Health-Related and Lifestyle Factors as Predictors of Intentions to Improve Lifestyle Habits in Employees Participating in a Workplace Health Promotion Program.

OBJECTIVES: To explore employees' intentions to improve lifestyle habits, investigate the health and lifestyle-related predictors of these intentions, and how it translated into behavioral improvement. METHODS: Employees participating in the Activate Your Health WHPP completed a questionnaire of their demographics, health-related variables, as well as six lifestyle habits and intention to improve them. RESULTS: At baseline (n = 2729), most employees wanted to focus on physical activity and eating habits. Many predictors were identified for each intention. Majority of intentions were associated with behavioral improvement post-program (n = 525), especially in High. CONCLUSIONS: In the context of WHPPs, intention to improve may lead to actual behavioral improvement. Exploring employees' intentions to improve various lifestyle habits at the start of the program could improve the effectiveness of these programs.

Activate Your Health, a 3-year, multi-site, workplace healthy lifestyle promotion program: study design.

BACKGROUND: Workplace Health Promotion Programs (WHPP) have been shown to be an efficient way of improving workers' health. These programs can be incorporated in the worker's daily schedule and improve their productivity at work. Improving employees' health also benefits the employers by increasing their return on investment and lowering healthcare costs. The Activate Your Health program, created by Capsana in 2015, is a WHPP targeting multiple lifestyle habits for a three-year period. This WHPP includes tailored web-based interventions and the support of different health professionals throughout the years. We hypothesize that this approach will yield long-term lifestyle changes. The objective of the current paper is to describe the Activate Your Health program's design. METHODS/DESIGN: Eleven companies are taking part in this WHPP and had to choose among five different options of this program and all their employees were encouraged to participate. Each option differs by the number and type of interventions included. The limited option, which is considered the control group, only consists in completing a questionnaire regarding their health status, lifestyle habits and behaviors. On the other end, the extensive option receives a combination of multiple interventions: online menus, health challenges, support in creating a healthy work environment, coaching by health professionals (nurse, nutritionist, and kinesiologist), health screening and flexibility assessment, online resources, social health platform, and activity tracking. The remaining options are in between these options and vary by the amount of intervention. Baseline data are already gathered; two other data collection periods will take place after one and 2 years into the program. The primary outcomes of the current program are physical activity and fitness measures, nutritional data, smoking habits, stress and intention to change. DISCUSSION: The Activate Your Health program will allow us to compare which combinations of interventions are the most effective. It is expected that the extensive option will be the most advantageous to improve lifestyle habits. The results will indicate the strength and weakness of each intervention and how it could be improved. TRIAL REGISTRATION: Clinicaltrails.gov, registration number: NCT02933385 (updated on the 26th of March 2019, initially registered on the 5th of October 2016).

Health and productivity at work: which active workstation for which benefits: a systematic review.

In order to reduce sedentary behaviour at work, research has examined the effectiveness of active workstations. However, despite their relevance in replacing conventional desks, the comparison between types of active workstations and their respective benefits remains unclear. The purpose of this review article is thus to compare the benefits between standing, treadmill and cycling workstations. Search criteria explored Embase, PubMed and Web of Science databases. The review included studies concerning adults using at least two types of active workstations, evaluating biomechanical, physiological work performance and/or psychobiological outcomes. Twelve original articles were included. Treadmill workstations induced greater movement/activity and greater muscular activity in the upper limbs compared with standing workstations. Treadmill and cycling workstations resulted in elevated heart rate, decreased ambulatory blood pressure and increased energy expenditure during the workday compared with standing workstations. Treadmill workstations reduced fine motor skill function (ie, typing, mouse pointing and combined keyboard/mouse tasks) compared with cycling and standing workstations. Cycling workstations resulted in improved simple processing task speeds compared with standing and treadmill workstations. Treadmill and cycling workstations increased arousal and decreased boredom compared with standing workstations. The benefits associated with each type of active workstation (eg, standing, treadmill, cycling) may not be equivalent. Overall, cycling and treadmill workstations appear to provide greater short-term physiological changes than standing workstations that could potentially lead to better health. Cycling, treadmill and standing workstations appear to show short-term productivity benefits; however, treadmill workstations can reduce the performance of computer tasks.

Vmax estimate from three-parameter critical velocity models: validity and impact on 800 m running performance prediction.

The purpose of this study was to evaluate the validity of maximal velocity (Vmax) estimated from three-parameter systems models, and to compare the predictive value of two- and three-parameter models for the 800 m. Seventeen trained male subjects (VO2max=66.54+/-7.29 ml min(-1) kg(-1)) performed five randomly ordered constant velocity tests (CVT), a maximal velocity test (mean velocity over the last 10 m portion of a 40 m sprint) and a 800 m time trial (V 800 m). Five systems models (two three-parameter and three two-parameter) were used to compute V max (three-parameter models), critical velocity (CV), anaerobic running capacity (ARC) and V800m from times to exhaustion during CVT. Vmax estimates were significantly lower than (0.19