A common situation in the evaluation of intervention programs is the researcher’s possibility to rely on two waves of data only (i.e., pretest and posttest), which profoundly impacts on his/her choice about the possible statistical analyses to be conducted. Indeed, the evaluation of intervention programs based on a pretest-posttest design has been usually carried out by using classic statistical tests, such as family-wise ANOVA analyses, which are strongly limited by exclusively analyzing the intervention effects at the group level. In this article, we showed how second order multiple group latent change modeling (SO-MG-LCM) could represent a useful methodological tool to have a more realistic and informative assessment of intervention programs with two waves of data. We offered a practical step-by-step guide to properly implement this methodology, and we outlined the advantages of the LCM approach over classic ANOVA analyses. Furthermore, we also provided a real-data example by re-analyzing the implementation of the Young Prosocial Animation, a universal intervention program aimed at promoting prosociality among youth. In conclusion, albeit there are previous studies that pointed to the usefulness of MG-LCM to evaluate intervention programs (Curran & Muthén, 1999; Muthén & Curran, 1997), no previous study showed that it is possible to use this approach even in pretest-posttest (i.e., with only two time points) designs. Given the advantages of latent variable analyses in examining differences in interindividual and intraindividual changes (McArdle, 2009), the methodological and substantive implications of our proposed approach are discussed.

Workaholism and overcommitment are often used as interchangeable constructs describing an individual’s over-involvement toward their own job. Employees with high levels in both constructs are characterized by an excessive effort and attachment to their job, with the incapability to detach from it and negative consequences in terms of poor health and job burnout. However, few studies have simultaneously measured both constructs, and their relationships are still not clear. In this study, we try to disentangle workaholism and overcommitment by comparing them with theoretically related contextual and personal antecedents, as well as their health consequences. We conducted a nonprobability mixed mode research design on 133 employees from different organizations in Italy using both self- and other-reported measures. To test our hypothesis that workaholism and overcommitment are related yet different constructs, we used partial correlations and regression analyses. The results confirm that these two constructs are related to each other, but also outline that overcommitment (and not workaholism) is uniquely related to job burnout, so that overcommitment rather than workaholism could represent the true negative aspect of work drive. Additionally, workaholism is more related to conscientiousness than overcommitment, while overcommitment shows a stronger relationship with neuroticism than workaholism. The theoretical implications are discussed.