Technology-Based Monitoring and Intervention Delivery: Expanding Behavior-Analytic Treatment to Health Behavior

2017 ◽  
Vol 43 (2) ◽  
pp. 254-281
Author(s):  
Lisa Stedman-Falls ◽  
◽  
Jesse Dallery
Keyword(s):  
Health Behavior ◽  
Analytic Treatment ◽  
Intervention Delivery ◽  
Behavior Analytic Treatment

Behavior Analytic Treatment of Behavioral Excesses and Deficits of Autism: The Case of Jorge

2013 ◽  
pp. 54-76
Author(s):  
W. Larry Williams ◽  
Ashley E. Greenwald ◽  
Holly A. Seniuk
Keyword(s):  
Applied Behavior Analysis ◽  
Case History ◽  
Behavior Intervention ◽  
Case Formulation ◽  
Potential Treatment ◽  
Ethical Considerations ◽  
Childhood Behavior ◽  
Analytic Treatment ◽  
Intervention Planning ◽  
Behavior Analytic Treatment

Chapter 3 discusses a case of behavioral analytic treatment in relation to behavioral excesses and deficits of autism, including the case history, epidemiological considerations, applied behavior analysis (ABA), early childhood behavior intervention, assessment, case formulation, intervention planning, addressing nonspecifics within the therapy module, potential treatment obstacles, ethical considerations, and common treatment mistakes to avoid.

scholarly journals Interest in Health Behavior Intervention Delivery Modalities Among Cancer Survivors: A Cross-Sectional Study

JMIR Cancer ◽  
2016 ◽  
Vol 2 (1) ◽  
pp. e1 ◽  
Author(s):  
Emily C Martin ◽  
Karen Basen-Engquist ◽  
Matthew G Cox ◽  
Elizabeth J Lyons ◽  
Cindy L Carmack ◽  
...  
Keyword(s):  
Health Behavior ◽  
Cancer Survivors ◽  
Cross Sectional Study ◽  
Behavior Intervention ◽  
Sectional Study ◽  
Cross Sectional ◽  
Intervention Delivery ◽  
Health Behavior Intervention

Behavior-Analytic Treatment Progression for a Child With Tube Dependence: Reaching Age-Typical Feeding

2020 ◽  
Vol 19 (6) ◽  
pp. 403-417
Author(s):  
Bethany A. Hansen ◽  
Ashley S. Andersen
Keyword(s):  
Interdisciplinary Collaboration ◽  
Day Treatment ◽  
Current Case ◽  
Analytic Treatment ◽  
Effective Interventions ◽  
Age Appropriate ◽  
Day Treatment Program ◽  
Behavior Analytic Treatment

The current case study outlines a behavior-analytic treatment progression for a child with a pediatric feeding disorder and tube dependence. The child participated in an intensive day-treatment program for 8 weeks where she transitioned from tube feedings to oral feedings. She successfully transitioned to a less intensive, telehealth outpatient model for follow-up care where she continued to progress to age-typical feeding. Following a systematic and gradual reduction in follow-up appointments, she consumed all meals of age-appropriate foods in both home and school environments. Another important contribution of the case study is that it demonstrated the importance of follow-up services that occur in the child’s natural environment while highlighting the utility of rubrics. With rubrics, caregivers effectively and efficiently progressed toward treatment goals independently. This case study also discusses the importance of ongoing interdisciplinary collaboration and the unique contributions of each team member in employing effective interventions while ensuring client safety.

scholarly journals Digital health data-driven approaches to understand human behavior

2020 ◽  
Vol 46 (1) ◽  
pp. 191-196 ◽  
Author(s):  
Lisa A. Marsch
Keyword(s):  
Health Behavior ◽  
Human Behavior ◽  
Digital Health ◽  
Health Assessment ◽  
Health Data ◽  
Data Driven ◽  
Impact Behavior ◽  
Intervention Delivery ◽  
The Moment ◽  
Over Time

AbstractAdvances in digital technologies and data analytics have created unparalleled opportunities to assess and modify health behavior and thus accelerate the ability of science to understand and contribute to improved health behavior and health outcomes. Digital health data capture the richness and granularity of individuals’ behavior, the confluence of factors that impact behavior in the moment, and the within-individual evolution of behavior over time. These data may contribute to discovery science by revealing digital markers of health/risk behavior as well as translational science by informing personalized and timely models of intervention delivery. And they may help inform diagnostic classification of clinically problematic behavior and the clinical trajectories of diagnosable disorders over time. This manuscript provides a review of the state of the science of digital health data-driven approaches to understanding human behavior. It reviews methods of digital health assessment and sources of digital health data. It provides a synthesis of the scientific literature evaluating how digitally derived empirical data can inform our understanding of health behavior, with a particular focus on understanding the assessment, diagnosis and clinical trajectories of psychiatric disorders. And, it concludes with a discussion of future directions and timely opportunities in this line of research and its clinical application.

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