CBT-I and other sleep interventions tend to yield significant improvements for 50-80% of individuals, and there is still a major gap in our understanding of the individual-level data for optimal treatment-matching, as well as how to improve motivation for the behavior change needed to maximize outcomes. In addition to the benefit of improving behavioral interventions themselves (e.g., adapting CBT-I for specific cultural contexts), behavioral adjuncts can meaningfully improve treatment response in myriad other sleep medicine interventions, such as motivational enhancement for PAP adherence. Finally, efforts to improve overall sleep health in non-clinical populations can benefit from similar considerations around motivation and behavior change, such as better contextualizing sleep hygiene and developing skills for self-assessment.
The goal of this research topic is to increase our understanding of current barriers to intervention delivery, identify strategies for overcoming these barriers, improve predictors of treatment response to enable better treatment matching, and innovate new interventions that are either broadly reaching (i.e. transdiagnostic) or tailored to a specific population. We welcome all article formats and encourage the use of archival data, such as from existing clinical databases, completed RCT’s, as well as larger scale surveys.
Topics of interest may include (but are not limited to):
Understanding patient experiences undergoing sleep interventions
Identifying predictors of outcomes
Increasing motivation for behavior change
Adapting CBT-I and other sleep interventions for specific populations
Promoting diversity & inclusion as a key component in behavioral sleep interventions
Distinguishing sleep hygiene from other sleep intervention components/strategies
Technology integration (e.g., wearable devices and mobile apps)
Topic editor PC is employed by Henry Ford Health. Topic Editor JO is employed by Nox Health. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
CBT-I and other sleep interventions tend to yield significant improvements for 50-80% of individuals, and there is still a major gap in our understanding of the individual-level data for optimal treatment-matching, as well as how to improve motivation for the behavior change needed to maximize outcomes. In addition to the benefit of improving behavioral interventions themselves (e.g., adapting CBT-I for specific cultural contexts), behavioral adjuncts can meaningfully improve treatment response in myriad other sleep medicine interventions, such as motivational enhancement for PAP adherence. Finally, efforts to improve overall sleep health in non-clinical populations can benefit from similar considerations around motivation and behavior change, such as better contextualizing sleep hygiene and developing skills for self-assessment.
The goal of this research topic is to increase our understanding of current barriers to intervention delivery, identify strategies for overcoming these barriers, improve predictors of treatment response to enable better treatment matching, and innovate new interventions that are either broadly reaching (i.e. transdiagnostic) or tailored to a specific population. We welcome all article formats and encourage the use of archival data, such as from existing clinical databases, completed RCT’s, as well as larger scale surveys.
Topics of interest may include (but are not limited to):
Understanding patient experiences undergoing sleep interventions
Identifying predictors of outcomes
Increasing motivation for behavior change
Adapting CBT-I and other sleep interventions for specific populations
Promoting diversity & inclusion as a key component in behavioral sleep interventions
Distinguishing sleep hygiene from other sleep intervention components/strategies
Technology integration (e.g., wearable devices and mobile apps)
Topic editor PC is employed by Henry Ford Health. Topic Editor JO is employed by Nox Health. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
