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Paul B. Gastin, Denny Meyer, Emy Huntsman and Jill Cook

Purpose:

To assess the relationships between player characteristics (including age, playing experience, ethnicity, and physical fitness) and in-season injury in elite Australian football.

Design:

Single-cohort, prospective, longitudinal study.

Methods:

Player characteristics (height, body mass, age, experience, ethnicity, playing position), preseason fitness (6-min run, 40-m sprint, 6 × 40-m sprint, vertical jump), and in-season injury data were collected over 4 seasons from 1 professional Australian football club. Data were analyzed for 69 players, for a total of 3879 player rounds and 174 seasons. Injury risk (odds ratio [OR]) and injury severity (matches missed; rate ratio [RR]) were assessed using a series of multilevel univariate and multivariate hierarchical linear models.

Results:

A total of 177 injuries were recorded with 494 matches missed (2.8 ± 3.3 matches/injury). The majority (87%) of injuries affected the lower body, with hamstring (20%) and groin/hip (14%) most prevalent. Nineteen players (28%) suffered recurrent injuries. Injury incidence was increased in players with low body mass (OR = 0.887, P = .005), with poor 6-min-run performance (OR = 0.994, P = .051), and playing as forwards (OR = 2.216, P = .036). Injury severity was increased in players with low body mass (RR = 0.892, P = .008), tall stature (RR = 1.131, P = .002), poor 6-min-run (RR = 0.990, P = .006), and slow 40-m-sprint (RR = 3.963, P = .082) performance.

Conclusions:

The potential to modify intrinsic risk factors is greatest in the preseason period, and improvements in aerobic-running fitness and increased body mass may protect against in-season injury in elite Australian football.

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Denny Meyer, Madawa W. Jayawar, Samuel Muir, David Ho and Olivia Sackett

Background: To evaluate the impact of an online workplace program that promotes physical activity and health, while focusing on performance measures relating to physical activity, nutrition, and overall health. Methods: The large sample size (more than 18,000 participants) allowed the use of text mining and machine-learning methods to determine what descriptions of the program identify successful outcomes, and hierarchical linear models to determine the most beneficial program modules and features. Results: The program increased overall health and awareness of levels of physical activity and nutrition, especially for people who scored low on these measures initially. Interestingly, although physical activity is the most popular program module, the daily step–tracking process was associated with smaller improvements in overall health. Conclusions: This study finds that the Virgin Pulse Global Challenge is an effective workplace intervention for improving overall health and awareness of physical activity and nutrition. Effectiveness relates to the holistic approach adopted rather than to individual modules in isolation. Future evaluations of workplace health and exercise programs should explore a variety of outcome measures within the rich context provided by open-ended participant experience feedback. In addition, a control group and a follow-up study are required.

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Samuel D. Muir, Sandun S.M. Silva, Mulu A. Woldegiorgis, Hayley Rider, Denny Meyer and Madawa W. Jayawardana

Background: Despite holding great potential for addressing concerns regarding public health, recent systematic reviews have found effect sizes for interventions targeting physical activity to be small. Before interventions can be improved, the factors influencing outcomes must be identified. This systematic review aimed to identify predictors of success, measured in terms of engagement (eg, involvement duration) and health behavior change (eg, increased step counts), of workplace interventions targeting physical activity. Methods: A structured search of 3 databases (PubMed, PsycINFO, and Web of Science) was conducted to identify articles published between January 2000 and April 2017. For inclusion, articles needed to test a workplace intervention targeting physical activity and perform a quantitative analysis, identifying predictors of engagement or health behavior change. Results: Twenty-two studies were identified for review (median quality score = 70%). Demographic variables (eg, gender, age) were inconsistent predictors of success. However, employees in better health and physically active at baseline were found to have a greater likelihood of success. Conclusions: It appears that achieving successful results among employees at high risk of poor health outcomes remains a significant challenge for interventions. It is hoped that program developers can use this information to create effective interventions particularly for more sedentary employees.