Organizational change is a system-wide process that begins at the individual level. Individuals who act as catalysts for change are often referred to as “change agents” and are lower level employees rather than designated leaders. In the current study Conservation of Resources Theory (COR) is utilized to construct a conditional process model of key resources and change agent influence. Specifically, this model tests the direct effects of General Cognitive Ability (GCA), Five Factor Model (FFM) personality facets, and Psychological Capital (PsyCap) – as well as the mediating role of PsyCap – on simulated change agent performance. Results suggest PsyCap positively correlates with performance, and, mediates the relationship between GCA and performance. Related narrow FFM facets moderate both stages of the mediation. These findings provide theoretical implication for COR as well as practical implications for human resource development interventions geared towards identification and development of change agents.

Trials of recovery training report mean gains in psychological detachment, but the mean does not show whether training helped the employees who detached least or those who already detached well. An aptitude-treatment account predicts larger gains at the low end of the baseline distribution (compensation), and a cumulative-advantage account predicts larger gains at the high end (accumulation). I tested the two accounts in a prespecified reanalysis of a randomized trial among German employees (N = 393, 76% women, mean age 41; 247 with posttest data) that compared a wait-list control with a 6-week cognitive-behavioral recovery training and a 6-week mindfulness-based training. The primary test was the baseline × condition interaction in a Lin-adjusted regression of posttest detachment; secondary analyses were quantile treatment effects, changes-in-changes and Lee bounds, multiple imputation, and a missingness model. Both trainings raised detachment at the mean baseline by about 0.9 points, and quantile effects were larger at the .25 than at the .75 quantile in both groups. The cognitive-behavioral interaction was −0.21 (95% CI [−0.50, 0.08]), leaning toward compensation, and the mindfulness interaction 0.04 (95% CI [−0.24, 0.33]); the condition contrast was 0.25 (95% CI [−0.01, 0.51]), and all three intervals included zero. Dropout before the posttest was not detectably patterned by baseline detachment in any group. The results support neither compensation nor accumulation. Neither training detectably favored employees at either end of the baseline distribution, and the intervals bound how large either pattern could be in a trial of this size.

Evaluations of brief self-compassion programs usually compare phases, leaving open whether meditation and nonmeditation days differ. With few nonmeditation days, subtracting each person's observed average can distort the separation of day-level from person-level effects. This secondary analysis used the archival 28-day diary of 65 employees in a two-week online selfcompassion meditation program, with morning reports of meditation over the previous 24 hours (Li et al., 2021). Across 14 intervention days, a prespecified Bayesian two-level model treated each person's meditation propensity as latent, separating the within-person contrast between meditation and nonmeditation days from stable differences in meditation frequency. Hypotheses were higher same-day self-compassion on meditation days (primary) and lower next-day emotional exhaustion, adjusting for same-day exhaustion (secondary). Results are posterior medians, 95% credible intervals (CrIs), and directional probabilities. For same-day selfcompassion, the meditation-day slope had median = 0.00 SD, 95% CrI [−0.09, 0.09], P(b > 0) = .48; for next-day exhaustion, the slope had median = −0.03 SD, 95% CrI [−0.16, 0.11], P(b < 0) = .65. Both CrIs spanned zero. An archival intervention diary can answer an adherence question its original phase-based analysis did not ask.