scholarly journals Impact of Puberty and Age on Adolescent Inhibition Over Time

2019 ◽  
Vol 34 (6) ◽  
pp. 840-840
Author(s):  
J Harrison ◽  
M Wong ◽  
S McManimen
Keyword(s):  
Structural Equation Modeling ◽  
Reaction Time ◽  
Structural Equation ◽  
Early Adolescent ◽  
Equation Modeling ◽  
Chronological Age ◽  
P 75 ◽  
Stop Signal Reaction Time ◽  
Over Time ◽  
Time Point

Abstract Objective We measured how puberty impacted inhibition over three years. We hypothesized that age and puberty development would predict inhibition at each time point. Results revealed differential effects of puberty and age over time. Method Participants from Southern Idaho were 245 adolescents at Time 1 (T1) (M = 10.4, SD = 1.5, 50% female, 64% Caucasian), 196 adolescents at Time 2 (T2) (M = 11.8, SD = 1.5, 50% female, 81% Caucasian), and 87 adolescents at Time 3 (T3) (M = 13, SD = 1.5, 56% female, 82% Caucasian). Participants completed a physical exam with a registered nurse, which included the Tanner Scale (Apter & Hermanson, 2002; Tinggaard et. al., 2012) and the Puberty Development Scale (Petersen et al., 1988). Inhibition was assessed using stop-signal reaction time (SSRT) within the Stop-it Task (Logan, Cowan, & Davis, 1984). Results Using structural equation modeling, for T1, the overall model demonstrated a good fit, χ2(3) = 1.23, p = .75, RMSEA = .00, CFI = 1.00, TLI = 1.04. Puberty significantly predicted inhibition (β = -.21, p < .05), i.e., higher puberty scores predicted stronger inhibition. However, age was not a significant predictor. At T2, the model demonstrated a good fit, χ2(7) = 7.77, p = .35, RMSEA = .03, CFI = 1.00, TLI = .99. Age significantly predicted inhibition (β=-.39, p < .001). However, puberty was not a significant predictor. In T3, neither age nor puberty predicted inhibition. Conclusions Our results indicate that early adolescent increases in inhibition may be due to puberty development rather than age. As one ages, puberty has less effect, and chronological age becomes more significant. Finally, in mid-adolescence, neither age nor puberty significantly affects inhibition. These findings highlight the changing effects of age and puberty on inhibitory control across adolescence.

scholarly journals Predicting Changes in PM Exposure Over Time at U.S. Trucking Terminals Using Structural Equation Modeling Techniques

2009 ◽  
Vol 6 (7) ◽  
pp. 396-403 ◽  
Author(s):  
Mary E. Davis ◽  
Francine Laden ◽  
Jaime E. Hart ◽  
Eric Garshick ◽  
Andrew Blicharz ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Modeling Techniques ◽  
Over Time

Fathers’ Time Off Work, Co-Residence, and Paternal Engagement among Socioeconomically Disadvantaged Fathers

2020 ◽  
pp. 0192513X2092151
Author(s):  
Brianne Pragg
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Fragile Families ◽  
Socioeconomically Disadvantaged ◽  
Biological Mothers ◽  
Mediating Factor ◽  
Paternal Engagement ◽  
Child Engagement ◽  
Over Time

Research consistently finds that fathers who take time off work when their children are born exhibit higher levels of paternal engagement relative to fathers who do not take time off work. This study aims to identify one possible mediating factor: fathers’ co-residence with their children and their children’s biological mothers over time. The current study uses data from the Fragile Families and Wellbeing Study and structural equation modeling (SEM) to examine the relationships between fathers’ time off work when their children were born, residence with their children and their children’s biological mothers, and levels of father-child engagement ( n = 2,453). Results indicated that the number of weeks taken off work was positively associated with men’s subsequent residence with their children and children’s mothers when their children were five-years-old, which in turn was positively associated with paternal engagement.

The Impacts of Brand Equity, Security, and Personalization on Trust Processes in an E-Commerce Environment

2011 ◽  
pp. 1-41
Author(s):  
Catharina Stoecklin-Serino ◽  
David Paradice ◽  
Robert Hooker
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Brand Names ◽  
Equation Modeling ◽  
Incremental Development ◽  
Lasting Effect ◽  
Electronic Environments ◽  
Trusting Beliefs ◽  
Conceptual Work ◽  
Over Time

This research broadens the study of trust as it applies to developing stable relationships in electronic environments. Prior studies have investigated many aspects of trust, but few have looked at its incremental development. Previous empirical research identifies antecedents to initial perceptions of trust that may influence the progression of trust to deeper levels. More conceptual work identifies antecedents that swiftly cultivate trust, allowing for stable relationships to develop more quickly. The antecedents investigated in this study, using regression and structural equation modeling, are the use of security symbols, trustworthy brand names, and personalization techniques. The results of the study indicate that the use of security symbols and trustworthy brand names have a positive and lasting effect on trusting beliefs and that personalization has a decreasing and lasting effect on trusting beliefs. There was no support for the hypothesis that trust develops over time in electronic environments.

scholarly journals Information Technology and Market Orientation on the Competitiveness and Performance of a Kuningan's Tourism Activity

2020 ◽  
Vol 7 (2) ◽  
pp. 105
Author(s):  
Wely Hadi Gunawan ◽  
Wachyuni Wachyuni
Keyword(s):  
Information Technology ◽  
Structural Equation Modeling ◽  
Market Orientation ◽  
Structural Equation ◽  
Business Performance ◽  
Equation Modeling ◽  
Tourist Attractions ◽  
Tourism Activity ◽  
And Performance ◽  
Over Time

Kuningan local tourism possesses a promising future. However, some investigations cite a decrease in visitors over time, revealing underlying problems in the organization. Critical inquiries may arise from the interaction of information technology and market orientation to increase competitiveness and, finally, tourist attractions' performance. Thus, this study investigates the local tourism activity of Panembongan Hill in Kuningan, Banten, Indonesia. One hundred thirty visitors agree to participate in the study, and the coded responses are analyzed using structural equation modeling. The results reveal that Information Technology does not relate to competitiveness and tourism business performance; market orientation increases competitiveness and business performance. Finally, the competitiveness of tourism activities propels business performance considerably.

scholarly journals Worry and metacognitions as predictors of the development of anxiety and paranoia

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Xiaoqi Sun ◽  
Suzanne H. So ◽  
Raymond C. K. Chan ◽  
Chui-De Chiu ◽  
Patrick W. L. Leung
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Clinical Implications ◽  
Generalized Anxiety ◽  
Time Period ◽  
One Year ◽  
Development Of Anxiety ◽  
Over Time

Abstract Recent studies have shown that worry and related negative metacognitions are characteristic in generalized anxiety and paranoia respectively. However, most of these studies did not take into account common co-occurrence of anxiety and paranoia, and longitudinal modelling of the role of worry and metacognitions on the development of anxiety and paranoia is rare. The current study aimed at examining the bidirectional longitudinal relationship between anxiety and paranoia, as well as the importance of worry and metacognitions in the development of these symptoms. Our validated sample consisted of 2291 participants recruited from universities, among whom 1746 participants (76.21%) completed online questionnaires at baseline and at one year, reporting levels of anxiety, paranoia, worry, and negative metacognitions. Structural equation modeling analyses, followed by path comparisons, revealed that anxiety and paranoia mutually reinforced each other over time. Negative metacognitions, rather than worry itself, were contributive to the development of both symptoms over time. Negative metacognitions showed bi-directional relationships with anxiety over the time period assessed and showed uni-directional relationships with paranoia. Clinical implications of our findings are discussed.

Long-term Persuasive Effects in Narrative Communication Research: A Meta-Analysis

2020 ◽  
Vol 70 (4) ◽  
pp. 473-496
Author(s):  
Corinna Oschatz ◽  
Caroline Marker
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Equation Modeling ◽  
Communication Research ◽  
Delayed Measurement ◽  
Persuasive Power ◽  
Over Time

Abstract This meta-analysis builds on the broad and diverse research on the persuasive effects of narrative communication. Researchers have found that narratives are a particularly effective type of message that often has greater persuasive effects than non-narratives immediately after exposure. The present study meta-analyzes whether this greater persuasive power persists over time. Results are based on k1 = 14 studies with k2 = 51 effect sizes for immediate measurement (N = 2,834) and k2 = 66 effect sizes for delayed measurement (N = 2,459). They show that a single narrative message has a stronger persuasive impact than a non-narrative message on attitudes and intentions at immediate as well as on attitudes, intentions, and behaviors at delayed measurement. Both message types did not differently affect the participants’ beliefs. Meta-analytic structural equation modeling confirms transportation as a mediator of immediate persuasive effects.

A Methodological Note: An Introduction to Autoregressive Models

2021 ◽  
pp. 009141502110665
Author(s):  
Christopher J. Burant
Keyword(s):  
Structural Equation ◽  
Well Being ◽  
Autoregressive Models ◽  
Equation Modeling ◽  
Time Score ◽  
Gerontological Research ◽  
Causal Ordering ◽  
Lagged Effects ◽  
Over Time ◽  
Time Point

The autoregressive model is a useful tool to analyze longitudinal data. It is particularly suitable for gerontological research as autoregressive models can be used to establish the causal relationship within a single variable over time as well as the causal ordering between two or more variables (e.g., physical health and psychological well-being) over time through bivariate autoregressive cross-lagged or contemporaneous models. Specifically, bivariate autoregressive models can explore the cross-lagged effects between two variables over time to determine the proper causal ordering between these variables. The advantage of analyzing cross-lagged effects is to test for the strength of prediction between two variables controlling for each variable's previous time score as well as the autoregressive component of the model. Bivariate autoregressive contemporaneous models can also be used to determine causal ordering within the same time point when compared to cross-lagged effects. Since the technique uses structural equation modeling, models are also adjusted for measurement error. This paper will present an introduction to setting up models and a step-by-step approach to analyzing univariate simplex autoregressive models, bivariate autoregressive cross-lagged models, and bivariate autoregressive contemporaneous models.

Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue
Keyword(s):  
Structural Equation Modeling ◽  
Negative Correlation ◽  
Structural Equation ◽  
Error Score ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equation Modeling ◽  
Eysenck Personality Questionnaire ◽  
Personality Questionnaire ◽  
True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

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