Group-Based Symptom Trajectories in Indicated Prevention of Adolescent Depression

Background: Adolescent depression prevention research has focused on mean intervention outcomes, but has not considered heterogeneity in symptom course. Here, we empirically identify subgroups with distinct trajectories of depressive symptom change among adolescents enrolled in two indicated depression preven- tion trials and examine how cognitive-behavioral (CB) interventions and baseline predictors relate to trajectory membership. Methods: Six hundred thirty-one participants were assigned to one of three conditions: CB group intervention, CB bibliotherapy, and brochure control. We used group-based trajectory modeling to identify trajectories of depressive symptoms from pretest to 2-year follow-up. We examined associations between class membership and conditions using chi- square tests and baseline predictors using multinomial regressions. Results: We identified four trajectories in the full sample. Qualitatively similar trajectories were found in each condition separately. Two trajectories of positive symptom course (low-declining, high-declining) had declining symptoms and were dis- tinguished by baseline symptom severity. Two trajectories of negative course (high-persistent, resurging), respectively, showed no decline in symptoms or de- cline followed by symptom reappearance. Participants in the brochure control condition were significantly more likely to populate the high-persistent trajectory relative to either CB condition and were significantly less likely to populate the low-declining trajectory relative to CB group. Several baseline factors predicted trajectory classes, but gender was the most informative prognostic factor, with males having increased odds of membership in a high-persistent trajectory rel- ative to other trajectories. Conclusions: Findings suggest that CB preventive interventions do not alter the nature of trajectories, but reduce the risk that adolescents follow a trajectory of chronically elevated symptoms.

Group-Based Symptom Trajectories in Indicated Prevention of Adolescent Depression

Background: Adolescent depression prevention research has focused on mean intervention outcomes, but has not considered heterogeneity in symptom course. Here, we empirically identify subgroups with distinct trajectories of depressive symptom change among adolescents enrolled in two indicated depression preven- tion trials and examine how cognitive-behavioral (CB) interventions and baseline predictors relate to trajectory membership. Methods: Six hundred thirty-one participants were assigned to one of three conditions: CB group intervention, CB bibliotherapy, and brochure control. We used group-based trajectory modeling to identify trajectories of depressive symptoms from pretest to 2-year follow-up. We examined associations between class membership and conditions using chi- square tests and baseline predictors using multinomial regressions. Results: We identified four trajectories in the full sample. Qualitatively similar trajectories were found in each condition separately. Two trajectories of positive symptom course (low-declining, high-declining) had declining symptoms and were dis- tinguished by baseline symptom severity. Two trajectories of negative course (high-persistent, resurging), respectively, showed no decline in symptoms or de- cline followed by symptom reappearance. Participants in the brochure control condition were significantly more likely to populate the high-persistent trajectory relative to either CB condition and were significantly less likely to populate the low-declining trajectory relative to CB group. Several baseline factors predicted trajectory classes, but gender was the most informative prognostic factor, with males having increased odds of membership in a high-persistent trajectory rel- ative to other trajectories. Conclusions: Findings suggest that CB preventive interventions do not alter the nature of trajectories, but reduce the risk that adolescents follow a trajectory of chronically elevated symptoms.

Examining the Longitudinal Stability of a Dual-Factor Model of Mental Health in Early Elementary School Students

Thesis (Ph.D.)--University of Washington, 2016-08

Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling

PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.

Perceived self-other differences in persuasibility: the effects of interpersonal and group-based similarity

Two experiments examined the effects of interpersonal and group-based similarity on perceived self-other differences in persuasibility (i.e. on third-person effects, Davison, 1983). Results of Experiment 1 (N=121), based on experimentally-created groups, indicated that third-person perceptions with respect to the impact of televised product ads were accentuated when the comparison was made with interpersonally different others. Contrary to predictions, third-person perceptions were not affected by group-based similarity (i.e. ingroup or outgroup other). Results of Experiment 2 (N = 102), based an an enduring social identity, indicated that both interpersonal and group-based similarity moderated perceptions of the impact on self and other of least-liked product ads. Overall, third-person effects were more pronounced with respect to interpersonally dissimilar others. However, when social identity was salient, information about interpersonal similarity of the target did not affect perceived self-other differences with respect to ingroup targets. Results also highlighted significant differences in third-person perceptions according to the perceiver's affective evaluation of the persuasive message. (C) 1998 John Wiley & Sons, Ltd.

An L-system-based plant modeling language

Cpfg is a program for simulating and visualizing plant development, based on the theory of L-systems. A special-purpose programming language, used to specify plant models, is an essential feature of cpfg. We review postulates of L-system theory that have influenced the design of this language. We then present the main constructs of this language, and evaluate it from a user's perspective.

Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

CHIP-Community Health Improvement Programme (Group-Based)

This intervention aims to: - Increase fruit and vegetable intake - Increase activity levelsInitiate weight loss - Reduce health risks - Provide effective weight loss tools - Increase participant behaviour change skills

Physiologically based pharmacokinetic modeling of arsenic in the mouse

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process. [Authors]

Measurements of glial metabolic fluxes with C-11-acetate using positron emission and an adapted NMR-based metabolic modeling approach

Objectives: Acetate brain metabolism has the particularity to occur specifically in glial cells. Labeling studies, using acetate labeled either with 13C (NMR) or 11C (PET), are governed by the same biochemical reactions and thus follow the same mathematical principles. In this study, the objective was to adapt an NMR acetate brain metabolism model to analyse [1-11C]acetate infusion in rats. Methods: Brain acetate infusion experiments were modeled using a two-compartment model approach used in NMR.1-3 The [1-11C]acetate labeling study was done using a beta scintillator.4 The measured radioactive signal represents the time evolution of the sum of all labeled metabolites in the brain. Using a coincidence counter in parallel, an arterial input curve was measured. The 11C at position C-1 of acetate is metabolized in the first turn of the TCA cycle to the position 5 of glutamate (Figure 1A). Through the neurotransmission process, it is further transported to the position 5 of glutamine and the position 5 of neuronal glutamate. After the second turn of the TCA cycle, tracer from [1-11C]acetate (and also a part from glial [5-11C]glutamate) is transferred to glial [1-11C]glutamate and further to [1-11C]glutamine and neuronal glutamate through the neurotransmission cycle. Brain poster session: oxidative mechanisms S460 Journal of Cerebral Blood Flow & Metabolism (2009) 29, S455-S466 Results: The standard acetate two-pool PET model describes the system by a plasma pool and a tissue pool linked by rate constants. Experimental data are not fully described with only one tissue compartment (Figure 1B). The modified NMR model was fitted successfully to tissue time-activity curves from 6 single animals, by varying the glial mitochondrial fluxes and the neurotransmission flux Vnt. A glial composite rate constant Kgtg=Vgtg/[Ace]plasma was extracted. Considering an average acetate concentration in plasma of 1 mmol/g5 and the negligible additional amount injected, we found an average Vgtg = 0.08±0.02 (n = 6), in agreement with previous NMR measurements.1 The tissue time-activity curve is dominated by glial glutamate and later by glutamine (Figure 1B). Labeling of neuronal pools has a low influence, at least for the 20 mins of beta-probe acquisition. Based on the high diffusivity of CO2 across the blood-brain barrier; 11CO2 is not predominant in the total tissue curve, even if the brain CO2 pool is big compared with other metabolites, due to its strong dilution through unlabeled CO2 from neuronal metabolism and diffusion from plasma. Conclusion: The two-compartment model presented here is also able to fit data of positron emission experiments and to extract specific glial metabolic fluxes. 11C-labeled acetate presents an alternative for faster measurements of glial oxidative metabolism compared to NMR, potentially applicable to human PET imaging. However, to quantify the relative value of the TCA cycle flux compared to the transmitochondrial flux, the chemical sensitivity of NMR is required. PET and NMR are thus complementary.

Maintaining unlinkability in group based P2P environments

In the wake of the success of Peer-to-Peer (P2P) networking, security has arisen as one of its main concerns, becoming a key issue when evaluating a P2P system. Unfortunately, some systems' design focus targeted issues such as scalabil-ity or overall performance, but not security. As a result, security mechanisms must be provided at a later stage, after the system has already been designed and partially (or even fully) implemented, which may prove a cumbersome proposition. This work exposes how a security layer was provided under such circumstances for a specic Java based P2P framework: JXTA-Overlay.

Identifying first graders at risk of reading and writing difficulties : creating a group-based screening tool in kiswahili in Tanzania

Early identification of beginning readers at risk of developing reading and writing difficulties plays an important role in the prevention and provision of appropriate intervention. In Tanzania, as in other countries, there are children in schools who are at risk of developing reading and writing difficulties. Many of these children complete school without being identified and without proper and relevant support. The main language in Tanzania is Kiswahili, a transparent language. Contextually relevant, reliable and valid instruments of identification are needed in Tanzanian schools. This study aimed at the construction and validation of a group-based screening instrument in the Kiswahili language for identifying beginning readers at risk of reading and writing difficulties. In studying the function of the test there was special interest in analyzing the explanatory power of certain contextual factors related to the home and school. Halfway through grade one, 337 children from four purposively selected primary schools in Morogoro municipality were screened with a group test consisting of 7 subscales measuring phonological awareness, word and letter knowledge and spelling. A questionnaire about background factors and the home and school environments related to literacy was also used. The schools were chosen based on performance status (i.e. high, good, average and low performing schools) in order to include variation. For validation, 64 children were chosen from the original sample to take an individual test measuring nonsense word reading, word reading, actual text reading, one-minute reading and writing. School marks from grade one and a follow-up test half way through grade two were also used for validation. The correlations between the results from the group test and the three measures used for validation were very high (.83-.95). Content validity of the group test was established by using items drawn from authorized text books for reading in grade one. Construct validity was analyzed through item analysis and principal component analysis. The difficulty level of most items in both the group test and the follow-up test was good. The items also discriminated well. Principal component analysis revealed one powerful latent dimension (initial literacy factor), accounting for 93% of the variance. This implies that it could be possible to use any set of the subtests of the group test for screening and prediction. The K-Means cluster analysis revealed four clusters: at-risk children, strugglers, readers and good readers. The main concern in this study was with the groups of at-risk children (24%) and strugglers (22%), who need the most assistance. The predictive validity of the group test was analyzed by correlating the measures from the two school years and by cross tabulating grade one and grade two clusters. All the correlations were positive and very high, and 94% of the at-risk children in grade two were already identified in the group test in grade one. The explanatory power of some of the home and school factors was very strong. The number of books at home accounted for 38% of the variance in reading and writing ability measured by the group test. Parents´ reading ability and the support children received at home for schoolwork were also influential factors. Among the studied school factors school attendance had the strongest explanatory power, accounting for 21% of the variance in reading and writing ability. Having been in nursery school was also of importance. Based on the findings in the study a short version of the group test was created. It is suggested for use in the screening processes in grade one aiming at identifying children at risk of reading and writing difficulties in the Tanzanian context. Suggestions for further research as well as for actions for improving the literacy skills of Tanzanian children are presented.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

A longitudinal study of one cochlear implant recipient from baseline to twelve months, following a group-based rehabilitation program

This paper provides an in-depth examination of the experiences of one cochlear implant recipient who participated in a psychosocial group rehabilitation program that was aimed at overcoming the communication and psychosocial handicaps that may accompany hearing loss.

The effects of group-based psychosocial therapy on conversational fluency and communication handicap

This paper studies whether a combination of group rehabilitation in conjunction with psychosocial therapy enhances conversational fluency and diminishes communication handicap in cochlear implant recipients.