Refining the Allostatic Self-Efficacy Theory of Fatigue and Depression Using Causal Inference.

Area of Science:

• Computational psychiatry
• Neuroscience
• Psychology

Background:

• Allostatic self-efficacy (ASE) theory proposes fatigue arises from perceived loss of bodily control and depression from generalized low self-efficacy.
• Existing ASE theory lacks a formal causal structure for empirical testing.

Purpose of the Study:

• To convert ASE theory into a structural causal model (SCM) for empirical validation.
• To test specific causal hypotheses derived from the ASE SCM using questionnaire data.
• To refine the ASE SCM based on empirical findings.

Main Methods:

• Development of a structural causal model (SCM) based on ASE theory.
• Application of conditional independence tests to questionnaire data from healthy volunteers.
• Estimation of causal effects using three distinct statistical methods.

Main Results:

• Identified inconsistencies between the initial ASE SCM and the collected data, leading to an updated SCM.
• Confirmed a negative causal effect of metacognition of allostatic control on fatigue across all estimation methods.
• Validated key predictions of ASE theory while highlighting areas for revision.

Conclusions:

• The study successfully formalized ASE theory using causal inference, providing testable hypotheses.
• Results support core tenets of ASE theory regarding fatigue and self-efficacy but necessitate model refinement.
• An updated ASE SCM is proposed for future empirical verification and advancement of fatigue and depression research.