scholarly journals Something Scary is Out There II: the Interplay of Childhood Experiences, Relict Sexual Dinichism, and Cross-cultural Differences in Spatial Fears

2021 ◽  
Author(s):  
Richard G. Coss ◽  
Shelley A. Blozis
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Australopithecus Afarensis ◽  
Foreign Born ◽  
Childhood Experiences ◽  
Ethnic Chinese ◽  
Cross Cultural Differences ◽  
Exploratory Factor Analyses ◽  
The Usa

AbstractChildren’s nighttime fear is hypothesized as a cognitive relict reflecting a long history of natural selection for anticipating the direction of nighttime predatory attacks on the presumed human ancestor, Australopithecus afarensis, whose small-bodied females nesting in trees would have anticipated predatory attacks from below. Heavier males nesting on the ground would have anticipated nighttime predatory attacks from their sides. Previous research on preschool children and adults supports this cognitive-relict hypothesis by showing developmental consistencies in their remembrances of the location of a “scary thing” relative to their beds. The current study expands this research by investigating whether nighttime fear in childhood, including the effect of parental threats to behave, influenced adult spatial fears in different biotic and abiotic situations. A 25-item questionnaire employing ordinal scales was given to 474 foreign-born Vietnamese and ethnic Chinese adults living in the USA. Univariate analyses of adult remembrances of childhood indicated that females were more fearful of something scary below their beds than males. To examine the influence of childhood nighttime fear on adult fears, exploratory factor analyses supported three factors: (1) indeterminate agents, indicated something scary under the bed, the difficulty locating unspecific threats, and the brief appearances of large apparitions; (2) environmental uncertainty, indicated by potential encounters with unseen animate threats; (3) predictable animals, as the relative comfort of viewing animals in zoo exhibits. Using structural equation modeling, the results suggest that childhood nighttime fear influenced only the latent variable, indeterminate agents, in both groups via the mediating variable, parental threats.

Neuroimaging of Individual Differences: A Latent Variable Modeling Perspective

2018 ◽  
Author(s):  
Shelly Renee Cooper ◽  
Joshua James Jackson ◽  
Deanna Barch ◽  
Todd Samuel Braver
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
Latent Variable ◽  
Structural Equation ◽  
Behavioral Measure ◽  
Equation Modeling ◽  
Latent Variable Modeling ◽  
Psychometric Theory ◽  
Human Connectome Project ◽  
Neuroimaging Data

Neuroimaging data is being increasingly utilized to address questions of individual difference. When examined with task-related fMRI (t-fMRI), individual differences are typically investigated via correlations between the BOLD activation signal at every voxel and a particular behavioral measure. This can be problematic because: 1) correlational designs require evaluation of t-fMRI psychometric properties, yet these are not well understood; and 2) bivariate correlations are severely limited in modeling the complexities of brain-behavior relationships. Analytic tools from psychometric theory such as latent variable modeling (e.g., structural equation modeling) can help simultaneously address both concerns. This review explores the advantages gained from integrating psychometric theory and methods with cognitive neuroscience for the assessment and interpretation of individual differences. The first section provides background on classic and modern psychometric theories and analytics. The second section details current approaches to t-fMRI individual difference analyses and their psychometric limitations. The last section uses data from the Human Connectome Project to provide illustrative examples of how t-fMRI individual differences research can benefit by utilizing latent variable models.

scholarly journals Postpartum depression symptoms in survey-based research: a structural equation analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Che Wan Jasimah Bt Wan Mohamed Radzi ◽  
Hashem Salarzadeh Jenatabadi ◽  
Nadia Samsudin
Keyword(s):  
Postpartum Depression ◽  
Latent Variable ◽  
Structural Equation ◽  
Depression Scale ◽  
Public Health Problem ◽  
Equation Modeling ◽  
Depression Symptoms ◽  
Postpartum Women ◽  
Unhealthy Food ◽  
High Level

Abstract Background Since the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis. In this research, we introduced a new framework for postpartum depression modeling for women. Methods We structured the model of this research to take into consideration the Malaysian culture in particular. A total of 387 postpartum women have completed the questionnaire. The symptoms of postpartum depression were examined using the Edinburgh Postnatal Depression Scale (EPDS), and they act as a dependent variable in this research model. Results Four hundred fifty mothers were invited to participate in this research. 86% of the total distributed questionnaire received feedback. The majority of 79.6% of respondents were having depression symptoms. The highest coefficients of factor loading analysis obtained in every latent variable indicator were income (β = 0.77), screen time (β = 0.83), chips (β = 0.85), and anxiety (β = 0.88). Lifestyle, unhealthy food, and BMI variables were directly affected by the dependent variable. Based on the output, respondents with a high level of depression symptoms tended to consume more unhealthy food and had a high level of body mass indexes (BMI). The highest significant impact on depression level among postpartum women was unhealthy food consumption. Based on our model, the findings indicated that 76% of the variances stemmed from a variety of factors: socio-demographics, lifestyle, healthy food, unhealthy food, and BMI. The strength of the exogenous and endogenous variables in this research framework is strong. Conclusion The prevalence of postpartum women with depression symptoms in this study is considerably high. It is, therefore, imperative that postpartum women seek medical help to prevent postpartum depressive symptoms from worsening.

scholarly journals Insights Into the Correspondence Between Land Use Pattern and Spatial Distribution of Rail Transit Services

2021 ◽  
Author(s):  
Zhongqi Wang ◽  
Qi Han ◽  
Bauke de Vries ◽  
Li Dai
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Operations Management ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Rail Transit ◽  
Land Use Patterns ◽  
Transit Services ◽  
The Relationship

AbstractThe identification of the relationship between land use and transport lays the foundation for integrated land use and transport planning and management. This work aims to investigate how rail transit is linked to land use. The research on the relationship between land use and rail-based transport is dominated by the impacts of rail projects on land use, without an in-depth understanding of the reverse. However, it is important to note that issues of operation management rather than new constructions deserve greater attention for regions with established rail networks. Given that there is a correspondence between land use patterns and spatial distribution of heavy railway transit (HRT) services at such regions, the study area (i.e., the Netherlands) is partitioned by the Voronoi diagram of HRT stations and the causal relationship between land use and HRT services is examined by structural equation modeling (SEM). The case study of Helmond (a Dutch city) shows the potential of the SEM model for discussing the rail station selection problem in a multiple transit station region (MTSR). Furthermore, in this study, the node place model is adapted with the derivatives of the SEM model (i.e., the latent variable scores for rail service levels and land use characteristics), which are assigned as node and place indexes respectively, to analyze and differentiate the integration of land use and HRT services at the regional level. The answer to whether and how land use affects rail transit services from this study strengthens the scientific basis for rail transit operations management. The SEM model and the modified node place model are complementary to be used as analytical and decision-making tools for rail transit-oriented regional development.

Attributional Style as a Predictor of Hopelessness Depression

2006 ◽  
Vol 20 (4) ◽  
pp. 447-458 ◽  
Author(s):  
Edward D. Sturman ◽  
Myriam Mongrain ◽  
Paul M. Kohn
Keyword(s):  
Attributional Style ◽  
Latent Variable ◽  
Structural Equation ◽  
Depression Scale ◽  
Epidemiological Studies ◽  
Psychomotor Retardation ◽  
Equation Modeling ◽  
Depression Symptoms ◽  
Negative Events ◽  
Hopelessness Depression

Stable and global attributions for negative events were tested as predictors of hopelessness depression symptoms, obtained from a diagnostic interview for a past depressive episode in a sample of 102 graduate students. All participants were administered the Structured Clinical Interview for DSM–IV, Center for Epidemiological Studies Depression Scale, Personal Style Inventory, and a modified version of the Extended Attributional Style Questionnaire. A stable and global attributional style for negative events was significantly associated with a composite of hopelessness depression symptoms. A regression analysis revealed that attributional style significantly postdicted hopelessness depression symptoms when controlling for both sociotropy and autonomy. Structural equation modeling supported a model in which stable and global attributions predicted a latent variable, which we refer to as a motivational deficit, involving psychomotor retardation and fatigue as indicators. Therefore, this study obtained some support for the hopelessness model and highlights the vulnerability posed by attributional style ( Abramson, Metalsky, & Alloy, 1989 ).

Privacy helplessness on social media: its constituents, antecedents and consequences

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hichang Cho
Keyword(s):  
Theoretical Model ◽  
Structural Equation ◽  
Factor Model ◽  
Measurement Model ◽  
Equation Modeling ◽  
Confirmatory Factor Analyses ◽  
Content Type ◽  
Internet Users ◽  
The Usa ◽  
Antecedents And Consequences

PurposeMany internet users exhibit signs of privacy helplessness and entirely give up online privacy management. However, we know little about what privacy helplessness is, when users are likely to experience it and its implications for privacy behavior. The objectives of this study were twofold: (a) the conceptual explication of privacy helplessness as a novel construct in privacy research and (b) the development of a theoretical model that specifies the antecedents and consequences of privacy helplessness.Design/methodology/approachA research model of privacy helplessness that contains three subcomponents of privacy helplessness, five antecedents and one outcome was developed. The model was empirically examined based on survey data collected from 589 Facebook users in the USA.FindingsThe results of exploratory and confirmatory factor analyses showed that privacy helplessness is adequately assessed by a three-factor model with affective, cognitive and motivational components. The results of structural equation modeling indicated that these three aspects of privacy helplessness are uniquely predicted by five theoretical factors: (a) prior experience of privacy risks, (b) personal mastery, (c) perceived costs of adaptive privacy actions, (d) perceived rewards of privacy inactions and (e) perceived vulnerability. Furthermore, it was found that helplessness as motivational deficits (and cognitive helplessness via this) impedes adaptive privacy actions, while cognitive helplessness promotes adaptive privacy actions when they do not result in motivational deficits.Originality/valueThis study pioneers investigation in understanding key constituents, attributes and processes underlying privacy helplessness. First, the present study developed the first theory-derived, successively validated measurement model of privacy helplessness. Second, this research proposed a theoretical model of privacy helplessness, specifying antecedents and consequences of privacy helplessness.

What makes up intentions to purchase the pioneer? A theory of reasoned action approach in India and the USA

2018 ◽  
Vol 13 (5) ◽  
pp. 734-757 ◽  
Author(s):  
Tarek Mady
Keyword(s):  
Social Norms ◽  
Purchase Intention ◽  
Structural Equation ◽  
Theory Of Reasoned Action ◽  
Reasoned Action ◽  
Dominant Role ◽  
Emerging Market ◽  
Equation Modeling ◽  
Content Type ◽  
The Usa

Purpose The purpose of this paper is to extend the research paradigm focusing on behaviorally-based first-mover advantages (FMA) by applying the widely-accepted Theory of Reasoned Action (TRA) and offers insights into differences between a mature market (USA) and an emerging market (EM) (India) regarding how intentions to purchase the pioneer are formed. Design/methodology/approach Utilizing samples of 208 USA and 194 Indian consumers, hypotheses examining the underlying beliefs, attitudes, social norms and purchasing intentions regarding pioneer brands are developed and tested using structural equation modeling. Findings Insights from the study suggest the TRA provides a means for assessing behaviorally-based FMAs across cultures, even as manifestations of purchase intentions differ significantly. According to the TRA and findings of this study, intentions are a function of overall attitudes and social norms. In the USA, individual attitudes were found to play a more significant role than social norms in formulating purchase intention. In India, social norms played a more dominant role in intention formation. Originality/value The study represents one of the first empirical attempts to shed light on the extent of behaviorally-based FMAs in an EM and how manifestations of intention to purchase the pioneer differ from mature markets. The study expands the behavioral paradigm of analysis to include one of the most sought-after EMs today (India) and provides one of the first empirical studies to utilize the TRA in addressing behaviorally-based FMAs.

scholarly journals Determinants of Adoption of New Technology in Telecom Sector: A Structural Equation Modeling Approach

2018 ◽  
Vol 20 (1) ◽  
pp. 166-178 ◽  
Author(s):  
Susmita Chatterjee ◽  
Bibek Ray Chaudhuri ◽  
Debabrata Dutta
Keyword(s):  
Structural Equation Modeling ◽  
Mobile Communications ◽  
Structural Equation ◽  
Low Cost ◽  
New Technology ◽  
Equation Modeling ◽  
Technology Standards ◽  
Technology Standard ◽  
The Usa ◽  
Adoption Of New Technology

In this article, we look at the determinants of the new technology adoption by consumers in the case of mobile telecommunications. The dynamic nature of the telecom industry is a result of the frequent technological change. Consumers witness different technology standards in mobile communications, starting from the first generation (1G) to second generation (2G) subsequently to third (3G) and now experiencing fourth (4G) in some countries such as Norway, Sweden, South Korea, and the USA including ours. The movement from one standard to the other has been predicted to be smooth as all of them are vertical substitutes for each other. Given the various dimensions such as price, requirements, utility and so on, these technology standards are not perfect substitutes. The article investigates the prospect of a new technology standard roll out in India. A survey of 400 mobile phone customers in metro telecom circles has been carried out for this purpose. The study applies structural equation modeling (SEM) and explores the adoption intention of this new technology among the respondents. Results show that the presence of low-cost alternatives that is the availability of a lower technology standard poses a significant hurdle to the adoption of new technology services.

scholarly journals Structural Equation Modeling for the Effect of Main Factors on Abortion Issue

2019 ◽  
Vol 7 (1) ◽  
pp. 1-13
Author(s):  
Aras Jalal Mhamad ◽  
Renas Abubaker Ahmed
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Close Contact ◽  
Maternity Hospital ◽  
Equation Modeling ◽  
Research Model ◽  
Statistical Tools ◽  
Main Factors

       Based on medical exchange and medical information processing theories with statistical tools, our study proposes and tests a research model that investigates main factors behind abortion issue. Data were collected from the survey of Maternity hospital in Sulaimani, Kurdistan-Iraq. Structural Equation Modelling (SEM) is a powerful technique as it estimates the causal relationship between more than one dependent variable and many independent variables, which is ability to incorporate quantitative and qualitative data, and it shows how all latent variables are related to each other. The dependent latent variable in SEM which have one-way arrows pointing to them is called endogenous variable while others are exogenous variables. The structural equation modeling results reveal is underlying mechanism through which statistical tools, as relationship between factors; previous disease information, food and drug information, patient address, mother’s information, abortion information, which are caused abortion problem. Simply stated, the empirical data support the study hypothesis and the research model we have proposed is viable. The data of the study were obtained from a survey of Maternity hospital in Sulaimani, Kurdistan-Iraq, which is in close contact with patients for long periods, and it is number one area for pregnant women to obtain information about the abortion issue. The results shows arrangement about factors effectiveness as mentioned at section five of the study. This gives the conclusion that abortion problem must be more concern than the other pregnancy problem.

scholarly journals A Behavioral Model of Drivers’ Mean Speed Influenced by Weather Conditions, Road Geometry, and Driver Characteristics Using a Driving Simulator Study

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Mehdi Zolali ◽  
Babak Mirbaha ◽  
Maziyar Layegh ◽  
Hamid Reza Behnood
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Driving Simulator ◽  
Weather Conditions ◽  
Geometric Design ◽  
Equation Modeling ◽  
Novice Drivers ◽  
Sight Distance ◽  
The Mean

Driving above the speed limit is one of the factors that significantly affect safety. Many studies examined the factors affecting the speed of vehicles in the simulated environment. The present study aimed to analyze drivers’ characteristics, time and weather conditions, and geometric features’ effect on mean speed in simulated conditions simultaneously. In this regard, the simulator experiment data of 70 drivers were collected in a two-lane rural highway at six different times, and weather scenarios and their socioeconomic characteristics were collected by a questionnaire. Structural equation modeling (SEM) was used to capture the complex relationships among related variables. Eleven variables were grouped into four latent variables in the structural model. Latent variables including “Novice Drivers,” “Experienced Drivers,” “Sight Distance,” and “Geometric Design” were defined and found significant on their mean speed. The results showed that “Novice Drivers” have a positive correlation with the mean speed. Meanwhile, “Experienced Drivers,” who drive 12% slower than the novice group, negatively affect the mean speed with a standard regression weight of −0.08. This relation means that young and novice drivers are more inclined to choose higher speeds. Among variables, the latent variable “Sight Distance” has the most significant effect on the mean speed. This model shows that foggy weather conditions strongly affect the speed selection behavior and reduce the mean speed by 40%. Nighttime also reduces mean speed due to poor visibility conditions. Furthermore, “Geometric design” as the latent variable indicates the presence of curves on the simulated road, and it can be concluded that the existence of a curve on the road encourages drivers to slow down, even young drivers. It is noteworthy that the parts of the simulated road with a horizontal curve act as a speed reduction tool for drivers.

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