To what extent is the association between disability and mental health in adolescents mediated by bullying?:A causal mediation analysis

Background: Disability among adolescents is associated with both poorer mental health (MH) and higher levels of bullying-victimization. Bullying, therefore, conceivably mediates the association between disability and MH. Quantifying this pathway is challenging as the exposure (disability), mediator (bullying) and outcome (MH) are subjective, and subject to dependent measurement error if the same respondent reports on two or more variables. Methods: Utilizing the counterfactual and potential outcomes approaches to causal mediation, we decomposed the total effect of disability on MH into natural indirect effects (through bullying) and natural direct effects (not through bullying) using a sample of 3409 adolescents. As the study included data from multiple informants (teacher, parent, adolescent) on the outcome (MH, as measured on the Strengths and Difficulties Questionnaire) and two informants (adolescent, parent) on the mediator (bullying), we assessed the influence of dependent measurement error. Results: For preferred analysis (using parent-reported bullying and adolescent-reported MH), the total effect was a 2.18 [95% confidence interval (CI): 0.66-3.40] lower MH score for adolescents with a disability, compared with those with no disability (strength of association equivalent to 37% of the standard deviation for MH). Bullying explained 46% of the total effect. Use of adolescent-reported bullying with adolescent-reported MH produced similar results (37% mediation, 95% CI: 12-74%). Conclusions: Disability exerts a detrimental effect on adolescent MH, and a large proportion of this appears to operate through bullying. This finding does not appear to be spurious due to dependent measurement error

Response to physical rehabilitation and recovery trajectories following critical illness: individual participant data meta-analysis protocol.

INTRODUCTION: The number of inconclusive physical rehabilitation randomised controlled trials for patients with critical illness is increasing. Evidence suggests critical illness patient subgroups may exist that benefit from targeted physical rehabilitation interventions that could improve their recovery trajectory. We aim to identify critical illness patient subgroups that respond to physical rehabilitation and map recovery trajectories according to physical function and quality of life outcomes. Additionally, the utilisation of healthcare resources will be examined for subgroups identified. METHODS AND ANALYSIS: This is an individual participant data meta-analysis protocol. A systematic literature review was conducted for randomised controlled trials that delivered additional physical rehabilitation for patients with critical illness during their acute hospital stay, assessed chronic disease burden, with a minimum follow-up period of 3 months measuring performance-based physical function and health-related quality of life outcomes. From 2178 records retrieved in the systematic literature review, four eligible trials were identified by two independent reviewers. Principal investigators of eligible trials were invited to contribute their data to this individual participant data meta-analysis. Risk of bias will be assessed (Cochrane risk of bias tool for randomised trials). Participant and trial characteristics, interventions and outcomes data of included studies will be summarised. Meta-analyses will entail a one-stage model, which will account for the heterogeneity across and the clustering between studies. Multiple imputation using chained equations will be used to account for the missing data. ETHICS AND DISSEMINATION: This individual participant data meta-analysis does not require ethical review as anonymised participant data will be used and no new data collected. Additionally, eligible trials were granted approval by institutional review boards or research ethics committees and informed consent was provided for participants. Data sharing agreements are in place permitting contribution of data. The study findings will be disseminated at conferences and through peer-reviewed publications. PROSPERO REGISTRATION NUMBER: CRD42019152526

Theoretical study of Oldroyd-b visco-elastic fluid flow through curved pipes with slip effects in polymer flow processing

The characteristics of the flow field of both viscous and viscoelastic fluids passing through a curved pipe with a Navier slip boundary condition have been investigated analytically in the present study. The Oldroyd-B constitutive equation is employed to simulate realistic transport of dilute polymeric solutions in curved channels. In order to linearize the momentum and constitutive equations, a perturbation method is used in which the ratio of radius of cross section to the radius of channel curvature is employed as the perturbation parameter. The intensity of secondary and main flows is mainly affected by the hoop stress and it is demonstrated in the present study that both the Weissenberg number (the ratio of elastic force to viscous force) and slip coefficient play major roles in determining the strengths of both flows. It is also shown that as a result of an increment in slip coefficient, the position of maximum velocity markedly migrates away from the pipe center towards the outer side of curvature. Furthermore, results corresponding to Navier slip scenarios exhibit non-uniform distributions in both the main and lateral components of velocity near the wall which can notably vary from the inner side of curvature to the outer side. The present solution is also important in polymeric flow processing systems because of experimental evidence indicating that the no-slip condition can fail for these flows, which is of relevance to chemical engineers

Evaluation of a weighting approach for performing sensitivity analysis after multiple imputation

Abstract Background Multiple imputation (MI) is a well-recognised statistical technique for handling missing data. As usually implemented in standard statistical software, MI assumes that data are ‘Missing at random’ (MAR); an assumption that in many settings is implausible. It is not possible to distinguish whether data are MAR or ‘Missing not at random’ (MNAR) using the observed data, so it is desirable to discover the impact of departures from the MAR assumption on the MI results by conducting sensitivity analyses. A weighting approach based on a selection model has been proposed for performing MNAR analyses to assess the robustness of results obtained under standard MI to departures from MAR. Methods In this article, we use simulation to evaluate the weighting approach as a method for exploring possible departures from MAR, with missingness in a single variable, where the parameters of interest are the marginal mean (and probability) of a partially observed outcome variable and a measure of association between the outcome and a fully observed exposure. The simulation studies compare the weighting-based MNAR estimates for various numbers of imputations in small and large samples, for moderate to large magnitudes of departure from MAR, where the degree of departure from MAR was assumed known. Further, we evaluated a proposed graphical method, which uses the dataset with missing data, for obtaining a plausible range of values for the parameter that quantifies the magnitude of departure from MAR. Results Our simulation studies confirm that the weighting approach outperformed the MAR approach, but it still suffered from bias. In particular, our findings demonstrate that the weighting approach provides biased parameter estimates, even when a large number of imputations is performed. In the examples presented, the graphical approach for selecting a range of values for the possible departures from MAR did not capture the true parameter value of departure used in generating the data. Conclusions Overall, the weighting approach is not recommended for sensitivity analyses following MI, and further research is required to develop more appropriate methods to perform such sensitivity analyses

Effect of Exercise Interventions on Anxiety in People with Multiple Sclerosis: A Systematic Review and Meta-analysis.

Background: Evidence suggests that exercise can alleviate symptoms associated with multiple sclerosis (MS). However, it is unclear whether exercise alleviates symptoms of anxiety, present in one-third of people with MS. This systematic review and meta-analysis investigates whether exercise interventions are effective in reducing anxiety in people with MS. Methods: CINAHL, Embase, MEDLINE, PsycINFO, and the Cochrane Controlled Clinical Trials Register were searched to identify relevant randomized controlled trials (RCTs) published up to March 30, 2018. The primary outcome was postintervention difference in anxiety scores between intervention and control groups. Using a restricted maximum likelihood random-effects model, standardized mean differences were pooled and heterogeneity was estimated. Risk of bias was assessed using an a priori modified Cochrane Risk of Bias 2.0 tool. Results: Four RCTs with 133 participants were included. Exercise type included walking, aerobic activities, and cycling. Intervention duration ranged from 8 to 26 weeks. The pooled standardized mean difference in anxiety score was -0.16 (95% CI, -0.50 to 0.19), without heterogeneity. Two studies had high risk of bias, and two had some risk of bias. Conclusions: Based on available RCT data, exercise does not seem to have an effect on anxiety in people with MS. These results should be interpreted with caution because studies had concerns of bias and small sample sizes, and anxiety was not the primary outcome measure. Future studies should exhibit sufficient reporting standards, alongside publishing protocols. There is opportunity to investigate the effect of exercise in people with MS experiencing clinically relevant levels of anxiety rather than in the general MS population