Volume 29, Issue 1, Pages 57-64 (January 2009)

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ABSTRACT

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The incidence of technological stress among baccalaureate nurse educators using technology during course preparation and delivery

Accepted 26 June 2008. published online 11 August 2008.

Summary

The concept of technology-related stress was first introduced in the 1980s when computers became more prevalent in the business and academic world. Nurse educators have been impacted by the rapid changes in technology in recent years. A review of the literature revealed no research studies that have been conducted to investigate the incidence of technological stress among nurse educators. The purpose of this descriptive-correlational study was to describe the technological stressors that Louisiana baccalaureate nurse educators experienced while teaching nursing theory courses.

A researcher-developed questionnaire, the nurse educator technostress scale (NETS) was administered to a census sample of 311 baccalaureate nurse educators in Louisiana. Findings revealed that Louisiana baccalaureate nurse educators are experiencing technological stress. The variable, perceived administrative support for use of technology in the classroom, was a significant predictor in a regression model predicting Louisiana baccalaureate nurse educators’ technological stress (F=14.157, p<.001).

Keywords: Technostress, Computer stress, Computer anxiety

Article Outline

• Summary

• Introduction

• Purpose

• Background/literature

• Methods

• Research objectives

• Instrumentation

• Population and sample

• Data analysis

• Data collection

• Results

• Demographics

• Discussion

• Limitations of the study

• Conclusions

• References

• Copyright

Introduction

Computers are now a part of everyday life, with the majority of daily activities involving the use of technology. The computer revolution has also greatly impacted the field of education. Computers have enabled course work to be completed, and entire degree programs are available on-line. Today’s college students were born during the computer technology explosion and usually have adequate computer skills necessary to adapt to the changes in technology. Technostress can affect both students and educators. The concept of technostress was first introduced in the 1980s when computers became more prevalent in the business and academic world. Technostress is “a modern disease of adaptation caused by an inability to cope with new technologies in a healthy manner” (Brod, 1984, p. 16).

Nurse educators have been impacted by the rapid changes in technology in recent years. However, nurse educators today are also faced with increasing workloads due to faculty shortages and the demands from administration and students to teach traditional courses in a non-traditional manner (American Association of Colleges of Nursing, 2000, Brendtro and Hegge, 2000, Hinshaw, 2001, Reinert and Fryback, 1997). Nurse educators are faced with changing their teaching methodology when they are not knowledgeable about the technology they are expected to use (Care and Scanlan, 2000). Furthermore, today’s nurse educators typically do not have the computer skills that most typical college students possess. The requirement to use technology will increase nurse educators’ already overwhelming workload and ultimately increase their chance of developing technological stress.

Purpose

The purpose of this descriptive-correlational study was to describe the technological stressors that Louisiana baccalaureate nurse educators experience while teaching nursing theory courses. Although nurse educators utilize different types of technology in the clinical setting, this study focused on the specific technologies that were utilized in the classroom setting rather than the clinical setting.

Background/literature

The term, technostress, was first introduced in the 1980s by Brod as “a condition resulting from the inability of an individual or organization to adapt to the introduction and operation of new technology” (Brod, 1984, p. 754). Technostress manifests in several ways. An individual may exhibit physical symptoms such as repetitive strain injuries, carpel tunnel syndrome, or back problems resulting from poor machine design or ergonomics. Furthermore, an individual may experience computer anxiety which manifests in several ways: temporary confusion as to how to use the technology, fear of being rushed or dehumanized by the computer or technology, or computerphobia or technophobia. But the primary symptom of technostress is anxiety (Brod, 1984). Important variables that affect the probability of developing technostress include the age of the user, past experience with technology, perceived control over new tasks, and organizational climate (Brod, 1984).

Technostress has a negative impact on human performance. It shifts a person’s work-congruent stress to an internal state of distress resulting in a reduced-ability to process information accurately. Technostress slows the response time to computer-generated demands and interrupts normal work patterns (Brod, 1984). Technostress often begins as reduced work performance, thus limiting the usefulness of the technology. After new technology is introduced many employees show initial excitement and begin to experiment with the new technology; however, few will excel in using these technologies. Later, employees become unable to adjust to new technology because of technostress. Employees begin to withdraw from using the technology and spend more time on non-technology tasks and social activities away from technology.

However, Harper (2000) suggests that the term technostress has been defined in so many ways and that some authors change their previous definitions of the term, conflicting themselves. Harper also advises that Brod’s (1984) definition of technostress should be closely scrutinized. According to Harper, the Greek meaning of the word “techne” means skill and the term technostress can be applied to situations when employees have to adapt to using new work processes, even those that do not require the use of technology.

An extensive review of the literature revealed no available studies that examined technological stress among nurse educators. However, a similar study by Beam et al. (2003) examined how technology induced stressors affected journalism and mass communication faculty’s job satisfaction and workplace exhaustion levels. The findings from this study indicated that technology stressors contributed to lower job satisfaction, higher job dissatisfaction, and higher job exhaustion for teachers of journalism and mass communication. The participants indicated that technology stressors were more important in influencing job satisfaction than course load, tenure status, rank, or gender.

An on-line survey by Kupersmith (2005) examined the incidence of technological stress among 92 library staff members. This survey was not a scientific survey; the sample was self-selected. Kupersmith (2005) found that 59% of the respondents’ level of technological stress had increased in the past five years. In addition, 65% of the respondents indicated that this type of stress was a serious problem for them. Stressors that led to the development of technostress identified by the participants included: “information overload, networking problems, security issues, computer hardware and ergonomics, and vendor-produced databases” (Kupersmith, 2005, p. 4). Participants reported strategies to manage and cope with technological stress. These strategies included the need for individuals to be flexible and open to learning and the need for training and technological support provided by the organization.

Methods

A census sampling design was used in this study. The participants included all full-time Baccalaureate nurse educators teaching in Louisiana Baccalaureate Nursing programs. Approval for the research was obtained from the Louisiana State University Institutional Review Board (IRB). The variables investigated in this study included selected demographic characteristics of the participants and the nurse educators’ technostress score as measured by the researcher-developed nurse educator technostress scale (NETS). The variable technostress was defined in this study according to the technostress definitions suggested by Brod, 1984, Kupersmith, 1992.

Research objectives

The first research objective of this study was to describe selected personal and professional characteristics of Louisiana baccalaureate nurse educators including age, gender, ethnic origin, educational level, years of experience as a nurse educator, academic rank, previous computer training, use of a computer at home, use of technology in nursing theory courses, types of technology used in nursing theory courses, on-line teaching, compensation for use of technology in nursing theory courses, perceived administrative support for use of technology. Research objective two sought to describe the technological stressors of Louisiana baccalaureate nurse educators as measured by the NETS. Research objective three was to determine if a relationship existed between Louisiana nurse educators’ perceived technology stress as measured by the nurse educator technostress scale and the demographic variables. The fourth research objective was to determine if a model existed that explained a significant portion of the variance in technological stress as measured by the nurse educator technostress scale from the demographic variables.

Instrumentation

A review of the literature review revealed no existing instrument, which measured technological stressors experienced while teaching; therefore, a new instrument, The nurse educator technostress scale (NETS) was developed (Burke, 2005). This instrument was developed based on a review of the literature, the definitions of technostress suggested by Brod, 1984, Kupersmith, 1992, existing technology and computer anxiety instruments, and expert input. The instrument was reviewed for content validity by an expert panel. A pilot test was then conducted utilizing a comparative sample of five nursing educators who taught a nursing theory course in a Louisiana associate degree nursing program. The NETS is a 35-item questionnaire which consists of two parts: technology issues related to course development and planning, and technological stressors experienced during course delivery. The NETS required participants to think about the technology stressors experienced during the past six months while teaching nursing theory courses. The participants were then required to rate the severity of those stressors on a five-point anchored scale: (1) not at all; (2) little stress; (3) moderate stress; (4) stressful; (5) very stressful. Overall means were calculated to determine nurse educators’ technostress score and the following researcher-developed scale was used to interpret the results: 1–1.49=no technological stress; 1.50–2.49=mild technological stress; 2.50–3.49=moderate technological stress; 3.50–4.49=severe technological stress; and 4.50–5.00=very severe technological stress. A separate instrument was developed to collect the demographic characteristics of the participants.

Population and sample

The accessible population for this study was full-time nurse educators in 13 baccalaureate degree nursing programs in Louisiana. The educators were currently using technology while teaching a nursing theory course and had taught at least one nursing theory course in a baccalaureate program during the six months prior to data collection. A population frame of 311 nurse educators was established and a census sampling design of all Louisiana baccalaureate nurse educators was used.

Data analysis

Descriptive and inferential statistics were used to analyze the data. Frequencies and percentages were computed for each of the demographic variables. Means and standard deviations of each item of the NETS were also calculated to determine the nurse educators’ technostress score. The use of one-way ANOVAs and multiple regression analyses were utilized to answer research objectives three and four. Exploratory factor analysis of the NETS using utilizing principal axis extraction, Promax oblique rotation, and requesting eigenvalues over the numerical value of one was conducted in order to determine construct validity. The NETS consisted of two parts: technology issues related to course development and planning and technological stressors experienced during course delivery. Each part was treated as a subscale of the instrument and exploratory factor analysis was performed on each subscale. However, the sample size was not large enough to perform a factor analysis of the overall NETS. The statistical software, statistical package for the social sciences (SPSS) software, was used to compute the statistical procedures.

Data collection

The questionnaires were made available on-line through an on-line survey delivery service called Zoomerang©. Data collection was conducted over a period of six weeks during March and April 2005. The total number of Louisiana baccalaureate nurse educators responding to the surveys after follow-up procedures was 180, resulting in a 55% response rate. However, of the 180 completed questionnaires, 61 participants indicated that they had not taught a baccalaureate nursing theory course in the past six months and four additional participants indicated that they did not utilize technology in their theory course. Since these 65 questionnaires did not meet the study criteria of using technology in a baccalaureate nursing theory course, they were discarded. The end result was 115 usable questionnaires for data analysis.

Results

Demographics

The largest group of the respondents indicated that they had been a nurse educator for 11–20 years (n=39, 33.9%), their highest educational degree obtained was at the master’s level (n=81, 70.4%), and their academic rank was assistant professor (n=56, 48.8%). Additionally, the participants were asked to indicate the types of technology used in the classroom. The technology used most frequently by Louisiana baccalaureate nurse educators while teaching nursing theory courses was the presentation software, PowerPoint© (n=108, 93.9%). Furthermore, the majority (n=68, 59.1%) of the participants reported that they believed that administration supported the use of technology in nursing theory courses. Participants indicated through multiple open-ended responses that administration supported their use of technology in the class room by providing technology in-service training (n=24), access to computer help desk and technological support (n=28), updated technology hardware and software (n=20), and by allowing time off to attend technology in-service training (n=4).

The mean and standard deviation for each question and an overall mean score were calculated. Results indicated that Louisiana baccalaureate nurse educators experienced mild technological stress while teaching nursing theory courses (mean=2.45, SD=.76). Furthermore, nurse educators rated computer hardware failure during class (mean=3.22, SD=1.44) as causing the most technological stress, Internet access during class preparation was rated as causing the least amount of stress (mean 1.90, SD=.99). See Table 1 for a presentation of the means and standard deviations of each NETS item. The overall mean for the technology issues related to course development and planning subscale was determined to be 2.46 (SD=.76). The mean of the technological stressors experienced during course delivery subscale was calculated to be 2.15 (SD=.85).

Table 1.

Mean scores of nurse educator technostress scale items


Scale item	Mean	SD
Computer hardware failure during class	3.22	1.43
Too much spam e-mail	3.16	1.37
Technology support during class time	2.79	1.33
Computer hardware failure during course preparation	2.70	1.53
Availability of technical support during course preparation	2.65	1.24
Loss of data during course preparation	2.64	1.37
Fear of computer viruses	2.64	1.12
Outdated computer technology	2.63	1.35
Need to learn new software	2.63	1.04
Knowledge of computer setup during class time	2.62	1.14
Fear of unauthorized access to files	2.62	1.17
Computer software failure during course preparation	2.60	1.16
Ability to incorporate technology into course	2.50	1.10
Work-group network failure during class	2.50	1.27
Computer software failures during class	2.49	1.34
Work-group network failure during course preparation	2.43	1.28
Not having needed software during course preparation	2.42	1.24
Knowledge of computer technology	2.40	1.02
Damage to storage media	2.38	1.38
Internet access during class time	2.37	1.20
Pressure to use technology	2.35	1.02
On-line course evaluations	2.31	1.06
Knowledge of technology in classroom	2.28	1.01
Access to technology during class time	2.26	1.10
Computer technology makes me feel stressed	2.23	1.04
Forget to save work	2.22	1.24
Software is user friendly	2.18	.93
Feel anxious using technology in classroom	2.14	1.03
Student knowledge of technology	2.10	1.05
Access to computer technology during course preparation	2.06	1.01
Use of personal digital assistants (PDAs) to organize course schedule	2.03	1.21
Student access to technology	1.92	.87
Availability of internet access during course preparation	1.90	.99

Scale items: 1=no stress, 2=little stress, 3=moderate stress, 4=stressful, 5=very stressful.

Construct validity is an examination that determines if the instrument is measuring what it intended to measure (Brown, 2000). In order to determine construct validity of the NETS subscale, technological issues related to course development and planning exploratory factor analysis was completed. This resulted in a three-factor model that explained 56.2% of the variance of baccalaureate nurse educators’ technological stress. Three factors were easily identifiable and were labeled as: computer/technology failure, technology knowledge concerns, and external technology concerns. The computer/technology Failure factor consisted of items that related to problems with computer hardware and software, loss of course content data files, and lack of technological support personnel. The technology knowledge concerns factor included items that centered on the incorporation of technology into the classroom such as availability, knowledge of how to use it, and pressure to incorporate technology into the classroom. The third factor, external technology concerns, consisted of items that related to fears of computer viruses and unauthorized access to files, and too much spam e-mails.

To further determine construct validity, an exploratory factor analysis of the technological stressors during course delivery subscale was also conducted. A three-factor solution resulted in a model that explained 66.1% of the variance of baccalaureate nurse educators’ technostress. Three factors were easily identifiable and were labeled as: technology knowledge/stress, computer/technology failure during class time, and student technology issues. The technology knowledge/stress factor contained items that centered around knowledge on how to use technology in the classroom and the stress associated with using technology. The computer/technology failure during class time factor consisted of items that related to technology equipment failure in the classroom and access to technological support to help resolve these issues. The third factor, student technology issues, included items that centered on students’ knowledge and access to technology during class time.

Cronbach’s alpha of the NETS instrument was determined to be .957. According to George and Mallery (2003), Cronbach scores greater than .7 are considered to be acceptable coefficients, while scores greater than .9 are considered to be excellent.

Results of one-way ANOVAs indicated that no significant differences existed between the demographic and professional variables (age, gender, ethnic origin, educational level, years of experience as a nurse educator, academic rank, previous computer training, use of a computer at home, on-line teaching, and compensation for incorporation of technology in nursing theory classes) and the independent variable, NETS overall mean. Results, as presented in Table 2, indicated that there were significant differences, F=14.941 (1,113), p<.001, in the NETS mean score by the variable, perceived administrative support. Results indicated that the mean NETS score tended to be lower when the participants perceived that university administration supported the use of technology in nursing theory courses.

Table 2.

Analysis of variance illustrating differences in the variable, perceived administrative support as reported by respondents of the nurse educator technostress scale


Source	SS	df	MS	Fa	pb
Between groups	7.860	1	7.860	14.941	<.001
Within groups	59.443	113	.526
Total	67.302	114

One-way analysis of variance.

.05 alpha level for 2-tailed test of significance.

One-way ANOVAs were also calculated to determine if differences existed between the mean of each subscale and the demographic variables. Results indicated a significant relationship between the subscale means and the variable, Training prepared for the incorporation of technology (subscale one [F=4.054 (1,89), p=.047]; subscale two [F=8.716 (1,89), p=.004]). This finding indicates that nurse educators had a lower level of technological stress when the educators believed that technology training prepares them to incorporate technology in the classroom. There was also a significant relationship between the subscale means, and the variable, perceived administrative support (subscale one [F=12.371 (1,89), p=.001]; subscale two [F=16.581 (1,89), p<.001]). This significant finding indicates that nurse educators experienced a lower level of technological stress when the educators believed that their administration supported the incorporation of technology in the classroom.

Regression analysis can provide the researcher with a better understanding of how the dependent variable relates to the independent variable. A regression model that explained a significant portion of the variance in technological stress as measured by the nurse educator technostress scale from the demographic variables was determined. The only variable to enter into the regression model was perceived administrative support. The significance of this finding is that when Louisiana Baccalaureate nurse educators perceived that administration supported the incorporation of technology in theory courses, baccalaureate nurse educators tended to have a lower level of technological stress. The overall regression analysis was significant (F=14.157, p<.001) and explained 12% of the overall variance in the dependent variable, nurse educator technostress score.

A regression analysis utilizing the mean of technological issues related to course development and planning subscale as the dependent variable revealed that the variable, perceived administrative support was the only variable to enter the model. The model was significant (F=10.268, p=.002) and explained 10% of the variance. Examination of the regression analysis results of technological stressors during course delivery subscale indicated that two variables, perceived administrative support and 11–20 years of nursing education experience, entered the model. The model was significant (F=10.542, p=.002) and explained 19% of the variance.

Discussion

The first objective of this study was to describe Louisiana baccalaureate nurse educators in terms of selected professional and demographic characteristics. The findings from this study indicate that baccalaureate nursing education in Louisiana has an aging faculty and is facing a shortage of nurse educators due to retirement. This is supported by findings from this study in that the largest group of the participants was 45–54 years of age (n=47, 40.9%). This finding is also supported by the American Association of Colleges in Nursing 2003 report on Salaries of Instructional and Administrative Nursing Faculty in Baccalaureate and Graduate Programs in Nursing, which reported the median age of full-time nurse faculty was 51.5 years (American Association of Colleges of Nursing, 2004). In addition, Louisiana baccalaureate nurse educators are experienced in nursing education. This is based on the finding that the largest group of the study participants had indicated they had taught in nursing education for 11–20 years (n=39, 33.9%). Furthermore, 29% (n=33) indicated that they had taught in nursing education for 21–30 years.

The second objective of this study was to describe the technological stressors of Louisiana baccalaureate nurse educators. Based on the findings, Louisiana baccalaureate nurse educators are experiencing mild technological stress. This conclusion is supported by the mean score of the NETS (mean=2.45, SD=.76). This finding was determined by using the following researcher-developed scale: 1–1.49=no technological stress; 1.50–2.49=mild technological stress; 2.50–3.49=moderate technological stress; 3.50–4.49=severe technological stress; and 4.50–5.00=very severe technological stress. This finding is similar to the findings of Beam et al. (2003) who reported that journalism and mass communication faculty were also experiencing technological stress. Readily accessible technological support and having up-to-date and functional equipment is necessary in order to reduce the likelihood of nurse educators experiencing technological stress.

The researcher-developed, NETS proved to be reliable as indicated by Cronbach’s alpha of .957. The instrument easily identified items, which caused the most technological stress for baccalaureate nurse educators. Construct validity was demonstrated through factor analysis.

The third objective of the study was to determine if there were significant relationships between the selected demographic and professional characteristics and the NETS mean. Findings revealed no relationship between the demographic variables, age, gender, ethnic origin, and educational level and Louisiana baccalaureate nurse educators’ technological stress. This finding supports the findings from a previous study conducted by Yang et al. (1999), which examined the relationship between computer anxiety and selected demographic variables. Yang et al. (1999) found no significant relationships between age, teaching area, and ethnic origin and the development of computer anxiety. However, the researchers did find a relationship between educational level and the development of computer anxiety; those educators with a higher educational level experienced less computer anxiety. Findings also indicated that there was no relationship between the variable, academic rank and the NETS mean. This finding supports previous results from Kupersmith, 2005, Beam et al., 2003. However, Voakes et al. (2003) found that a relationship existed between academic rank and journalism and mass communication educators’ technological stress. Journalism and mass communication educators who were at the academic rank of associate professor had higher levels of technological stress compared to those at assistant professor and full professor. However, results revealed a significant relationship between the variables, perceived administrative support and training prepared for incorporation of technology into nursing theory course, and the means of each subscale. This further validates the need for technology training and administrative support during course planning and course delivery.

The last research objective was to determine if a model existed which explained a significant portion of the variance of the variable, nurse educator technostresss. Perceived administrative support was a significant predictor of Louisiana baccalaureate nurse educators’ technological stress. If baccalaureate nurse educators perceive that administration supports the use of technology in the classroom, they will experience a lower level of technological stress. The majority of the participants reported that they perceived administration supported their efforts to utilize technology in the classroom (n=68, 59.1%) through providing access to technological support and up-to-date equipment. This finding supports previous research by Kupersmith (2005). Kupersmith (2005) found lower reported levels of technological stress when administration provided adequate technological support and training. Moreover, Beam et al., 2003, Voakes et al., 2003 also found that the perceived quality of the technology support available to faculty was negatively related to the level of technological stress. This finding is important for university administrators especially during the current shortage of nurse educators and the looming shortage of nurse educators.

Limitations of the study

It should be noted that the research instrument used to collect data was researcher-developed; therefore reliability and validity of the instrument were not determined prior to data collection. It was assumed that baccalaureate nurse educators were knowledgeable about technological terms and were able to relate their experiences when using technology during course preparation and delivery. Furthermore, results can only be generalized to Louisiana baccalaureate nurse educators because random sampling was not utilized.

Conclusions

Louisiana baccalaureate nurse educators are experiencing technological stress. However, nurse educators experience lower levels of technological stress when they perceived that administration supported the use of technology in nursing theory courses. By providing continuous access to technical support and updated technology for course preparation and for use in the classroom, administrators can provide an atmosphere that is supportive of technology usage. As stated by Trossman (2002), the current nurse education workforce is aging and few nurses are qualified to take their place. A work environment with reduced technological stress could result in a nursing education workforce with increased job satisfaction and greater retention. Furthermore, universities will be more likely to attract and retain new nurse educators if adequate technology and technological support is available.

Additional research should be conducted to support the reliability and construct validity of the NETS. Because of the low percentage of variance explained by the regression model, other variables are responsible for predicting baccalaureate nurse educators’ technological stress. Due to the significance of the variable, perceived administrative support, future research should be conducted to investigate specific variables which measure administrative support. Moreover, with the increase of on-line education, educators are faced with converting traditional courses into on-line courses. The technological stress of converting courses to an on-line format as well as nurse educators’ fears of on-line courses taking over the role of the nurse educator require additional research.

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