Quantifying Multi-step Avoidance in Anxiety
- Conditions
- AnxietyAnxiety Disorders
- Registration Number
- NCT07203027
- Lead Sponsor
- Emory University
- Brief Summary
This study aims to learn more about avoidance behavior in people with anxiety, using mathematical models of decision-making processes and decoded neural signals of threat imminence.
Researchers are investigating anxiety-related behavior and brain function in people with and without anxiety. Investigators are also looking at how behavior and brain function during tasks in the lab relate to avoidance in their daily lives. The investigators will also test whether changing how people avoid things in a behavioral task affects how people avoid things in their everyday life.
- Detailed Description
Current learning theories of anxiety propose that disrupted fear learning underlie anxiety disorders. This suggests that treatments like exposure therapy work by changing learned threat values. However, empirical data does not support these models where changes in fear conditioning lead to symptom changes and later reductions of avoidance behavior. Instead, recent findings suggest that avoidance behavior can be a mechanism on its own, and reductions in avoidance behavior both precede and predict improvements in anxiety symptoms. To target avoidance, a working theory of the processes underlying avoidance behavior is needed. Recently, Markov Decision Process (MDP) models have been used to measure threat expectancy, which has the advantage of capturing the difference between avoidance and fear learning as mechanisms in anxiety disorders. Initial MDP models that demonstrate the rise of avoidance behavior show promise; however, additional non-behavioral information is needed to fit these models in humans.
The researcher's main hypothesis is that MDP models, augmented with decoded neural signals of threat imminence, can characterize and modify anxiety disorder-related avoidance behavior in and outside of the laboratory.
Aim 1: Adults unselected for psychopathology (120, assessed twice): develop a brain signature of threat imminence (from a predictive model independently trained on fMRI data from other threat imminence tasks) and combine with task behavior to create an MDP model of avoidance behavior.
Aims 2 and 3: A separate set of participants with clinical anxiety and maladaptive avoidance (N=163, assessed four times) will complete an MDP-based learning task assessing avoidance during fMRI scanning and quantify differences in MDP-modeled behavior and test if the magnitude of these task-based differences predicts between-and within-person differences in the severity of real-world avoidance behavior.
Multivariate predictors of functional magnetic resonance imaging (fMRI) data can decode latent values and enhance the computational fit of the MDP models. To identify these latent values, previously validated neural signatures of a threat-imminence model will be used. In the threat-imminence model, the same brain regions (e.g., amygdala, vmPFC), but different ensembles and neural populations, are involved in different stages of threat imminence, and these patterns do not differ between humans with different levels of clinical anxiety, allowing for a neurobiologically supported approach to creating latent values of threat. Therefore, researchers aim to use MDP models, augmented with decoded neural signals of threat imminence, to characterize and support a new mechanism (avoidance behavior) of symptom change in anxiety and modify anxiety disorder-related avoidance behavior.
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 163
- Ability to comprehend written and spoken English
- Ability to provide informed consent
- Estimated intelligence quotient (IQ) >70.
- Clinically significant anxiety symptoms (scoring above clinical cutoff on at least one Inventory of Depression and Anxiety Symptoms (IDAS) anxiety-related subscale and/or OASIS total)
- Significant anxiety-related avoidance (scoring 2 or above on a 0-4 scale, indicating at least "occasional" avoidance) on the avoidance-related question on the Overall Anxiety Severity and Impairment Scale (OASIS)
- Functional impairment, defined as at least moderate impairment in one WHO Disability Assessment Schedule (WHODAS 2.0) domain related to anxiety.
- Individuals younger than 22 or older than 55,
- Individuals with an IQ < 70,
- A lifetime history of neurological disorder or brain damage,
- Contraindications for undergoing MRI scanning,
- A lifetime history or diagnosis of psychosis or bipolar disorder,
- Current substance use intoxication or withdrawal,
- Severe risk of suicide, or
- Recent (<3 months) changes in psychotropic medicine or psychotherapy treatment,
- Ineligible at the PI's discretion, are excluded.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Ecological momentary assessment (EMA) Baseline, week 1, week 2, week 3, and week 4 Participants will complete one week of ecological momentary assessment (EMA) to assess real-world avoidance behaviors after each of the scanning visits. The proportion of assessments where participants report engaging in avoidance behavior in the last hour will be assessed. Changes in the proportion of assessments where avoidance is reported will be used to measure changes in avoidance severity.
Avoidance Severity Based on Location Entropy Baseline, week 1, week 2, week 3, and week 4 Avoidance severity will be assessed using passive sensing of daily location patterns after each fMRI scanning visit. Participants will complete one week of passive sensing of location (using phone-based GPS measures) to assess real-world avoidance behaviors after each of the scanning visits. Changes in location entropy, representing the distribution of unique locations visited per day, will be used to measure changes in avoidance severity. Lower entropy values will indicate greater avoidance severity, while higher values will indicate less avoidance.
Change in Location Entropy Baseline, week 1, week 2, week 3, and week 4 Location entropy, defined as the distribution of unique locations visited per day, will be measured using one week of passive phone-based GPS monitoring after each fMRI scanning visit. This measure reflects variability in movement patterns and real-world avoidance behaviors.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (2)
Emory College
🇺🇸Atlanta, Georgia, United States
Facility for Education and Research in Neuroscience (FERN)
🇺🇸Atlanta, Georgia, United States
Emory College🇺🇸Atlanta, Georgia, United States