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Hongjun Yu, Xiaoping Chen, Weimo Zhu and Chunmei Cao

Purpose:

To examine the effectiveness of threshold and polarized models in the training organization of Chinese top-level sprint speed skaters using a 2-y quasi-experimental design.

Methods:

Two years (2004–05 and 2005–06 seasons) of the Chinese national speed-skating team’s daily training load (N = 9; 5 men, 23.6 ± 1.7 y, weight 76.6 ± 4.1 kg, competitive experience 5.0 ± 0.8 y, 500-m time 35.45 ± 0.72 s, 1000-m time 71.18 ± 2.28 s; 4 women, 25.3 ± 6.8 y, 73.0 ± 8.5 kg, 6.3 ± 3.5 y, 37.81 ± 0.46 s, 75.70 ± 0.81 s) were collected and analyzed. Each season’s training load included overall duration (calculated in min and km), frequency (calculated by overall sessions), and training intensity (measured by ear blood lactate or estimated by heart rate), Their performances at national, World Cup, and Olympic competitions during the 2 seasons (2004–06), as well as lactate data measured 15 and 30 min after these competitions, were also collected and analyzed. Based on the lactate data (<2, 2–4, >4 mmol/L), training zones were classified as low, moderate, and high intensity.

Results:

The total durations and frequencies of the training load were similar across the seasons, but a threshold-training model distribution was used in 2004–05, and a polarized-training-load organization in 2005–06. Under the polarized-training model, or load organization, all speed skaters’ performance improved and their lactate after competition decreased considerably.

Conclusion:

Training-intensity distribution based on a polarized-training model led to the success in top Chinese sprint speed skaters in the 2005–06 season.

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Chunmei Cao, Yu Liu, Weimo Zhu and Jiangjun Ma

Background:

Recently developed active workstation could become a potential means for worksite physical activity and wellness promotion. The aim of this review was to quantitatively examine the effectiveness of active workstation in energy expenditure and job performance.

Methods:

The literature search was conducted in 6 databases (PubMed, SPORTDiscuss, Web of Science, ProQuest, ScienceDirect, and Scopuse) for articles published up to February 2014, from which a systematic review and meta-analysis was conducted.

Results:

The cumulative analysis for EE showed there was significant increase in EE using active workstation [mean effect size (MES): 1.47; 95% confidence interval (CI): 1.22 to 1.72, P < .0001]. Results from job performance indicated 2 findings: (1) active workstation did not affect selective attention, processing speed, speech quality, reading comprehension, interpretation and accuracy of transcription; and (2) it could decrease the efficiency of typing speed (MES: –0.55; CI: –0.88 to –0.21, P < .001) and mouse clicking (MES: –1.10; CI: –1.29 to –0.92, P < .001).

Conclusion:

Active workstation could significantly increase daily PA and be potentially useful in reducing workplace sedentariness. Although some parts of job performance were significantly lower, others were not. As a result there was little effect on real-life work productivity if we made a good arrangement of job tasks.