Purpose The number of cancer survivors worldwide is growing, with over 15.5 million cancer survivors in the United States alone—a figure expected to double in the coming decades. Cancer survivors face unique health challenges as a result of their cancer diagnosis and the impact of treatments on their physical and mental well-being. For example, cancer survivors often experience declines in physical functioning and quality of life while facing an increased risk of cancer recurrence and all-cause mortality compared with persons without cancer. The 2010 American College of Sports Medicine Roundtable was among the first reports to conclude that cancer survivors could safely engage in enough exercise training to improve physical fitness and restore physical functioning, enhance quality of life, and mitigate cancer-related fatigue. Methods A second Roundtable was convened in 2018 to advance exercise recommendations beyond public health guidelines and toward prescriptive programs specific to cancer type, treatments, and/or outcomes. Results Overall findings retained the conclusions that exercise training and testing were generally safe for cancer survivors and that every survivor should “avoid inactivity.” Enough evidence was available to conclude that specific doses of aerobic, combined aerobic plus resistance training, and/or resistance training could improve common cancer-related health outcomes, including anxiety, depressive symptoms, fatigue, physical functioning, and health-related quality of life. Implications for other outcomes, such as peripheral neuropathy and cognitive functioning, remain uncertain. Conclusions The proposed recommendations should serve as a guide for the fitness and health care professional working with cancer survivors. More research is needed to fill remaining gaps in knowledge to better serve cancer survivors, as well as fitness and health care professionals, to improve clinical practice.

Objective Given the critical role of behavior in preventing and treating chronic diseases, it is important to accelerate the development of behavioral treatments that can improve chronic disease prevention and outcomes. Findings from basic behavioral and social science research hold great promise for addressing behaviorally-based clinical health problems, yet there is currently no established pathway for translating fundamental behavioral science discoveries into health-related treatments ready for Phase III efficacy testing. This article provides a systematic framework for guiding efforts to translate basic behavioral science findings into behavioral treatments for preventing and treating chronic illness. Methods The ORBIT model for behavioral treatment development is described as involving a flexible and progressive process, pre-specified clinically significant milestones for forward movement, and return to earlier stages for refinement and optimization. Results This article presents the background and rationale for the ORBIT model, a summary of key questions for each phase, a selection of study designs and methodologies well-suited to answering these questions, and pre-specified milestones for forward or backward movement across phases. Conclusions The ORBIT model provides a progressive, clinically-relevant approach to increasing the number of evidence-based behavioral treatments available to prevent and treat chronic diseases.

No abstract

Results suggest that increased relative handgrip strength may be associated with a better profile of cardiovascular health biomarkers among U.S. adults. Relative grip strength, which both adjusts for the confounding of mass and assesses concomitant health risks of increased body size and low muscle strength, may be a useful public health measure of muscle strength.

Objectively measured MVPA displayed stronger associations with physiological and anthropometric biomarkers than self-reported MVPA. However, self-reported and objectively measured MVPA appear to capture distinct aspects of PA that are independently associated with certain biomarkers. Further understanding of the distinct contributions of self-reported and objectively measured PA to health outcomes could help to better identify optimal activity level and pattern.