247 resultados para latent growth curve modeling
em Queensland University of Technology - ePrints Archive
Resumo:
Cognitive-energetical theories of information processing were used to generate predictions regarding the relationship between workload and fatigue within and across consecutive days of work. Repeated measures were taken on board a naval vessel during a non-routine and a routine patrol. Data were analyzed using growth curve modeling. Fatigue demonstrated a non-monotonic relationship within days in both patrols – fatigue was high at midnight, started decreasing until noontime and then increased again. Fatigue increased across days towards the end of the non-routine patrol, but remained stable across days in the routine patrol. The relationship between workload and fatigue changed over consecutive days in the non-routine patrol. At the beginning of the patrol, low workload was associated with fatigue. At the end of the patrol, high workload was associated with fatigue. This relationship could not be tested in the routine patrol, however it demonstrated a non-monotonic relationship between workload and fatigue – low and high workloads were associated with the highest fatigue. These results suggest that the optimal level of workload can change over time and thus have implications for the management of fatigue.
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Critical analysis and problem-solving skills are two graduate attributes that are important in ensuring that graduates are well equipped in working across research and practice settings within the discipline of psychology. Despite the importance of these skills, few psychology undergraduate programmes have undertaken any systematic development, implementation, and evaluation of curriculum activities to foster these graduate skills. The current study reports on the development and implementation of a tutorial programme designed to enhance the critical analysis and problem-solving skills of undergraduate psychology students. Underpinned by collaborative learning and problem-based learning, the tutorial programme was administered to 273 third year undergraduate students in psychology. Latent Growth Curve Modelling revealed that students demonstrated a significant linear increase in self-reported critical analysis and problem-solving skills across the tutorial programme. The findings suggest that the development of inquiry-based curriculum offers important opportunities for psychology undergraduates to develop critical analysis and problem-solving skills.
Resumo:
Changes at work are often accompanied with the threat of, or actual, resource loss. Through an experiment, we investigated the detrimental effect of the threat of resource loss on adaptive task performance. Self-regulation (i.e., task focus and emotion control) was hypothesized to buffer the negative relationship between the threat of resource loss and adaptive task performance. Adaptation was conceptualized as relearning after a change in task execution rules. Threat of resource loss was manipulated for 100 participants undertaking an air traffic control task. Using discontinuous growth curve modeling, 2 kinds of adaptation—transition adaptation and reacquisition adaptation—were differentiated. The results showed that individuals who experienced the threat of resource loss had a stronger drop in performance (less transition adaptation) and a subsequent slower recovery (less reacquisition adaptation) compared with the control group who experienced no threat. Emotion control (but not task focus) moderated the relationship between the threat of resource loss and transition adaptation. In this respect, individuals who felt threatened but regulated their emotions performed better immediately after the task change (but not later on) compared with those individuals who felt threatened and did not regulate their emotions as well. However, later on, relearning (reacquisition adaptation) under the threat of resource loss was facilitated when individuals concentrated on the task at hand.
Resumo:
PURPOSE/OBJECTIVES: To identify latent classes of individuals with distinct quality-of-life (QOL) trajectories, to evaluate for differences in demographic characteristics between the latent classes, and to evaluate for variations in pro- and anti-inflammatory cytokine genes between the latent classes. DESIGN: Descriptive, longitudinal study. SETTING: Two radiation therapy departments located in a comprehensive cancer center and a community-based oncology program in northern California. SAMPLE: 168 outpatients with prostate, breast, brain, or lung cancer and 85 of their family caregivers (FCs). METHODS: Growth mixture modeling (GMM) was employed to identify latent classes of individuals based on QOL scores measured prior to, during, and for four months following completion of radiation therapy. Single nucleotide polymorphisms (SNPs) and haplotypes in 16 candidate cytokine genes were tested between the latent classes. Logistic regression was used to evaluate the relationships among genotypic and phenotypic characteristics and QOL GMM group membership. MAIN RESEARCH VARIABLES: QOL latent class membership and variations in cytokine genes. FINDINGS: Two latent QOL classes were found: higher and lower. Patients and FCs who were younger, identified with an ethnic minority group, had poorer functional status, or had children living at home were more likely to belong to the lower QOL class. After controlling for significant covariates, between-group differences were found in SNPs in interleukin 1 receptor 2 (IL1R2) and nuclear factor kappa beta 2 (NFKB2). For IL1R2, carrying one or two doses of the rare C allele was associated with decreased odds of belonging to the lower QOL class. For NFKB2, carriers with two doses of the rare G allele were more likely to belong to the lower QOL class. CONCLUSIONS: Unique genetic markers in cytokine genes may partially explain interindividual variability in QOL. IMPLICATIONS FOR NURSING: Determination of high-risk characteristics and unique genetic markers would allow for earlier identification of patients with cancer and FCs at higher risk for poorer QOL. Knowledge of these risk factors could assist in the development of more targeted clinical or supportive care interventions for those identified.
Resumo:
Aim: This study aimed to document the growth patterns of a contemporary cohort of preterm infants born appropriate for gestational age (AGA). It was hypothesised that preterm AGA (PT-AGA) infants would display poorer growth than full-term AGA (FT-AGA) infants. Methods: Sixty-four PT-AGA infants and 64 FT-AGA infants were assessed at 0, 4, 8 and 12 months of corrected age (CA). Measurements of weight and length were recorded at each of the specified ages. Centers for Disease Control and Prevention growth data were used to calculate Z-scores for weight and length based on CA. Results: The mean length and weight Z-scores of PT-AGA infants were found to be significantly less than those of FT-AGA infants at term, 4, 8 and 12 months of CA (P < 0.001). The mean weight Z-score of PT-AGA infants was found to be less than their mean length Z-score at each time point, though the differences were not significant. Conclusions: The results of this study suggest that PT-AGA infants are likely to display poorer growth than FT-AGA infants until at least 1 year of CA. Long-term growth monitoring in this population is recommended. © 2008 The Authors.
Resumo:
James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.
Resumo:
Two-stroke outboard boat engines using total loss lubrication deposit a significant proportion of their lubricant and fuel directly into the water. The purpose of this work is to document the velocity and concentration field characteristics of a submerged swirling water jet emanating from a propeller in order to provide information on its fundamental characteristics. Measurements of the velocity and concentration field were performed in a turbulent jet generated by a model boat propeller (0.02 m diameter) operating at 1500 rpm and 3000 rpm. The measurements were carried out in the Zone of Established Flow up to 50 propeller diameters downstream of the propeller. Both the mean axial velocity profile and the mean concentration profile showed self-similarity. Further, the stand deviation growth curve was linear. The effects of propeller speed and dye release location were also investigated.
Resumo:
Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.
Resumo:
Regenerative medicine includes two efficient techniques, namely tissue-engineering and cell-based therapy in order to repair tissue damage efficiently. Most importantly, huge numbers of autologous cells are required to deal these practices. Nevertheless, primary cells, from autologous tissue, grow very slowly while culturing in vitro; moreover, they lose their natural characteristics over prolonged culturing period. Transforming growth factors-beta (TGF-β) is a ubiquitous protein found biologically in its latent form, which prevents it from eliciting a response until conversion to its active form. In active form, TGF-β acts as a proliferative agent in many cell lines of mesenchymal origin in vitro. This article reviews on some of the important activation methods-physiochemical, enzyme-mediated, non-specific protein interaction mediated, and drug-induced- of TGF-β, which may be established as exogenous factors to be used in culturing medium to obtain extensive proliferation of primary cells.
Resumo:
Purpose: To examine the ability of silver nano-particles to prevent the growth of Pseudomonas aeruginosa and Staphylococcus aureus in solution or when adsorbed into contact lenses. To examine the ability of silver nano-particles to prevent the growth of Acanthamoeba castellanii. ----- ----- Methods: Etafilcon A lenses were soaked in various concentrations of silver nano-particles. Bacterial cells were then exposed to these lenses, and numbers of viable cells on lens surface or in solution compared to etafilcon A lenses not soaked in silver. Acanthamoeba trophozoites were exposed to silver nano-particles and their ability to form tracks was examined. ----- ----- Results: Silver nano-particle containing lenses reduced bacterial viability and adhesion. There was a dose-dependent response curve, with 10 ppm or 20 ppm silver showing > 5 log reduction in bacterial viability in solution or on the lens surface. For Acanthamoeba, 20 ppm silver reduced the ability to form tracks by approximately 1 log unit. ----- ----- Conclusions: Silver nanoparticles are effective antimicrobial agents, and can reduce the ability of viable bacterial cells to colonise contact lenses once incorporated into the lens.----- ----- Resumen: Objetivos: Examinar la capacidad de las nanopartículas de plata para prevenir el crecimiento de Pseudomonas aeruginosa y Staphylococcus aureus en soluciones para lentes de contacto o cuando éstas las adsorben. Examinar la capacidad de las nanopartículas de plata para prevenir el crecimiento de Acanthamoeba castellanii.----- ----- Métodos: Se sumergieron lentes etafilcon A en diversas concentraciones de nanopartículas de plata. Las células bacterianas fueron posteriormente expuestas a dichas lentes, y se compararon cantidades de células viables en la superficie de la lente o en la solución con las presentes en lentes etafilcon A que no habían sido sumergidas en plata. Trofozoítos de Acanthamoeba fueron expuestos a nanopartículas de plata y se examinó su capacidad para formar quistes.----- ----- Resultados: Las lentes que contienen nanopartículas de plata redujeron la viabilidad bacteriana y la adhesión. Hubo una curva de respuesta dependiente de la dosis, en la que 10 ppm o 20 ppm de plata mostró una reducción logarítmica > 5 en la viabilidad bacteriana tanto en la solución como en la superficie de la lente. Para Acanthamoeba, 20 ppm de plata redujeron la capacidad de formar quistes en aproximadamente 1 unidad logarítmica.----- ----- Conclusiones: Las nanopartículas de plata son agentes antimicrobianos eficaces y pueden reducir la capacidad de células bacterianas viables para colonizar las lentes de contacto una vez que se han incorporado en la lente.
Resumo:
Despite considerable success in treatment of early stage localized prostate cancer (PC), acute inadequacy of late stage PC treatment and its inherent heterogeneity poses a formidable challenge. Clearly, an improved understanding of PC genesis and progression along with the development of new targeted therapies are warranted. Animal models, especially, transgenic immunocompetent mouse models, have proven to be the best ally in this respect. A series of models have been developed by modulation of expression of genes implicated in cancer-genesis and progression; mainly, modulation of expression of oncogenes, steroid hormone receptors, growth factors and their receptors, cell cycle and apoptosis regulators, and tumor suppressor genes have been used. Such models have contributed significantly to our understanding of the molecular and pathological aspects of PC initiation and progression. In particular, the transgenic mouse models based on multiple genetic alterations can more accurately address the inherent complexity of PC, not only in revealing the mechanisms of tumorigenesis and progression but also for clinically relevant evaluation of new therapies. Further, with advances in conditional knockout technologies, otherwise embryonically lethal gene changes can be incorporated leading to the development of new generation transgenics, thus adding significantly to our existing knowledge base. Different models and their relevance to PC research are discussed.