Sorjonen Kimmo, Melin Bo, Folke Filippa, Melin Marika
Karolinska Institutet (KI), Solna, Sweden.
Front Psychol. 2025 Aug 29;16:1618120. doi: 10.3389/fpsyg.2025.1618120. eCollection 2025.
Burnout and exhaustion has been extensively studied in organizational, work, and health psychology. Studies using the cross-lagged panel models have tended to conclude, explicitly or implicitly (e.g., in the form of policy recommendations), causal prospective effects of, for example, organizational demands, job insecurity, and depression on burnout and exhaustion. However, it is well established that effects in the cross-lagged panel model may be artifactual, e.g., due to correlations with residuals and regression to the mean. Here, we scrutinized 23 previously reported prospective effects on burnout/exhaustion by fitting complementary models to data that were simulated to resemble data in the evaluated studies. With one possible exception, the previously reported prospective effects did not withstand scrutiny, i.e., they appeared to be artifactual. It is important for researchers to bear in mind that correlations, including effects in cross-lagged panel models, do not prove causality in order not to overinterpret findings. We recommend researchers to scrutinize findings from cross-lagged panel models by fitting complementary models to their data. If findings from complementary models converge, conclusions are corroborated. If, on the other hand, findings diverge, caution is advised and claims of causality, explicit or implicit, should probably be avoided.
职业倦怠和疲惫在组织心理学、工作心理学和健康心理学领域已得到广泛研究。使用交叉滞后面板模型的研究往往会明确或隐含地（例如以政策建议的形式）得出诸如组织需求、工作不安全感和抑郁等因素对职业倦怠和疲惫的因果前瞻性影响。然而，众所周知，交叉滞后面板模型中的效应可能是人为造成的，例如由于与残差的相关性以及均值回归。在此，我们通过对模拟数据拟合补充模型，仔细审查了之前报道的23个关于职业倦怠/疲惫的前瞻性影响，这些模拟数据类似于评估研究中的数据。除了一个可能的例外，之前报道的前瞻性影响经不起审查，也就是说，它们似乎是人为造成的。研究人员必须牢记，相关性，包括交叉滞后面板模型中的效应，并不能证明因果关系，以免过度解读研究结果。我们建议研究人员通过对自己的数据拟合补充模型来仔细审查交叉滞后面板模型的研究结果。如果补充模型的结果一致，则结论得到证实。另一方面，如果结果不一致，则建议谨慎行事，应避免明确或隐含地声称存在因果关系。
