Drawing on a conceptual model integrating research on training, work–family interventions, and social support, we conducted a quasi-experimental field study to assess the impact of a supervisor training and self-monitoring intervention designed to increase supervisors' use of family-supportive supervisor behaviors. Pre- and postintervention surveys were completed, 9 months apart, by 239 employees at 6 intervention (N = 117) and 6 control (N = 122) grocery store sites. Thirty-nine supervisors in the 6 intervention sites received the training consisting of 1 hr of self-paced computer-based training, 1 hr of face-to-face group training, followed by instructions for behavioral self-monitoring (recording the frequency of supportive behaviors) to facilitate on-the-job transfer. Results demonstrated a disordinal interaction for the effect of training and family-to-work conflict on employee job satisfaction, turnover intentions, and physical health. In particular, for these outcomes, positive training effects were observed for employees with high family-to-work conflict, whereas negative training effects were observed for employees with low family-to-work conflict. These moderation effects were mediated by the interactive effect of training and family-to-work conflict on employee perceptions of family-supportive supervisor behaviors. Implications of our findings for future work–family intervention development and evaluation are discussed.

The effective socialization of newcomers into organizations is critical for employee and organizational success. As such, ensuring successful onboarding has become even more pivotal for newcomer adjustment, performance, and retention. The literature has seen significant growth and incorporated new theoretical perspectives, such as resource-based approaches since the most recent comprehensive meta-analytic review of the literature. Therefore, we extended earlier reviews by presenting an updated model of the socialization process, reviewing the literature, and examining this updated model via meta-analysis. In all, we identified 256 studies that met our meta-analytic inclusion criteria, and 183 with sufficient k across construct categories were included in our meta-analysis. At the correlational level, we analyzed antecedents to proximal adjustment indicators and proximal adjustment to distal outcomes. We examined a potential moderator, whether the study took place in a horizontal-individualistic (HI) versus vertical-collectivistic (VC) culture. Last, we analyzed a path model to identify unique relationships between specific antecedents (age, full-time work experience, organizational tenure, proactive personality, information seeking, organizational tactics, insider mentoring/supporting), proximal adjustment indicators (social acceptance, role clarity, task mastery, perceived fit), and distal outcomes (job satisfaction, organizational commitment, turnover intentions, other-rated performance, and well-being). Our analyses uncover the role of proactive personality and proactive newcomer behaviors in newcomer adjustment and the importance of social acceptance for newcomers. They also identify perceptions of fit as an important but relatively under-examined adjustment indicator and newcomer well-being as an additional socialization outcome. We develop future directions for socialization theory and research methods.

Wilkinson et al. (1999) recommended that researchers include information on the practical magnitude of effects (e.g., using standardized effect sizes) to distinguish between the statistical and practical significance of research results. To date, however, researchers have not widely incorporated this recommendation into the interpretation and communication of the conditional effects and differences in conditional effects underlying statistical interactions involving a continuous moderator variable where at least one of the involved variables has an arbitrary metric. This article presents a descriptive approach to investigate two-way statistical interactions involving continuous moderator variables where the conditional effects underlying these interactions are expressed in standardized effect size metrics (i.e., standardized mean differences and semi-partial correlations). This approach permits researchers to evaluate and communicate the practical magnitude of particular conditional effects and differences in conditional effects using conventional and proposed guidelines, respectively, for the standardized effect size and therefore provides the researcher important supplementary information lacking under current approaches. The utility of this approach is demonstrated with two real data examples and important assumptions underlying the standardization process are highlighted.

Results are described for a survey assessing prevalence of missing data and reporting practices in studies with missing data in a random sample of empirical research journal articles from the PsychINFO database for the year 1999, two years prior to the publication of a special section on missing data in Psychological Methods. Analysis indicates missing data problems were found in about one-third of the studies. Further, analytical methods and reporting practices varied widely for studies with missing data. One may consider these results as baseline data to assess progress as reporting standards evolve for studies with missing data. Some potential reporting standards are discussed.