78 research outputs found
How Schools Affect Student Well-Being: A Cross-Cultural Approach in 35 OECD Countries
A common approach for measuring the effectiveness of an education system or a school
is the estimation of the impact that school interventions have on students’ academic
performance. However, the latest trends aim to extend the focus beyond students’
acquisition of knowledge and skills, and to consider aspects such as well-being in the
academic context. For this reason, the 2015 edition of the international assessment
system Programme for International Student Assessment (PISA) incorporated a new tool
aimed at evaluating the socio-emotional variables related to the well-being of students. It
is based on a definition focused on the five dimensions proposed in the PISA theoretical
framework: cognitive, psychological, social, physical, and material. The main purpose
of this study is to identify the well-being components that significantly affect student
academic performance and to estimate the magnitude of school effects on the wellbeing
of students in OECD countries, the school effect being understood as the ability of
schools to increase subjective student well-being. To achieve this goal, we analyzed the
responses of 248,620 students from 35 OECD countries to PISA 2015 questionnaires.
Specifically, we considered non-cognitive variables in the questionnaires and student
performance in science. The results indicated that the cognitive well-being dimension,
composed of enjoyment of science, self-efficacy, and instrumental motivation, as well as
test anxiety all had a consistent relationship with student performance across countries.
In addition, the school effect, estimated through a two-level hierarchical linear model, in
terms of student well-being was systematically low. While the school effect accounted
for approximately 25% of the variance in the results for the cognitive dimension, only
5–9% of variance in well-being indicators was attributable to it. This suggests that the
influence of school on student welfare is weak, and the effect is similar across countries.
The present study contributes to the general discussion currently underway about the
definition of well-being and the connection between well-being and achievement. The
results highlighted two complementary concerns: there is a clear need to promote socioemotional
education in schools, and it is important to develop a rigorous framework for
well-being assessment. The implications of the results and proposals for future studies
are discussed.Spain Ministry of Science, Innovation and Universities
PSI2017-85724-P2E Estudios, Evaluaciones e Investigacion, S.
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Six years beyond pediatric trauma: child and parental ratings of children’s health-related quality of life in relation to parental mental health
Purpose: To examine the relationship between child self-report and parent proxy report of health-related quality of life (HRQL) and how parents’ mental health status relates to the HRQL ratings 6 years after minor to severe injury of the child.
Materials and methods: This cross-sectional cohort study was performed at a regional pediatric trauma center in Stockholm, Sweden. The PedsQL 4.0 versions for ages 5–7, 8–12, and 13–18 years were completed by 177 child–parent dyads 6 years after injury to the child. The parents also rated their own mental health through the mental health domain (MH) in the SF-36 Health Survey.
Results: The children’s median age was 13 years (IQR 10–16 years), 54 % were males, and the median ISS was 5 (IQR 2–9). Most of the parents were female (77 %), born in Sweden (79 %), and half had university degrees. There was no statistically significant difference between child self-report and parent proxy report in any of the PedsQL 4.0 scales or summary scales. The levels of agreement between child self-report and parent proxy reports were excellent (ICC ≥ 0.80) for all scales with the exception of emotional functioning (ICC 0.53) which also was the scale with the lowest internal consistency in child self-report (α 0.60). Multiple regression analyses showed that worse parental mental health status correlated with worse child self-report and parent proxy report of children’s HRQL.
Conclusions: Children and their parents’ reports on child’s HRQL were in agreement. Decreased mental health in parents was associated with lower scores on parent proxy reports and child self-reports of HRQL after injury. The current investigation highlights the possible relationship between parent’s mental health status and children’s HRQL long after an injury, which should be considered in future investigations and in clinical care
Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: A simulation study
<p>Abstract</p> <p>Background</p> <p>Multicentre randomized controlled trials (RCTs) routinely use randomization and analysis stratified by centre to control for differences between centres and to improve precision. No consensus has been reached on how to best analyze correlated continuous outcomes in such settings. Our objective was to investigate the properties of commonly used statistical models at various levels of clustering in the context of multicentre RCTs.</p> <p>Methods</p> <p>Assuming no treatment by centre interaction, we compared six methods (ignoring centre effects, including centres as fixed effects, including centres as random effects, generalized estimating equation (GEE), and fixed- and random-effects centre-level analysis) to analyze continuous outcomes in multicentre RCTs using simulations over a wide spectrum of intraclass correlation (ICC) values, and varying numbers of centres and centre size. The performance of models was evaluated in terms of bias, precision, mean squared error of the point estimator of treatment effect, empirical coverage of the 95% confidence interval, and statistical power of the procedure.</p> <p>Results</p> <p>While all methods yielded unbiased estimates of treatment effect, ignoring centres led to inflation of standard error and loss of statistical power when within centre correlation was present. Mixed-effects model was most efficient and attained nominal coverage of 95% and 90% power in almost all scenarios. Fixed-effects model was less precise when the number of centres was large and treatment allocation was subject to chance imbalance within centre. GEE approach underestimated standard error of the treatment effect when the number of centres was small. The two centre-level models led to more variable point estimates and relatively low interval coverage or statistical power depending on whether or not heterogeneity of treatment contrasts was considered in the analysis.</p> <p>Conclusions</p> <p>All six models produced unbiased estimates of treatment effect in the context of multicentre trials. Adjusting for centre as a random intercept led to the most efficient treatment effect estimation across all simulations under the normality assumption, when there was no treatment by centre interaction.</p
Computational Models of Timing Mechanisms in the Cerebellar Granular Layer
A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum
Localization of orphanin FQ (nociceptin) peptide and messenger RNA in the central nervous system of the rat
Orphanin FQ (OFQ) is the endogenous agonist of the opioid receptor-like receptor (ORL-1). It and its precursor, prepro-OFQ, exhibit structural features suggestive of the opioid peptides. A cDNA encoding the OFQ precursor sequence in the rat recently has been cloned, and the authors recently generated a polyclonal antibody directed against the OFQ peptide. In the present study, the authors used in situ hybridization and immunohistochemistry to examine the distribution of OFQ peptide and mRNA in the central nervous system of the adult rat. OFQ immunoreactivity and prepro-OFQ mRNA expression correlated virtually in all brain areas studied. In the forebrain, OFQ peptide and mRNA were prominent in the neocortex endopiriform nucleus, claustrum, lateral septum, ventral forebrain, hypothalamus, mammillary bodies, central and medial nuclei of the amygdala, hippocampal formation, paratenial and reticular nuclei of the thalamus, medial habenula, and zona incerta. No OFQ was observed in the pineal or pituitary glands. In the brainstem, OFQ was prominent in the ventral tegmental area, substantia nigra, nucleus of the posterior commissure, central gray, nucleus of Darkschewitsch, peripeduncular nucleus, interpeduncular nucleus, tegmental nuclei, locus coeruleus, raphe complex, lateral parabrachial nucleus, inferior olivary complex, vestibular nuclear complex, prepositus hypoglossus, solitary nucleus, nucleus ambiguous, caudal spinal trigeminal nucleus, and reticular formation. In the spinal cord, OFQ was observed throughout the dorsal and ventral horns. The wide distribution of this peptide provides support for its role in a multitude of functions, including not only nociception but also motor and balance control, special sensory processing, and various autonomic and physiologic processes. J. Comp. Neurol. 406:503–547, 1999. © 1999 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34452/1/7_ftp.pd
Classification of longitudinal profiles based on semi-parametric regression with mixed effects
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