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Results for “Structural equation modeling”

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PubMed2005

Neighborhood social disorder as a determinant of drug injection behaviors: a structural equation modeling approach.

Neighborhood environments are increasingly recognized as a contextual determinant of health, behaviors, and disease; however, the pathways through which neighborhood characteristics impact health behaviors are poorly understood. This article examines pathways to elucidate how neighborhood social disorder may lead to HIV transmission. Data are from a baseline survey of 701 injection drug users from the Self-Help in Eliminating Lethal Diseases Study, an HIV prevention intervention in Baltimore. Structural equation modeling was used to examine the pathways among social disorder, psychological distress, and drug injection behaviors. The relationship between disorder and injection behaviors in the models tested suggests that psychological distress is higher in more socially disordered neighborhoods, that distress leads to greater injection frequency and equipment sharing, and that injection frequency predicts equipment sharing.

Adolescent↗

PubMed2005

Estimation of the cortical connectivity by high-resolution EEG and structural equation modeling: simulations and application to finger tapping data.

Today, the concept of brain connectivity plays a central role in the neuroscience. While functional connectivity is defined as the temporal coherence between the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally between cortical sites. The most used method to estimate effective connectivity in neuroscience is the structural equation modeling (SEM), typically used on data related to the brain hemodynamic behavior. However, the use of hemodynamic measures limits the temporal resolution on which the brain process can be followed. The present research proposes the use of the SEM approach on the cortical waveforms estimated from the high-resolution EEG data, which exhibits a good spatial resolution and a higher temporal resolution than hemodynamic measures. We performed a simulation study, in which different main factors were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). Such factors were the signal-to-noise ratio and the duration of the simulated cortical activity. Since SEM technique is based on the use of a model formulated on the basis of anatomical and physiological constraints, different experimental conditions were analyzed, in order to evaluate the effect of errors made in the a priori model formulation on its performances. The feasibility of the proposed approach has been shown in a human study using high-resolution EEG recordings related to finger tapping movements.

Algorithms↗

PubMedDate not supplied

[Analysis of etiologic models of disease development and continuation of bulimia nervosa using structural equation modeling].

In contrast to the great number of etiological models for bulimia nervosa, few conceptions determine the therapeutic practice. Two of these models, the ego-psychological model of reduced impulse-control and the behavioural model focussing the influence of "restrained eating" are empirically compared. Both models are not supposed to be of ubiquitous validity, but valid for subgroups of bulimic women. The theoretical assumptions are translated into structural equations and a sample of 127 bulimic women is divided up into 2 subsamples according to criteria which are presumed to define the validity of both etiological models. In agreement with the assumptions the "restrained eating" model shows the better "fit" with the one subsample while the ego-psychological model is more adequate for the other group.

Adult↗

PubMed2003

Quality of life for adolescents: assessing measurement properties using structural equation modelling.

Assessments for quality of life (QOL) of the adolescent have received relatively little attention in the literature. Although there is no consensus on the definition of adolescent QOL and what aspects should be measured, it is generally accepted that QOL is a multidimensional construct. The objective of this study is to determine the measurement properties of the latent factors underlying adolescent QOL based on a second-order confirmatory factor analysis (CFA). A recursive structural equation model (SEM) is then proposed to determine the direction and magnitude of the interdependent effects among the latent factors. The questionnaire used was the Quality of Life Profile-Adolescent Version (QOLPAV). A sample of 363 adolescents was recruited from 20 secondary schools in Perth, Australia. The second-order CFA suggested that adolescent QOL may be measured by five underlying constructs namely social, environment, psychological, health, and opportunities for growth. The interdependent relations among these constructs identified the environment factor as primary, exerting both direct and indirect effects on the other four factors.

Adolescent↗

PubMed2000

Is racism dead? Comparing (expressive) means and (structural equation) models.

Much scholarship suggests that racism--belief in out-group inferiority--is unrelated to contemporary attitudes. Purportedly, a new form of racism, one which relies upon a belief in cultural difference, has become a more acceptable basis for such attitudes. The authors argue that an appropriate empirical assessment of racism (both 'old' and 'new') depends upon (1) clear conceptualization and operationalization, and (2) attention to both mean-level expression and explanatory value in structural equation models. This study assessed the endorsement of racism and belief in cultural difference as well as their association with a measure of general attitude in a secondary analysis of parallel representative surveys of attitudes toward different ethnic out-groups in France, The Netherlands, Western Germany and Britain (N = 3242; see Reif & Melich, 1991). For six of the seven out-group targets, racism was strongly related to ethnic majority attitudes, despite low mean-level endorsement. In a pattern consistent with a 'new', indirect racism, the relationship between British racism and attitudes toward Afro-Caribbeans was mediated by belief in cultural difference.

Adult↗

PubMed2006

Psychotropic substance abuse among adolescents: a structural equation model on risk and protective factors.

The use of psychotropic substances in adolescents represents a serious public health problem. In this study a representative sample of 485 Austrian students between 14 and 18 years of age were investigated with a semistructured interview about substance-related issues and completed the general health questionnaire. The following rates of regular psychotropic substance use were found: cigarettes 41.4%, alcohol 44.5%, cannabis 10.1%, and other illicit substances 3%. Logistic regression analyses and structural equation modeling revealed the following major risk factors for substance use: peer pressure, negative family atmosphere, school difficulties, and psychopathology. Knowledge about substance use acted as a protective factor. Prevention of adolescent substance use and misuse should aim at these different targets. Information about coping with peer pressure may be a particularly promising route of intervention.

Adaptation, Psychological↗

PubMed2006

A structural equation model analysis of postfire plant diversity in California shrublands.

This study investigates patterns of plant diversity following wildfires in fire-prone shrublands of California, seeks to understand those patterns in terms of both local and landscape factors, and considers the implications for fire management. Ninety study sites were established following extensive wildfires in 1993, and 1000-m(2) plots were used to sample a variety of parameters. Data on community responses were collected for five years following fire. Structural equation modeling (SEM) was used to relate plant species richness to plant abundance, fire severity, abiotic conditions, within-plot heterogeneity, stand age, and position in the landscape. Temporal dynamics of average richness response was also modeled. Richness was highest in the first year following fire, indicating postfire enhancement of diversity. A general decline in richness over time was detected, with year-to-year variation attributable to annual variations in precipitation. Peak richness in the landscape was found where (1) plant abundance was moderately high, (2) within-plot heterogeneity was high, (3) soils were moderately low in nitrogen, high in sand content, and with high rock cover, (4) fire severity was low, and (5) stands were young prior to fire. Many of these characteristics were correlated with position in the landscape and associated conditions. We infer from the SEM results that postfire richness in this system is strongly influenced by local conditions and that these conditions are, in turn, predictably related to landscape-level conditions. For example, we observed that older stands of shrubs were characterized by more severe fires, which were associated with a low recovery of plant cover and low richness. These results may have implications for the use of prescribed fire in this system if these findings extrapolate to prescribed burns as we would expect.

Biodiversity↗

PubMed2006

Relationships among mental health status, social context, and demographic characteristics in Taiwanese aboriginal adolescents: a structural equation model.

The purposes of this study were to examine the relationships among mental health status, demographic characteristics, and social contexts, including family conflict and support, connectedness to school, and affiliation with peers who exhibit delinquent behavior and who use substances, among Taiwanese aboriginal adolescents. A total of 251 aboriginal junior high school students in an isolated mountainous area of southern Taiwan were recruited, and the relationships among mental health status, demographic characteristics, and social contexts among them were examined using a structural equation model (SEM). The SEM revealed that family conflict and support had direct influences on mental health status and connectedness to school. Family conflict had a direct relationship with affiliation with peers who use substances, and family conflict and support were both indirectly linked with affiliation with peers who exhibit delinquent behavior and who used substances; these were mediated by a poor mental health status. Female and older age were directly linked with a poor mental health status and were indirectly linked with a greater number of peers who exhibit delinquent behavior and who use substances via the poor mental health status. Disruptive parenting was directly linked with affiliation with peers who use substances. The authors suggest that those who devise strategies to improve aboriginal adolescents' mental health and discourage substance use should take these relationships among mental health, demographic characteristics, and social contexts into account.

Adolescent↗

PubMed1997

Academic goals and emotions: results of a structural equation model and a cluster analysis.

BACKGROUND: Motivational researchers have suggested that the environment plays a key role in students' goal formation. However, some recent work (Seifert, 1996) suggests that students' emotions may play a role in goal formation. AIM: This study examined the relationship between environment, emotions, and goals. Do emotions and perceptions of teachers both contribute to goal orientation, or do emotions mediate the influence of perceptions of teachers on goal orientation? SAMPLE: 559 Grade 10 students in Newfoundland and Labrador. METHOD: Two structural equations were postulated: one in which students' affect mediated the influence of perceptions of teachers on goal orientation and one in which students' affect contributed to goal formation in addition to perceptions of teachers. A cluster analysis of affect scores was performed followed by between-group and within-group contrasts of goal orientation scores. RESULTS: The structural equation model in which emotions mediate the influence of perceptions of teachers on goal orientation fit the data better than the model in which perceptions of teachers directly predicted goal orientation. The cluster analysis showed that groups with different profiles of affect pursued different goals. CONCLUSIONS: Emotions seem to be directly linked to goal orientation. Teachers who are perceived as nurturing will foster feelings of self-assuredness and control in students which will lead to a learning orientation.

Adolescent↗

PubMed2003

Factors of home dream recall: a structural equation model.

Previous research has indicated that personality factors such as openness to experience, creativity, visual memory, attitude toward dreams, and sleep behavior is related to home dream recall frequency (DRF). However, a study investigating all areas simultaneously within one sample in order to determine the percentage of variance explained by all variables and to take intercorrelations between the influencing factors into account has not been performed till now. The present study with 444 participants fills this gap. Using several indicators for each of the variables mentioned above, a structural equation model was tested. Although the model fit was satisfying, the four factors which were significantly related to DRF: personality (openness to experience, thin boundaries, absorption), creativity, nocturnal awakenings, and attitude toward dreams, explained only 8.4% of the total variance. As this value is considerably lower than those of studies investigating a single influencing factor and using similar measurement instruments in similar samples, one might speculate about possible expectancy effects in these previous studies, an effect which has been demonstrated for DRF in the laboratory setting. In addition, the small percentage of explained variance of each single factors (<3%) may indicate that other, in this study unmeasured, variables such as sleep duration (state aspect), introspection, and cognitive functioning immediately upon awakening (sleep inertia) show substantial covariance with the interindividual differences in DRF. Future studies should focus on longitudinal aspects in order to differentiate between state versus trait factors (although methodologic issues, e.g. the effect of the measurement technique on DRF itself, have to be clarified) and investigate additional variables which might be associated with DRF (see above).

Attitude↗

PubMed2006

Testing relationships between clinical and non-clinical variables in xerostomia: a structural equation model of oral health-related quality of life.

OBJECTIVES: The aim of the study was to systematically test Wilson and Cleary's [Wilson IB, Cleary PD. JAMA 1995; 273: 59-65] conceptual model of the direct and mediated pathways between clinical and non-clinical variables in relation to the oral health-related quality of life (OHRQoL) of patients with xerostomia. METHODS: We collected measures of clinical variables, self-reported symptoms, OHRQoL, global oral health perceptions and subjective well-being from 85 patients attending outpatient clinics. RESULTS: Structural equation modelling indicated support for the dominant direct pathways between the main levels of the model; more severe clinical signs predicted worse patient reported symptoms; worse symptom perception was associated with a lower functional status as measured by OHRQoL; and lower OHRQoL predicted worse global oral health perceptions. There was no relationship between the final two levels of the model; global oral health perceptions and subjective well-being. Subjective well-being was associated instead with earlier non-adjacent levels; biological variables, symptoms and functional status. These pathways were both direct (salivary flow-well-being, functioning-well-being) and indirect (clinical signs-well being, symptom status-well-being). There were also indirect pathways; most notably, the impact of clinical variables on OHRQoL was mediated by patient reported symptom status. CONCLUSIONS: The results support Wilson and Cleary's conceptual model of patient outcomes as applied to a chronic oral health condition and highlight the complexity of (inter)relationships between key clinical and non-clinical variables. Further conceptual development of the model is discussed, particularly the role of individual difference factors, and theoretical and methodological issues in OHRQoL research are highlighted.

Female↗

PubMed1999

Linear structural equation model in analyzing quality-of-life-data from clinical trials.

Assessment of quality of life (QOL) in clinical trials becomes a challenging task from the viewpoint of clinical biostatistics. The responses of the items for measuring QOL indices usually vary widely from patient to patient and from time to time. Measurement errors might be present in the responses of the items, and they might be correlated. Hence, in analyzing QOL data, the usual assumption that there are no measurement errors in responses is too liberal. Because the QOL indices are likely to be correlated, separate analysis of each index might not be efficient from the point of view of statistical methodology. We apply linear structural equation modeling (LISREL) in assessing the QOL data obtained from a clinical trial. A basic premise of the LISREL approach is that the abstract concepts (latent constructs) that are not directly measurable can be studied. LISREL is a statistical procedure for conceiving and testing structural hypotheses that cannot be tested adequately with other statistical procedures. It allows us to specify relations between unobserved and observed variables while controlling for measurement errors and correlations among both the measurement errors and the latent constructs.

Arterial Occlusive Diseases↗

PubMed2004

[Analysis of paired comparison data based on experimental design: expression using structural equation modeling].

Paired comparison is a useful method for assessing ranks among several objects, and it enables us to obtain more reliable data than assessing objects one by one. But paired comparison principally provides information only about the ranks of the objects. On the other hand, experimental design provides a framework for elucidating causal associations. If we could analyze paired comparison data by the experimental design framework, it would be a very effective method. But experimental design, in its original form, is not readily applicable to paired comparison data. However, if we adopt the perspective of structural equation modeling (SEM), we can deal with paired comparison and experimental design in a unified way, because they are both submodels of SEM. The purpose of this study is to provide a new method to analyze causal connection of paired comparison data by using SEM. Here, two actual numerical examples are shown, one of which is obtained by within-subject design and the other is obtained by between-subject design.

Humans↗

PubMed2006

[Analysis by structural equation modeling of the questionnaire about the risk and its preventive measures in a pharmacy].

Pharmacists are now facing a problem of developing measures for dispensing mistakes, because there recently is increasing social awareness on medical accidents and a tendency to increase medical accidents in pharmacies due to popularizing separation of dispensing and prescribing functions. In this study, questionnaire survey was conducted to investigate pharmacist's views on human error measures and the relationship between mistakes and the preventive measures. To clarify relationship between human error measures and preventive measures for avoiding mistakes, questionnaire result was analyzed based on structural equation modeling (SEM). Questionnaire survey was sent to community pharmacies in Hokkaido. The result was analyzed by SEM. The recovery rate of the questionnaire was 71.0%. Human error measures were classified into "The measures against deficient knowledge and insufficient experiences". "Attention problem measures" and "The measures against a cognitive error". While attention problem was strongly related to the cognitive error, there was no relationship between "Attention problem measures" and "The measures against a cognitive error". Moreover, it were clarified that to develop human error measures for deficient knowledge and insufficient experiences was effective for the preventive against the mismatch of the cognitive mechanism and the intentional mistake and for bridging the gap between knowledge and experiences. This study showed that SEM was effective for adopting efficient preventive measures for medical accident and analyzing risk management in pharmacies. Applying these results to the medical accident preventive measures contribute to improvement of the risk management.

Humans↗

PubMed2005

Perception of tap water risks and quality: a structural equation model approach.

The present study aims to test a model of tap water risk and quality perception. A questionnaire was designed and applied to a convenience sample of 499 people in Portugal. The model includes aesthetic variables (colour, odour, and flavour), contextual indicators and risk perception. Other variables were also considered, including external information, trust in water companies, familiarity with tap water, and past water-related health problems. A behavioural outcome--drinking tap water--was also studied. Due to multivariate non-normality (Mardia's Coefficient (G2,P) = 460.3), the AGLS estimator was used for the structural equation model (SEM). A triangulation approach with multivariate regression analysis was used to explain the use of tap water to drink and to propose a more holistic model that could not be tested using SEM. Results show that perceived water quality is largely influenced by flavour. Other factors, such as perceived risk and contextual indicators, also have a role but their relevance is relatively weak. On the other hand, risk perception seems to be mainly a result of external information, past health problems, and water colour. Finally, the use of tap water to drink at home can be moderately explained and depends mostly on the ability to use alternatives (i.e. bottled water), tap water taste, and perceived risk.

Humans↗

PubMed1999

The inheritance of migraine with aura estimated by means of structural equation modelling.

Studies of migraine with aura (MA) have shown familial aggregation of the disorder, which cannot be explained by simple mendelian inheritance. The interest in a genetic basis for the disorder has increased after identification of three genetic loci for familial hemiplegic migraine (FHM), which is a rare subtype of MA with autosomal dominant inheritance. Both genetic and environmental factors seem to be important in the expression of MA. To elucidate the molecular pathogenesis of MA, knowledge of the relative role of genetic and environmental factors is essential. Twin studies are a classic way to analyse this. We applied structural equation modelling on MA with twin data obtained from a population based twin register in order to evaluate the effects of genes and environment. The correlation in liability of MA was 0.68 in monozygotic (MZ) and 0.22 in dizygotic (DZ) twin pairs, indicating a high degree of genetic determination in the total variance of liability. The best fitting model combined additive genetic effects and environmental effects that were not shared by the twins. The estimate of heritability was 0.65 and similar in males and females.

Female↗

PubMed2002

Relationships between hormones and aggressive behavior in green anole lizards: an analysis using structural equation modeling.

We investigated the relationship between aggressive behavior and circulating androgens in the context of agonistic social interaction and examined the effect of this interaction on the androgen-aggression relationship in response to a subsequent social challenge in male Anolis carolinensis lizards. Individuals comprising an aggressive encounter group were exposed to an aggressive conspecific male for 10 min per day during a 5-day encounter period, while controls were exposed to a neutral stimulus for the same period. On the sixth day, their responses to an intruder test were observed. At intervals, individuals were sacrificed to monitor plasma androgen levels. Structural equation modeling (SEM) was used to test three a priori interaction models of the relationship between social stimulus, aggressive behavior, and androgen. Model 1 posits that exposure to a social stimulus influences androgen and aggressive behavior independently. In Model 2, a social stimulus triggers aggressive behavior, which in turn increases circulating levels of androgen. In Model 3, exposure to a social stimulus influences circulating androgen levels, which in turn triggers aggressive behavior. During the 5 days of the encounter period, circulating testosterone (T) levels of the aggressive encounter group followed the same pattern as their aggressive behavioral responses, while the control group did not show significant changes in their aggressive behavior or T level. Our SEM results supported Model 2. A means analysis showed that during the intruder test, animals with 5 days of aggressive encounters showed more aggressive responses than did control animals, while their circulating androgen levels did not differ. This further supports Model 2, suggesting that an animal's own aggressive behavior may trigger increases in levels of plasma androgen.

Aggression↗

PubMed2002

Structural equation modeling of determinants of planning.

A model is proposed that implies that planning evoked by the formation of an implementation intention is related to behavioral intention and perceived behavioral control, whereas in accordance with the theory of planned behavior, behavioral intention is related to attitude and perceived behavioral control. Measures of attitude toward the behavior, perceived behavioral control, behavioral intention, and planning were constructed from 192 undergraduates' ratings of descriptions of two fictitious situations in which a target behavior was varied with respect to benefit and actual behavioral control. Structural equation modeling yielded an acceptable fit of the proposed model.

Adult↗