The Shift Task was designed to understand reinforcement learning (RL) in a complex, multidimensional environment. In this task, participants are presented with three stimuli characterized by three dimensions: (1) color, (2) texture, and (3) shape. Each of these dimensions has three different exemplars (e.g., shape could be circle, square, or triangle), so that, across the three stimuli, each exemplar from each dimension is represented once. The combinations of the three dimensions differ across presentations. One exemplar of one dimension (e.g., the triangle exemplar from the shape dimension) is associated with a 75% probability of reward; stimuli without this characteristic are associated with a 25% probability of reward. Participants select one of the three stimuli on each presentation, and are instructed to try to get as many points (“rewards”) as possible. Thus participants are incentivized to learn which exemplar is associated with a greater probability of reward. The rewarded exemplar is switched every 15-25 trials without notifying the participants. This switch could be to a different exemplar from the same dimension (e.g., from triangle to square) or to a different dimension (e.g., shape/triangle to color/red). Switching patterns are analyzed to determine the balance between a computationally efficient process of serial-hypothesis-testing – attending to one feature at a time – versus a fully Bayesian procedure taking advantage of all available probabilistic information.
Reinforcement Learning (RL) concerns the ways in which people come to identify which states (stimuli) and actions lead to a reward. The Shift Task was intended to extend RL models to a multidimensional context with multiple, potentially relevant stimuli, and to understand how people identify the relevant stimuli for reward (i.e. “representation learning”; Wilson & Niv, 2011). Understanding the ways in which people decide which stimuli are relevant and subsequent actions could shed light on self-regulatory processes governing behavior and behavior change.
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Text Citation: Wilson, R. C., & Niv, Y. (2011). Inferring relevance in a changing world. Frontiers in human neuroscience, 5.
This measure has not been measured yet.
This measure has not been influenced yet.
This measure has not been validated yet.
The Science of Behavior Change (SOBC) program seeks to promote basic research on the initiation, personalization and maintenance of behavior change. By integrating work across disciplines, this effort will lead to an improved understanding of the underlying principles of behavior change. The SOBC program aims to implement a mechanisms-focused, experimental medicine approach to behavior change research and to develop the tools required to implement such an approach. The experimental medicine approach involves: identifying an intervention target, developing measures to permit verification of the target, engaging the target through experimentation or intervention, and testing the degree to which target engagement produces the desired behavior change.
Within the SOBC Measures Repository, researchers have access to measures of mechanistic targets that have been (or are in the processing of being) validated by SOBC Research Network Members and other experts in the field. The SOBC Validation Process includes three important stages of evaluation for each proposed measure: Identification, Measurement, and Influence.
The first stage of validation requires a measure to be Identified within the field; there must be theoretical support for the specific measure of the proposed mechanistic target or potential mechanism of behavior change. This evidence may include references for the proposed measure, or theoretical support for the construct that the proposed measure is intended to assess. The second stage of validation requires demonstration that the level and change in level of the chosen mechanistic target can be Measured with the proposed measure (assay). For example, if the proposed measure is a questionnaire, the score on the measure should indicate the activity of the target process, and it must have strong psychometric properties. The third stage of validation requires demonstration that the measure can be Influenced; there must be evidence that the measured target is malleable and responsive to manipulation. Evidence relating to each stage includes at least one peer-reviewed publication or original data presentation (if no peer-reviewed research is available to support the claim) and is evaluated by SOBC Research Network Members and experts in the field.
Once a measure has gone through these three stages, it will then either be Validated or Not validated according to SOBC Research Network standards. If a measure is Validated, then change in the measured target was reliably associated with Behavior Change. If a measure is Not validated, then change in the measured target was not reliably associated with Behavior Change. Why would we share measures that are not validated? The SOBC Research Network values open, rigorous, and transparent research. Our goal is to make meaningful progress and develop replicable and effective interventions in behavior change science. Therefore, the SOBC sees value in providing other researchers in the field with information regarding measures that work and measures that fall short for specific targets. Further, a measure that is not validated for one target in one population may be validated in another target or population.
Want to learn more? For any questions regarding the SOBC Validation Process or Measures Repository, please email email@example.com.
Has the mechanism been identified as a potential target for behavior change? This section summarizes theoretical support for the mechanism.
Have the psychometric properties of this measure been assessed? This section includes information such as content validity, internal consistency, and test-retest reliability.
Has a study manipulation led to change in the mechanism? This section addresses evidence that this measure is modifiable by experimental manipulation or clinical intervention.
Has a change in this mechanism been associated with behavior change? This section addresses empirical evidence that causing change in the measure reliably produces subsequent behavior change.