Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Behavior Modification01:21

Behavior Modification

139
Behavioral approaches have often been criticized for ignoring mental processes and focusing solely on observable behavior. However, these approaches provide an optimistic perspective for individuals seeking to change their behaviors. Rather than concentrating on intrinsic personality traits, behavioral approaches suggest that even longstanding habits can be modified by changing the reward contingencies that maintain them.
A real-world application of operant conditioning principles is applied...
139
Operant Conditioning Intervention01:24

Operant Conditioning Intervention

56
Operant conditioning serves as a foundational principle in therapeutic interventions aimed at modifying maladaptive behaviors. Central to this approach is the notion that behaviors, both adaptive and maladaptive, are learned through reinforcement. By analyzing the environmental factors that reinforce problematic behaviors, clinicians can design interventions to weaken these reinforcements and replace maladaptive behaviors with healthier alternatives.
In operant conditioning, behaviors that are...
56
Modeling in Therapy01:26

Modeling in Therapy

66
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
66

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Community-Led Transformation in Practice: A Framework for Trust-Driven Community-Academic Partnerships to Advance Public Health.

Journal of immigrant and minority health·2026
Same author

Game, Set, and Match: A Scoping Review of Matching Characteristics for Control and Intervention Groups in Adaptive Behavioral Interventions for Physical Activity or Healthy Eating Designs for Populations with Overweight and Obesity.

Behavioral medicine (Washington, D.C.)·2026
Same author

Bridging the divide in digital therapeutics (DTx): Partnership strategies for broader representation across DTx development and deployment.

PLOS digital health·2026
Same author

An Early-Stage Digital Therapeutic Intervention to Enhance Affective Response During Physical Activity Among Adults With Overweight or Obesity: Benchmark-Driven Formative Testing Study.

JMIR human factors·2026
Same author

A Scoping Review of Sensor-Based Capture of Eating and Drinking Occasions That Could Be Used for Enhancing Personalized Nutrition Interventions in Real Time.

Advances in nutrition (Bethesda, Md.)·2025
Same author

An Optimized Behavioral Intervention for Managing Gestational Weight Gain Using Semi-Physical Modeling and Hybrid Model Predictive Control.

IEEE International Conference on Communications : [proceedings]. IEEE International Conference on Communications·2025
Same journal

State estimation of the time-space propagation of COVID-19 using a distributed parameter observer based on a SEIR-type model.

Journal of process control·2022
Same journal

On timeline of enhancing testing-capacity of COVID-19: A case study via an optimal replacement model.

Journal of process control·2021
Same journal

State estimation-based control of COVID-19 epidemic before and after vaccine development.

Journal of process control·2021
Same journal

Closed-Loop Control with Unannounced Exercise for Adults with Type 1 Diabetes using the Ensemble Model Predictive Control.

Journal of process control·2020
Same journal

Plasma-Insulin-Cognizant Adaptive Model Predictive Control for Artificial Pancreas Systems.

Journal of process control·2019
Same journal

A New Animal Model of Insulin-Glucose Dynamics in the Intraperitoneal Space Enhances Closed-Loop Control Performance.

Journal of process control·2019
See all related articles

Related Experiment Video

Updated: Jun 24, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

5.9K

Predicting Goal Attainment in Process-Oriented Behavioral Interventions Using a Data-Driven System Identification

Sarasij Banerjee1, Rachael T Kha1, Daniel E Rivera1

  • 1Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.

Journal of Process Control
|June 10, 2024
PubMed
Summary
This summary is machine-generated.

Personalized behavioral interventions can be optimized using system identification. This study used Discrete Simultaneous Perturbation Stochastic Approximation (DSPSA) to model individual differences in health behavior change, improving intervention design.

Keywords:
Data-driven estimationmHealthmodel validationmodeling and identificationpersonalized healthstochastic search

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K
Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.3K

Related Experiment Videos

Last Updated: Jun 24, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

5.9K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K
Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.3K

Area of Science:

  • Behavioral science
  • Systems engineering
  • Control theory

Background:

  • Behavioral interventions for health can be complex dynamic systems.
  • Understanding individual motivations is key to optimizing interventions.
  • System identification offers methods to model these complex behaviors.

Purpose of the Study:

  • To efficiently estimate personalized, dynamic models of health behavior.
  • To develop control systems for optimizing behavioral interventions.
  • To apply system identification to the 'Just Walk' study for increasing physical activity.

Main Methods:

  • Utilized Discrete Simultaneous Perturbation Stochastic Approximation (DSPSA) for modeling.
  • Employed AutoRegressive with eXogenous inputs (ARX) models for estimation.
  • DSPSA facilitated feature and model order selection for complex datasets.

Main Results:

  • DSPSA efficiently estimated personalized dynamic models of behavior.
  • The study identified significant individual variability in motivating factors.
  • DSPSA handled computationally intensive calculations effectively.

Conclusions:

  • Personalized dynamic models are crucial for effective behavioral interventions.
  • DSPSA is a powerful tool for analyzing complex behavioral data.
  • Optimized interventions require understanding and adapting to individual differences.