Greater understanding of the complex interrelationships among workrelevant constructs has increased the number of constructs on organizational surveys. Good psychometric practice also dictates the use of multiple items per construct. The net result has been longer surveys. Longer surveys take more time to complete, tend to have more missing data, and have higher refusal rates than short surveys. Arguably, then, techniques for reducing the length of scales while maintaining psychometric quality are worthwhile. Little guidance exists on how to reduce the length of a multi-item scale and we argue that the most common technique, maximizing internal consistency, is problematic and should be avoided. We present a set of item "quality indices" to help conceptualize the competing issues that influence item retention decisions. Statistical analysis of an example case using these indices suggested that there are 3 key aspects of item quality to consider when reducing a scale. We describe strategies that can assist scale developers in using these 3 aspects of item quality when making scale reduction decisions.

Identical questionnaire items were used to gather data from 2 samples of employees. One sample (n= 50) responded to a survey implemented on the World Wide Web. Another sample (n= 181) filled out a paper version of the survey. Analyses of the 2 data sets supported an exploration of the viability of World Wide Web data collection. The World Wide Web data had fewer missing values than the paper and pencil data. A covariance analysis simultaneously conducted in both samples indicated similar covariance structures among the tested variables. The costs and benefits of using access controls to improve sampling are discussed. Four applications that do not require such access controls are discussed.

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The objective of this research was to investigate the institutional and individual factors that influence scientists' data-sharing behaviors across different scientific disciplines. Two theoretical perspectives, institutional theory, and theory of planned behavior, were employed in developing a research model that showed the complementary nature of the institutional and individual factors influencing scientists' data-sharing behaviors. This research used a survey method to examine to what extent those institutional and individual factors influence scientists' data-sharing behaviors in a range of scientific disciplines. A national survey (with 1,317 scientists in 43 disciplines) showed that regulative pressure by journals, normative pressure at a discipline level, and perceived career benefit and scholarly altruism at an individual level had significant positive relationships with data-sharing behaviors, and that perceived effort had a significant negative relationship. Regulative pressure by funding agencies and the availability of data repositories at a discipline level and perceived career risk at an individual level were not found to have any significant relationships with data-sharing behaviors.

The present study focused on the development and validation of scores on the Stress in General scale. Three diverse samples of workers ( n = 4,322, n = 574, n = 34) provided psychometric and validity evidence. All evidence converged on the existence of two distinct subscales, each of which measured a different aspect of general work stress. The studies also resulted in meaningful patterns of correlations with stressor measures, a physiological measure of chronic stress (blood-pressure reactivity), general job attitude measures, and intentions to quit.