Predicting long-term growth in students' mathematics achievement: the unique contributions of motivation and cognitive strategies

This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies.

Relationship between Comprehensive School Readiness Profiles and Longer-Term Academic Growth

Thesis (Master's)--University of Washington, 2016-06

Therapist-assisted Internet-delivered cognitive behavior therapy for depression and anxiety: translating evidence into clinical practice.

This dissemination study examined the effectiveness of therapist-assisted Internet-delivered Cognitive Behavior Therapy (ICBT) when offered in clinical practice. A centralized unit screened and coordinated ICBT delivered by newly trained therapists working in six geographically dispersed clinical settings. Using an open trial design, 221 patients were offered 12 modules of ICBT for symptoms of generalized anxiety (n=112), depression (n=83), or panic (n=26). At baseline, midpoint and post-treatment, patients completed self-report measures. On average, patients completed 8 of 12 modules. Latent growth curve modeling identified significant reductions in depression, anxiety, stress and impairment (d=.65-.78), and improvements in quality of life (d=.48-.66). Improvements in primary symptoms were large (d=.91-1.25). Overall, therapist-assisted ICBT was effective when coordinated across settings in clinical practice, but further attention should be given to strategies to improve completion of treatment modules.

Investigating group processes in a positive youth development program for multi -problem youth

This study investigated group processes as potential mediators or moderators of positive development outcome and negative reduction intervention response by evaluating the utility of a group measure modified from a widely known measure of group impact found in the group therapy research literature. Four group processes were of primary interest, (1) Group Impact; (2) Facilitator Impact; (3) Skills Impact; and (4) Exploration Impact as assessed by the Session Evaluation Form (SEF). Outcome measures included the Personally Expressive Activities Questionnaire (PEAQ), Erikson Psycho-Social Index (EPSI) and the Zill Behavior Items, Behavior Problem Index (ZBI (BPI)). The sample consisted of 121 multi-ethnic participants drawn from four alternative high schools from the Miami-Dade County Public School system. Utilizing a Latent Growth Curve Modeling approach with Structural Equation Modeling (SEM) statistics, preliminary analyses were conducted to evaluate the psychometric properties of the SEF and its role in the mediation or moderation of intervention outcome. Preliminary results revealed evidence of a single higher order factor representing a "General" global reaction, which was hypothesized to be a "Positive Group Climate" construct to the program as opposed to the four distinct group processes that were initially hypothesized to affect outcomes. The results of the evaluation of the mediation or moderation role of intervention outcome of the single "General" global latent factor ("Positive Group Climate" construct) did not significantly predict treatment response on any of the outcome variables. Nevertheless, the evidence of an underlying "General" global latent factor ("Positive Group Climate" construct) has important future directions for research on positive youth development programs as well as in group therapy research.

Changes in doctors' working hours: a longitudinal analysis

The study examined changes in doctors’ working hours and satisfaction with working hours over five time points and explored the influence of personal characteristics on these outcomes. Latent growth curve modeling was applied to Medicine in Australia: Balancing Employment and Life data, collected from 2008 to 2012. Findings showed that working hours significantly declined over time, with a greater decrease among males, older doctors, and doctors with fewer children. Satisfaction increased faster over time among specialists, doctors with poorer health, those whose partners did not work full-time, and those with older children. The more hours the doctors worked initially, the lower satisfaction reported, and the greater the increase in satisfaction. Findings are consistent with a culture change in the medical profession, whereby long working hours are no longer seen as synonymous with professionalism. This is important to take into account in projecting future workforce supply.

Modeling of average growth curve in Santa Ines sheep using random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Body mass index trajectories and predictors among 3rd to 12th graders using growth curve mixture modeling the Child and Adolescent Trial for Cardiovascular Health (CATCH) study

This dissertation examined body mass index (BMI) growth trajectories and the effects of gender, ethnicity, dietary intake, and physical activity (PA) on BMI growth trajectories among 3rd to 12th graders (9-18 years of age). Growth curve model analysis was performed using data from The Child and Adolescent Trial for Cardiovascular Health (CATCH) study. The study population included 2909 students who were followed up from grades 3-12. The main outcome was BMI at grades 3, 4, 5, 8, and 12. ^ The results revealed that BMI growth differed across two distinct developmental periods of childhood and adolescence. Rate of BMI growth was faster in middle childhood (9-11 years old or 3rd - 5th grades) than in adolescence (11-18 years old or 5th - 12th grades). Students with higher BMI at 3rd grade (baseline) had faster rates of BMI growth. Three groups of students with distinct BMI growth trajectories were identified: high, average, and low. ^ Black and Hispanic children were more likely to be in the groups with higher baseline BMI and faster rates of BMI growth over time. The effects of gender or ethnicity on BMI growth differed across the three groups. The effects of ethnicity on BMI growth were weakened as the children aged. The effects of gender on BMI growth were attenuated in the groups with a large proportion of black and Hispanic children, i.e., “high” or “average” BMI trajectory group. After controlling for gender, ethnicity, and age at baseline, in the “high BMI trajectory”, rate of yearly BMI growth in middle childhood increased 0.102 for every 500 Kcals increase (p=0.049). No significant effects of percentage of energy from total fat and saturated fat on BMI growth were found. Baseline BMI increased 0.041 for every 30 minutes increased in moderate-to-vigorous PA (MVPA) in the “low BMI trajectory”, while Baseline BMI decreased 0.345 for every 30 minutes increased in vigorous PA (VPA) in the “high BMI trajectory”. ^ Childhood overweight and obesity interventions should start at the earliest possible ages, prior to 3rd grade and continue through grade school. Interventions should focus on all children, but specifically black and Hispanic children, who are more likely to be highest at-risk. Promoting VPA earlier in childhood is important for preventing overweight and obesity among children and adolescents. Interventions should target total energy intake, rather than only percentage of energy from total fat or saturated fat. ^

Predicting random level and seasonality of hotel prices. A structural equation growth curve approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the Spanish continental Mediterranean coast are gathered from May to October 1999 from the tour operator catalogues. Hedonic functions are specified as random-effect models and parametrized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. Characteristics of the hotel and the region where they are located are used as predictors of both latent variables. Besides hotel category, region, distance to the beach, availability of parking place and room equipment have an effect on peak price and also on seasonality. 3- star hotels have the highest seasonality and hotels located in the southern regions the lowest, which could be explained by a warmer climate in autumn

Estimation of the growth curve parameters in Macrobrachium rosenbergii

Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideration

The von Bertalanffy growth curve: when a good fit is not good enough

The von Bertalanffy growth function is used for length based analysis of growth and mortality patterns for management of fisheries. However, certain fish have growth patterns that the VBGF may not be able to describe adequately.e.g. the Acanthurus lineatus in Samoa. In such cases a two phase VBGF may be a useful approach.

A note on application of hills procedure for growth-curve analysis of Indian major carp, Labeo rohita (Ham.), during the gonodal development period at Shillong, Meghalaya

The present study deals with the length increment data of 15 adult Labeo rohita (Ham.) over a period of five months by the applicatin of finite difference method at an altitude of 1496 m above mean sea level at Shilllong, Meghalaya.