Registatrion for the Behaviour Change for Health and Sustainability 8th Annual Conference

The UCL Centre for Behaviour Change would be delighted to see you at the 8th annual conference, hosted online from the 7th-9th November 2022, with the theme Behaviour Change for Health and Sustainability.

Keynote speakers include: Elena AltieriDr Kim Lavoie, and Dr Felix Naughton.

You can register here: https://abbey.eventsair.com/cbc2022/cbc2022reg/Site/Register

 

Early bird rates will end on 30th September 2022!

For further information on the conference please visit https://www.ucl.ac.uk/behaviour-change/cbc-conference-2022-behaviour-change-health-and-sustainability

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NIH Stage Model for Behavioral Intervention Development

The Stage Model is a model of behavioral intervention development composed of six stages: basic science (Stage 0), intervention generation, refinement, modification, and adaptation and pilot testing (Stage I); traditional efficacy testing (Stage II); efficacy testing with real-world providers (Stage III); effectiveness research (Stage IV) and; dissemination and implementation research (Stage V). Examination of mechanisms of behavior change is encouraged in every stage of intervention development. Consideration of the intervention’s ease of implementation is encouraged as early as possible in the intervention development process. The ultimate goal is to produce highly potent and maximally implementable behavioral interventions that improve health and well-being.

Learn about the NIH Stage Model through this training video: click here

 

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Call for Papers: Special Issue in Behavior Therapy

Special Issue Title: Cognitive Behavioral Treatment Development: An Experimental Therapeutics Focus on Novel Mechanistic Targets

Special Issue Guest Editors: Michael W. Otto, PhD and Jeffrey L. Birk, PhD

The core of the National Institutes of Health (NIH) experimental therapeutics approach is a focus on specifying and then rigorously testing potential mechanisms by which treatments may exert their beneficial effects. The purpose of this special issue for Behavior Therapy is to put a direct focus on the “pipeline” of potential mechanistic targets for behavior change by presenting a series of empirical papers on novel mechanistic variables. We encourage submitted papers that investigate mechanistic variables in research reflecting an early stage of intervention development prior to clinical trial testing. This special issue highlights research that follows the recommended NIH Science of Behavior Change (SOBC) developmental format of: (1) identifying hypothesized mechanisms of behavior change, (2) utilizing reliable measures of those mechanisms, (3) conducting experiments to influence those mechanisms, and/or (4) testing whether influencing a hypothesized mechanism indeed yields behavior change (see Nielson et al., 2018, BRAT; Riddle et al., 2015, Translational Behavioral Medicine). For the series, we are interested in empirical articles offering elements #1, #2, and/or #3 that present new data showing the identification of novel mechanistic factors that may underlie behavior change, as relevant to psychopathology or negative health behaviors. Relevant to element #1, identification of novel mechanistic targets often starts by showing associations with psychopathology cross-sectionally and longitudinally. The focus will be on papers that span the range between basic science and initial intervention development.

This special issue is particularly interested in studies that include diverse and representative samples and/or that explicitly address issues of race, ethnicity, and culture.

* Deadline for article proposals/letter of intent: December 3, 2021. Please submit article proposals/letters of intent by email directly to SOBC’s Project Coordinator, Deanna Lewis, at djl2185@cumc.columbia.edu.

Timeline

Deadline for article proposals/letter of intent: December 3, 2021

Deadline for submission of full papers: February 10, 2022

 

November 2, 2021 | Sean D. Young, Ph.D., M.S. Presents: Reading Between the Tweets: Social Technologies for Predicting and Changing Health Behavior

Speaker: Sean D. Young, Ph.D., M.S.

Executive Director, University of California Institute for Prediction Technology

Associate Professor, Departments of Emergency Medicine and Informatics, University of California, Irvine

Date: November 2, 2021 – 1:00 p.m. ET to 2:00 p.m. ET

Location: VirtualNIH videocast >

Description: Social technologies and their associated data are increasingly being used as tools in public health research and practice. Examples include social media, mobile apps, internet searches, and wearable sensors. More than half the world (4.5 billion people) uses social media sites to create, share, and discuss content—often in the form of personal thoughts, behaviors, and clinical diagnoses. Dr. Young will discuss how social technologies and data (e.g., artificial intelligence and data science modeling) are being used to impact public health and how researchers and health departments/agencies might apply them in public health surveillance/intervention efforts. He will also present his team’s research on how these tools can be employed to predict and change health behaviors, and on implementation-related issues such as policy and ethical questions. The studies to be discussed involve populations affected by HIV, mental health and substance use disorders, car crashes, or COVID-19.

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Funding Opportunity | Columbia Roybal Center Pilot Award Program: Pilot Grants for Health Behavior Interventions

The NIA-funded Columbia Roybal Center for Fearless Behavior Change will fund one-year pilot studies relevant to developing health behavior interventions for patients who have suffered acute medical events. Our prior research has shown that many patients develop fear-based responses to these traumatic events (e.g., fear of recurrence, heightened distress from internal physiologic stimuli) that lead to avoidance of the very health behaviors (e.g., exercise, take medications regularly) that are recommended to prevent recurrence. Accordingly, our Center seeks to develop interventions that address these fear-related mechanisms. Relevant study populations include, but are not limited to, patients with stroke, myocardial infarction, cardiac arrest, COPD, heart failure, respiratory failure, COVID-19, or recent diagnosis with cancer or end-stage renal disease. Relevant behavioral outcomes include, but are not limited to, medication adherence, physical activity, sleep, as well as measures of psychological distress and quality of life. The goal of the award is to help investigators obtain preliminary data to support independent grant applications to the NIH or other funders. Applicants are encouraged to follow the experimental medicine approach to intervention development promoted by the Science of Behavior Change.

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