0771 the National Sleep Foundation’s Sleep Health Index

Knutson, KL; Phelan, Jo C.; Paskow, Michael; Roach, Anita; Whiton, Kaitlyn; Langer, Gary; Hillygus, D. Sunshine; Broughton, WA; Chokroverty, S; Lichstein, K; Weaver, Terri E.; Hirshkowitz, Max

doi:10.1093/sleepj/zsx050.770

Cited by 4 publications

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“…In addition, graduates of health care programs would need to be better prepared to screen, treat, and seek referrals for clients experiencing inadequate/poor sleep. One way this could be achieved would be to include training on use of the Sleep Health Index, developed by the National Sleep Foundation, 50 in educational curricula.…”

Section: Discussionmentioning

confidence: 99%

Sleep—an Essential Component of Obesity Screening and Counseling: A Policy Analysis of the Affordable Care Act

Owens

2019

INQUIRY

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The Patient Protection and Affordable Care Act (PPACA) has provided access to health care for millions of people in the United States. One of the most beneficial aspects of the PPACA is the obesity screening and counseling provision. Currently, it is estimated that over 39% of US adults are obese. Research has linked sleep disturbances to obesity and obesity-related behaviors. The purpose of this article is to advocate for evidence-based care through the inclusion of sleep disturbance screening and management under the PPACA obesity screening and counseling provision. An in-depth policy analysis of the PPACA was conducted to examine the feasibility of adding sleep screenings to the obesity screening and counseling provision available under current law. Findings suggest that the adoption of this policy would require stakeholder advocacy and educational reform. Implementation of the policy would require additional economic investments, but the long-term savings could be significant. A campaign to raise awareness regarding the association between sleep disturbance and obesity among the public and health care professionals would be essential. Policy implementation would require interprofessional collaboration when performing sleep disordered screening and management. Preventative health care for individuals who have not previously accessed the health care system has the potential to socially and economically benefit society if policies provide for evidence-based care. Sleep screening and counseling is essential under the PPACA to adequately address the US obesity crisis.

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Section: Discussionmentioning

confidence: 99%

Sleep—an Essential Component of Obesity Screening and Counseling: A Policy Analysis of the Affordable Care Act

Owens

2019

INQUIRY

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“…Sleep plays a critical role in sustaining life and health, with acutely or chronically disrupted sleep associated with diverse effects on brain function and systemic physiology, including hormonal, cardiovascular, immune, and metabolic effects ( Medic et al, 2017 ). Unfortunately, most American adults report trouble falling asleep, poor quality sleep, or difficulty staying asleep ( Knutson et al, 2017 ). Military work schedules exacerbate this issue, with chronic demands for continuous operations minimizing the quantity and quality of sleep ( Mysliwiec et al, 2013 ).…”

Section: Predictors Of Interest: Stress Sleep and Physical Exertionmentioning

confidence: 99%

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

et al. 2021

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Wearable technologies for measuring digital and chemical physiology are pervading the consumer market and hold potential to reliably classify states of relevance to human performance including stress, sleep deprivation, and physical exertion. The ability to efficiently and accurately classify physiological states based on wearable devices is improving. However, the inherent variability of human behavior within and across individuals makes it challenging to predict how identified states influence human performance outcomes of relevance to military operations and other high-stakes domains. We describe a computational modeling approach to address this challenge, seeking to translate user states obtained from a variety of sources including wearable devices into relevant and actionable insights across the cognitive and physical domains. Three status predictors were considered: stress level, sleep status, and extent of physical exertion; these independent variables were used to predict three human performance outcomes: reaction time, executive function, and perceptuo-motor control. The approach provides a complete, conditional probabilistic model of the performance variables given the status predictors. Construction of the model leverages diverse raw data sources to estimate marginal probability density functions for each of six independent and dependent variables of interest using parametric modeling and maximum likelihood estimation. The joint distributions among variables were optimized using an adaptive LASSO approach based on the strength and directionality of conditional relationships (effect sizes) derived from meta-analyses of extant research. The model optimization process converged on solutions that maintain the integrity of the original marginal distributions and the directionality and robustness of conditional relationships. The modeling framework described provides a flexible and extensible solution for human performance prediction, affording efficient expansion with additional independent and dependent variables of interest, ingestion of new raw data, and extension to two- and three-way interactions among independent variables. Continuing work includes model expansion to multiple independent and dependent variables, real-time model stimulation by wearable devices, individualized and small-group prediction, and laboratory and field validation.

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“…Sleep falls well below physical fitness, nutrition, or work on respondents’ lists of priorities. To examine the relationship between effectiveness and sleep more closely, the team from the NSF divided their sample into 4 quartiles based on each participant’s Sleep Health Index 2 (ie, a 12-item assessment of duration, quality, and disorders of sleep developed by the NSF). Sleep Health Index scores range from 0 to 100, with higher scores reflecting better sleep health.…”

Section: Sleep: a Fundamental Building Block For The Health And Well-mentioning

confidence: 99%

“…Sleep Health Index scores range from 0 to 100, with higher scores reflecting better sleep health. 2 Among those in the bottom quartile (ie, the worst sleepers with an average Sleep Health Index of 54), 1 only 46% rated themselves as extremely, highly, or very effective when it comes to getting things done each day. Among the top quartile—who had an average Sleep Health Index of 94—nearly double that percentage (89%) rated themselves as extremely, highly, or very effective.…”

Section: Sleep: a Fundamental Building Block For The Health And Well-mentioning

confidence: 99%

The Art of Health Promotion: linking research to practice

Johnson¹

2018

Am J Health Promot

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0771 the National Sleep Foundation’s Sleep Health Index

Cited by 4 publications

References 0 publications

Sleep—an Essential Component of Obesity Screening and Counseling: A Policy Analysis of the Affordable Care Act

Sleep—an Essential Component of Obesity Screening and Counseling: A Policy Analysis of the Affordable Care Act

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

The Art of Health Promotion: linking research to practice

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