Human energy is a widely studied concept in organizational psychology and is embedded in several theoretical frameworks. This meta-analysis examines the nomological network of individual human energy at work, compares different conceptualizations and measures of human energy, and investigates its empirical overlap with related constructs such as engagement and thriving.
Artificial intelligence–enabled clinical decision support systems (AI-CDSSs) offer potential for improving health care outcomes, but their adoption among health care practitioners remains limited. The meta-analysis identified predictors influencing health care practitioners’ intention to use AI-CDSSs based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Additional predictors were examined based on existing empirical evidence.
One primary reason entrepreneurs abandon their goals is due to financial difficulties. In one experimental and two field studies, we found a positive relationship between financial stress and quit intention, mediated by affective commitment to their entrepreneurial endeavors. The findings are in line with the challenge–hindrance stressor (CHS) framework and self-determination theory (SDT).
According to transactional stress theory (TST), entrepreneurs’ coping strategies depend on viewing errors as challenges or threats. This study uses latent profile analysis to explore distinct profiles of challenge and threat appraisals among entrepreneurs. The findings reveal five appraisal profiles that highlight differences in error damage control and rumination, suggesting improvements for TST and error management interventions.
We conducted a study on the predictors of using AI-enabled mental health tools among psychology students and early practitioners.