Neuropsychological Function for Accessibility of Computer Program for People with Mental Retardation Alex W.W. Wong1, Chetwyn C.H. Chan1, Cecilia W.P. Li-Tsang2, and Chow S. Lam3 1
Ergonomics and Human Performance Laboratory, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong {alex.wk.wong,rschchan}@polyu.edu.hk 2 Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong
[email protected] 3 Institute of Psychology, Illinois Institute of Technology, Chicago, Illinois, USA
[email protected]
Abstract. The extent to which people with mental retardation are benefit from the modern information technology is not well explored. A better understanding on ways that the existing human-computer interface would challenge people with mental retardation would shed light on this issue. This study was investigated the neuropsychological functions which are important for enhancing the competence of people with mental retardation to operate on the Internet Explorer (IE) program. Sixty-two participants with mental retardation were invited to conduct a set of neuropsychological tests. Their computer performance was also evaluated. Resulted indicated that some specific neuropsychological functions including attention and visual scanning, psychomotor and language were predictive of their overall computer competence. The implication on ways to improve the design for computer programs for this population was discussed.
1 Introduction Access to computing technology has become important in our lives. The contribution of information technology has increased people with mental retardation successful integration into community [1]. However, the design of existing information technology remains underutilized by people with mental retardation. Some studies suggested that the cognitive demands to operate these computer systems were not accommodated the needs of the people with mental retardation which in turn interfere their use and learn most of existing computer systems [2]. The theoretical model of human information processing for human-computer interaction is used as a basis from which to make prediction about participants’ computer performance and investigate which cognitive processes are importantly involved when they interact with the computer [3]. The central theme of this model is that human is like an active information processor in which the human performance, from displayed information to response, is a function of several processing stages including stimulus identification, response selection and response execution. Interacting with K. Miesenberger et al. (Eds.): ICCHP 2004, LNCS 3118, pp. 1062–1068, 2004. © Springer-Verlag Berlin Heidelberg 2004
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the web browser and operating system required the user to identify displayed information e.g. menus, scrollbars, or icons (stimulus identification), to select responses based on the displayed information (response selection), and to executive those response e.g. clicking the icon via mouse button (response execution). These processes when the user interacts with the computer required to devote different extent of cognitive resources. For example, the user must search the displayed information and attend to the appropriate aspects of it. The user must also recall the commands, remember information specific to the task that is being performed, and make decisions and solve problems during the process [4]. These task demands seemed not to fit the lower neuropsychological profiles of people with mental retardation. The promise of technological design should be explicitly considered the cognitive compatibility of ultimate users [5]. In order to design a user-centered interface which is matched with the user’s information processing capabilities, it is worthwhile to explore how neuropsychological functions to attribute people with mental retardation to operate IE program. The purpose of this study sought to determine the relative importance of neuropsychological functions in predicting the computer competence in the people with mental retardation. It will also shed light on ways to improve the design of the computer technologies to fit the profiles of this population.
2 Method 2.1 Participants Total 62 participants with mental retardation were available for this study. They were recruited from those who enrolled computer training program designed for people with mental handicapped held in The Hong Kong Polytechnic University. To reduce any training effect of this program, they were invited to participate in this study before the training program was started. As part of their participations in our institutions, ethical approval was obtained and informed written consent was obtained from all their guardians. All the subjects were selected from the following criteria: 1) an ability to follow instructions; 2) an absence of identified organic etiology or secondary diagnoses; and 3) an non-verbal intelligence quotient score from the Test of Non-verbal Intelligence (TONI-3) ranged from 55 to 80. They were then classified into high (n=33) and low (n=29) IQ groups (cut-off score= 70). Demographic characteristics for the two groups are presented in Table 1. They were youths and only 29% of them were adults (18 years of age or older). They averaged about 17.37 years of age and had used computers, on average, for about 4.1 years on the time of this study. Table 1. Demographic characteristics of participants.
Age (years) Education (years) Computer usage (hrs/wk) Gender Male Female
Mean
SD
17.37 7.44 4.10
5.98 1.78 2.83
40 22
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2.2 Experimental Materials and Procedures IE Competence Test. The demographic characteristics of participants were gathered and TONI-3 was conducted before the commencement of IE competence test. The IE competence test consisted of 16 IE-related tasks which was validated by an expert panel consisted of 9 professionals working in mental retardation field with a mean of 7.1 years (SD= 4.41). These tasks constituted a total of 161 subtasks which are used as the test items for assessing the computer competence on using IE. The reliability of these tasks was from moderate to good in which the ICC values ranged from 0.69 to 0.99. The discriminative method of this test based on two of 16 tasks (Use customized bookmark & General motor function) for differentiating people with mental retardation into three competence groups was also produced [6]. The participants were instructed to sit in front of the computer running with Window XP operating system and Microsoft’s Internet Explorer 6.0 for the IE competence test. The tasks were administered in random sequence for each participant. Standardized instructions and ultimate goals on each of the sixteen tasks were given by the first author before the participants performed each of the tasks. The participants’ performance on each of the test items was observed and rated on a four-point scale with “1” indicated “complete assistance”, “2” indicated “performance with verbal and physical prompts”, “3” indicated “performance with verbal prompts” and “4” indicated “competent performance”. It took approximately 40-60 min per subject to complete. Neuropsychological Testing. After the IE competence test, the neuropsychological assessments were conducted. Six cognitive domains including attention, visualspatial, language, memory/ working memory, reasoning/ executive function, and psychomotor functions were selected. All subjects were administered the neuropsychological tests in a random order. All assessments were administered by the first author who was trained on the administration and scoring criteria of both tests by a certified neuropsychologist. The standardized instructions were given throughout the tests. The time to complete all tests is around 2 hours per subject. The following is the tests with regard to primary cognitive domains: Attention. Digit Span Forward (DSF) (span & sequence scores), Part A of Trail Making Test (TMT) (total time), Sustained Attention to Response Task (SART) (commission error), Digit Vigilance Test (DVT) (omission error) & Symbol Digit Modalities Test (SDMT) (total score). Visual-Spatial. Judgment of Line Orientation (JLO) (correct score), Chinese version of Neurobehavioral Cognitive Status Examination (Cognistat) (Construction subtest score), and Hooper Visual Organization Test (HVOT) (total score). Language. Cognistat (Comprehension, Repetitive, and Naming subtests scores), and Chinese Characters Test (CCT) (total score). Memory/Working Memory. Cognistat (Memory subtest score) and Digit Span Backward (DSB) (span & sequence scores).
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Reasoning/Executive Function. Cognistat (Similarities and Judgment subtests scores), TMT (interference time score) and Chinese version of the Stroop Color-Word Test (Victoria Version) (CST) (interference time score). Psychomotor. McCarron Assessment of Neuromuscular Development (MAND) (fine motor & gross motor scores), Development Test of Visual-Motor Integration (VMI) (total score) and Purdue Pegboard (PP) (dominant hand, nondominant hand, both hands, & assembly scores).
3 Statistical Analysis and Results The mean task score of the 16 IE competence test was computed. These 16 IE task scores were then summated to derive the global IE competence score. Possible scores of global IE competence range from a minimum of 0 to a maximum of 644, with higher scores reflecting higher overall competence in computer utilization. A series of stepwise multiple regression analyses were conducted to examine the overall IE competence as dependent variable and the neuropsychological test scores in each of the cognitive domains as predictors in the sample with mental retardation. To determine the relative importance of neuropsychological domains in predicting IE competence, separate multiple regression analyses in each of the six domains on the global IE competence score were conducted. For attention domain, the SDMT was first entered. This was followed by the DSF-Span, the SART and the DVT. All predictors in the equation were significant [total R2 = .609, Model F(4, 57) = 22.196, p
