Mediation of Climate Anxiety in Doctors and Nurses: A Structural Equation Modelling Study - Ali, Yumna; Kazmi, Syeda Farhana (ETHICS IN PROGRESS, 2024)
Aims. The goal of this meteorological psychology study is to understand the behavioral implications on the professional lives of medical professionals in one of the most polluted regions of the world with a compromised air quality index. There is a paucity of literature to explore climate ethics as to how behavioral aspects of morals may alter related to climate change. Methods. The study is a cross-sectional correlational quantitative study formulated through purposive sampling. Research took place during the smog season of the world’s most polluted city. The research instruments of Climate anxiety, pain and distress, and cognitive failure were administered to a sample of 211 medical professionals. Confirmatory factor analysis was conducted and resulted in robust model fitness with indices between .80 and .90. Item loadings for three factors were statistically ideal of greater than. 30. Barron and Kenny’s approach was applied to conduct mediation through path analysis in which climate anxiety significantly mediates between pain distress and cognitive failure (β = .51; p < .0001). Multiple regression results using bootstrap confidence showed that climate anxiety (β = .993; p < .0001), and pain distress result in cognitive failure. The independent sample t-test was carried out to explore if nurses and doctors are different in terms of experiencing climate anxiety, pain distress, and cognitive failure. Results. There is a strong significant association among climate anxiety, pain distress, and cognitive failure with strong to moderate correlation values, p < .001. Confirmatory factor analysis was conducted and resulted in robust model fitness with indices between .80 and .90. Item loadings for three factors were statistically ideal at .30. 102 Nurses (M = 85.216; SD = 4.94) were more painfully distressed, prone to cognitive failure, and have climate anxiety as compared to 109 doctors (M = 71.211; SD = 9.23).