Through a case study, this article explores a number of theoretical issues related to the often taken for granted relationship between simulator fidelity and the quality and transferability of training in complex, dynamic, safety-critical settings. A counterexample based on mid-fidelity simulation is presented and the assumed coincidence of fidelity and validity is tested, that is the study tests the equation of constructed photorealism (built to mimic reality) and effective development of the competence that operators require to manage situations that involve underspecified problems, time pressure constraints and complex group interaction. The article concludes that such competence development cannot rely only on highly context-specific (photorealistic) environments. Further, it will be argued that lower-fidelity simulation, when appropriately designed, can provide competence development with pedagogical and economic advantages.

Syndromic data sources have been sought to improve the timely detection of increased influenza transmission. This study set out to examine the prospective performance of telenursing chief complaints in predicting influenza activity. Data from two influenza seasons (2007/08 and 2008/09) were collected in a Swedish county (population 427,000) to retrospectively determine which grouping of telenursing chief complaints had the largest correlation with influenza case rates. This grouping was prospectively evaluated in the three subsequent seasons. The best performing telenursing complaint grouping in the retrospective algorithm calibration was fever (child, adult) and syncope (r=0.66; p<0.001). In the prospective evaluation, the performance of 14-day predictions was acceptable for the part of the evaluation period including the 2009 influenza pandemic (area under the curve (AUC)=0.84; positive predictive value (PPV)=0.58), while it was strong (AUC=0.89; PPV=0.93) for the remaining evaluation period including only influenza winter seasons. We recommend the use of telenursing complaints for predicting winter influenza seasons. The method requires adjustments when used during pandemics.

Engaging in competitive sports as a youth can have many health benefits, but recent studies also report a high risk for injury. The long-term purpose of this Swedish research program is to develop a framework for safe track and field training for young athletes (aged 12-15 years). The aim of this study was to establish what is perceived to contribute and cause injuries in youth track and field by compiling the best available experiential knowledge about the underlying factors and use this knowledge to identify appropriate areas to handle these in practical ways. Nine focus group interviews with in total 74 participants and confirming interviews with five individuals were performed in seven Swedish regions. Qualitative research methods were used for data analysis. Injuries in youth athletes were not considered to be strictly the result of individual factors but rather the result of the interactions between factors at different levels. Three major factors emerged as follows: Insufficient knowledge for athletic development in daily practice; shortsighted communities of practice and sports policies not adjusted to youth; and societal health behaviors. The experiential knowledge in the national sporting community suggests that if effective and sustainable injury prevention processes are to be implemented for youth track and field, an ecological (holistic-developmental) approach to injury prevention is needed. Such an approach allows a longitudinal development-focused strategy for prevention that spans an athlete's entire career.

No abstract

BackgroundThere is abundant global interest in using syndromic data from population-wide health information systems—referred to as eHealth resources—to improve infectious disease surveillance. Recently, the necessity for these systems to achieve two potentially conflicting requirements has been emphasized. First, they must be evidence-based; second, they must be adjusted for the diversity of populations, lifestyles, and environments.ObjectiveThe primary objective was to examine correlations between data from Google Flu Trends (GFT), computer-supported telenursing centers, health service websites, and influenza case rates during seasonal and pandemic influenza outbreaks. The secondary objective was to investigate associations between eHealth data, media coverage, and the interaction between circulating influenza strain(s) and the age-related population immunity.MethodsAn open cohort design was used for a five-year study in a Swedish county (population 427,000). Syndromic eHealth data were collected from GFT, telenursing call centers, and local health service website visits at page level. Data on mass media coverage of influenza was collected from the major regional newspaper. The performance of eHealth data in surveillance was measured by correlation effect size and time lag to clinically diagnosed influenza cases.ResultsLocal media coverage data and influenza case rates showed correlations with large effect sizes only for the influenza A (A) pH1N1 outbreak in 2009 (r=.74, 95% CI .42-.90; P<.001) and the severe seasonal A H3N2 outbreak in 2011-2012 (r=.79, 95% CI .42-.93; P=.001), with media coverage preceding case rates with one week. Correlations between GFT and influenza case data showed large effect sizes for all outbreaks, the largest being the seasonal A H3N2 outbreak in 2008-2009 (r=.96, 95% CI .88-.99; P<.001). The preceding time lag decreased from two weeks during the first outbreaks to one week from the 2009 A pH1N1 pandemic. Telenursing data and influenza case data showed correlations with large effect sizes for all outbreaks after the seasonal B and A H1 outbreak in 2007-2008, with a time lag decreasing from two weeks for the seasonal A H3N2 outbreak in 2008-2009 (r=.95, 95% CI .82-.98; P<.001) to none for the A p H1N1 outbreak in 2009 (r=.84, 95% CI .62-.94; P<.001). Large effect sizes were also observed between website visits and influenza case data.ConclusionsCorrelations between the eHealth data and influenza case rates in a Swedish county showed large effect sizes throughout a five-year period, while the time lag between signals in eHealth data and influenza rates changed. Further research is needed on analytic methods for adjusting eHealth surveillance systems to shifts in media coverage and to variations in age-group related immunity between virus strains. The results can be used to inform the development of alert-generating eHealth surveillance systems that can be subject for prospective evaluations in routine public health practice.