Randomised controlled trial of primary school based intervention to reduce risk factors for obesity

OBJECTIVE: To assess if a school based intervention was effective in reducing risk factors for obesity. DESIGN: Group randomised controlled trial. SETTING: 10 primary schools in Leeds. PARTICIPANTS: 634 children aged 7­-11 years. INTERVENTION: Teacher training, modification of school meals, and the development of school action plans targeting the curriculum, physical education, tuck shops, and playground activities. MAIN OUTCOME MEASURES: Body mass index, diet, physical activity, and psychological state. RESULTS: Vegetable consumption by 24 hour recall was higher in children in the intervention group than the control group (weighted mean difference 0.3 portions/day, 95% confidence interval 0.2 to 0.4), representing a difference equivalent to 50% of baseline consumption. Fruit consumption was lower in obese children in the intervention group ( - 1.0, - 1.8 to - 0.2) than those in the control group. The three day diary showed higher consumption of high sugar foods (0.8, 0.1 to 1.6)) among overweight children in the intervention group than the control group. Sedentary behaviour was higher in overweight children in the intervention group (0.3, 0.0 to 0.7). Global self worth was higher in obese children in the intervention group (0.3, 0.3 to 0.6). There was no difference in body mass index, other psychological measures, or dieting behaviour between the groups. Focus groups indicated higher levels of self reported behaviour change, understanding, and knowledge among children who had received the intervention. CONCLUSION: Although it was successful in producing changes at school level, the programme had little effect on children's behaviour other than a modest increase in consumption of vegetables

Evaluation of implementation and effect of primary school based intervention to reduce risk factors for obesity

OBJECTIVES: To implement a school based health promotion programme aimed at reducing risk factors for obesity and to evaluate the implementation process and its effect on the school. DESIGN: Data from 10 schools participating in a group randomised controlled crossover trial were pooled and analysed. SETTING: 10 primary schools in Leeds. Participants 634 children (350 boys and 284 girls) aged 7­11 years. MAIN OUTCOME MEASURES: Response rates to questionnaires, teachers' evaluation of training and input, success of school action plans, content of school meals, and children's knowledge of healthy living and self reported behaviour. RESULTS: All 10 schools participated throughout the study. 76 (89%) of the action points determined by schools in their school action plans were achieved, along with positive changes in school meals. A high level of support for nutrition education and promotion of physical activity was expressed by both teachers and parents. 410 (64%) parents responded to the questionnaire concerning changes they would like to see implemented in school. 19 out of 20 teachers attended the training, and all reported satisfaction with the training, resources, and support. Intervention children showed a higher score for knowledge, attitudes, and self reported behaviour for healthy eating and physical activity. CONCLUSION: This programme was successfully implemented and produced changes at school level that tackled risk factors for obesity

Hairy Leukoplakia

Oral hairy leukoplakia (OHL) is a disease of the mucosa first described in 1984. This pathology is associated with Epstein-Barr virus (EBV) and occurs mostly in people with HIV infection, both immunocompromised and immunocompetent, and can affect patients who are HIV negative. [1, 2] The first case in an HIV-negative patient was reported in 1999 in a 56-year-old patient with acute lymphocytic leukemia. Later, many cases were reported in heart, kidney, and bone marrow transplant recipients and patients with hematological malignancies. [3, 4

Overcoming Algorithm Aversion: People will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them

Although evidence-based algorithms consistently outperform human forecasters, people often fail to use them after learning that they are imperfect, a phenomenon known as algorithm aversion. In this paper, we present three studies investigating how to reduce algorithm aversion. In incentivized forecasting tasks, participants chose between using their own forecasts or those of an algorithm that was built by experts. Participants were considerably more likely to choose to use an imperfect algorithm when they could modify its forecasts, and they performed better as a result. Notably, the preference for modifiable algorithms held even when participants were severely restricted in the modifications they could make (Stuides 1-3). In fact, our results suggest that participants\u27 preference for modifiable algorithms was indicative of a desire for some control over the forecasting outcome, and not for a desire for greater control over the forecasting outcome, as participants\u27 preference for modifiable was relatively insensitive to the magnitude of the modifications they were able to make (Study 2). Additionally, we found that giving participants the freedom to modify an imperfect algorithm made them feel more satisfied with the forecasting process, more likely to believe that the algorithm was superior, and more likely to choose to use an algorithm to make subsequent forecasts (Study 3). This research suggests that one can reduce algorithm aversion by giving people some control—even a slight amount—over an imperfect algorithm\u27s forecast

Hope Over Experience Desirability and the Persistence of Optimism

Many important decisions hinge on expectations of future outcomes. Decisions about health, investments, and relationships all depend on predictions of the future. These expectations are often optimistic: People frequently believe that their preferred outcomes are more likely than is merited. Yet it is unclear whether optimism persists with experience and, surprisingly, whether optimism is truly caused by desire. These are important questions because life’s most consequential decisions often feature both strong preferences and the opportunity to learn. We investigated these questions by collecting football predictions from National Football League fans during each week of the 2008 season. Despite accuracy incentives and extensive feedback, predictions about preferred teams remained optimistically biased through the entire season. Optimism was as strong after 4 months as it was after 4 weeks. We exploited variation in preferences and matchups to show that desirability fueled this optimistic bias

Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err

Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human

The Effect of Storm Events on Diet of Adult Mummichogs (Fundulus heteroclitus)

More frequent storms due to climate change may impact estuarine species such as the mummichog (Fundulus hetereoclitus), an ecologically important salt marsh fish. This study investigated the effect of storm events and month on consumption of terrestrial insects by mummichogs in Hoffler Creek, Portsmouth, VA, as well as the effect of storms on consumption of major categories of benthic prey. Samples were taken monthly in the summers of 2017 and 2019. Additional paired samples were taken in June and July 2019, with the first collection during dry weather and the second during a subsequent storm. Month had a significant effect on the proportion of terrestrial insect prey in the diet in both years; consumption was highest in August, particularly in 2017 when the sample coincided with a storm event. However, storms increased consumption of terrestrial insects in only one of four paired dry weather-storm samples in 2019, indicating that temporal variation in insect abundance has a larger effect than increased availability that might occur when storms knock insects into the water. Storms had a significant effect on the proportion of different benthic prey in the diet in paired samples from 2019, but these effects were not consistent across months, sites, or in whether storms increased or decreased consumption. These patterns may be driven by mummichogs taking advantage of small-scale temporal or spatial variation in benthic prey. The ability to utilize locally abundant resources, including terrestrial insects, may help minimize the negative impacts of climate change on mummichogs

Positron and positronium affinities in the work-formalism Hartree-Fock approximation

Positron binding to anions is investigated within the work formalism proposed by Harbola and Sahni for the halide anions and the systems Li^- through O^- excluding Be^- and N^-. The toal ground-state energies of the anion-positron bound systems are empirically found to be an upper bound to the Hartree-Fock energies. The computed expectation values as well as positron and positronium affinities are in good agreement with their restricted Hartree-Fock counterparts. Binding of a positron to neutral species is also investigated using an iterative method.Comment: 12 pages, to appear in Physical Review