Correlation or Causation? Optimal Safe Threshold between Prediction and Inference towards Human Behavior in Conservation Psychology

Conservation psychology is pure and applied science with the tenet of reconciling self-in-relation to nature and bestirring sustainable behavior. Conceptually, predicting and inferring human behavior is an essential linkage to touch base with the marrow of conservation psychology. Empirical evidence from multiple experience-based models has been leveraged to gauge human behavior in conservation psychology. Yet, most of them fail to elucidate the underlying mechanism for better intervention to the inclusion of nature in self, just to demonstrate the statistical correlation. Namely, the exploration for causality of intervention corresponding to human behavior is lacunae. There is a rife consensus that the paucity of detecting endogenous might spawn an apathy toward causation. Thus, the causal inference models are contemplated to be harnessed. From the classic perspective of the attribution theory, this article reviews major ingenious-conceived experience-based models for sustainable behavior prediction first. Penetratingly converging research efforts on the statistical methods and theories for causal inference under the framework of potential outcomes (aka.Counter-factual) to forge robust causality and ultimately stimulate positive sustainable behavior.Retrofitting the research paradigm from statistical correlation to true causation. Still, we initiate the trade-off between correlation and causation in real-world scenarios. Truly, selecting the model is supposed to be congenial to the research topic. In the wake of the recognition that human behavior rests on both inside-out internal variables (e.g.self-intention) and outside-in external variables (e.g.policy) in conservation psychology, we recommend that experience-based models are employed in human behavior prediction with internal variables since the inherent theoretical chains in models could withstand rigorous empirical testing. Correspondingly, causal analysis is a warranting apparatus for policy evaluation, thereby causal inference models are tending to be labeled to infer human behavior with external variables in conservation psychology.