Physical activity barriers in the workplace : an exploration of factors contributing to non-participation in a UK workplace physical activity intervention

Purpose– The purpose of this paper is to explore factors contributing to non-participation in a workplace physical activity (PA) intervention in a large UK call centre. Design/methodology/approach – In total, 16 inactive individuals (nine male/seven female), aged 27±9 years, who had not taken part in the intervention were interviewed to explore their perceptions of PA, the intervention and factors which contributed to their non-participation. Transcripts were analysed using thematic analysis. Findings – Six superordinate themes were identified: self-efficacy for exercise; attitudes towards PA; lack of time and energy; facilities and the physical environment; response to the PA programme and PA culture. Barriers occurred at multiple levels of influence, and support the use of ecological or multilevel models to help guide future programme design/delivery. Research limitations/implications – The 16 participants were not selected to be representative of the workplace gender or structure. Future intentions relating to PA participation were not considered and participants may have withheld negative opinions about the workplace or intervention despite use of an external researcher. Practical implications – In this group of employees education about the importance of PA for young adults and providing opportunities to gain social benefits from PA would increase perceived benefits and reduce perceived costs of PA. Workplace cultural norms with respect to PA must also be addressed to create a shift in PA participation. Originality/value – Employees’ reasons for non-participation in workplace interventions remain poorly understood and infrequently studied. The study considers a relatively under-studied population of employed young adults, providing practical recommendations for future interventions

Maximum Likelihood and Bayesian Estimation of Skeletal Age-at-Death from the Human Pubic Symphysis

A number of methodological problems have recently plagued studies of adult skeletal age-at-death estimation. Over the last two decades, researchers have extended considerable effort to place age estimation studies on a firmer statistical ground. However, many of the current methods can still be criticized because they make unjustifiable assumptions or use inappropriate statistical models. Much of the controversy surrounding age-at-death estimation has focused specifically on the question of applying age standards from a reference collection of known-age individuals to a target group of unknown age. The current study, involving a large sample (n=739) of adult male pubic symphysis data, demonstrates a probability-based method in order to obtain the full posterior distribution for age-at-death conditional on observed symphyseal phases using both a maximum likelihood and Bayesian estimator. With the application of the maximum likelihood or Bayesian estimator (where the prior distribution for age is external to the reference sample) it is possible to produce age estimates that are independent of the reference sample age-at-death distribution

Validation of chronic obstructive pulmonary disease recording in the Clinical Practice Research Datalink (CPRD-GOLD)

Objectives: The optimal method of identifying people with chronic obstructive pulmonary disease (COPD) from electronic primary care records is not known. We assessed the accuracy of different approaches using the Clinical Practice Research Datalink, a UK electronic health record database. Setting: 951 participants registered with a CPRD practice in the UK between 1 January 2004 and 31 December 2012. Individuals were selected for ≥1 of 8 algorithms to identify people with COPD. General practitioners were sent a brief questionnaire and additional evidence to support a COPD diagnosis was requested. All information received was reviewed independently by two respiratory physicians whose opinion was taken as the gold standard. Primary outcome measure: The primary measure of accuracy was the positive predictive value (PPV), the proportion of people identified by each algorithm for whom COPD was confirmed. Results: 951 questionnaires were sent and 738 (78%) returned. After quality control, 696 (73.2%) patients were included in the final analysis. All four algorithms including a specific COPD diagnostic code performed well. Using a diagnostic code alone, the PPV was 86.5% (77.5-92.3%) while requiring a diagnosis plus spirometry plus specific medication; the PPV was slightly higher at 89.4% (80.7-94.5%) but reduced case numbers by 10%. Algorithms without specific diagnostic codes had low PPVs (range 12.2-44.4%). Conclusions: Patients with COPD can be accurately identified from UK primary care records using specific diagnostic codes. Requiring spirometry or COPD medications only marginally improved accuracy. The high accuracy applies since the introduction of an incentivised disease register for COPD as part of Quality and Outcomes Framework in 2004

A University and Community Partnership for Enhancing Rural Business Performance and Sustainability: The Iowa Retail Initiative

Rural communities and businesses are in need of fresh approaches aimed at enhancing business and community growth, entrepreneurship, resilient response to change, and sustainability. To address the need for a more coordinated approach to rural retail business assistance, we proposed and received significant funding for a university-community partnership model called the Iowa Retail Initiative (IRI). The IRI unites university researchers, faculty, Extension professionals, students, and community partners to fulfill the university’s land grant vision of combining science, technology, and creativity to improve the quality of life in Iowa by creating thriving rural communities

International Human Rights: Problems of Law, Policy, and Practice

The introductory chapter of this book discusses how a unifying concern for human dignity led to the establishment of human rights as part of the body of international law. Next, the chapter includes excerpts from multiple writers’ works to employ slavery as a case study to demonstrate how the international community has used the notion of human rights to create binding law. Third, this chapter discusses the philosophical drivers of human rights by including writings from other scholars and the history of the presence of human rights in international law. The chapter concludes that increasing concern for human rights may indicate that protection of human rights is presently in danger rather than improving

Quantifying signals with power-law correlations: A comparative study of detrended fluctuation analysis and detrended moving average techniques

Detrended fluctuation analysis (DFA) and detrended moving average (DMA) are two scaling analysis methods designed to quantify correlations in noisy non-stationary signals. We systematically study the performance of different variants of the DMA method when applied to artificially generated long-range power-law correlated signals with an {\it a-priori} known scaling exponent $\alpha_{0}$ and compare them with the DFA method. We find that the scaling results obtained from different variants of the DMA method strongly depend on the type of the moving average filter. Further, we investigate the optimal scaling regime where the DFA and DMA methods accurately quantify the scaling exponent $\alpha_{0}$, and how this regime depends on the correlations in the signal. Finally, we develop a three-dimensional representation to determine how the stability of the scaling curves obtained from the DFA and DMA methods depends on the scale of analysis, the order of detrending, and the order of the moving average we use, as well as on the type of correlations in the signal.Comment: 15 pages, 16 figure

Effect of significant data loss on identifying electric signals that precede rupture by detrended fluctuation analysis in natural time

Electric field variations that appear before rupture have been recently studied by employing the detrended fluctuation analysis (DFA) as a scaling method to quantify long-range temporal correlations. These studies revealed that seismic electric signals (SES) activities exhibit a scale invariant feature with an exponent $\alpha_{DFA} \approx 1$ over all scales investigated (around five orders of magnitude). Here, we study what happens upon significant data loss, which is a question of primary practical importance, and show that the DFA applied to the natural time representation of the remaining data still reveals for SES activities an exponent close to 1.0, which markedly exceeds the exponent found in artificial (man-made) noises. This, in combination with natural time analysis, enables the identification of a SES activity with probability 75% even after a significant (70%) data loss. The probability increases to 90% or larger for 50% data loss.Comment: 12 Pages, 11 Figure

Low-cost directionally-solidified turbine blades, volume 2

An endothermically heated technology was used to manufacture low cost, directionally solidified, uncooled nickel-alloy blades for the TFE731-3 turbofan engine. The MAR-M 247 and MER-M 100+Hf blades were finish processed through heat treatment, machining, and coating operations prior to 150 hour engine tests consisting of the following sequences: (1) 50 hours of simulated cruise cycling (high fatigue evaluation); (2) 50 hours at the maximum continuous power rating (stress rupture endurance (low cycle fatigue). None of the blades visually showed any detrimental effects from the test. This was verified by post test metallurgical evaluation. The specific fuel consumption was reduced by 2.4% with the uncooled blades

Extreme value statistics and return intervals in long-range correlated uniform deviates

We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to minimum are such that the reference point from which the maximum is measured is itself a random quantity. We analytically calculate the limiting distributions for independent and identically distributed random variables, and use these as a reference point for correlated cases. The distributions are different from that of the maximum itself i.e., a Weibull distribution, reflecting the fact that the distribution of the reference point either dominates over or convolves with the distribution of the maximum. The functional form of the limiting distributions is unaffected by correlations, although the convergence is slower. We show that our findings can be directly generalized to a wide class of stochastic processes. We also analyze return interval distributions, and compare them to recent conjectures of their functional form

Improving measurements of SF6 for the study of atmospheric transport and emissions

Sulfur hexafluoride (SF6) is a potent greenhouse gas and useful atmospheric tracer. Measurements of SF6 on global and regional scales are necessary to estimate emissions and to verify or examine the performance of atmospheric transport models. Typical precision for common gas chromatographic methods with electron capture detection (GC-ECD) is 1–2%. We have modified a common GC-ECD method to achieve measurement precision of 0.5% or better. Global mean SF6 measurements were used to examine changes in the growth rate of SF6 and corresponding SF6 emissions. Global emissions and mixing ratios from 2000–2008 are consistent with recently published work. More recent observations show a 10% decline in SF6 emissions in 2008–2009, which seems to coincide with a decrease in world economic output. This decline was short-lived, as the global SF6 growth rate has recently increased to near its 2007–2008 maximum value of 0.30±0.03 pmol mol−1 (ppt) yr−1 (95% C.L.)