Neonatal Adverse Outcomes, Neonatal Birth Risks, and Socioeconomic Status: Combined Influence on Preterm Infants’ Cognitive, Language, and Motor Development in Brazil

Background: This study extended previous research by investigating the combined effects of neonatal birth risks, neonatal adverse outcomes, and socioeconomic status on preterm neurodevelopment. Method: A total of 184 preterm infants were assessed using the Bayley Scales of Infant Development III in a follow-up clinic in southern Brazil. Structural equation modeling was conducted with 3 latent variables (neonatal birth risks, neonatal adverse outcomes, and socioeconomic status) and 3 outcomes (cognitive, language, and motor development). Results: The analyses showed that neonatal adverse outcomes were associated with infants’ cognitive (b = –0.45, P < .001), language (b = –0.23, P = .001), and motor (b = –0.51, P < .001) development. Socioeconomic status also explained the variances (cognitive: b = 0.20, P = .006; language: b = 0.28, P = .001; and motor: b = 0.21, P = .004), whereas neonatal birth risks remained significant only in the motor development (b = 0.15, P = .040). Conclusion: This study suggests that the most evident contributors to poor neurodevelopment were adverse outcomes and socioeconomic risk factors.

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Using WarpPLS in e-Collaboration Studies

International Journal of e-Collaboration ◽

10.4018/jec.2011070101 ◽

2011 ◽

Vol 7 (3) ◽

pp. 1-13 ◽

Cited By ~ 49

Author(s):

Ned Kock

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Descriptive Statistics ◽

Equation Modeling ◽

Mediating Effects ◽

Analysis Algorithm ◽

Modeling Analysis ◽

Nonlinear Structural Equation ◽

The Right

This is a follow-up on two previous articles on WarpPLS and e-collaboration. The first discussed the five main steps through which a variance-based nonlinear structural equation modeling analysis could be conducted with the software WarpPLS (Kock, 2010b). The second covered specific features related to grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving various results (Kock, 2011). This and the previous articles use data from the same e-collaboration study as a basis for the discussion of important WarpPLS features. Unlike the previous articles, the focus here is on a brief discussion of more advanced issues, such as: testing the significance of mediating effects, including control variables in an analysis, using second order latent variables, choosing the right warping algorithm, and using bootstrapping and jackknifing in combination.

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Abstract P212: How Much Do Psychosocial Factors Mediate the Association Between Socioeconomic Status and 1-Year Angina After Myocardial Infarction?

Circulation Cardiovascular Quality and Outcomes ◽

10.1161/circoutcomes.4.suppl_1.ap212 ◽

2011 ◽

Vol 4 (suppl_1) ◽

Author(s):

Donna M Buchanan ◽

Kymberley K Bennett ◽

Philip G Jones ◽

Judith H Lichtman ◽

John A Spertus

Keyword(s):

Socioeconomic Status ◽

Depressive Symptoms ◽

Psychosocial Factors ◽

Perceived Stress ◽

Low Socioeconomic Status ◽

Latent Variables ◽

Structural Equation ◽

Equation Modeling ◽

Reserve Capacity ◽

Capacity Model

Background: Low socioeconomic status (SES) is associated with worse cardiovascular (CV) outcomes. The Reserve Capacity Model (RCM) is a published, but not yet fully tested, framework linking SES, psychosocial factors and health outcomes. “Reserve capacity” is one's inter-/intrapersonal resources for managing stress. We tested the RCM to determine what portion of the association between SES and angina frequency 1 year post-MI is attributable to psychosocial factors. Methods: In 2481 post-MI patients enrolled in the 19-center PREMIER registry, we used confirmatory factor analysis to create latent variables of health-related SES and reserve capacity (including social support, optimism, and internal health locus of control). Structural equation modeling was used to test the associations between baseline SES, 1-month psychosocial factors (perceived stress, reserve capacity, and depressive symptoms) and 1-yr angina, adjusting for age, sex, and baseline angina. Results: The overall correlation between SES and 1-yr angina was significant (r = -.21*). Of this, 37% was explained by psychosocial factors. (See figure.) Higher SES was associated with greater reserve capacity (r = .43*), which was strongly and inversely associated with stress (r = -.68*) and depressive symptoms (r = -.36*). Depressive symptoms were directly associated with angina (r = .12*). (*p < .05) Conclusion: These results validate the RCM, showing that perceived stress, reserve capacity, and depressive symptoms partially mediate the link between SES and 1-yr angina post-MI. This identifies possible areas for intervention to reduce SES-related disparities in angina and potentially other CV outcomes.

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Adolescent Obesity Modeling: A Framework of Socio-Economic Analysis on Public Health

Healthcare ◽

10.3390/healthcare9080925 ◽

2021 ◽

Vol 9 (8) ◽

pp. 925

Author(s):

Hashem Salarzadeh Jenatabadi ◽

Nurulaini Abu Shamsi ◽

Boon-Kwee Ng ◽

Nor Aishah Abdullah ◽

Khairul Anam Che Mentri

Keyword(s):

Socioeconomic Status ◽

Food Intake ◽

Body Fat ◽

Latent Variables ◽

Structural Equation ◽

Adolescent Obesity ◽

Equation Modeling ◽

Time Data ◽

Research Areas ◽

Household Socioeconomic Status

Bayesian Structural Equation Modeling (SEM-Bayesian) was applied across different research areas to model the correlation between manifest and latent variables. The primary purpose of this study is to introduce a new framework of complexity to adolescent obesity modeling based on adolescent lifestyle through the application of SEM-Bayesian. The introduced model was designed based on the relationships among several factors: household socioeconomic status, healthy food intake, unhealthy food intake, lifestyle, body mass index (BMI) and body fat. One of the main contributions of this study is from considering both BMI and body fat as dependent variables. To demonstrate the reliability of the model, especially in terms of its fitting and accuracy, real-time data were extracted and analyzed across 881 adolescents from secondary schools in Tehran, Iran. The output of this study may be helpful for researchers who are interested in adolescent obesity modeling based on the lifestyle and household socioeconomic status of adolescents.

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Using WarpPLS in E-Collaboration Studies

Interdisciplinary Applications of Electronic Collaboration Approaches and Technologies ◽

10.4018/978-1-4666-2020-9.ch008 ◽

2012 ◽

pp. 112-124

Author(s):

Ned Kock

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Descriptive Statistics ◽

Equation Modeling ◽

Mediating Effects ◽

Analysis Algorithm ◽

Modeling Analysis ◽

Nonlinear Structural Equation ◽

The Right

This is a follow-up on two previous articles on WarpPLS and E-collaboration. The first discussed the five main steps through which a variancE-based nonlinear structural equation modeling analysis could be conducted with the software WarpPLS (Kock, 2010b). The second covered specific features related to grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving various results (Kock, 2011). This and the previous articles use data from the same E-collaboration study as a basis for the discussion of important WarpPLS features. Unlike the previous articles, the focus here is on a brief discussion of more advanced issues, such as: testing the significance of mediating effects, including control variables in an analysis, using second order latent variables, choosing the right warping algorithm, and using bootstrapping and jackknifing in combination.

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Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

Social Psychology ◽

10.1027/1864-9335/a000356 ◽

2019 ◽

Vol 50 (1) ◽

pp. 24-37

Author(s):

Ben Porter ◽

Camilla S. Øverup ◽

Julie A. Brunson ◽

Paras D. Mehta

Keyword(s):

Structural Equation Modeling ◽

Social Relations ◽

Latent Variables ◽

Structural Equation ◽

Multilevel Structural Equation Modeling ◽

Equation Modeling ◽

Complete Understanding ◽

Social Relations Model ◽

Flexible Framework ◽

Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

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Factors Affecting the Use and Consequences of Management Accounting Practices in A Transitional Economy: The Case of Vietnam

Journal of Economics and Development ◽

10.33301/2016.18.01.04 ◽

2016 ◽

pp. 54-73 ◽

Cited By ~ 2

Author(s):

Anh Doan Ngoc Phi

Keyword(s):

Significant Influence ◽

Quantitative Data ◽

Structural Equation ◽

Qualitative Data ◽

Management Accounting ◽

Transitional Economy ◽

Equation Modeling ◽

Enterprise Performance ◽

Factors Affecting

This study seeks to help fill an important gap in the literature by investigating factors that have facilitated the use of management accounting practices (MAPs) in Vietnam - a transitional economy. Data were collected from 220 medium-to-large enterprises. Follow-up interviews were conducted with 20 accounting heads/vice heads to obtain further information and clarification. The quantitative data collected was analyzed using both descriptive and inferential statistics (including t-tests and structural equation modeling), while the qualitative data was used to shed further light on the various relationships described by the quantitative analysis. This paper reveals that both decentralization and competition have a positive, significant influence on the use of new MAPs except for the old ones. Consequently, the use of MAPs has a positive, significant influence on enterprise performance.

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Connecting Climate and Communicable Disease to Penta Helix Using Hierarchical Likelihood Structural Equation Modelling

Symmetry ◽

10.3390/sym13040657 ◽

2021 ◽

Vol 13 (4) ◽

pp. 657

Author(s):

Rezzy Eko Caraka ◽

Maengseok Noh ◽

Rung-Ching Chen ◽

Youngjo Lee ◽

Prana Ugiana Gio ◽

...

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Healthy Lifestyle ◽

Communicable Disease ◽

Well Being ◽

Equation Modeling ◽

Human Beings ◽

The Sustainable Development ◽

Healthcare Facilities ◽

Hierarchical Likelihood

Design: Health issues throughout the sustainable development goals have also been integrated into one ultimate goal, which helps to ensure a healthy lifestyle as well as enhances well-being for any and all human beings of all social level. Meanwhile, regarding the clime change, we may take urgent action to its impacts. Purpose: Nowadays, climate change makes it much more difficult to control the pattern of diseases transmitted and sometimes hard to prevent. In line with this, Centres for Disease Control (CDC) Taiwan grouped the spread of disease through its source in the first six main groups. Those are food or waterborne, airborne or droplet, vector-borne, sexually transmitted or blood-borne, contact transmission, and miscellaneous. According to this, academics, government, and the private sector should work together and collaborate to maintain the health issue. This article examines and connects the climate and communicable aspects towards Penta-Helix in Taiwan. Finding: In summary, we have been addressing the knowledge center on the number of private companies throughout the health care sector, the number of healthcare facilities, and the education institutions widely recognized as Penta Helix. In addition, we used hierarchical likelihood structural equation modeling (HSEMs). All the relationship variables among climate, communicable disease, and Penta Helix can be interpreted through the latent variables with GoF 79.24%.

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A Study on Supply–Demand Satisfaction of Community-Based Senior Care Combined with the Psychological Perception of the Elderly

Healthcare ◽

10.3390/healthcare9060643 ◽

2021 ◽

Vol 9 (6) ◽

pp. 643

Author(s):

Jiangang Shi ◽

Wenwen Hua ◽

Daizhong Tang ◽

Ke Xu ◽

Quanwei Xu

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Care Service ◽

Elderly Care ◽

The Elderly ◽

Living Environment ◽

Equation Modeling ◽

Strategic Decisions ◽

Community Based ◽

The Government

Based on Maslow’s hierarchy of needs theory and customer satisfaction theory, we constructed a satisfaction model for supply–demand satisfaction for community-based senior care (SSCSC) combined with the psychological perspective of the elderly, and four dimensions of basic living needs (BLNs), living environment (LE), personal traits (PTs), and livability for the aged (LA) were selected to construct the model. The data were obtained from 296 questionnaires from seniors over 50 years old (or completed by relatives on their behalf, according to their actual situation). Twenty-two observed variables were selected for the five latent variables, and their interactions were explored using structural equation modeling. The results showed that LA was the most significant factor influencing SSCSC, and it was followed by BLNs and LE. PTs did not show a direct effect on LA, but they could have an indirect effect on SSCSC through influencing BLNs and LE. Based on the current state of community aging satisfaction, we propose to establish a community elderly care service system based on the basic needs of the elderly population, providing differentiated and refined elderly care services and improving the level of aging-friendly communities. This study provides references for the government to formulate relevant policies and other supply entities to make strategic decisions and has important implications for further enhancing community elderly services to become an important part of the social security system for the elderly.

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Building a Model of Family Caregiving for Children with Emotional Disorders

Journal of Emotional and Behavioral Disorders ◽

10.1177/106342669700500302 ◽

1997 ◽

Vol 5 (3) ◽

pp. 138-148 ◽

Cited By ~ 19

Author(s):

Thomas P. Mcdonald ◽

Thomas K. Gregoire ◽

John Poertner ◽

Theresa J. Early

Keyword(s):

Structural Equation Modeling ◽

Emotional Disorders ◽

Problem Behaviors ◽

Family Caregiving ◽

Latent Variables ◽

Structural Equation ◽

Empirical Literature ◽

Equation Modeling ◽

Special Challenge ◽

And Coping

In this article we describe the results of an ongoing effort to better understand the caregiving process in families of children with severe emotional problems. We make two assumptions. First, we assume that these families are essentially like other families but are faced with a special challenge in raising and caring for their special children while at the same time performing the multiple tasks and demands faced by all families. Second, we assume that public policy and programs must be supportive of the care of these children in their own homes and communities whenever possible. The purpose of this article is to present a model of family caregiving that draws broadly from available theory and empirical literature in multiple fields and to subject this model to empirical testing. We use structural equation modeling with latent variables to estimate an empirical model based on the theoretical model. Results of the model testing point to the importance of the child's external problem behaviors and the family's socioeconomic status and coping strategies as determinants of caregiver stress. Other findings highlight difficulties in measuring and modeling the complex mediating process, which includes formal and informal supports, perceptions, and coping behaviors. The use of structural equation modeling can benefit our efforts to support families by making explicit our theories about the important dimensions of this process and the relationship between these dimensions, which can then be subjected to measurement and validation.

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