Computational Model for Behavior Shaping as an Adaptive Health Intervention Strategy

Background: Adaptive behavioral interventions that automatically adjust in real-time to participants’ changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. Purpose: JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. Methods: A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Results: Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared to a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. Conclusions: The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated.

Analysis on Pilot's Behavior Shaping Factors upon Aviation Case Base

In recent years, over 75% civil aviation accidents are caused by pilots manipulation mistake or cognitive error, but there is still no quantitative method to research pilots error. With the statistics and analysis of NTSB (National Transportation Safety Board) aviation database, the aviation case base ontology model has been established in the paper, which was the closest airworthiness directive to classify the aviation accidents according to the classification of aviation system. The pilots error in the aviation accident and the factors possibly causing the pilots error were analyzed based on Reason model to propose the inducing factors for pilots error. With the human factor analytical method, the behavior factors inducing the pilots error obtained from the pilot himself included excessive manipulation number, external environment interference, insufficient experience, physiological and psychological conditions, insufficient time margin. Pilots behavior shaping factors can guide the rational design of manipulation procedure and pilot training, thus enhancing the flight safety.