eHealth and eWelfare of Finland - Checkpoint 2011

This eHealth and eWelfare report was produced by the National Institute for Health and Welfare (THL), Finland, and FinnTelemedicum, the Centre of Excellence for Telehealth at the University of Oulu, from the results of the national eHealth implementation survey commissioned by the Finnish Ministry of Social Affairs and Health and the eWelfare survey that was conducted as part of the SADe programme funded by the Ministry of Finance. The eHealth survey describes the status and trends in health care information and communication technology (ICT) and eHealth usage in Finland in 2011, comparing the results with earlier surveys carried out in 2003, 2005 and 2007. The eWelfare survey was a national review of the electronic social services and social welfare client information systems currently available in Finland and of how they function in the social services context. This report also includes current information on Finnish eHealth and eWelfare policies and other e activities such as reviews on the main results of two other surveys performed in Finland during the same time period. This report is produced for international readers and gives a comprehensive picture of the current eHealth and eWelfare situation in Finland

Physical training for loaded marching performance among British Army recruits

Study 1 quantified the validity and repeatability of an automated on-line (ON) gas analysis system during sub-maximal loaded marching (LM) against that of the Douglas Bag (DB) approach. The 95% ratio Limits of Agreement (LoA) revealed the ON system systematically overestimated V02 by -16% (1.16 (x/-i-1.19). The Bland and Altman plots revealed DB repeatability was almost two-fold better than ON (-9% vs. -15%), thus the DB approach should be used subsequently to measure human expired gases. Study 2 investigated the difference between an LM maximal oxygen uptake protocol (LMp) versus a standard running protocol (Rp). The LMp V02max was lower than Rp (48.6 ± 4.3 ml·kg-I·min-I vs. 51.3 ± 4.0 ml·kg-I·min-I, P=0.001). Thus, the quantification of sub-maximal LM exercise intensity will be underestimated by -5% if derived from a running tiOzmax protocol. Study 3 investigated the repeatability of accepted and potential determinants of Loaded Marching Performance (LMP). The LoA revealed the repeatability of Loaded Marching Economy (LME) (0.98 (x/-i-1.09», V02max (1.01 (xl-i-1.07», upper body dynamic strength (1.01 (x/-i- 1.11», and anthropometric measures (1.00 (x/-i- 1.02» to (1.00 (x/-i- 1.07» was reasonable, but dynamic leg strength (1.06 (x/-i-1.14» and isometric strength (1.00 (x/-i-1.12» to (0.99 (x/-i-1.l6» were large. Study 4 established the determinants of 2.4 km LMP from a test battery performed at the beginning of British Army infantry training. The best mathematical model of LMP included the independent variables of LME (r=0.65), 2.4 km run time (r=0.42), and peak static lift strength (r=0.48). This explained 65% of the variation in LMP, and had a prediction error of ± 51 s. Mathematically, LME and 2.4 km run time exerted the greatest influence on LMP, whereas the influence of static lift strength on LMP was small. Study 5 investigated the physical and physiological responses of the established determinants of LMP during 24 weeks of British Army infantry training. Loaded marching performance improved 7.0% (900 s to 837 s, P=0.001), LME 9.6% (2.28 I·min- I to 2.06 I·min- I , P ...EThOS - Electronic Theses Online ServiceGBUnited Kingdo