Biomedical subjects

R A Hudiburg

Publications and source records attributed to R A Hudiburg.

10 recordsLinked to original sources

PubMed1999

Preliminary investigation of computer stress and the big five personality factors.

This study investigated correlates of personality factors, measured with the Big Five Inventory, with computer users' stress, measured with the Computer Hassles Scale. Based on an analysis of the responses of 95 college students using computers, there was a significant correlation between the computer users' stress and Openness, one of the Big Five personality factors. There was a significant correlation between the Computer Hassles Scale and the somatic complaints and anxiety reactions, typical responses to stress. Hierarchical regression analyses indicated that Neuroticism and Extraversion had a "buffering effect" between computer stressors and typical stress responses. The significant correlation between scores on the Computer Hassles Scale and on Openness was a surprising finding and suggested that additional research was needed to clarify the nature of this relationship.

Adult↗

PubMed1998

Confirmatory factor analysis of the Computer Hassles Scale.

The objective of this research was to determine the latent structure of the Computer Hassles Scale using confirmatory factor analysis. This study employed a normative database of 1199 student computer users. Both a priori and a posteriori latent structure models were tested using LISREL. The analyses did not support a latent structure of the scale based on the scale's original two-factor definition. Using various goodness-of-fit indices, a four-factor model was the best fit.

Attitude to Computers↗

PubMed1996

Psychology of computer use: XXXV. Differences in computer users' stress and self-concept in college personnel and students.

104 college students and 88 college faculty/staff at a midwestern university completed a questionnaire composed of the Computer Hassles Scale, a measure of computer users' stress, somatization/anxiety items from the Symptoms Checklist-90, a measure of stress reactions, and the Revised Personal Attribute Inventory, a measure of self-concept. Correlations indicated that for students there was a significant negative relationship between computer users' stress and self-concept (r = -.30), while for faculty/staff there was a significant positive relationship (r = .28). Regression analyses showed that self-concept moderated the relationship between computer users' stress and stress outcomes for only the faculty-staff sample. The moderator effect was interpreted using Linville's 1987 "buffering hypothesis," which suggests that persons with higher scores on self-concept are less prone to experience stress-related outcomes like somatization/anxiety symptoms.

Adult↗

PubMed1995

Psychology of computer use: XXXIV. The Computer Hassles Scale: subscales, norms, and reliability.

Data from 1199 students users formed the normative database for the Computer Hassles Scale, a 37-item measuring computer users' stress. The Computer Hassles Scale was scored to yield a severity of hassles score for the total scale and two subscales, Computer Runtime Errors and Computer Information Problems. The total scale and both subscales showed high internal consistency as measured by the Cronbach coefficient alpha. Guidelines for identifying high and low severity of computer users' stress were suggested.

Adult↗

PubMed1994

Psychology of computer use: XXXI. Relating computer users' stress, daily hassles, somatic complaints, and anxiety.

The relation of computer users' stress, measured by the Computer Hassles Scale, and global stress, measured by the Daily Hassles Scale, with stress reactions, measured by the somatization-anxiety items of the SCL-90, was investigated in a college sample (N = 101). Computer hassles ratings were correlated .54 with daily hassles ratings and .57 with somatization-anxiety ratings. Daily hassles ratings were correlated .74 with somatization-anxiety ratings. These results provide important evidence on convergent validity for the Computer Hassles Scale as a measure of computer users' stress.

Adult↗

PubMed1993

Psychology of computer use: XXIX. Measuring computer users' stress: the Computer Hassles Scale.

Measurement of computer users' stress was based on the Computer Hassles Scale. 65 questionnaires were returned from 113 mailed to users of accounting information systems who worked for manufacturing companies. Correlations were calculated for the total sample and subsamples divided by gender. The analysis indicated that persons with college degrees experienced greater computer users' stress than those who were without. Those persons who reported more computer hassles experienced more somatic complaints which indicated that the computer hassles were stressful. There were no significant mean differences between women and men on computer hassles or somatic complaints. The correlations of computer hassles with somatic complaints differed by gender. Women's computer hassles were significantly correlated .61 with somatic complaints, but men's computer hassles were not significantly correlated (r = .18) with somatic complaints. The gender differences suggest that there is a complex relationship between stressors (computer hassles) and stress reactions (somatic complaints).

Adult↗

PubMed1991

Psychology of computer use: XXIII. Validating a measure of computer-related stress.

Prediction of the final grade in a computer course using the Computer Technology Hassles Scale, a measure of computer-related stress, was investigated. A sample of 154 university students enrolled in computer courses completed questionnaires covering demographic data, information on computer use, the Computer Technology Hassles Scale, and somatic complaint items of the Hopkins Symptom Checklist. Pearson correlations indicated scores on the Computer Technology Hassles Scale were significantly associated .27 with somatic complaints, -.24 with computer-course grades, and -.18 with self-rated computer knowledge. Regression analysis indicated that self-rated computer knowledge and scores on the Computer Technology Hassles Scale significantly predicted computer-course grade.

Adult↗

PubMed1991

Relationship of computer hassles, somatic complaints, and daily hassles.

The relationships between computer hassles, measured by the Computer Technology Hassles Scale, daily hassles, measured by the Daily Hassles Scale, and somatic complaints, measured by the Hopkins Symptom Checklist, were investigated in a college sample of 103. Computer hassles were correlated .57 with daily hassles and .39 with somatic complaints. Daily hassles were correlated .62 with somatic complaints. In general, these measures were uncorrelated with computer experience or computer knowledge. The daily Hassles Scale, a measure of stress, is a better correlate for the Computer Technology Hassles Scale, a measure of computer-related stress, than the Perceived Stress Scale.

Adult↗

PubMed1990

Relating computer-associated stress to computerphobia.

The associations of computer-related stress, somatic complaints, and computerphobia were studied by administering questionnaires covering demographic data, exposure to computer information, computer-related stress, as measured by the Computer Technology Hassles Scale, somatic complaint items of the Hopkins Symptom Checklist, and Rosen, Sears, and Weil's measures of computerphobia: Computer Anxiety Rating Scale, Attitudes Toward Computers Scale, and Computer Thoughts Scale to 109 students. Correlations indicated scores on the Computer Technology Hassles Scale were significantly correlated .35 with somatic complaints, .27 with years used a computer, and .28 with self-rated computer knowledge. The Computer Technology Hassles Scale was not significantly correlated (.18, -.08, and -.05) with the three measures of computerphobia. Computer-related stress appears to be distinct from computerphobia.

Adult↗

PubMed1978

Behavioral correlates of age at first marijuana use.

Relationships between age at initial marijuana use and selected behavioral measures representing education, arrests, employment, alcohol use, and other drug use were examined for a sample of 370 male veterans. Younger age at marijuana use was found to be associated with less education, more arrests, and more other drug use prior to entering the service. A factor analysis of the correlates of age at initial marijiana use suggested three factors of delinquent activities: drug use, school delinquency, and other propensities for delinquency.

Adolescent↗