Effects of alien woody plant invasion on the birds of Mountain Fynbos in the Cape of Good Hope Nature Reserve

The density, biomass, species richness and composition of birds in plots in two Mountain Fynbos plant-species assemblages (Tall Mixed Fynbos and Restionaceous Tussock Marsh), infested with alien woody plants (mainly Australian Acacia spp.) at the Cape of Good Hope Nature Reserve, South Africa, were compared with those of uninfested plots. The relative density of frugivorous and granivorous birds tended to increase, but total bird density did not change significantly with increasing density of Acacia cyclops in Tall Mixed Fynbos. However, the density of nectarivorous birds decreased with increasing A. cyclops infestation as a result of the elimination of their food plants (proteaceous and ericaceous shrubs). Thus, alien woody plants have the capacity to disrupt the putative avian nectarivore – indigenous plant pollination relationship. Dense infestations of mixed alien species in Restionaceous Tussock Marsh supported fewer nectarivorous birds, but more granivores and insectivores than did uninfested vegetation. Moreover, bird species more typical of woodland and thicket (and absent from uninfested fynbos vegetation), notably large granivores, were found in dense mixed-alien infestations of this plant-species assemblage

A bayesian perspective on intervention research: Using prior information in the development of social and health programs

Objective: By presenting a simulation study that compares Bayesian and classical frequentist approaches to research design, this paper describes and demonstrates a Bayesian perspective on intervention research. Method: Using hypothetical pilot-study data where an effect size of 0.2 had been observed, we designed a 2-arm trial intended to compare an intervention with a control condition (e.g., usual services). We determined the trial sample size by a power analysis with a Type I error probability of 2.5% (1-sided) at 80% power. Following a Monte-Carlo computational algorithm, we simulated 1 million outcomes for this study and then compared the performance of the Bayesian perspective with the performance of the frequentist analytic perspective. Treatment effectiveness was assessed using a frequentist t-test and an empirical Bayesian t-test. Statistical power was calculated as the criterion for comparison of the 2 approaches to analysis. Results: In the simulations, the classical frequentist t-test yielded 80% power as designed. However, the Bayesian approach yielded 92% power. Conclusion: Holding sample size constant, a Bayesian analytic approach can improve power in intervention research. A Bayesian approach may also permit smaller samples holding power constant. Using a Bayesian analytic perspective could reduce design demands in the developmental experimentation that typifies intervention research

A bayesian approach to sample size estimation and the decision to continue program development in intervention research

Objective: In intervention research, the decision to continue developing a new program or treatment is dependent on both the change-inducing potential of a new strategy (i.e., its effect size) and the methods used to measure change, including the size of samples. This article describes a Bayesian approach to determining sample sizes in the sequential development of interventions. Description: Because sample sizes are related to the likelihood of detecting program effects, large samples are preferred. But in the design and development process that characterizes intervention research, smaller scale studies are usually required to justify more costly, larger scale studies. We present 4 scenarios designed to address common but complex questions regarding sample-size determination and the risk of observing misleading (e.g., false-positive) findings. From a Bayesian perspective, this article describes the use of decision rules composed of different target probabilities and prespecified effect sizes. Monte-Carlo simulations are used to demonstrate a Bayesian approach—which tends to require smaller samples than the classical frequentist approach—in the development of interventions from one study to the next

Assurance in intervention research: A bayesian perspective on statistical power

Objective: This article introduces Bayesian assurance as an alternative to traditional power analysis in intervention research. Bayesian assurance is defined as the unconditional probability of identifying an intervention effect. Method: Assurance can be calculated as the expected statistical power based on a prior distribution of the unknown parameters related to the effect size. Using Monte Carlo simulation methods, we demonstrate Bayesian assurance in 2 small-scale randomized trials: a trial of motivational interviewing for patients with behavioral health disorders and a trial of a specialty mental health probation. Results: The findings suggest that traditional statistical power is highly sensitive to misspecification. Because assurance can be calculated across all possible effect sizes, it controls the uncertainty associated with the selection of a point effect size in traditional power estimation. Assurance usually produces larger sample-size estimates, and thus cutoff values for assurance may be lower than those typically used in classical power estimation. Conclusions: Compared to traditional power estimation, assurance appears to be more robust against inaccurate prior information. Assurance may be a preferred method for estimating sample sizes when prior information is poor and the costs of underpowering a study are great

Suboptimal blood pressure control in chronic kidney disease stage 3: baseline data from a cohort study in primary care

Background: poorly controlled hypertension is independently associated with mortality, cardiovascular risk and disease progression in chronic kidney disease (CKD). In the UK, CKD stage 3 is principally managed in primary care, including blood pressure (BP) management. Controlling BP is key to improving outcomes in CKD. This study aimed to investigate associations of BP control in people with CKD stage 3.Methods: 1,741 patients with CKD 3 recruited from 32 general practices for the Renal Risk in Derby Study underwent medical history, clinical assessment and biochemistry testing. BP control was assessed by three standards: National Institute for Health and Clinical Excellence (NICE), National Kidney Foundation Kidney Disease Outcome Quality Initiative (KDOQI) and Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. Descriptive statistics were used to compare characteristics of people achieving and not achieving BP control. Univariate and multivariate logistic regression was used to identify factors associated with BP control.Results: the prevalence of hypertension was 88%. Among people with hypertension, 829/1426 (58.1%) achieved NICE BP targets, 512/1426 (35.9%) KDOQI targets and 859/1426 (60.2%) KDIGO targets. Smaller proportions of people with diabetes and/or albuminuria achieved hypertension targets. 615/1426 (43.1%) were only taking one antihypertensive agent. On multivariable analysis, BP control (NICE and KDIGO) was negatively associated with age (NICE odds ratio (OR) 0.27; 95% confidence interval (95% CI) 0.17-0.43) 70–79 compared to &lt;60), diabetes (OR 0.32; 95% CI 0.25-0.43)), and albuminuria (OR 0.56; 95% CI 0.42-0.74)). For the KDOQI target, there was also association with males (OR 0.76; 95% CI 0.60-0.96)) but not diabetes (target not diabetes specific). Older people were less likely to achieve systolic targets (NICE target OR 0.17 (95% CI 0.09,0.32) p?&lt;?0.001) and more likely to achieve diastolic targets (OR 2.35 (95% CI 1.11,4.96) p?&lt;?0.001) for people &gt;80 compared to?&lt;?60).Conclusions: suboptimal BP control was common in CKD patients with hypertension in this study, particularly those at highest risk of adverse outcomes due to diabetes and or albuminuria. This study suggests there is scope for improving BP control in people with CKD by using more antihypertensive agents in combination while considering issues of adherence and potential side effects.<br/

What lies beneath: predicting seagrass below-ground biomass from above-ground biomass, environmental conditions and seagrass community composition

Seagrass condition, resilience and ecosystem services are affected by the below-ground tissues (BGr) but these are rarely monitored. In this study we compiled historical data across northern Australia to investigate biomass allocation strategies in 13 tropical seagrass species. There was sufficient data to undertake statistical analysis for five species: Cymodocea serrulata, Halophila mutts, Halodule uninervis, Thalassia hemprichii, and Zostera muelleri. The response of below-ground biomass (BGr) to above-ground biomass (AGr) and other environmental and seagrass community composition predictor variables were assessed using Generalized Linear Models. Environmental data included: region, season, sediment type, water depth, proximity to land-based sources of pollution, and a light stress index. Seagrass community data included: species diversity and dominant species class (colonising, opportunistic or persistant) based on biomass. The predictor variables explained 84-97% of variance in BGr on the log-scale depending on the species. Multi-species meadows showed a greater investment into BGr than mono-specific meadows and when dominated by opportunistic or persistent seagrass species. This greater investment into BGr is likely to enhance their resistance to disturbances if carbohydrate storage reserves also increase with biomass. Region was very important for the estimation of BGr from AGr in four species (not in C. serrulata). No temporally changing environmental features were included in the models, therefore, they cannot be used to predict local-scale responses of BGr to environmental change. We used a case study for Cairns Harbour to predict BGr by applying the models to AGr measured at 362 sites in 2017. This case study demonstrates how the model can be used to estimate BGr when only AGr is measured. However, the general approach can be applied broadly with suitable calibration data for model development providing a more complete assessment of seagrass resources and their potential to provide ecosystem services

Welfare Participation and Depression Symptoms Among Youth in China

Background: Although welfare programs in China provide a safety net for low-income people by directly lifting their incomes, receiving benefits has the potential to affect recipients’ mental health because of the demanding and demeaning means-testing application process required by Chinese policymakers. However, little research has examined the relationship between welfare participation and mental health symptoms—particularly those of depression—among Chinese youth. This study aims to examine the relationship between family participation in the Dibao income-assistance program in China and symptoms of depression among youth. Methods: This study used a youth sample (n = 4192) of nationally representative data from the China Family Panel Studies (CFPS) survey. Multiple imputation was used to deal with missing data. The imputed data were analyzed using aggregated robust multiple regression. The Center for Epidemiological Studies Depression (CES-D-20) scale was used to measure depression symptoms. In addition, a variety of subgroup analyses were conducted to explore whether the relationship between Dibao participation and symptoms of depression differs significantly by the sociodemographic characteristics. Results: Youth whose families received Dibao assistance had significantly greater risk for symptoms of depression when compared with peers who did not receive assistance. Results also showed that young women—and especially young mothers—whose families participated in the Dibao program in rural areas were at significantly higher risk compared with others. Conclusion and Discussion: The relationship between welfare participation and symptoms of depression varies significantly by the characteristics of youths and their families. As a marker for collective disadvantage and adversity, welfare participation warrants research to study program processes and to distinguish pathways—possibly differentiated by gender—that may elevate risk for depression among Dibao program recipients

Welfare participation and depression among youth in the United States: A systematic review

Welfare programs play important roles in the lives of vulnerable populations. However, since their inception, welfare programs have been accompanied by contentious debate about their impact on the wellbeing of participants and, hence, about their collective value as a strategy for alleviating poverty. This study uses welfare participation as a marker of lower socioeconomic status to identify and synthesize the relationship between welfare participation and depression among youth. A systematic review was undertaken based on literature published between 1997 and 2017 through a search of 9 electronic databases, 15 reports met criteria for study inclusion. Four descriptive studies reported mixed findings. Of the 11 comparison studies, 10 studies showed consistent findings that participation in welfare programs was associated with a higher vulnerability for depression. Discussion includes the effects of stigma related to welfare and mental health treatment, and the implications for policy makers, social workers, and future research

Integrated primary care and social work: A systematic review

Objective: Behavioral and physical health services are increasingly being integrated, with care provided by interprofessional teams of physicians, nurses, social workers, and other professionals. The objective of this study was to describe the functions of social workers on interprofessional teams in primary care and to assess the impact of interprofessional teams that include social workers in integrated care settings. Method: We undertook a systematic review of randomized controlled trials (RCTs) of routine vs. integrated primary care where social workers served on interprofessional teams. A 5-phase search process to identify RCTs from 9 electronic databases and the gray literature published between 2000 and 2016 was used. We calculated effect sizes across identified studies and conducted 2 subsample meta-analyses for behavioral health outcomes. Results: The searches recovered 502 citations. After screening, 107 reports were retained for a full-text review, and 32 of those (from 26 RCTs) met study criteria. In the 26 RCTs, social workers engaged in 3 patient-centered activities: behavioral health treatment, care management, and referral for social services. Conclusion: Although mixed, the findings suggest that, compared to routine services, integrated primary care provided by interprofessional teams that include social workers significantly improves the behavioral health and care of patients

Mutual Events in the Cold Classical Transneptunian Binary System Sila and Nunam

Hubble Space Telescope observations between 2001 and 2010 resolved the binary components of the Cold Classical transneptunian object (79360) Sila-Nunam (provisionally designated 1997 CS29). From these observations we have determined the circular, retrograde mutual orbit of Nunam relative to Sila with a period of 12.50995 \pm 0.00036 days and a semimajor axis of 2777 \pm 19 km. A multi-year season of mutual events, in which the two near-equal brightness bodies alternate in passing in front of one another as seen from Earth, is in progress right now, and on 2011 Feb. 1 UT, one such event was observed from two different telescopes. The mutual event season offers a rich opportunity to learn much more about this barely-resolvable binary system, potentially including component sizes, colors, shapes, and albedo patterns. The low eccentricity of the orbit and a photometric lightcurve that appears to coincide with the orbital period are consistent with a system that is tidally locked and synchronized, like the Pluto-Charon system. The orbital period and semimajor axis imply a system mass of (10.84 \pm 0.22) \times 10^18 kg, which can be combined with a size estimate based on Spitzer and Herschel thermal infrared observations to infer an average bulk density of 0.72 +0.37 -0.23 g cm^-3, comparable to the very low bulk densities estimated for small transneptunian binaries of other dynamical classes.Comment: In press in Icaru