Journal of Nursing Education

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Computer Anxiety in Nursing Students

Billie Ann Wilson, PhD, RN

Abstract

ABSTRACT

The purpose of the study was to estimate the prevalence and severity of computer anxiety in beginning AD and BS nursing students and to determine the effect of hands-on computer experience on computer anxiety. The sample consisted of 272 volunteer subjects from five schools of nursing in a central southern state. Computer anxiety was measured using the Computer Anxiety Index by Maurer and Simonson. Factor analysis of the index was carried out to provide construct validity for the tool. Twenty-one percent of the subjects were found to have high computer anxiety. No significant difference in computer anxiety was demonstrated between associate degree (AD) and baccalaureate (BS) students. However, subjects with more hands-on computer experience had significantly less computer anxiety.

Abstract

ABSTRACT

The purpose of the study was to estimate the prevalence and severity of computer anxiety in beginning AD and BS nursing students and to determine the effect of hands-on computer experience on computer anxiety. The sample consisted of 272 volunteer subjects from five schools of nursing in a central southern state. Computer anxiety was measured using the Computer Anxiety Index by Maurer and Simonson. Factor analysis of the index was carried out to provide construct validity for the tool. Twenty-one percent of the subjects were found to have high computer anxiety. No significant difference in computer anxiety was demonstrated between associate degree (AD) and baccalaureate (BS) students. However, subjects with more hands-on computer experience had significantly less computer anxiety.

Introduction

The concept of computer anxiety first began to appear in the literature in the early 1980s. It is believed to be a situational manifestation of the general anxiety construct, similar to math anxiety and test anxiety. The potential impact of computer anxiety on nursing students might be estimated by comparison with what is known about math anxiety. It has been observed by several researchers that many capable students avoid math in high school and college even at the expense of handicapping themselves in their daily lives and limiting their career choices to those which do not require quantitative skills (Betz, 1978; Sherard, 1981). If math anxiety leads to math avoidance, a parallel might be drawn with computer anxiety. Students with a high degree of computer anxiety might not choose to enroll in elective courses designed to develop computer literacy. This would be particularly problematic in nursing programs which use the elective route as the primary means of exposing students to computer technology.

The primary purpose of this study was to estimate the prevalence and severity of computer anxiety in beginning associate (AD) and baccalaureate (BS) degree nursing students and to determine the relationship of hands-on computer experience to computer anxiety. Three specific research questions were asked:

1. To what degree do beginning nursing students experience computer anxiety?

2. What is the relationship between computer experience and computer anxiety in beginning nursing students?

3. Is there a difference in computer anxiety between beginning AD and BS degree nursing students?

In order to answer questions 2 and 3, two null hypotheses were formulated and tested:

* Hypothesis One: There will be no significant difference in computer anxiety for subjects with different levels of computer experience.

* Hypothesis Two: There will be no significant difference in computer anxiety for subjects in AD or BS nursing programs.

Review of the Literature

Computer anxiety is regarded as a type of state anxiety (Howard, 1984; Raub, 1981). Spielberger (1966) defines state anxiety as a temporary condition manifested as a result of the amount of stress that impinges on the individual at a given time. Spielberger differentiates state anxiety from trait anxiety which reflects a stable personality characteristic of anxiety proneness. High trait anxiety produces a predisposition to see many situations as threatening and to respond to them with heightened anxiety state reactions.

Computer anxiety has been defined by Maurer and Simonson (1984) as subjective feelings of fear or apprehension experienced by persons when using computers. In the literature, several different terms have been used to refer to feelings of anxiety related to computer use. Among these are cyberphobia (Weinberg & English, 1983), technostress (Brod, 1984), computer cowardice (Grobe, 1984), and computer fear (Vrendenburg, Fleet, Krames, & Pliner, 1984). According to Brod, technostress or computer anxiety may be manifested as resistance to learning about and using computers or even complete rejection of computer technology.

In many students, computer anxiety may be lessened by successful interactions with computers. Two studies using college students found that computer anxiety was inversely related to amount of hands-on experience (Jordan & Stroup, 1982; Raub, 1981). In previous studies, two approaches to the measurement of computer anxiety have been utilized. One involves measurement of physiological parameters (Powers, Cummings, & Talbott, 1973) and the other is use of subjective self-report inventories or questionnaires. By far the most frequently cited approach to measuring computer anxiety is through use of subjective measures. During periods of anxiety, subjective psychological symptoms are often present even though objective physiological symptoms are absent; therefore, subjective measures are considered better indices of anxiety (Caplan & Jones, 1975).

Because computer anxiety has been regarded as a type of state anxiety, several self-report, Likert-type inventories of computer anxiety, modeled after the State-Trait Anxiety Inventory (Spielberger, Gorsuch, & Lushene, 1970) have been developed. Raub (1981) designed the 25-item Attitudes Toward Computer Scale to assess the cognitive component of computer anxiety in undergraduate students. Loyd and Gressard (1984) developed the 30-item Computer Attitude Scale to identify computer anxiety in junior high and high school students. The Computer Anxiety Index, developed by Maurer and Simonson (1984), is an extensively revised version of an earlier scale designed by Rohner (1981). Of the available computer anxiety instruments, the Computer Anxiety Index (CAIN) has been used most extensively with undergraduate students. Using the CAIN on multiple samples, Simonson (personal communication, July 1, 1985) estimates that 15% to 20% of undergraduates have high computer anxiety.

Methods

Subjects

The subjects were a convenience sample of 272 volunteer participants from five different schools of nursing in a central southern state. All students had completed less than half of the credits in nursing required by their program of studies. Of the subjects, 52% were BS degree students and 48% were AD students. Approximately 11% of the subjects were males, among whom 67% were enrolled in BS and 33% in AD programs.

Since 48% of the subjects were AD students, the sample was older than a typical undergraduate population. The mean age was 26.8 years with a range of 18 to 54 years. Thirty-nine percent of the subjects were over 29 years of age. The mean age of BS students was 23.4 years compared to 30.2 years for AD students. In terms of locale, 63.6% were attending school in a large metropolitan area while 36.4% were in schools in smaller cities in more rural settings.

In terms of computer availability, 16.5% had personal computers in their homes; however, 80% of these were BS students. Regarding hands-on experience, 40.8% had 0 hours, 22.8% had 1 to 5 hours, 9.9% had 6 to 15 hours, and 26.5% had more than 16 hours. Of those with no computer experience, 69% were AD and 31% were BS students. Conversely, among the students with 16+ hours, 60% were BS and 40% were AD students. To determine if the amount of computer experience between AD and BS students was significantly different, the independent sample chi-square test was used. Using four levels of hands-on computer experience (0 hours, 1 to 5 hours, 6 to 15 hours, 16+ hours), the obtained chi-square value, x2 (3, n = 272) = 34.438, p = .001, was found to be significant.

The Computer Anxiety Index

In this study the Computer Anxiety Index (CAIN) by Maurer and Simonson (1984) was used. The CAIN consists of 26 Likert-type items which differentiate subjects according to their level of computer anxiety. To statements such as "I doubt if I would ever use computers very much" students respond with: (1) Strongly Agree, (2) Agree, (3) Slightly Agree, (4) Slightly Disagree, (5) Disagree, and (6) Strongly Disagree. Maurer and Simonson (1984) established concurrent validity for the CAIN by correlation with the state portion of the State-Trait Anxiety Inventory (STAI). Prior to being seated at a computer, 111 students completed the CAIN. Next, when these same subjects were seated in front of computers, they completed the state portion of the STAI before actually interacting with the computers. A correlation of .32, p<.01 was found between the scores on the CAIN and on the state portion of the STAI. In studies using a group of 25 subjects retested after a 3-week interval, a reliability coefficient of .90 was obtained. The internal consistency of the second administration of the test was .94 using Cronbach's alpha (Maurer & Simonson, 1984).

The CALN has a possible score range of 26 (low computer anxiety) to 156 (high computer anxiety). In norming the instrument, the authors used six different groups including undergraduates, junior high students, teachers, computer professionals, computer users, and others. The mean for all subjects (in = 514) was 57.89; however, the mean for the undergraduates alone (n = 111) was much higher, 70.2, SD= 18.46 (Montage, Simonson, & Maurer, 1984). A score in the upper third of the score range (84 or higher) indicates high computer anxiety (Maurer & Simonson, 1984).

Table

TABLE 1Sample Factor Loadings of Computer Anxiety Index Items

TABLE 1

Sample Factor Loadings of Computer Anxiety Index Items

In the present study, post-hoc factor analysis was employed for the purpose of defining the fundamental constructs which underlie the CAIN. Principal component factor analysis was used. A solution was sought which accounted for at least 60% of the total variance. Three alternative factor patterns were evaluated for simplicity, parsimony, and interpretability. A three-factor solution was identified which accounted for 63% of the variance in responses.

Significant factor loadings were identified as those at least equal to .40. Twelve of the 26 CAIN items loaded on Factor 1. The theme of these items is an appreciation of the usefulness of computers, which represents a positive response and can be considered an anxiety-absent factor. Five of the 26 CAIN items loaded very heavily on Factor 2. The theme of these items is the intimidating nature of computers and it represents a negative response based on fear of an incomprehensibly complex machine. The remaining nine items loaded on Factor 3. The theme of these items is mistrust and dislike of computers which also represents a negative response. Factors 2 and 3 are considered anxiety-present factors. The results of the factor analysis provide construct validity for the CAIN as a measure of computer anxiety. Sample items with factor loadings are presented in Table 1.

Procedure

Data on demographic variables of interest and on degree of computer anxiety were collected by means of an anonymous self-report questionnaire administered by the investigator during the last 15 minutes of a regularly scheduled class period. Students were told that participation was voluntary and that the research study concerned the attitudes and feelings of student nurses toward computers. Each student who agreed to participate signed a consent form. Of the available students, 97% volunteered for the study.

Results

The mean score on the CAIN for the sample (n = 272) was 73.7 (SD = 13.8) with similar means noted for AD (x = 74.27, SD =14.33) and BS (x = 73.01, SD = 13.40) students. The mean for male subjects was 69.8 (SD = 13.61) compared to 74.5 (SD = 13.9) for female subjects. Subjects in smaller cities and towns had a mean of 75.3 (SD = 14.73) compared to 72.7 (SD = 13.27) for subjects in a large urban area.

Research Question One

Twenty-one percent of the subjects scored in the upper one third of the score range (84 or higher) which indicates high computer anxiety. Separating the sample by gender, program type, and program locale yielded the following percentages of high computer anxiety subjects: males, 10% and females, 24.7%; AD students, 24.6% and BS students, 19.1%; students in more rural settings, 29.6% and students in large urban areas, 17.9%.

Research Question Two

The null hypothesis for research question two, regarding the relationship of computer anxiety to computer experience, was tested using analysis of variance. Four levels of hands-on computer experience were used: (a) 0 hrs, (b) 1 to 5 hrs, (c) 6 to 15 hrs, and (d) 16+ hrs. Mean scores on the CAIN by level of computer experience were: 0 hrs= 77.1, 1 to 5 hrs = 75.9, 6 to 15 hrs = 71.7, 16 + hrs = 67.5. The results of the ANOVA, presented in Table 2, indicate a significant difference in computer anxiety, F(3,265) = 8.34, /?<.0001, among the groups with different levels of hands-on computer experience. Duncan's multiple range, post-hoc test found statistically higher means on the CAIN (more computer anxiety) for the subjects with 0 hrs versus 6 to 15 hrs, 0 to 5 hrs versus 6 or more hrs, and 1 to 5 hrs versus 16+ hrs. These results indicate that subjects with 6 or more hours of hands-on computer experience have significantly lower computer anxiety than those with 5 or fewer hours. Based on these tests, null Hypothesis One was rejected.

Table

TABLE 2Analysis of Variance for the Effect of Computer Experience on Computer Anxiety

TABLE 2

Analysis of Variance for the Effect of Computer Experience on Computer Anxiety

Table

TABLE 3Two-Way Analysis of Variance for the Effect of Computer Experience and Program on Computer Anxiety

TABLE 3

Two-Way Analysis of Variance for the Effect of Computer Experience and Program on Computer Anxiety

Research Question Three

The null hypothesis for research question three, regarding the degree of computer anxiety in AD versus BS students, was tested using two different statistical techniques. First, the i-test for independent samples was used and the result was nonsignificant. Second, a Two-Way ANOVA was used in which the independent variables were program and computer experience. This analysis was conducted to increase the chance of finding a program effect. The results of the ANOVA, presented in Table 3, indicated no interaction and no main effect for program. Therefore, null Hypothesis Two could not be rejected.

Discussion

Based on the findings of this study, the incidence of high computer anxiety among nursing students is about 21%. However, the percent of students with high computer anxiety may vary with gender of the students, locale of the program, and type of program attended. It is also possible that these variations are related to another variable, such as computer experience. This may be true since, among possible comparison groups (i.e., females versus males, AD versus BS students, and students in programs in large versus small cities), the group having more subjects with high computer anxiety had fewer hours of hands-on computer experience. The only exception was that females had more computer experience than males.

The results of this study support previous findings (Jordan & Stroup, 1982; Raub, 1981) that an inverse relationship exists between computer anxiety and computer experience. It can be further concluded that the amount of hands-on experience must exceed some minimal level (in this study, 5 hours) in order to make a substantial difference in one's level of computer anxiety.

Based on the present analysis, it is not possible to state that there was a significant difference in computer anxiety between AD and BS students. This finding was of interest for two reasons. First, statistical tests for Hypothesis One indicated that computer experience reduces computer anxiety. Second, AD students had less computer experience than BS students. Since AD students had significantly less computer experience, one might have anticipated that AD students would have significantly higher computer anxiety than BS students but this was not the case. One possible explanation is that the difference in computer experience between AD and BS students in this sample, while statistically significant, was not substantial enough to account for a significant difference in computer anxiety between the groups.

Given the above findings, one might speculate that other intervening variables may have been operative within the groups. It has been demonstrated, for example, that both state and trait anxiety scores are lower in working adults than in college students (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). Multiple developmental factors are probably responsible for these differences. In some respects, the AD students in this study were demographically more like working adults than undergraduate college students in general. For example, the mean age of the AD students was 30 years with 55% of the group age 29 and older. Based on age, the AD students in the sample were more likely to have varied work experiences and to have taken on family responsibilities than their BS counterparts, whose mean age was 23 years with 54% of the group 22 years or younger. Since computer anxiety is thought to be a situation-specific type of state anxiety, it may be influenced by the same kinds of developmental factors which result in working adults having lower state and trait anxiety scores than college students. With the AD students in this study, unidentified developmental factors may have actually offset the effect of less hands-on computer experience, resulting in less computer anxiety than would have been predicted on the basis of computer experience alone.

In summary, a substantial percentage of nursing students may experience computer anxiety. The significance of this finding lies in the fact that individuals tend to avoid activities which are anxiety-provoking. Therefore, if the elective route for attainment of computer literacy becomes commonplace, an area of real concern for nurse educators is how many students will actually choose to enroll in such courses. Based on the findings of this study, it is recommended that nurse educators consider the use of elective courses to obtain computer literacy among nursing students as a poor alternative. To assure that all students are computer literate and understand the rudiments of computer applications in nursing, courses designed to achieve these goals should be required.

References

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TABLE 1

Sample Factor Loadings of Computer Anxiety Index Items

TABLE 2

Analysis of Variance for the Effect of Computer Experience on Computer Anxiety

TABLE 3

Two-Way Analysis of Variance for the Effect of Computer Experience and Program on Computer Anxiety

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