Building a climate of faculty trust in students through principal support of student psychological needs

PurposeThis study was designed to test the relationship between principal support of student psychological needs and faculty trust in students. Without direct empirical evidence to draw from, the line of reasoning integrated evidence on social-cognitive processes involved in trust formation and conversation theory to advance two hypotheses: (1) After accounting for school and leadership conditions, principal support of student psychological needs will be related to school differences in faculty trust in students; (2) The relationship between principal support of student psychological needs and faculty trust in students is mediated by a positive view of the teaching task.Design/methodology/approachHypotheses were tested with a nonexperimental, correlational research design using ex post facto data. Due to the hierarchical structure of the data, hypotheses were tested with a 2-2-1 multilevel mediation model in HLM 7.03 with restricted maximum likelihood estimation.FindingsFindings were consistent with the hypothesized relationships – principal support of student psychological needs was related to faculty trust in students and this relationship was mediated by teacher perceptions of the teaching task.Originality/valueSchool research has primarily examined interpersonal antecedents of trust, focusing on behaviors and characteristics that position a person or group as trustworthy. This study extends trust research to the cognitive side of the formation process, calling attention to the function of mental representation in shaping trust discernments. Results suggest that cognitive processes hold promise as both a source of faculty trust in students and as a malleable mental structure that school leaders can shape through conversation.

Effects of Compounded Nonnormality of Residuals in Hierarchical Linear Modeling

While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality assumption simultaneously across all levels could bias parameter estimates in unforeseen ways. This article aims to raise awareness of the drawbacks associated with compounded nonnormality residuals across levels when the number of clusters range from small to large. The effects of the breach of the normality assumption at both individual and cluster levels were explored. A simulation study was conducted to evaluate the relative bias and the root mean square of the model parameter estimates by manipulating the normality of the data. The results indicate that nonnormal residuals have a larger impact on the random effects than fixed effects, especially when the number of clusters and cluster size are small. In addition, for a simple random-effects structure, the use of restricted maximum likelihood estimation is recommended to improve parameter estimates when compounded residuals across levels show moderate nonnormality, with a combination of small number of clusters and a large cluster size.

Vagus Nerve Stimulation and Seizure Outcomes in Pediatric Refractory Epilepsy

ObjectiveWe synthesized evidence for effectiveness of vagus nerve stimulation (VNS) as adjuvant therapy in pediatric drug-resistant epilepsy (DRE) by obtaining pooled estimates for seizure outcomes and analyzing their determinants.MethodsMEDLINE, EMBASE, and Cochrane databases were searched up to July 2019, for original research on VNS in pediatric (≤18 years-of-age) epilepsy. The primary outcome was 50% responder rate (50%-RR), the proportion of patients with ≥50% seizure reduction, at the last reported follow-up. Other outcomes included 50%-RR and proportion of seizure-free patients at additional reported time points. A random effects meta-analysis with restricted maximum likelihood estimation was performed to obtain pooled effect estimates. Meta-regression using multiple linear models was performed to obtain determinants of seizure outcomes and sources of heterogeneity.ResultsA total of 101 studies were included. The pooled prevalence estimates for 50%-RR and seizure freedom at last follow-up (mean 2.54 years) were 56.4% (95% confidence intervals [CIs] 52.4, 60.4) and 11.6% (95% CI 9.6, 13.9) respectively. Fewer anti-seizure medications (ASMs) tried before VNS, and later age at onset of seizures were associated with better seizure outcomes following VNS implantation. An effect of sex-distribution of studies on long-term outcomes and a potential publication bias for short-term outcomes were also observed.ConclusionPooled evidence supports possible effectiveness of VNS in pediatric DRE, although complete seizure freedom is less common. Early referral (fewer trials of ASMs) may be a modifiable factor for desirable seizure outcomes with VNS from a clinical perspective.

MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses

Background Few microRNAs were found consistently dysregulated in type 2 diabetes (T2D) that would gain confidence from Big Pharma to develop diagnostic or therapeutic biomarkers. This study aimed to corroborate evidence from eligible microRNAs-T2D association studies according to stringent quality criteria covering both biological and statistical significance in T2D for biomarker development. Methods and analyses Controlled microRNA expression profiling studies on human with T2D will be retrieved from PubMed, ScienceDirect, and Embase for selecting the statistically significant microRNAs according to pre-specified search strategies and inclusion criteria. Multiple meta-analyses with restricted maximum-likelihood estimation and empirical Bayes estimation under the random-effects model will be conducted by metafor package in R. Subgroup and sensitivity analyses further examine the microRNA candidates for their disease specificity, tissue specificity, blood fraction specificity, and statistical robustness of evidence. Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). Meta-analysis of AUC of potential biomarkers will also be conducted. Enrichment analysis on potential microRNA biomarkers and their target genes will be performed by iPathwayGuide and clusterProfiler, respectively. The corresponding reporting guidelines will be used to assess the quality of included studies according to their profiling methods (microarray, RT-PCR, and RNA-Seq). Ethics and dissemination No ethics approval is required since this study does not include identifiable personal patient data. Protocol registration number CRD42017081659.

Effect of Tourism Pressure on the Mediterranean Diet Pattern

Despite proposed conceptual frameworks of eating behaviors, little is known about environmental factors contributing to changes in food habits. Few studies have reported the external influence of tourism on the inhabitants’ eating patterns. The present study aimed to investigate whether tourism pressure affects Canary Islands inhabitants’ adherence to the Mediterranean diet pattern. Data were obtained from a health and lifestyle population-based survey conducted in 2009 and 2015. From the reported intake frequency, a Mediterranean diet score was defined (0 to 11 points). Tourist overnight stays, which were stratified by nationality and area of destination, were used as a proxy variable to measure tourism pressure. A multilevel linear regression analysis by restricted maximum likelihood estimation was performed to examine the relationship between tourism pressure and the Mediterranean diet score. A significant negative association between the Mediterranean diet score and British tourism pressure was observed (β = −0.0064, p = 0.010), whereas German tourism pressure increased inhabitants’ adherence (β = 0.0092, p = 0.042). The socioeconomic level of tourists seems to play a role in differences in the tourism pressure effect by nationality. Further investigation of other highly touristic destinations is needed to confirm these findings that could contribute to a shift in tourism and public health nutrition policies.

Analyzing Repeated Measurements while Accounting for Derivative Tracking, Varying Within-subject Variance, and Autocorrelation: The Xtmixediou Command

Linear mixed-effects models are commonly used to model trajectories of repeated measures of biomarkers of disease. Taylor, Cumberland, and Sy (1994, Journal of the American Statistical Association 89: 727–736) proposed a linear mixed-effects model with an added integrated Ornstein–Uhlenbeck (IOU) process (linear mixed-effects IOU model). This allows for autocorrelation, changing within-subject variance, and the incorporation of derivative tracking (that is, how much a subject tends to maintain the same trajectory for extended periods of time). They argued that the covariance structure induced by the stochastic process in this model was interpretable and more biologically plausible than the standard linear mixed-effects model. However, their model is rarely used, partly because of the lack of available software. In this article, we present the new command xtmixediou, which fits the linear mixed-effects IOU model and its special case, the linear mixed-effects Brownian motion model. The model is fit to balanced and unbalanced data using restricted maximum-likelihood estimation, where the optimization algorithm is the Newton–Raphson, Fisher scoring, or average information algorithm, or any combination of these. To aid convergence, xtmixediou allows the user to change the method for deriving the starting values for optimization, the optimization algorithm, and the parameterization of the IOU process. We also provide a predict command to generate predictions under the model. We illustrate xtmixediou and predict with a simulated example of repeated biomarker measurements from HIV-positive patients.

Principal support for student psychological needs

Purpose Although leadership evidence highlights the importance of cooperative principal-teacher relationships, research has not looked thoroughly at the content behind principal-teacher interactions. The purpose of this paper is to use self-determination theory and organizational conversation to develop principal support for student psychological needs (PSSPN), a concept that represents principal-teacher interactions based on social and psychological factors contributing to student learning. The empirical part of the study tests the relationship between PSSPN and faculty trust in students and student self-regulated learning. Design/methodology/approach Hypotheses were tested with a non-experimental, correlational research design using ex post facto data. Data were collected from 3,339 students and 633 teachers in 71 schools located in a metropolitan area of a southwestern city in the USA. Hypotheses were tested with a 2-2-1 multi-level mediation model in HLM 7.0 with restricted maximum likelihood estimation. Findings Principal support for student psychological needs had a positive and statistically significant relationship with faculty trust in students and self-regulated learning. Additionally faculty trust mediated the relationship between principal support for student psychological needs and self-regulated learning. Originality/value This is one of the first studies to examine school leadership by the content that is exchanged during principal-teacher interactions. Principal support for student psychological needs establishes a theoretically-based framework to study leadership conversations and to guide administrative practices. Empirical results offer encouraging evidence that the simple act of framing interactions around the science of wellbeing can be an effective resource for school principals.