This research investigated problems commonly experienced by children and young adolescents, and the strategies they use to cope with these events. Six hundred seventy-six children, ages 9-13 years, were asked to identify a problem they recently experienced and to describe the strategies they used to cope with it. In addition, they were also asked to complete a scale describing how they coped with a common problem (being grounded by parents). In general, we found that children reported four common Stressors: parents, siblings, school, and friends. These Stressors were the same across age and sex; however, the coping strategies employed differed by age and type of problem. Both age and sex effects were found in reported use of coping strategies to deal with being grounded by parents. The results of this study suggest that more research must be performed to offset the lack of data in the area of children's normative coping. The implications of the findings for clinical assessment and treatment of children are discussed.

Undergraduate subjects possessing normative or idiosyncratic rating standards were given frame-ofreference training, rater-error training, training that controlled for structural similarities between frame-of-reference training and rater-error training, or null control training. Hypothesized pretest differences that normative raters are more accurate than idiosyncratic raters were not found. However, when data were collapsed across rating aptitude, different trainings were found to improve different measures of accuracy. Frame-of-reference trainees were most accurate on stereotype accuracy and differential accuracy, rater-error trainees were most accurate on elevation, and all groups improved on differential elevation. Results are discussed in relation to the role of rater aptitude in frame-of-reference training and the future of rater-training programs.Recent performance appraisal studies on rater training have focused on frame-of-reference training (FOR) and rater-error training (RET; e.g., Hedge &Kavanaugh, 1988;Pulakos, 1984). These studies have generally concluded that FOR is superior to RET. As a result, researchers have begun to isolate aspects of the content of FOR that lead to increased accuracy in performance ratings (Athey & Mclntyre, 1987;Sulsky & Day, 1992). However, there are several limitations in the FOR research that raise questions about the general superiority of FOR. Our purpose in this study was to address these limitations and to assess whether FOR is best for all types of rating accuracy.From a historical perspective, FOR evolved from Bernardin's work (Bernardin & Buckley, 1981;Bernardin & Pence, 1980) on rater training. Bernardin and Pence noted that traditional RET stresses that certain rating distributions are more desirable than others and that RET facilitates the learning of a new response set, which may result in lower mean ratings (less leniency) and lower scale intercorrelations (less halo), but which may also lower levels of accuracy. Indeed, they found that RET led to less accurate ratings than those obtained from a group of untrained raters. Bernardin and Pence concluded that there was a need to develop new rater-training programs that increase rating accuracy, and Bernardin and Buckley (1981) proposed FOR as an alternative training strategy.As originally proposed, FOR initially involves the identification of raters who possess idiosyncratic performance standards.

The Myers-Briggs Type Indicator (MBTI) has achieved widespread use in organizational settings, despite the fact that research on its dimensionality has been scarce and that some studies have questioned the validity of its four-factor scoring system. Confirmatory factor analyses of 94 MBTI items (N = 1,091) were performed, the results of which provided qualified support for the four-factor model; the qualifications arose from the fact that model-fit indexes for even the best-fitting models were considerably below their maximum desirable values. In an attempt to identify areas in which model fit could be improved, exploratory factor analyses were also conducted; these analyses strongly supported a four-factor view of the MBTI and indicated several additional factor loadings that could be freed to improve model fit.

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