determine if the level of compliance related to change in performance. Age and baseline testing scores were controlled for in the analysis. A significant negative linear relationship between compliance and the change in performance on the TVPS-3 Visual Sequential

Memory subtest was found (B = -0.44; p = 0.04). Also, CAS Figure Memory scores demonstrated a significant negative linear relationship (B = -0.08; p = 0.01), No other significant relationships between compliance and change in score were found (p ≥ 0.35 for all comparisons) (see Table 14).

Change (Outcome - Baseline) Variables Slope Sig. Age 0.81 0.31 Conners' Oppositional Compliance 0.01 0.94 (T-scores) Baseline -0.28 0.06** Age 1.37 0.17 Conners' Cognitive Problems/Inattention Compliance 0.04 0.65 (T-scores) Baseline -0.49 0.04* Age 2.23 0.07** Conners' Hyperactivity Compliance 0.03 0.70 (T-scores) Baseline -0.17 0.07** Age 2.04 0.02* Conners' ADHD Index Compliance 0.07 0.35 (T-scores) Baseline -0.62 0.003* Age -1.36 0.23 VMI Compliance 0.08 0.40 (Standard Scores) Baseline -0.29 0.20 Age -0.40 0.80 VP Compliance -0.06 0.64 (Standard Scores) Baseline -0.23 0.58 Age 3.21 0.15 TVPS-3 Visual Discrimination Compliance -0.04 0.82 (Standard Scores) Baseline -0.45 0.10 Age -0.05 0.98 TVPS-3 Visual Memory Compliance 0.12 0.48 (Standard Scores) Baseline -0.96 0.0002* Age 3.07 0.18 TVPS-3 Visual Sequential Memory Compliance -0.44 0.04* (Standard Scores) Baseline -0.76 0.004* Age -0.09 0.75 CAS Figure Memory Compliance -0.08 0.01* (Scaled Scores) Baseline 0.21 0.39 *significance p ≤ 0.05 **trend toward significance Table 14 Linear relationship between test scores and compliance

Software Issues

All software issues were quickly corrected by referral to the HTS software technical support. Children were consistently able to continue therapy with minimal interruption.

However, some patients reported having completed up to 6 sessions which had not been recorded by the software.

At no time was the software’s automatic setting altered or adjusted for any child, except in one case when the child completed the target levels for every exercise as determined by the automatic program prior to the 16 week outcome visit. In this case, the program was changed to manual mode and target goals were maximized for every exercise.

Because the manual mode does not provide an automatic list of exercises to perform each day, the child was asked to select the programs in the order they appeared on the program interface, doing 3 separate exercises per day, 5 days per week.

Chapter 4: Discussion

This pilot study investigated whether home-based perceptual therapy using the PTS II improved performance on standardized tests of visual perception and decreased frequency of any problem behaviors as reported on a standardized parent rating scale in children with below age normal performance on a standardized test of visual perception.

This study showed a significant decrease in the frequency of parent reported problem behaviors (Oppositional scale, Cognitive Problems/Inattention scale, and ADHD Index) as assessed by the Conners’. However, no statistically significant improvements were found in performance on standardized tests of visual perception including the VMI, the

VP, or the TVPS-3 (Visual Discrimination, Visual Memory, or Visual Sequential

Memory subtests).

It is not possible to directly compare the results of this study with those of previous studies which have investigated the effect of visual perceptual therapy due to methodological differences such as involving office- rather than home-based therapy and/or evaluating the effect of therapy on academic achievement or processing skills rather than specifically on visual perceptual skill.

A number of reasons could explain the lack of improvement found with the visual perceptual tests used in this study. The lack of improvement may be due to differences in the effectiveness of home- versus office-based therapy. However, Groffman reported significant improvements in visual perceptual processing following therapy with the PTS

II. The lack of a significant improvement on the TVPS-3 subtests may have been attributed to the wide variability found in the TVPS-3 subtest scores. While the TVPS-3 manual reports moderate subtest test-retest reliability, a previous study reported poor test- retest reliability within subtests in children with reading disabilities (McFall, Deitz et al.

1993). As well, the failure to find a significant improvement on the VMI and the VP may have been due to poor alignment between the PTS II therapy program and the tests.

However, regardless of the therapy and test alignment, improvements in visual perceptual skill should still be expected to result in improvements in visual perception testing performance.

The significant decrease in the parent reported frequency of problem behaviors

(Oppositional scale, Cognitive Problems/Inattention scale, and the ADHD Index]) may be attributable to a treatment effect from the therapy, a placebo effect, or regression to the mean. If a real treatment effect exists, it is possible that reports of significant improvements in academic performance and/or processing skills with relation to perceptual therapy, may be mediated by improved attention rather than improved visual perceptual skill. Inclusion of a control group should be considered in future research. In

56 addition, long-term follow-up is needed to determine whether any improvements are maintained.

The loss of patients to withdrawal or to follow-up was high and may have been attributed to a lack of interest in the PTS II. This was supported by the parental report concerning their child’s performance and the low compliance levels demonstrated by the two children who were lost to follow-up. Although there were no statistically significant differences between those who completed the study and those who did not, the average

Conners’ Hyperactivity scale score was more than one standard deviation higher among children who did not complete the study and the average Cognitive Problems/Inattention scale score was 0.45 standard deviations higher. This suggests that the children who failed to complete the study had a greater frequency of hyperactive behaviors or attention difficulties, which may have made it harder for them to complete the therapy. Further research should include a more in-depth evaluation of attention.

When comparing the change in test scores with compliance while controlling for age and baseline test scores, a significant negative linear relationship was found between compliance and the TVPS-3 Visual Sequential Memory subtest scores (B = -0.44; p =

0.04) and between compliance and the CAS Figure Memory scores (B = -0.08; p = 0.01).

Additional research involving a larger sample size is needed to further investigate the effect of PTS therapy on visual memory skill.

While therapy was regularly monitored remotely, families were not brought in for a follow-up visit at 2 weeks as suggested by the manufacturer and it is not known whether children would have performed better given an additional visit to demonstrate and review the program. Although many of the children were initially excited to begin the therapy it seems that many, if not all, had lost interest in the program by the end of the 16 weeks.

Although the software program is intended to keep the child’s interest through increasingly challenging and interactive exercises, it is possible that the automated mode

(as used in this study due to manufacturer recommendations) may cause a child to lose interest as they get closer to reaching their target levels. In this mode, the child will quickly finish procedures he/she does well. Then, rather than occasionally interspersing a few of these procedures, the program only offers the procedures that are still below target level, which most likely, are the exercises the child struggles with or dislikes; this may cause the child to lose interest in doing the therapy altogether. Future studies should weigh the advantages and disadvantages of using the standardized, automated mode versus using the manual mode to create a more individualized therapy program.

Chapter 5: Conclusions

The use of the PTS II resulted in a decreased frequency of problem behaviors as reported by parents on the Conners’. No significant changes in visual perceptual skills were found with the TVPS-3, VMI or VP. Further research is needed with a larger sample size and a control group to control for potential placebo effects. In addition, a test battery which includes an expanded assessment of visual perceptual skill, attention and cognitive processing is suggested for future studies.

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