05 Apr Read the following 3 articles and synthesize (Combine the ideas of all three sources into one overall point – DO NOT SUMMARIZE) ?
Read the following 3 articles and synthesize (Combine the ideas of all three sources into one overall point – DO NOT SUMMARIZE) them into 1 and half page word document. Also, write a well elaborated question from each reading. Keep in mind the following points when working on this task:
*Questions must be original, thought and not easily found in the articles.
*Follow APA Rules
*Use proper citations
*Use PAST TENSE when discussing the articles (Research already took place)
*DO NOT USE the following words: Me, you, I, we.
*Refer to the articles by their AUTHORS (year of publication)
*DO NOT USE the article name or words first, second, or third.
*DO NOT SUMMARIZE!!!
***MUST FOLLOW ATTACHED SAMPLE
Two Factor Model of ASD Symptoms
One of the key factors in determining whether an individual has Autism Spectrum Disorder (ASD) is in their social and communication skills. Individuals who are diagnosed with ASD have delayed joint attention, eye gazing, and other social interactions such as pointing (Swain et al., 2014).
Joint attention is an important social skill to master because it is a building block for developing theory of mind which, helps us to understand other’s perspectives. Korhonen et al. (2014) found that individuals with autism have impaired joint attention. However, some did not show impairment in joint attention, which lead to evidence that suggests there are different trajectories for joint attention. One suggestion as to why Korhonen et al. (2014) found mixed results, is that there is evidence that joint attention may not be directly linked to individuals with ASD since they were unable to find a difference in joint attention between ASD and developmentally delayed (DD) individuals. Another suggestion for the mixed results, is individual interest in the task vary. Research has found that while individualized studies are beneficial in detecting personal potential and abilities, it would be difficult to generalize the study in order to further research to ASD as a whole (Korhonen et al., 2014). In addition to joint attention, atypical gaze shifts is a distinguishing factor in individuals with ASD. Swain et al. (2014) found the main difference between typically developing (TD) and ASD individuals in the first 12 months of life is in gaze shifts. Individuals that were diagnosed with ASD earlier had lower scores on positive affect, joint attention, and gaze shifts, however those diagnosed later differed from typically developing (TD) only in gaze shifts. It is not until 24 months that later onset ASD individuals significantly differ from their TD peers, by displaying lower positive affect and gestures (Swain et al., 2014). These findings may lead to other ASD trajectories.
Another defining characteristic of ASD is the excess of restrictive patterns of interest and repetitive motor movements. These patterns and movements often impaired the individual from completing daily tasks. Like joint attention and gaze shifts, these repetitive movements and patterns of interest have different trajectories (Joseph et al., 2013). Joseph et al. (2013) found that individuals with high cognitive functioning ASD engage in more distinct and specific interests and less in repetitive motor movements than individuals with lower cognitive functioning ASD. Another finding showed that at the age of two, repetitive motor and play patterns were more common than compulsion. By the age of four all these behaviors increased however, repetitive use of specific objects was found to be less frequent in older children than younger children. This finding suggests that the ritualistic behaviors and motor movements may present themselves differently based on the age of the individual (Joseph et al., 2013).
Joseph et al. (2013), Korhornen et al. (2014), and Swain et al. (2014) all defined key characteristics of an ASD individual and explains the different trajectories of each characteristic. The difficulty with the trajectories is that it is specific to each individual, some symptoms may worsen while others remain stable. It is also difficult to generalize finding with small sample sizes (Joseph et al., 2013).
Discussion Questions:
1. Korhonen et al. (2014) did not use preference-based stimuli to look for joint attention and did not separate high- from low-functioning ASD individuals. Do you think that there could be a difference in level of motivation from each group? If so, how do you think this could change the results?
2. Swain et al. (2014) found that early and late onset of ASD did not differ in their social skills scores at the age of 12 months. If we know that their social skills do not differ then, is there another factor that would allow diagnosis of late onset ASD to be diagnosed at an earlier point in development?
3. Joseph et al. (2013) explains that it is difficult to assess the trajectories of ASD with a small sample size however, how do you think that their findings still help advance the research on ASD?
,
Focus on Autism and Other Developmental Disabilities 2015, Vol. 30(3) 174 –181 © Hammill Institute on Disabilities 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1088357614537353 focus.sagepub.com
Article
The use of information and communication technologies (ICTs), such as iPad (Apple Computer Inc., 2012) and tablet applications, as a platform to assist in the education and skill development of children with autism spectrum disor- der (ASD) is a relatively new area of investigation. Nevertheless, anecdotal evidence supports the potential usefulness of such applications (Attwood, 2003; Jowett, Moore, & Anderson, 2012; Ploog, Scharf, Nelson, & Brooks, 2013). Furthermore, ICTs such as iPad applications are potentially a time- and cost-effective, innovative, and widely accessible form of intervention (Abdullah & Brereton, 2012; Strain, Schwartz, & Barton, 2011). To assess the potential impact that new generation devices such as iPads have for children with ASD, it is necessary to explore the attitudes and behaviors of their parents and the professionals who work with these children toward this modality. The attitudes of parents and professionals are likely to be related to the degree to which children with ASD are encouraged and supported to use such technology for the purposes of education, behavior change, and/or skills development.
As methods of diagnosis for ASD become increasingly refined, diagnosis can occur as early as 18 months of age. This has created additional demand for early intervention for children with ASD. Early intervention typically refers to a series of individualized programs designed to meet the developmental needs and goals of the specific child (Ben
Itzchak & Zachor, 2011). Although early intervention has positive outcomes for children with ASD, the high cost associated with these therapies place financial pressure on the health care system and the families of children with ASD (Bailey, Hebbeler, Scarborough, Spiker, & Mallik, 2004).
A number of experimental studies have demonstrated that ICT-based programs are effective and engaging to children with ASD (Hutinger, 1996; Ploog et al., 2013; Rajendran & Mitchell, 2006; Silver & Oakes, 2001; Werry, Dautenhahn, & Harwin, 2001). A recent review of the literature concluded that there is accumulating evidence, albeit limited at this stage, that ICT-based programs can be used in the treatment and education of children with ASD to enhance social, com- municative, and language development, and that such tech- nologies are likely to play a central role in the treatment of children with ASD in coming years (Ploog et al., 2013). A number of factors have been postulated to explain the appeal of ICT for children with ASD: ICT is inherently less socially threatening than face-to-face interactions (Goodwin, 2008;
537353 FOAXXX10.1177/1088357614537353Focus on Autism and Other Developmental DisabilitiesClark et al. research-article2014
1Swinburne University of Technology, Hawthorn, Victoria, Australia 2Deakin University, Melbourne, Victoria, Australia
Corresponding Author: David W. Austin, School of Psychology, Deakin University, 221 Burwood Highway, Burwood, Melbourne, Victoria, 2134, Australia. Email: [email protected]
Professional and Parental Attitudes Toward iPad Application Use in Autism Spectrum Disorder
Megan L. E. Clark, BA1, David W. Austin, PhD2, and Melinda J. Craike, PhD2
Abstract This study explored the attitudes of parents and professionals who work with children with autism spectrum disorder (ASD) toward the utilization of iPads and use of iPad applications by children with ASD. A survey of parents (n = 90) and professionals (n = 31) assessed information and communication technology (ICT) anxiety and self-efficacy, attitude toward ICT and iPad applications, and iPad utilization. Both parents and professionals held positive attitudes toward ICT and iPad use for children with ASD. Parents reported high use of iPads by their children, and professionals reported some, albeit limited, utilization as part of their practice. These findings suggest that iPad applications are not being used by professionals to a degree that is consistent with their favorable attitudes toward them. iPad use has been enthusiastically adopted by many parents; however, there appears a need for training in their use and research to establish an evidence base.
Keywords autism spectrum disorder (ASD), information and communication technologies (ICT), intervention, iPad applications, technology-related anxiety, attitudes, computer self-efficacy, skill level, education, behavior, parents, children, professionals
Clark et al. 175
Rajendran, Mitchell, & Rickards, 2005), the nature of com- munication is more consistent with the autistic style of learn- ing and interaction (Rajendran & Mitchell, 2006), and children with ASD have a strong attraction to, and fascina- tion for, systems of a mechanical nature, given their inherent structure and predictable nature.
Technological advances have led to a shift in the use from more traditional ICT resources such as the computer, to newer mobile devices such as iPads and tablet computers. Touch screen devices such as the iPad are becoming a popu- lar choice for many children (both typically developing and with ASD) and offer many advantages over traditional devices; they are compact, portable, reinforcing (Murdock, Ganz, & Crittendon, 2013), and potentially cost-effective. Research into the effectiveness of iPad applications to deliver interventions for children with developmental disabilities is emerging. A recent systematic review evaluated the use of iPods, iPads, and related devices to deliver educational pro- grams for people with developmental disabilities and found that outcomes were largely positive, suggesting that these devices are viable technological aids for individuals with developmental disabilities (Kagohara et al., 2013). For chil- dren with ASD, exploratory research has examined the effec- tiveness of the iPad as a communication device (Flores et al., 2012), in the delivery of video modeling treatment (Jowett et al., 2012), and a play story to increase dialogue (Murdock et al., 2013). Research to date on the effectiveness of these devices, however, is limited; thus, there should be some cau- tion in their use (Maglione et al., 2012).
The cost-effectiveness of iPad applications contributes to their attractiveness as a mode of delivery for early inter- ventions. Applications are low in cost in comparison with face-to-face educational and therapeutic interventions for ASD. For example, an in-home intensive Applied Behavioral Analysis therapy program can cost between AUS$30,000 and AUS$50,000 per child per annum (Sharpe & Baker, 2007), making this impractical for use in the pub- lic health care or educational systems and inaccessible to many families. More similar to an iPad is an electronic communication device such as the DynaVox Maestro. This is available for approximately AUS$12,000. In contrast, iPad’s retail for less than AUS$1000 and ASD-specific iPad applications can be purchased from between AUS$0.99 (e.g., “Autism Track”) and AUS$200.00 (e.g., “Proloquo2Go”), with several alternatives available at no cost (e.g., “ABA Flashcards”).
Given the potential of iPad applications to enhance and increase the delivery of educational and/or therapeutic interventions to children with ASD, it is time to examine factors that might influence the uptake of such interven- tions. Examination of parental and professional attitudes toward iPads for children with ASD is an important compo- nent of the uptake of this technology since attitudes are typically a strong predictor of subsequent behavior (Kadel,
2005; Wang, Ertmer, & Newby, 2004). To better understand attitudes toward ICT generally, two predictors can be exam- ined: anxiety toward technology and self-efficacy. Early negative ICT experiences are detrimental to overall tech- nology use, creating an exaggerated, negative set of responses and cognitions about one’s ability to use technol- ogy (Brown & Inouye, 1978; Cassidy & Eachus, 2002). Conversely, positive first experiences with ICTs facilitate the development of positive self-beliefs about capabilities, associated with an increase in positive attitudes toward technology. However, even if one encounters a negative first experience with technology, continual exposure and assistance can alleviate some of the anxiety and negative cognitions associated with that experience. An understand- ing of anxiety and self-efficacy will assist in the prediction of attitudes and thus behavior toward ICT.
Although there is minimal research on the attitudes of parents toward the use of iPad applications for their chil- dren’s development, informal commentaries from parents suggest that they are generally viewed positively. Parents express expectations that applications might effectively enhance their children’s growth, communication, cognition, fine and gross motor, and social interactive skills through accessible activities for education and treatment (DeCurtis & Ferrer, 2011).
Professionals who work with children with ASD recog- nize the role that technology may play assisting children to reach therapeutic goals (Attwood, 2003). Despite this, many professionals have expressed concerns regarding imple- menting iPad use into lesson plans and therapy sessions (Gasparini & Culen, 2012). Research in related areas sug- gests that this anxiety toward iPad use might be attributed to a lack of confidence in the selection and use of applications, fearing lack of technological experience and awareness may inhibit children from gaining the maximum benefit from this adaptive technology (Hennessy, Ruthven, & Brindley, 2005).
Educators, support staff, therapists, and parents pro- foundly influence the assimilation of new technologies into education and therapeutic intervention (Smith, Caputi, & Rawstorne, 2000). Therefore, it is important for research to explore the attitudes of those who work with children with ASD as well as the children’s parents. Attitudes will likely affect the extent to which iPad applications are integrated into therapeutic and educational programs delivered both by professionals and, in the home, by parents.
Research Aims
To date, there has been little research into the attitudes of parents and professionals toward the use of iPad applica- tions by children with ASD. The aims of this exploratory study were to (a) examine the attitudes of parents and pro- fessionals (engaged in work with children with ASD)
176 Focus on Autism and Other Developmental Disabilities 30(3)
toward ICT generally and iPad application use specifically, (b) examine the extent to which children with ASD engage in iPad application use in the home and also the extent to which professionals utilize iPads in therapeutic settings, and (c) examine the extent to which education level, tech- nology-related anxiety, and self-efficacy predict attitudes toward ICT generally and iPad application use specifically.
Method
Demographic Information
Parents (n = 90) were asked to provide information regard- ing their age, level of education completed, and their child’s age. Professionals (n = 31) were asked to provide informa- tion on their age and occupation.
The age of parents ranged from 22 to 63 years (Mage = 42 years, SD = 5.75). Most parents had an undergraduate (n = 33, 36.7%) or postgraduate degree (n = 27, 30.0%). The age of children with ASD ranged from 2 to 12 years (Mage = 7 years, SD = 2.84). See Table 1.
Professionals’ ages ranged from 25 to 65 years (Mage = 39 years, SD = 8.34). They came from a range of back- grounds with the most common being speech pathologists (n = 7, 22.6%). See Table 2.
Measures
Technology-related self-efficacy, anxiety, and attitudes: Parent and professional questionnaires. The three domains of the 49-item Computer Technology Use Scale (CTUS; Conrad & Munro, 2008) were used to measure computer self- efficacy, technology-related anxiety, and attitudes to technology.
Computer self-efficacy. Items were derived from the four mediators of self-efficacy including persistence, goal setting, attribution, and coping strategies. Participants responded to 11 items indicating their perceived ability to effectively use different types of technology using a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). In separate samples, Conrad and Munro found the psycho- metric properties of the 11-item computer self-efficacy domain were satisfactory, ranging from .72 to .76 (Conrad & Munro, 2008).
Technology-related anxiety. This domain of the CTUS measured participant anxiety related to technology (Con- rad & Munro, 2008). Based on the unique two-factor struc- ture of this domain, all items loading onto factor 1 concern computer use, whereas factor 2 refers to the use of technol- ogy generally. Items were purposely intended to measure both unpleasant and positive emotional states. Participants respond to the 15 items on a 7-point Likert-type scale (1 = uncomfortable, 7 = comfortable). In separate samples, the internal consistency was satisfactory, with the overall alpha coefficients for the 15 items ranging between .76 and .87 (Conrad & Munro, 2008).
Attitudes toward technology. This domain was included to determine whether attitudes toward various types of tech- nologies were positive (e.g., “I can do more things with technology”) or negative (e.g., “Technology complicates people’s lives”). Responses were rated using a 7-point Lik- ert-type scale (1 = strongly disagree, 7 = strongly agree). The internal consistency of the 10-item attitudes to technol- ogy domain has been shown to be acceptable across the two samples, ranging between .70 and .74 (Conrad & Munro, 2008).
Attitude toward iPad applications: Parent and professional questionnaires. The “Attitudes Toward iPad Applications” subscale comprised the 10 items from the “Attitudes Toward Technology” subscale of the CTUS (Conrad & Munro, 2008). In this study, the items were contextualized to specifically measure attitudes toward iPad application use, rather than technology use in general. For example, Question 29 “iPad applications enrich people’s lives” was a modification of Item 19 from the original scale “Tech- nology Enriches People’s Lives” (Conrad & Munro, 2008).
Table 1. Parent and Child Demographic Characteristics.
Variable M SD N %
Age Child 07 2.84 Parent 42 5.75 Education Did not finish Year 12 19 21.1 Finished Year 12 20 22.2 Undergraduate degree 33 36.7 Postgraduate degree 27 30
Note. Total n = 90.
Table 2. Professional Age and Occupational Characteristics.
Variable M (SD) n %
Age (years) 39 (8.34) Occupation Speech pathologist 7 22.6 Education support worker 4 12.9 Special education teacher 4 12.9 Occupational therapist 4 12.9 Psychologist 4 12.9 Integration aide 3 9.6 Teacher 3 09.6 ABA therapist 2 06.4%
Note. n = 31. ABA = applied behavioral analysis therapy.
Clark et al. 177
Responses were rated on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). This new scale showed good internal consistency with a Cronbach’s alpha coefficient of .83, comparing favorably with the original CTUS. This indicated that the modified scale did not suffer psychometrically; indeed, it showed higher internal consis- tency than the original.
Frequency and duration of iPad use: Parent questionnaire. This domain was developed for the current study and included items to measure frequency of the child’s iPad use (i.e., “percentage of time spent engaging with iPad apps in the past 5 days”) and duration of iPad use (i.e., “provide an esti- mation of the amount of time your child spent engaging with iPad apps in the last 5 days”). The parents were also asked to report on the amount of time (months/years) their child with ASD had been using an iPad.
Frequency and duration of iPad use: Professional question- naire. Length of iPad use in months/years was estimated with the item “Provide an indication of how long you have been using an iPad as part of your occupation with children with an AD.” Professionals responded to the following item reporting an estimation of their total iPad use in the past working week: “provide an indication of how many days you have used an iPad as part of your occupation in the past 5 working days.” In an attempt to differentiate the use of iPad applications for therapy/education and or reinforce- ment/reward, the following items were included: “How often were iPad applications of a therapeutic and/or educa- tional nature used by children with ASD as part of your occupation” and “How often were iPad applications used by children with AD as part of your occupation for purposes other than education/therapy (i.e., reinforcement, reward, or entertainment).”
Procedure
Parents of children with ASD and professionals working with children with ASD were recruited through advertise- ments placed in school or organizational newsletters or on school/organizational websites. Autism-specific organiza- tions, early intervention centers, mainstream primary schools, parent support groups, and special education facili- ties Australia-wide were contacted during the recruitment process. All participants were asked to complete an online questionnaire that took approximately 20 min to complete.
Due to the online administration of the questionnaire, participants were not required to sign a consent form. However, all participants were asked to read a brief intro- duction to the study that included a statement explaining their consent would be implied through completion of the questionnaire. The project was approved by an accredited University Human Research Ethics Committee.
Data Analysis
Descriptive statistics (frequency percentage, M, SD) were used to analyze sample characteristics, computer self-effi- cacy, technology-related anxiety, attitude toward technol- ogy and iPad use, and iPad-related behavior for parents and professionals.
Two independent samples t-tests were conducted to compare general attitudes to technology, as well as attitudes specifically toward iPad applications, across parents and professionals. Correlation analyses were performed to investigate the relationship between attitudes and behaviors toward iPad applications for both professionals and parents. Four multiple linear regression analyses were conducted to explore the extent to which anxiety, self-efficacy, and level of education (for parents only) predicted Attitudes Toward Technology and iPad application use for parents and profes- sionals. “Total attitude toward iPad apps” and “Total atti- tudes toward technology” were entered as the dependent variable while education level (for parents only), computer self-efficacy, and technology-related anxiety were entered as predictors.
Results
Anxiety, Self-Efficacy, Attitudes, and Behaviors: Technology and iPad Applications
The attitudes toward technology in general and iPad appli- cations specifically were favorable among both parents and professionals. The results of t-tests revealed no significant difference in mean parent attitudes (M = 45.15, SD = 8.15) and professional attitudes (M = 46.14, SD = 6.65) toward general technology use, t(121) = −0.594, p = .55. Furthermore, there were no significant difference in parent attitudes (M = 51.73, SD = 9.26) and professional attitudes (M = 50.62, SD = 9.19) toward iPad application use, t(120) = 0.565, p = .57. No significant difference in mean technol- ogy-related anxiety was identified between professionals and parents, t(113) = −0.838, p = .40, although profession- als did have a slightly higher (although non-significant) mean technology-related anxiety (M = 85.83, SD = 11.88) than parents (M = 83.51, SD = 14.97) Comparisons of mean computer self-efficacy for parents (M = 49.40, SD = 8.37) and health professionals (M = 47.54, SD = 8.10) revealed no significant difference between the groups, t(117) = 1.30, p = .19.
iPad Application Use
As professionals and parents were asked slightly different questions in the “Behavior Toward iPad Applications” sub- scale, the variable “total behavior toward iPad applications” was computed separately for both groups.
178 Focus on Autism and Other Developmental Disabilities 30(3)
Parental reports of child iPad use. Parental reports of child iPad use showed that almost half of the children (46%) had begun using an iPad 12 to 18 months ago, while 30% had begun using an iPad in the past 6 months. Only a small per- centage of children in the sample (3%) had never used an iPad. iPad use was high for children with ASD, with the mean frequency of use reported as a total of 4.6 days (SD = 1.74) out of the previous 5 days. Child iPad usage was fur- ther broken down into estimated time spent using the device across the 5-day period: 22% of parents reported a total of 5 to 6 hr use by their child across the 5-day period. Further- more, 16% of parents stated their child’s iPad use exceeded 10 hr, with a mean of approximately 2 hr (SD = 2.03) of iPad use per day.
Professional iPad use. Based on self-report data, profession- als’ iPad usage was quite irregular: 26% of professionals had been using an iPad in their work with ASD children for less than 6 months. Furthermore, 35% of professionals reported having never used an iPad as part of their occupa- tion. Although approximately half of the sample reported limited to no use of iPads, the remaining half of the sample demonstrated some use of the iPad across three of the five previous working days, either for therapeutic intervention (16%) or purposes other than therapy, such as reward, rein- forcement, and play (16%).
Relationship Between Attitudes and iPad Use
There was a moderate positive, but not significant, relation- ship between Attitudes Toward iPad Applications and use of iPad applications (frequency/duration) for professionals, r(28) = .40, p = .38. Furthermore, a strong positive relation- ship, r(88) = .57, p = <.001, between iPad application use and Attitudes Toward iPad Applications was found in the parent group. When investigating the association between Attitudes Toward Technology generally and iPad use, a strong positive relationship was identified among parents, r(86) = .52, p = .001. In contrast, a weak positive relation- ship between Attitudes Toward Technology generally and iPad use was found in the professional group, r(28) = .18, p = .348. This association was not significant.
Predictors of Parent and Professional Attitudes
Parental attitudes. Together, the factors “computer self-effi- cacy,” “technology-related anxiety,” and “highest level of education” accounted for 39% of the total variance in paren- tal “Attitudes Toward Technology.” The standardized beta coefficients reveal technology-related anxiety was the strongest predictor of parental Attitudes Toward Technol- ogy and iPads (see Table 3).
An R2 value of .23 indicated that 23% of the total vari- ance in parents’ “Attitudes Toward iPad Applications” was
explained by “computer self-efficacy,” “technology-related anxiety,” and “highest level of education” combined. Standardized beta coefficients indicate that “technology- related anxiety” was the most significant predictor of paren- tal Attitudes Toward iPad Applications (see Table 4).
Professional attitudes. Predictors of professionals’ “Attitudes Toward Technology” revealed that combined “computer self-efficacy” and “technology-related anxiety” explained 39% of their “Attitudes Toward Technology.” Consistent with parental attitudes, “technology-related anxiety” was the strongest predictor of professionals’ Attitudes Toward Technology.
An R2 value of .21 indicated that 21% of the total vari- ance in professional “Attitudes Toward iPad Applications” was explained by “computer self-efficacy” and “technol- ogy-related anxiety,” combined. The standardized beta coefficients showed that “technology-related anxiety” was the strongest predictor of professionals’ attitudes toward “iPad applications” (see Tables 5 and 6).
Discussion
The present study was the first study, to the authors’ knowl- edge, to examine parental and professional attitudes and behaviors toward ICT-based support materials generally, and iPad application use specifically for use by children with ASD. Our findings indicated that both parents and professionals held positive attitudes toward ICT and iPad use and, for parents, positive attitudes were positively
Table 3. Predictors of Parental Attitudes Toward Technology.
Statistic Self-efficacy Anxiety Education
Parents β −0.211** −0.599** −0.198** SE −0.092** −0.048** −0.659** R2 = .39
Note. n = 90. Self-efficacy = computer self-efficacy; Education = highest level of education completed; Anxiety = technology-related anxiety. *p < .05. **p < .001.
Table 4. Predictors of Parental Attitudes Toward iPad Applications.
Statistic Self-efficacy Anxiety Education
Parents β −0.131** −0.501** −0.018** SE −0.109** −0.062** −0.828** R2 = .23
Note. n = 90. Self-efficacy = computer self-efficacy; Education = highest level education completed; Anxiety = technology-related anxiety. **p < .001.
Clark et al. 179
Table 6. Predictors of Professionals Attitudes Toward iPad Applications.
Statistic Self-efficacy Anxiety
Professionals β −.037* −0.47** SE −.099 −0.058 R2 = .21
Note. n = 31. Self-efficacy = computer self-efficacy; Anxiety = technology- related anxiety. *p < .05. **p < .001.
