Curve Modeling Approach Research Articles

A longitudinal study of enjoyment and group-level emotion regulation in online collaborative English language learning

This study investigates the dynamic connection between two emotional constructs, enjoyment and group-level emotion regulation (co- and socially-shared regulation), during one 21-week semester of online collaborative English language learning. The study involved 268 Chinese undergraduate English-major students who completed a series of English writing tasks in 88 online groups of three or four members. During their online collaboration, participants were invited to complete the enjoyment scale and the emotion regulation scale at three separate times at seven-week intervals. When analyzing the data, a latent growth curve (LGC) modeling approach was employed to examine the intercepts and slopes of participants’ scaled responses to questions regarding enjoyment, co-regulation, and socially-shared regulation and to analyze the covariance between them. The findings reveal that participants’ levels of enjoyment and group-level emotion regulation were generally high at the initial stage of their online collaboration and continued to increase toward the end of the semester. Furthermore, an increase in the level of their enjoyment was significantly and positively associated with an increase in the levels of both their co- and socially-shared regulation, with the relationship with socially-shared regulation during online collaborative learning being stronger. These findings will enable language teachers to develop strategies for supporting language learners’ emotion regulation in online contexts.

Autonomous single language interest predicts vocabulary achievement: the latent growth curve model approach

Autonomous single language interest predicts vocabulary achievement: the latent growth curve model approach

Language anxiety does not affect the growth of L2 reading achievement: The latent growth curve model approach

AbstractSecond language (L2) anxiety has been proposed to play a causal role in L2 achievement. However, most studies have failed to acknowledge confounding variables that may be relevant to the study of anxiety and L2 achievement or to investigate the causal effect of L2 anxiety using longitudinal data. For these reasons, we investigated the effect of L1 reading achievement, L2 aptitude, and L2 anxiety as covariates on the growth of L2 reading achievement across three time points. We used the latent growth curve model (LGCM) to estimate the growth trajectory of US secondary school students’ L2 reading growth in Spanish (N = 307) over three school years. The findings showed that students’ L1 reading achievement and L2 aptitude strongly and significantly predicted L2 reading achievement growth. However, L2 anxiety did not predict L2 reading achievement growth. Findings suggest that growth in L2 reading achievement depends on the language-related skills used for L1 reading and the language skills that comprise L2 aptitude, but not on anxiety. Similar to past cross-sectional studies, L2 anxiety related only to initial levels of L2 reading achievement, suggesting that anxiety reflects students’ initial experience of L2 reading but not their L2 achievement.

Foreign direct investment, sectoral distribution and income inequality in developed and developing economies

Despite some progress in reducing income inequality between countries over the last two decades, there is evidence that income inequality is on the rise within nations. This article uses panel data compiled from multiple sources and a growth curve modeling approach to examine the relationship between foreign direct investment (FDI) and within-nation income inequality across two samples: one comprising 2,095 country-year observations nested in 141 countries from 1991 to 2018 to explore the broader FDI-income inequality relationship, and a second, more focused sample of 405 country-year observations nested in 61 countries from 2000 to 2018, designed to analyze effects of the sectoral distribution of FDI. The analyses find that the relationship between FDI and income inequality is positive and linear for non-OECD economies but follows an inverted U-shaped path for developed countries. Moreover, in this article, I have developed and introduced two new indices, the FDI Pluralism Index and FDI Sectoral Gini Coefficient, to measure the distribution of FDI among the sectors of the host economy. Results show that a concentration of FDI in one sector aggravates income inequality since foreign capital tends to flow into the most profitable industries, creating uneven growth between sectors and increasing between-sector income inequality.

An investigation of cardiac vagal tone over time and its relation to vigilance performance: a growth curve modeling approach.

Research over the last couple of decades has demonstrated a relationship between psychophysiological measures, specifically cardiac functions, and cognitive performance. Regulation of the cardiac system under parasympathetic control is commonly referred to as cardiac vagal tone and is associated with the regulation of cognitive and socioemotional states. The goal of the current study was to capture the dynamic relationship between cardiac vagal tone and performance in a vigilance task. We implemented a longitudinal growth curve modeling approach which unveiled a relationship between cardiac vagal tone and vigilance that was non-monotonic and dependent upon each person. The findings suggest that cardiac vagal tone may be a process-based physiological measure that further explains how the vigilance decrement manifests over time and differs across individuals. This contributes to our understanding of vigilance by modeling individual differences in cardiac vagal tone changes that occur over the course of the vigilance task.

Effects of a brief self-compassion intervention for college students with impostor phenomenon.

The present study used a latent growth curve modeling approach to (a) examine the effectiveness of a brief self-compassion intervention on reducing impostor phenomenon, maladaptive perfectionism, and psychological distress and (b) explore who would benefit more from this intervention. A total of 227 college students at a large Midwest university were randomly assigned to participate in either a 4-week brief self-compassion intervention group or a nonintervention control group. Analyses of the effectiveness of the intervention suggested the brief self-compassion intervention had significant treatment effects for reducing impostor phenomenon and maladaptive perfectionism. Moreover, this study also examined whether participants with different levels of fear of self-compassion and core self-evaluation would report different levels of treatment effectiveness. Fear of self-compassion was found to be a significant moderator of the intervention effects in reducing maladaptive perfectionism and psychological distress. Specifically, participants in the intervention group with higher levels of fear of self-compassion reported a greater decline in both maladaptive perfectionism and psychological distress over time when compared to those with lower levels of fear of self-compassion. Core self-evaluation significantly moderated the effectiveness of this intervention in reducing participants' levels of impostor phenomenon and maladaptive perfectionism. Specifically, participants in the intervention group with lower core self-evaluation reported a greater reduction in maladaptive perfectionism over time when compared to those with higher core self-evaluation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The thriving kids and parents schools project: protocol of an incomplete stepped wedged cluster randomised trial evaluating the effectiveness of a Triple P seminar series

BackgroundThe COVID-19 pandemic disrupted the normality of daily life for many children, their families, and schools, resulting in heightened levels of anxiety, depression, social isolation, and loneliness among young people. An integrated public health model of interventions is needed to address the problem and to safeguard the mental health and wellbeing of children. The Triple P – Positive Parenting Program is one system of parenting support with a strong evidence-base and wide international reach. When implemented as a public health approach, Triple P has demonstrated population level positive effects on child wellbeing. This study will be the first large-scale, multi-site randomised controlled trial of a newly developed, low-intensity variant of Triple P, a school-based seminar series, as a response to the impacts of the pandemic.MethodsThe evaluation will employ an Incomplete Batched Stepped Wedge Cluster Randomised Trial Design. At least 300 Australian primary schools, from South Australia, Queensland, and Victoria will be recruited and randomised in three batches. Within each batch, schools will be randomly assigned to either start the intervention immediately or start in six weeks. Parents will be recruited from participating schools. The Triple P seminar series includes three seminars titled: “The Power of Positive Parenting”, “Helping Your Child to Manage Anxiety”, and “Keeping your Child Safe from Bullying”. Parents will complete measures about child wellbeing, parenting, parenting self-regulation and other key intervention targets at baseline, six weeks after baseline, and 12 weeks after baseline. Intervention effectiveness will be evaluated with a Multilevel Piecewise Latent Growth Curve Modelling approach. Data collection is currently underway, and the current phase of the project is anticipated to be completed in January 2024.DiscussionThe findings from this study will extend the current knowledge of the effects of evidence-based parenting support delivered through brief, universally offered, low intensity, school-based parenting seminars in a post pandemic world.Trial registrationThe trial is registered at the Australian New Zealand Clinical Trials Registry (Trial Registration Number: ACTRN12623000852651).

Rural-Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45.

Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural-urban disparities in multimorbidity. Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011-2018), linked with the full-coverage particulate matter 2.5 (PM2.5) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM2.5 concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural-urban disparities in multimorbidity related to temperature and PM2.5 exposure. We found the higher PM2.5 concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural-urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM2.5-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM2.5 exposure, but PM2.5 exposure or temperature is not associated with the rate of multimorbidity increase with age. Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural-urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals.

Genomewide analysis of Episodic Memory trajectories in The Mexican Health and Aging Study (MHAS)

AbstractBackgroundGenetic characterization of age‐related memory changes can help identify population subgroups at‐risk of memory decline and dementia. The majority of genetic studies examining memory trajectories in old age have used data from non‐Hispanic White populations. To our knowledge, there are no reports of genetic factors underlying memory function over time in the Mexican population.MethodUsing a previously described latent curve model approach, we estimated episodic memory trajectories in a longitudinal sample from the Mexican Health and Aging Study. We conducted GWAS analyses in a sub‐sample of 6,343 participants. Analyses were stratified by memory stability (Stables, n = 4,437) and APOE status. Three independent cohorts were used for replication purposes: two Non‐Hispanic White samples from the Alzheimer’s Disease Genetic Consortium and the Religious Orders Study, and a Caribbean‐Hispanic sample from the Washington Heights Inwood Community Aging Project.ResultThe strongest genome‐wide significant association was found for an intronic variant in the NR2F1‐AS1 gene (rs555528825, p = 1.8×10−9) among APOE non‐E4 carriers in the “Stables” group. NR2F1 gene is an evolutionarily conserved long non‐coding RNA that enhances neuronal cell maturation and regulates transcription of neuronal genes. SNP variants located less than 50Kb apart from the identified signal showed also nominally significant associations in the three replication datasets (p = 3.9×10−4, p = 1.8×10−4, and p = 0.006 respectively). Additional replication efforts using the UK biobank recourse are ongoing.ConclusionOur study nominates novel genetic variants associated with longitudinal changes in episodic memory performance using data from the Mexican Health and Aging Study, a representative and comprehensive longitudinal study that includes genetic data on a sub‐sample of participants 50 years and older.

Measuring the rate of psychological growth and examining its antecedents: A growth curve modeling approach.

Humanistic psychologists have conceptualized a tendency among humans to experience continual open-ended psychological growth. This study aims to measure the rate at which one grows psychologically using a novel growth curve modeling approach that addresses previous limitations. We also examine the effects of nine potential contributors to growth identified from the literature. Throughout the freshman year, 556 college students responded six times. Increments of growth were added up to create cumulative growth, which was then fit to a growth curve model to produce an estimate of the growth rate. The growth rate was then regressed on the Time 1 predictors to examine their unique effects. Models fit well. Five predictors significantly predicted the growth rate after controlling for the average of other predictors. When all predictors were entered simultaneously, three predictors (hope, meaning, and personal growth initiative) showed significant unique effects. The growth rate predicted well-being and satisfaction at Time 6. We successfully measured the rate of psychological growth and examined its antecedents. Follow-up analyses suggested that the predictors not showing unique effects may indirectly predict growth rates via the proximal role of the three significant predictors, an idea that awaits future corroboration using within-individual designs.

Long-term psychological distress trajectories and the COVID-19 pandemic in three British birth cohorts: A multi-cohort study.

Growing evidence suggests that population mental health outcomes have worsened since the pandemic started. The extent that these changes have altered common age-related trends in psychological distress, where distress typically rises until midlife and then falls after midlife in both sexes, is unknown. We aimed to analyse whether long-term pre-pandemic psychological distress trajectories were disrupted during the pandemic, and whether these changes have been different across cohorts and by sex. We used data from three nationally representative birth cohorts comprising all people born in Great Britain in a single week of 1946 (National Survey of Health and Development, NSHD), 1958 (National Child Development Study, NCDS), or 1970 (British Cohort Study, BCS70). The follow-up data used spanned 39 years in NSHD (1982 to 2021), 40 years in NCDS (1981 to 2001), and 25 years in BCS70 (1996 to 2021). We used psychological distress factor scores, as measured by validated self-reported questionnaires (NSHD: Present State Examination, Psychiatric Symptoms Frequency, and 28- and 12-item versions of General Health Questionnaire; NCDS and BCS70: Malaise Inventory; all: 2-item versions of Generalized Anxiety Disorder scale and Patient Health Questionnaire). We used a multilevel growth curve modelling approach to model the trajectories of distress across cohorts and sexes and obtained estimates of the differences between the distress levels observed during the pandemic and those observed at the most recent pre-pandemic assessment and at the peak in the cohort-specific pre-pandemic distress trajectory, located at midlife. We further analysed whether pre-existing cohort and sex inequalities had changed with the pandemic onset using a difference-in-differences (DiD) approach. The analytic sample included 16,389 participants. By September/October 2020, distress levels had reached or exceeded the levels of the peak in the pre-pandemic life-course trajectories, with larger increases in younger cohorts (standardised mean differences [SMD] and 95% confidence intervals of SMDNSHD,pre-peak = -0.02 [-0.07, 0.04], SMDNCDS,pre-peak = 0.05 [0.02, 0.07], and SMDBCS70,pre-peak = 0.09 [0.07, 0.12] for the 1946, 1958, and 1970 birth cohorts, respectively). Increases in distress were larger among women than men, widening pre-existing sex inequalities (DiD and 95% confidence intervals of DiDNSHD,sex,pre-peak = 0.17 [0.06, 0.28], DiDNCDS,sex,pre-peak = 0.11 [0.07, 0.16], and DiDBCS70,sex,pre-peak = 0.11 [0.05, 0.16] when comparing sex inequalities in the pre-pandemic peak in midlife to those observed by September/October 2020). As expected in cohort designs, our study suffered from high proportions of attrition with respect to the original samples. Although we used non-response weights to restore sample representativeness to the target populations (those born in the United Kingdom in 1946, 1958, and 1970, alive and residing in the UK), results may not be generalisable to other sections within the UK population (e.g., migrants and ethnic minority groups) and countries different than the UK. Pre-existing long-term psychological distress trajectories of adults born between 1946 and 1970 were disrupted during the COVID-19 pandemic, particularly among women, who reached the highest levels ever recorded in up to 40 years of follow-up data. This may impact future trends of morbidity, disability, and mortality due to common mental health problems.

Probabilistic power curve estimation based on meteorological factors and density LSTM

Wind power curve describes the relationship between wind speed and wind power output, which is useful for wind farm design and wind turbine condition monitoring. However, most research on power curves modeling neglected the effect of historical meteorological factors. Also, the research on probabilistic power curve is still limited. Therefore, this paper proposes a novel probabilistic power curve modeling approach. The effect of both current and historical meteorological variables, such as wind speed, wind direction, ambient temperature and turbulence intensity, on the power curve is studied by binning method and kernel density estimation. Next, instead of forecasting the wind power or its quantiles, a new probabilistic power curve model, Density LSTM with Negative Log-Likelihood Loss, is proposed to forecast the parameters of the probability density function of wind power directly. Finally, different probability distribution of wind power output is studied. Gamma, Laplace and Weibull distributions prove to be more suitable than Gaussian distribution. Based on the datasets of inland and offshore wind farms, it is verified that adding useful historical meteorological variables can improve the forecasting performance of the test dataset. Besides, the proposed probabilistic power curve can effectively improve the prediction performance in the probabilistic prediction task and can improve the prediction precision of the annual energy production.

How does residential solar PV system diffusion occur in Australia?-A logistic growth curve modelling approach

Australia is facing the twin problems of energy depletion and environmental pollution. This crisis can be alleviated by effective promotion of solar photovoltaic (PV) system installation. The question is: how does solar PV system diffusion occur in various regions in Australia? This study introduces an innovative five-parameter logistic (5PL) curve to analyse the diffusion of solar PV technology in all postcode areas of Australia. Furthermore, it combines principal component analysis (PCA) and cluster analysis to identify the major area types that have similar diffusion characteristics. The study identifies three main diffusion pathways and their corresponding distribution areas in Australia. The results provide a visual representation of the historical diffusion of residential PV systems in Australia. From a technology diffusion perspective, the results also show how residential solar panel diffusion occurs differently in areas at the postcode level. These findings provide insights on how to reduce regional disparities in solar panel adoption, thus facilitating renewable energy equity and justice.

Quantifying Emotional Flow: Testing the Emotional Flow Hypothesis from a Longitudinal Latent Growth Curve (LGC) Modeling Approach

ABSTRACT This paper presents a longitudinal, latent growth curve (LGC) modeling approach to refine the emotional flow measure and hypothesis testing. Emotional flow is operationalized as the marked within-individuals variations in one or more discrete emotions over time, which can be modeled as the amount and shape of change in emotions during message exposure. Emotional flow effects are tested in the LGC framework using data collected from a web-based experimental study where individuals (US Qualtrics Panel, N = 620) read an anti-sugary sweetened beverage message in the standard threat appeal format. Simultaneous fear and hope flows were established with unconditional LGC modeling. The two flows and their interaction were then used to predict message effects outcomes. Results showed that flow effects were nonsignificant when either the fear flow or the hope flow was relatively flat in form, but robust when both emotional flows were with marked variations over the course of message exposure.

Confidence in the therapist and confidence in the treatment predict symptomatic improvement week by week in therapy: A latent curve modeling approach.

Previous research suggests that common relationship factors are composed of two overarching factors, "Confidence in the therapist" and "Confidence in the treatment." The aim of this naturalistic process-outcome study was to investigate the reciprocal relationships between these two constructs and patients' symptom level across treatment. The sample consisted of 587 patients who were admitted to an inpatient program and treated with psychotherapy for a range of mental health disorders, such as chronic depression, anxiety disorders, and eating disorders. Our data consisted of weekly measures of symptomatic distress (Patient Health Questionnaire) and the common relationship factors were measured weekly using a newly developed scale. Latent curve modeling with structured residuals was used to investigate the between- and within effects of week-to-week changes in the two components as predictors of subsequent symptom level. An increase in both relationship factors predicted a decrease in subsequent levels of symptoms at the within-patient level, and the other way around, but the two relationship factors did not systematically relate to one another at the within-patient level over the course of treatment. Our findings indicate that patients' perceptions of the therapist as a person and their appraisal of the treatment, are important, different predictors of therapeutic change. Furthermore, they support prior research demonstrating a reciprocal relationship between common relationship factors and symptomatic distress and add to existing common factor theory by exploring the role of two central relationship dimensions and using a method which examines reciprocal relationships and within-patient effects simultaneously. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Subjective cognitive decline predicts lower cingulo-opercular network functional connectivity in individuals with lower neurite density in the forceps minor

Cognitive complaints of attention/concentration problems are highly frequent in older adults with subjective cognitive decline (SCD). Functional connectivity in the cingulo-opercular network (CON-FC) supports cognitive control, tonic alertness, and visual processing speed. Thus, those complaints in SCD may reflect a decrease in CON-FC. Frontal white-matter tracts such as the forceps minor exhibit age- and SCD-related alterations and, therefore, might influence the CON-FC decrease in SCD. Here, we aimed to determine whether SCD predicts an impairment in CON-FC and whether neurite density in the forceps minor modulates that effect. To do so, we integrated cross-sectional and longitudinal analyses of multimodal data in a latent growth curve modeling approach. Sixty-nine healthy older adults (13 males; 68.33 ± 7.95 years old) underwent resting-state functional and diffusion-weighted magnetic resonance imaging, and the degree of SCD was assessed at baseline with the memory functioning questionnaire (greater score indicating more SCD). Forty-nine of the participants were further enrolled in two follow-ups, each about 18 months apart. Baseline SCD did not predict CON-FC after three years or its rate of change (p-values > 0.092). Notably, however, the forceps minor neurite density did modulate the relation between SCD and CON-FC (intercept; b = 0.21, 95% confidence interval, CI, [0.03, 0.39], p = 0.021), so that SCD predicted a greater CON-FC decrease in older adults with relatively lower neurite density in the forceps minor. The neurite density of the forceps minor, in turn, negatively correlated with age. These results suggest that CON-FC alterations in SCD are dependent upon the forceps minor neurite density. Accordingly, these results imply modifiable age-related factors that could help delay or mitigate both age and SCD-related effects on brain connectivity.

Narcissists going above and beyond? The role of perceived negative inequity and self-enhancement motivation

PurposeUtilizing a self-regulatory perspective, the authors examine how narcissism influences perceived negative inequity and the downstream effects on self-enhancement motivation and organizational citizenship behaviors (OCBs) over time.Design/methodology/approachA total of 689 useable three-wave panel data were obtained via Amazon Mechanical Turk during a three-month period. A latent growth curve modeling approach using EQS 6.4 for Windows was employed to test the hypothesized model.FindingsResults illustrate that individuals with higher levels of narcissism perceive higher levels of perceived negative inequity and then form higher levels of self-enhancement motivation, which prompt more OCB directed toward the organization (OCBO) than OCB directed toward individuals (OCBI). When perceived negative inequity increases over time, narcissists experience a faster increase in self-enhancement motivation, which also leads to a faster increase in OCBO compared to the increase in OCBI.Originality/valueTheoretically, this study provides theoretical and empirical insights into understanding the process through which narcissists' OCBs are motivated. Practically, this study offers several practical recommendations that help managers manage OCBs effectively in the organization.

Disentangling the Influence of Data Contamination in Growth Curve Modeling: A Median Based Bayesian Approach

Growth curve models (GCMs), with their ability to directly investigate within-subject change over time and between-subject differences in change for longitudinal data, are widely used in social and behavioral sciences. While GCMs are typically studied with the normal distribution assumption, empirical data often violate the normality assumption in applications. Failure to account for the deviation from normality in data distribution may lead to unreliable model estimation and misleading statistical inferences. A robust GCM based on conditional medians was recently proposed and outperformed traditional growth curve modeling when outliers are present resulting in nonnormality. However, this robust approach was shown to perform less satisfactorily when leverage observations existed. In this work, we propose a robust double medians growth curve modeling approach (DOME GCM) to thoroughly disentangle the influence of data contamination on model estimation and inferences, where two conditional medians are employed for the distributions of the within-subject measurement errors and of random effects, respectively. Model estimation and inferences are conducted in the Bayesian framework, and Laplace distributions are used to convert the optimization problem of median estimation into a problem of obtaining the maximum likelihood estimator for a transformed model. A Monte Carlo simulation study has been conducted to evaluate the numerical performance of the proposed approach, and showed that the proposed approach yields more accurate and efficient parameter estimates when data contain outliers or leverage observations. The application of the developed robust approach is illustrated using a real dataset from the Virginia Cognitive Aging Project to study the change of memory ability.

A quadratic trigonometric B-Spline as an alternate to cubic B-spline

The idea of the quadratic trigonometric spline (QTS) for the curve modeling approach inspired this paper using a quadratic trigonometric function presented in it. By creating B-spline-like local support basis functions, a competent freeform curve design approach is created. Local support, unity partition, and positivity are satisfied by the built-in basis functions. These generated local support basis functions give the freeform designed curve technique geometric features like convex hull and variation diminishing. The shape features of point tension, interval tension, and global tension are also observed by employing data point repetitions in a freeform curve scheme. A converted Bernstein Bézier form is used to display the non-uniform freeform curve for consideration in the proposed approach. The recommended method is C2 as a benefit. The proposed method is an addition to the existing family of spline procedures, and it gives a superior quadratic equivalent to the cubic method.

Longitudinal changes in Chinese minority college students’ health-related fitness: A multilevel latent growth curve modeling approach

Purpose: The study aimed to test the overall changes of health-related fitness (HRF) in minority Chinese college students and to examine HRF differences in gender, race, and year in college. Method: Participants (n = 1320) were minority college students with more than two-thirds females (ie 76.1%), and Hui, Tibetan, and Mongolia consisted of 13.8%, 13.8%, and 11.2%, respectively. Student HRF was tracked for four years. Data were analyzed using multilevel latent growth curve modeling. Results: Muscular strength and endurance were the weakest component in minority college students’ HRF, while body mass index was within the category of “excellent”. Males outperformed female on all components of HRF. Conclusions: It is suggested that interventions concerning minority females’ HRF and muscular strength and endurance for both genders be constructed and tested.