Assessment of the response of pollinator abundance to environmental pressures using structured expert elicitation

Policy-makers often need to rely on experts with disparate fields of expertise when making policy choices in complex, multi-faceted, dynamic environments such as those dealing with ecosystem services. For policy-makers wishing to make evidence-based decisions which will best support pollinator abundance and pollination services, one of the problems faced is how to access the information and evidence they need, and how to combine it to formulate and evaluate candidate policies. This is even more complex when multiple factors provide influence in combination. The pressures affecting the survival and pollination capabilities of honey bees (Apis mellifera), wild bees, and other pollinators are well documented, but incomplete. In order to estimate the potential effectiveness of various candidate policy choices, there is an urgent need to quantify the effect of various combinations of factors on the pollination ecosystem service. Using high-quality experimental evidence is the most robust approach, but key aspects of the system may not be amenable to experimentation or may be prohibitive based on cost, time and effort. In such cases, it is possible to obtain the required evidence by using structured expert elicitation, a method for quantitatively characterizing the state of knowledge about an uncertain quantity. Here we report and discuss the outputs of the novel use of a structured expert elicitation, designed to quantify the probability of good pollinator abundance given a variety of weather, disease, and habitat scenarios

Effects of exercise-based cardiac rehabilitation on cardiorespiratory fitness: A meta-analysis of UK studies

Background Exercise-based cardiac rehabilitation can promote meaningful improvements in cardiorespiratory fitness (fitness) but the magnitude of such improvements varies according to local characteristics of exercise programmes. We aimed to determine if cardiac rehabilitation (CR), as practised in the United Kingdom (UK), could promote meaningful changes in fitness and to identify programme characteristics which may moderate these changes. Methods Electronic and manual searches to identify UK CR studies reporting fitness at baseline and follow up. Change in fitness (Δfitness) was expressed as mean difference (95% CI) and effect size (ES). A random effects model was used to calculate the mean estimate for change in Δfitness. Between-group heterogeneity was quantified (Q) and investigated using planned sub-group analyses. Results We identified n = 11 studies containing 16 patient groups (n = 1 578) which used the incremental shuttle walking test (ISWT) (distance walked) to assess fitness. The overall mean estimate for Δfitness showed a significant increase in distance walked (ES = 0.48, P  12 exercise sessions compared with those receiving n ≤ 12 sessions. Conclusion We found significant increases in fitness (based on ISWT) in patients attending exercise-based CR in the UK. However, UK studies provide approximately one-third of the exercise “dose”, and produce gains in fitness less than half the magnitude reported in international studies

教養部改善問題資料集 まえがき

古代ロシア研究特別

Matching patients to an intervention for back pain : classifying patients using a latent class approach

Rationale, aims and objectives Classification of patients with back pain in order to inform treatments is a long-standing aim in medicine. We used latent class analysis (LCA) to classify patients with low back pain and investigate whether different classes responded differently to a cognitive behavioural intervention. The objective was to provide additional guidance on the use of cognitive behavioural therapy to both patients and clinicians. Method We used data from 407 participants from the full study population of 701 with complete data at baseline for the variables the intervention was designed to affect and complete data at 12 months for important outcomes. Patients were classified using LCA, and a link between class membership and outcome was investigated. For comparison, the latent class partition was compared with a commonly used classification system called Subgroups for Targeted Treatment (STarT). Results Of the relatively parsimonious models tested for association between class membership and outcome, an association was only found with one model which had three classes. For the trial participants who received the intervention, there was an association between class membership and outcome, but not for those who did not receive the intervention. However, we were unable to detect an effect on outcome from interaction between class membership and the intervention. The results from the comparative classification system were similar. Conclusion We were able to classify the trial participants based on psychosocial baseline scores relevant to the intervention. An association between class membership and outcome was identified for those people receiving the intervention, but not those in the control group. However, we were not able to identify outcome associations for individual classes and so predict outcome in order to aid clinical decision making. For this cohort of patients, the STarT system was as successful, but not superior