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Research on resilience is a growing field, and resilience has been conceptualized and operationalized in multiple ways. The aim of this study was to compare the Brief Resilient Coping Scale (BRCS), a conventional measure of resilience, with within-person process indicators derived from experience sampling method (ESM). A sample of 177 teachers from southern Finland participated in the study, commencing with a startup session followed by an 8-day ESM period. Through twice-daily prompts, participants reported their immediate positive and negative affect as well as recent stressors encountered, such as workload and challenging social interactions. As expected, within-person variation in affect was predicted by stressors. However, contrary to expectations, individual differences in affective reactivity to stressors were not predicted by BRCS (βpositive affect [95% CI] = −.20, [−.51,.11]; βnegative affect =.33, [−.07,.69]). Item response theory analyses of the BRCS revealed problems with precision. The results call into question the validity of measuring resilience using single administrations of retrospective self-report questionnaires such as the BRCS. [ABSTRACT FROM AUTHOR]

Intensive longitudinal data (ILD) has been collected to capture the dynamic fluctuations of procrastination; however, researchers have typically measured daily procrastination by modifying trait measures (e.g., adding a time reference "today") without adequately testing their reliabilities. The main purpose of this study was to use an advanced approach, dynamic structural equation modeling, to assess the between- and within-person reliabilities of a widely used six-item measure of daily procrastination. A total of 252 participants completed retrospective measures of various types of trait procrastination and daily measures of procrastination over 34 consecutive days. The results showed that the entire scale for daily procrastination and five of its six items had high between- and within-person reliabilities, but one item had much lower reliabilities, suggesting that this item may be inappropriate in everyday contexts. Furthermore, we found moderate to strong associations between the latent trait factor of procrastination and trait measures of procrastination. In addition, we identified substantial between-person variation in person-specific reliabilities and explored its relevant factors. Overall, this study assessed the reliabilities of a daily measure of procrastination, which facilitated future studies to obtain more reliable and consistent results and to better estimate the reliability of ILD. [ABSTRACT FROM AUTHOR]

Recent developments in theories and data collection methods have made intensive longitudinal data (ILD) increasingly relevant and available for organizational research. New methods for analyzing ILD have emerged under the multilevel modeling framework. In this article, we first delineate features of ILD (including autoregressive relationships, trends, cycles/seasons, and between-subject variability in temporal trends). We discuss the analytic challenges for handling ILD using traditional analytic tools familiar to organizational researchers (e.g., growth models, single-subject time series analyses). We then introduce a statistical approach for handling ILD from the multilevel modeling framework: dynamic structural equation modeling (DSEM). We provide three examples using simulated data sets to demonstrate how to apply DSEM to examine ILD with a software program familiar to organizational researchers (i.e., M plus). Finally, we discuss issues related to applying DSEM, including centering, missing data, and sample size. [ABSTRACT FROM AUTHOR]