Translating cross-lagged effects into incidence rates and risk ratios: The case of psychosocial safety climate and depression
本文提出一种方法，将纵向研究中的交叉滞后效应转化为风险比，并以心理社会安全氛围与抑郁为例，利用澳大利亚数据估计了不同PSC水平下4年内持续抑郁障碍的发病率。
Longitudinal studies are the gold standard of empirical work and stress research whenever experiments are not plausible. Frequently, scales are used to assess risk factors and their consequences, and cross-lagged effects are estimated to determine possible risks. Methods to translate cross-lagged effects into risk ratios to facilitate risk assessment do not yet exist, which creates a divide between psychological and epidemiological work stress research. The aim of the present paper is to demonstrate how cross-lagged effects can be used to assess the risk ratio of different levels of psychosocial safety climate (PSC) in organisations, an important psychosocial risk for the development of depression. We used available longitudinal evidence from the Australian Workplace Barometer (N = 1905) to estimate cross-lagged effects of PSC on depression. We applied continuous time modelling to obtain time-scalable cross effects. These were further investigated in a 4-year Monte Carlo simulation, which translated them into 4-year incident rates. Incident rates were determined by relying on clinically relevant 2-year periods of depression. We suggest a critical value of PSC = 26 (corresponding to −1.4 SD), which is indicative of more than 100% increased incidents of persistent depressive disorder in 4-year periods compared to average levels of PSC across 4 years.