"Teacher self-efficacy and burnout: Determining the directions of prediction through an autoregressive cross-lagged panel model": Correction to Kim and Burić (2019).

Abstract

Reports an error in Teacher self-efficacy and burnout: Determining the directions of prediction through an autoregressive cross-lagged panel model by Lisa E. Kim and Irena Buric (Journal of Educational Psychology, Advanced Online Publication, Oct 10, 2019, np). In the original article, one of the studies discussed (Praetorius et al., 2017), was incorrectly interpreted. The longitudinal study findings from Praetorius et al (2017) challenged the assumption that TSE may be an antecedent construct. When teachers’ stable inter-individual differences were taken into account, there were no significant cross-lagged effects from TSE to teaching quality (or vice versa). (The following abstract of the original article appeared in record 2019-60502-001). It is often assumed that low levels of teacher self-efficacy (TSE) leads to negative outcomes, including burnout; however, the temporal order of the construct predictions has rarely been examined. We used an autoregressive cross-lagged panel design to examine whether TSE and burnout are concurrently associated with each other, whether TSE predicts future burnout levels, and/or whether burnout predicts future TSE levels. An initial sample of 3,002 Croatian teachers (82% female) from across three educational levels (i.e., elementary, middle, and secondary schools) with varying years of teaching experiences (M = 15.28, SD = 10.50) completed questionnaires on their levels of TSE and burnout (exhaustion and disengagement) at 3 time points (at approximately 6-month intervals). We found that burnout has a more prominent role in predicting future levels of TSE than TSE does in predicting future levels of burnout. These findings challenge the theoretical and empirical conceptualizations assuming that TSE is a predictor of burnout. Policies and interventions that focus on decreasing teacher burnout rather than increasing TSE levels may be best. (PsycInfo Database Record (c) 2020 APA, all rights reserved)