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Results for “Structural equation modeling”

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PubMed2001

IgE in unselected like-sexed monozygotic and dizygotic twins at birth and at 6 to 9 years of age: high but dissimilar genetic influence on IgE levels.

BACKGROUND: IgE is a major determinant of allergic disease. Twin analysis of serum levels of IgE has been carried out previously in children and adults with heritability estimates of 30% to 70% on the basis of ANOVA. OBJECTIVE: This study included the analysis of serum IgE in a population of 126 twins, 27 monozygotic pairs and 36 dizygotic pairs, studied at birth (cord blood [CB] IgE) and consecutively at the age of 6 to 9 years of age (serum IgE). METHODS: IgE was determined by means of RIA. ANOVA, correlation analysis, and structural equation modeling by maximal likelihood analysis was used for genetic analysis. RESULTS: Structural equation modeling by maximal likelihood analysis showed the best-fitting model to be the AE model (A for additive genetic variance and E for environmental variance) both at birth and later in childhood. The estimated heritability was 0.92 (95% CI, 0.84-0.95) for CB IgE and 0.78 (95% CI, 0.60-0.87) for serum IgE. The correlation between CB IgE and serum IgE was 0.04. CONCLUSIONS: The study demonstrated a higher genetic dependency of serum IgE than previously recognized. The low correlation between the IgE levels at birth and later in childhood suggested that different effector mechanisms may be operating at different ages.

Child↗

PubMed2005

Longitudinal relationships among transtheoretical model constructs for smokers in the precontemplation and contemplation stages of change.

BACKGROUND: This study examined the pattern, direction, and magnitude of longitudinal relationships among the constructs involved in the Transtheoretical Model (TTM). PURPOSE: The goal was to explore within-TTM relationships to create an integrated structural model that adequately represents the change process. METHOD: Data were collected as part of a representative general adult population study in Germany. A total of 688 smokers in the precontemplation and contemplation stages of change were assessed two times, 6 months apart, with respect to the TTM constructs. Structural equation modeling was used and a step approach was employed to evaluate the relationships between cognitive-affective processes, behavioral processes, the pros and cons of smoking, and self-efficacy, stratified for baseline stage of change. RESULTS: The model-building process resulted in two final structural equation models detailing longitudinal TTM relationships for precontemplation and contemplation. A structural invariance test showed that the precontemplation model also held for the contemplation sample and visa versa. CONCLUSIONS: The TTM constructs can be integrated in a longitudinal structural model. The findings provide empirical support for specific relationships that are posited in the TTM framework. However, differing relationships between TTM constructs for precontemplation and contemplation could not be established.

Adolescent↗

PubMed2006

Quality of life and menopause in women with physical disabilities.

OBJECTIVE: The goal of this cross-sectional study was to explore quality of life (QOL) in a sample of postmenopausal women with physical disabilities due to polio contracted in childhood. A structural equation model was used to confirm that menopause symptoms will have a minimal effect on QOL when disability-related variables are taken into account. METHODS: A sample of 752 women who were postmenopausal completed a written survey. The structural equation model contained two measured predictors (age, severity of postpolio sequelae) and one latent predictor (menopause symptoms defined by four measured indicators). Functional status (defined by two measured indicators) was included as a mediator, with QOL (defined by three measured indicators) as the outcome. RESULTS: The original model yielded acceptable fit indices (CFI = 0.96, RMSEA = 0.055) but resulted in a number of unexpected relationships that proved to be artifacts after model respecification. The respecified model yielded a nonsignificant chi-square value, which indicated no significant discrepancy between the proposed model and the observed data (chisquare = 18.5, df = 13, p = 0.138). All fit indices indicated a good fit: CFI = 0.997, NNFI = 0.987, chi-square/df = 1.43, and RMSEA = 0.024. CONCLUSIONS: When the effects of postpolio sequelae and functional status are included in the structural equation model, only the psychological symptoms of menopause play a prominent role in explaining QOL in this sample. The clinical implications of these findings suggest that attention to psychological symptoms and an exclusive focus on the physical aspects of menopause to the exclusion of other midlife life stressors and influences on a woman's psychological well-being ignore the larger context of life in which they live. In particular, many women with disabilities may contend with additional or exacerbated stressors related to their disability.

Adaptation, Psychological↗

PubMed2006

Duration of breast feeding and cognitive function: Population based cohort study.

Some evidence suggests that breast feeding is weakly but positively associated with cognitive function. This association has been robust to adjustment for various confounders. The aim of this paper is to determine if duration of breast feeding is associated with cognitive function in late childhood. Data was abstracted from the 1970 British Cohort Study. 11004 liveborn white singletons born during 5-11 April 1970 in the United Kingdom were followed from birth to 10 years. Cognitive function at 10 years is the dependent variable, a latent construct composed of one ability test and three performance measures. Estimates derived from multiple linear regression and structural equation modeling were compared. Effect sizes were estimated using standardized coefficients (SC). Differences in cognitive function according to breast feeding duration were estimated to be small by multiple linear regression (SC = 0.07) and much smaller and non-significant as estimated by structural equation modeling (SC = 0.02) after adjusting for parental socioeconomic status (SES), birth weight, parity, gestational age, maternal age and maternal smoking. Differences in cognitive function according to duration of breast feeding appear to be small and of little clinical importance as estimated by structural equation modeling.

Breast Feeding↗

PubMed2002

Drug use and neurobehavioral, respiratory, and cognitive problems: precursors and mediators.

PURPOSE: To test a model of the early predictors and mediators of drug use and respiratory, neurobehavioral, and cognitive problems in adolescence and young adulthood. METHODS: We prospectively examined self-reported measures of unconventional behavior, peer- and self-drug use, and self-reported health problems in a sample of 286 males and 327 females. The sample represented the northeastern United States at the time the data were first collected in 1975. The participants were assessed in early, middle, and late adolescence and in young adulthood. Latent variable structural equation models were used to examine the data. RESULTS: Structural equation modeling conducted on the data provided support for the proposed longitudinal model. The findings indicated that adolescent drug use was associated indirectly with respiratory and directly with neurobehavioral and cognitive symptoms in young adulthood. Adolescent drug use during middle and late adolescence served as a mediator between unconventional behavior in early adolescence and health problems in young adulthood. CONCLUSIONS: A reduction in adolescent drug use may reduce respiratory and neurobehavioral and cognitive symptoms in young adulthood. This study identifies several points in the biopsychosocial pathways in adolescence leading to later health problems in young adulthood.

Adolescent↗

PubMed1998

Top-down, bottom-up, and horizontal models: the direction of causality in multidimensional, hierarchical self-concept models.

A new structural equation modeling approach to questions of the direction of causal flow between global and specific multidimensional measures of self-concept (SC) in two 2-wave, longitudinal studies demonstrated that (a) higher order factors were unable to explain relations among first-order factors at Time 1 (T1), at Time 2 (T2), or between T1 and T2; (b) T1 global SC had little effect on specific SC factors at T2 (a top-down model), but specific factors at T1 had even less effect on T2 global SC (a bottom-up model); and (c) many specific factors were more stable than global factors, but higher order factors were most stable. Results provide little support for top-down, bottom-up, or reciprocal models, instead arguing for a horizontal model in which each T2 SC factor is primarily a function of the matching T1 SC. This casts further doubt on the usefulness of hierarchical representations of SC.

Achievement↗

PubMed2006

Computation of individual latent variable scores from data with multiple missingness patterns.

Latent variable models are used in biological and social sciences to investigate characteristics that are not directly measurable. The generation of individual scores of latent variables can simplify subsequent analyses. However, missing measurements in real data complicate the calculation of scores. Missing observations also result in different latent variable scores having different degrees of accuracy which should be taken into account in subsequent analyses. This manuscript presents a publicly available software tool that addresses both these problems, using as an example a dataset consisting of multiple ratings for ADHD symptomatology in children. The program computes latent variable scores with accompanying accuracy indices, under a 'user-specified' structural equation model, in data with missing data patterns. Since structural equation models encompass factor models, it can also be used for calculating factor scores. The program, documentation and a tutorial, containing worked examples and specimen input and output files, is available at http://statgen.iop.kcl.ac.uk/lsc .

Attention Deficit Disorder with Hyperactivity↗

PubMed2004

Detection of causal relationships between factors influencing adverse side-effects from anaesthesia and convalescence following surgery: a path analytical approach.

BACKGROUND AND OBJECTIVE: The anaesthesiologist's preoperative interview with the patient is important in preparing the patient for surgery. Its potential protective influence on adverse side-effects from anaesthesia and convalescence is rarely investigated within the context of other perioperative factors. Structural equation modelling allows detection and quantification of all causal relationships and mediator effects in multivariate models. Therefore, this method is presented as a tool and applied to discover the influence of the preoperative interview within socio-demographic variables and duration of surgery on complaints and recovery after anaesthesia. METHODS: The influence of individual satisfaction with the anaesthesiologist's preoperative interview on postoperative events such as nausea/vomiting, difficulties in recovering from anaesthesia, experience of postoperative pain, physical discomfort and satisfaction with convalescence expressed by the patient was analysed by means of structural equation modelling. The variables gender, age and duration of surgery were also included as predictors in the analyses. The model in the total sample of 710 patients was then analysed for structural differences between groups treated either with propofol (n = 204) or with isoflurane + nitrous oxide (n = 267) for maintenance of anaesthesia. RESULTS: The model revealed that the anaesthesiologist's preoperative interview in combination with associated mediating side-effects explains 45% of the variance of 'feeling physical discomfort' and 18% of the variance of 'satisfaction with convalescence'. The same model could be fitted in the propofol and the isoflurane + nitrous oxide group. Moreover, the structure and the strength of causal relations between variables were identical in the two groups. CONCLUSIONS: The anaesthesiologist's efforts to improve the interview with the patient by more reassuring and proper information will result in less side-effects from anaesthesia and better recovery from surgery. It could be demonstrated that structural equation modelling is a powerful tool for detection of causal relationships and mediator effects in perioperative medicine.

Adolescent↗

PubMed1994

Overview of methodological issues in the study of chronic care populations.

The intent of the methodology section of this volume was to provide an overview of recent thinking about analytic techniques that can be used to study chronic care populations, particularly dementia SCUs. As discussed earlier in this article, although not unique to these populations, longitudinal analysis of chronic care populations frequently involves several problems: nonequivalent comparison groups, unbalanced designs, censoring and attrition, autocorrelation (correlated repeated measures) and heterogeneous correlations across repeated measures. The last 5 years has witnessed considerable change and growth in the development of longitudinal modelling methodologies. Although developments in modelling cut across disciplines, there has been a focus on certain types of methods in several fields of applied statistics: psychometrics (e.g., analysis of change, item response theory, Rasch modelling of binary outcomes), mathematical sociology (e.g., structural equation modelling), demography (e.g., transition modelling), epidemiology (e.g., risk modelling), and biostatistics (e.g., examination of intervention effects using marginal and random effects modelling of repeated measures). An important issue is the interrelationship between measurement and outcome assessment. Source of measurement error must be considered (see Zimmerman and Magaziner in this volume), as must bias in assessments (see Teresi and Golden in this volume). While it has long been known that poor measurement can attenuate and bias estimates of longitudinal effects, the answer is not to attempt artificial solutions through use of corrections for attenuation (unreliability). Design and sampling issues are also critical to the correct conduct of any longitudinal study. Otherwise, estimates of prevalence, incidence, and intervention effects will be in error (see Beckett and Evans, in this volume). Several modelling approaches have been reviewed. Different points of view regarding change analysis have been presented; controversy remains regarding the "best" methods for examining change (see the commentary by Rogosa in this volume). Theory building using methods such as structural equation modelling remains a staple of longitudinal analysis, although several caveats have been discussed. New or revisited methodologies (random effects modelling, of which growth curve analysis can be viewed as a special case and event history modelling) offer promise in dealing with the knotty problems inherent in the longitudinal study of chronic care populations, namely, censoring, attrition, and unbalanced designs resulting in missing data (see the commentary by Nesselroade, in this issue). However, it remains clear that no one model or approach will be optimal for all applications.

Activities of Daily Living↗

PubMed2003

The potential synergy between cognitive models and modern psychometric models.

Analyses of cognitive aspects of survey methodology (CASM) and psychometric analysis are two methods that are able to complement each other. We use concrete examples to illustrate how psychometric analyses can test hypotheses from CASM. The psychometrics framework recognizes that survey responses are affected by other factors than the concept being assessed, for example by cognitive factors and processes. Such factors are subsumed under the concept of measurement error. Possible sources of measurement error can be tested, e.g. by randomized experiments. A standard way to reduce measurement error is to ask several questions about the same concept and combine the answers into a multi-item scale that is more precise than the individual items. Techniques like structural equation models use the item correlations to assess the magnitude of measurement error and to test the assumptions behind the multi-item scale, e.g. the effect of common response choices and item time frames. A central problem in modern psychometrics is how to model the mapping of the continuous latent variable onto the item response choice categories. This is achieved by threshold models (e.g. item response models and structural equation models for categorical data). These models can, for example, analyze the impact of mode of administration, test whether the items function in the same way for all people (measurement invariance/differential item functioning) and examine the consistency of responses from any single person. Such analyses provide new possibilities for combining psychometrics and cognitive methods.

Attitude to Health↗

PubMed2000

The SF-36 summary scales: problems and solutions.

To determine the accuracy of the SF-36 summary mental and physical health scales in reflecting their underlying subscales using the traditional method of scoring based on factor coefficients derived through principle components analysis and orthogonal rotation. A representative Australian population survey containing the SF-36 was used to obtain factor coefficients from principle components analysis and orthogonal rotation for scoring the physical component summary (PCS) and the mental component summary (MCS) of the SF-36 in the traditional way. In addition two other methods were used to produce coefficients. The first method used maximum likelihood extraction and oblique rotation. The second method fit a structural equation model to the data in a confirmatory factor analysis. The coefficients derived by each of the methods were applied to the data of a second representative population survey. This survey also provided data on physical and mental health status which allowed comparison of the summary scores and underlying subscales according to various health states. Neither of the scoring methods based on the exploratory factor analyses methods (orthogonal and oblique) produced summary scale scores, by age group, that adequately reflected the underlying subscales. When coefficients derived using structural equation modeling were fit to the data in a confirmatory factor analysis the MCS and PCS accurately reflected their underlying subscale scores. They also produced MCS and PCS scores for the various health states as would be expected from the underlying subscales. The traditional methods of scoring the SF-36 summary scales produce results that would not be expected from the underlying subscales. The problem was only corrected by fitting a structural equation model to the data in a confirmatory factor analysis. The results advise caution in the use of the SF-36 summary scales and suggests that alternative methods of developing factor coefficients need to be employed in studies using the SF-36 summary scales.

Adolescent↗

PubMed2004

Wellness lifestyles II: Modeling the dynamic of wellness, health lifestyle practices, and Network Spinal Analysis.

OBJECTIVE: Empirical application of a theoretical framework linking use of Network Spinal Analysis (NSA; a holistic, wellness-oriented form of complementary and alternative medicine [CAM]), health lifestyle practices, and self-reported health and wellness. DESIGN: Cross-sectional self-administered survey study. RESPONDENTS: Two thousand five hundred and ninety-six (2596) patients from 156 offices of doctors who were members of the Association for Network Chiropractic (currently titled Association for Network Care); estimated response rate was 69%. MEASURES: Exogenous variables entered into the structural equation model include gender, age, education, income, marital status, ailments, life change, and trauma. A wellness construct consisted of calculated difference scores between two referents, "presently" and "before Network" care, for self-reported items representing wellness domains of physical state, mental-emotional state, stress evaluation, and life enjoyment. Positive reported change in nine items assembled into dietary practices, health practices, and health risk dimensions serve as indicators of the construct of changes in health lifestyle practices. The NSA care construct consisted of duration of care in months, awareness of energy and awareness of breathing since beginning Network care. RESULTS: Of the exogenous variables only gender, age, and education remain in the final parsimonious structural equation model in these data. Reported wellness benefits accrue to individuals along a direct path from both self-reported positive lifestyle change (0.22), and from NSA care (0.43). The path (0.65) from NSA care to positive health lifestyle changes indicates that NSA care also has an indirect effect on wellness through changes in health lifestyle practices. CONCLUSIONS: The Structural Equation model tested in these analyses lends support to our theoretical framework linking wellness, health lifestyles, and CAM. This study provides further evidence that our measurements of health and wellness are particularly appropriate for investigating wellness-oriented CAM. There is a positive relationship between the experience of NSA care and self-reported improvements in wellness as well as self-reported changes in lifestyle practices. NSA care users tend toward the practice of a positive health lifestyle, which also has a direct effect on reported improvements in wellness. These empirical links are discussed relative to the sociodemographic characteristics of this population and show that use of NSA care is an aspect of a wellness lifestyle.

Adult↗

PubMed1994

Network interactions among limbic cortices, basal forebrain, and cerebellum differentiate a tone conditioned as a Pavlovian excitor or inhibitor: fluorodeoxyglucose mapping and covariance structural modeling.

1. The objective was to examine how opposite learned behavioral responses to the same physical tone were differentiated by the pattern of interactions between extraauditory neural regions. This was pursued using a new approach combining behavior, neuroimaging, and network analysis to integrate information about differences in regional activity with differences in the covariance relationships between brain areas. 2. A tone was used as either a Pavlovian conditioned excitor or inhibitor. Rats were conditioned with reinforced trials of a conditioned excitor (A+) intermixed with nonreinforced trials of a tone-light compound (AX-). The tone was the excitor (A+) for the tone-excitor group and was the inhibitor (X-) for the tone-inhibitor group. After conditioning, all rats were injected with [14C(U)]2-fluoro-2-deoxyglucose (FDG) and presented with the same tone. 3. FDG autoradiography was used to measure regional activity and to generate interregional correlations of activity resulting from the presentation of the tone. A stepwise discriminant analysis was used to select brain regions that differentiated the excitor from the inhibitor effects. 4. Network analysis consisted of constructing an anatomic model of the brain regions, selected by the discriminant analysis, linking the regions with their known anatomical connections. Then, functional models for the tone-excitor and -inhibitor groups were constructed using structural equation modeling. Correlations of activity between regions were decomposed to calculate numerical weights, or path coefficients, for each anatomic path. These path coefficients were used to compare the interactions for the tone-excitor and -inhibitor models. 5. Regional differences in FDG uptake were found in the sulcal frontal cortex (SFC), lateral septum (LS), medial septum/diagonal band (MS/DB), retrosplenial cortex (RS), and dentate-interpositus nuclei of the cerebellum (DEN). Discriminant analysis selected three other regions that significantly discriminated the tone-excitor and -inhibitor groups: perirhinal cortex (PRh), nucleus accumbens (ACB), and the anteroventral nucleus of the thalamus (AVN). 6. Structural equation modeling identified two functional circuits that differentiated the groups. One involved the basal forebrain regions (LS, MS/DB, ACB) and the other limbic thalamocortical structures (SFC, RS, PRh, AVN). Differences in the interactions within these circuits were mainly in sign of the covariance relationships between regions, from positive for the tone-excitor model to negative path coefficients for the tone-inhibitor model. The path coefficient between the basal forebrain circuit and the limbic thalamocortical circuit showed the largest magnitude difference. This quantitative difference was mediated by a path from the MS/DB to PRh.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed2000

Evaluation of a model of attention with confirmatory factor analysis.

Structural equation modeling (specifically, analysis of moment structures; J. L. Arbuckle, 1996) was used to evaluate the goodness of fit of a model of components of attention (A. F. Mirsky, B. J. Anthony, C. C. Duncan, M. B. Aheam, & S. G. Kellam, 1991) to neuropsychological test data from 2 samples. One sample consisted of psychiatrically normal persons with and without sleep-disordered breathing, and the other sample consisted of the adults studied by A. F. Mirsky et al. (1991), who gave rise to this model. That sample included psychiatric patients as well as normals. An exploratory data reduction procedure, principal-components analysis, suggested that attention might be conceptualized as composed of 4 independent elements or components: focus-execute, sustain, shift, and encode. Neither the proposed orthogonal model nor a model permitting correlated factors adequately fit either data set, suggesting that these 4 attention constructs are as yet not clearly validated in the measures used to assess them.

Adult↗

PubMed2004

Modelling functional integration: a comparison of structural equation and dynamic causal models.

The brain appears to adhere to two fundamental principles of functional organisation, functional integration and functional specialisation, where the integration within and among specialised areas is mediated by effective connectivity. In this paper, we review two different approaches to modelling effective connectivity from fMRI data, structural equation models (SEMs) and dynamic causal models (DCMs). In common to both approaches are model comparison frameworks in which inferences can be made about effective connectivity per se and about how that connectivity can be changed by perceptual or cognitive set. Underlying the two approaches, however, are two very different generative models. In DCM, a distinction is made between the 'neuronal level' and the 'hemodynamic level'. Experimental inputs cause changes in effective connectivity expressed at the level of neurodynamics, which in turn cause changes in the observed hemodynamics. In SEM, changes in effective connectivity lead directly to changes in the covariance structure of the observed hemodynamics. Because changes in effective connectivity in the brain occur at a neuronal level DCM is the preferred model for fMRI data. This review focuses on the underlying assumptions and limitations of each model and demonstrates their application to data from a study of attention to visual motion.

Algorithms↗

PubMed1995

Migraine and concomitant symptoms among 8167 adult twin pairs.

We studied the inheritance of migraine and concomitant symptoms among 2690 monozygotic (1524 female and 1166 male) pairs and 5497 dizygotic (2951 female and 2546 male) twin pairs. Our material consists of a population-based questionnaire study among Finnish twins in 1981. The definition of migraine is based on a questionnaire method. Concordance was assessed using probandwise concordance rates and tetrachoric correlations for monozygotic (MZ) and dizygotic (DZ) twin pairs. For estimating the contribution of genetic factors to the susceptibility of migraine, a polygenic multifactorial model was used. Structural equation models were applied for estimating variance components and to compare different genetic models. Nearly one-half (40% to 50%) of the liability to migraine is attributable to genetic factors. In all structural analyses, the model with both additive genetic and unshared environmental component had the best goodness-of-fit value. The genetic component varied between 34% to 51% in different migraine types. There were no remarkable differences between sexes except in the effects due to dominance, where the proportion was 26% for men and 14% for women. Concomitant symptoms among subjects within pairs concordant for headache had genetic effects varying from 56% (subjects with unilaterality) and 56% (subjects with visual symptoms) to 45% (persons with nausea and vomiting). The two threshold model of headache points to the continuum model of headache, and the thresholds represent different levels of severity of the pain. Our results emphasize a multifactorial and higher than previously reported genetic pattern in the etiology of migraine. Also unshared environmental factors play an important role.

Diseases in Twins↗

PubMed2004

Testing the functional status model in patients with chronic obstructive pulmonary disease.

BACKGROUND: Patients with chronic obstructive pulmonary disease usually experience gradual functional status degradation, especially dyspnoea, which may affect their daily activities and, eventually, quality of life. A full understanding of both their physiological and psychological functional status is therefore beneficial for effective treatment and helping patients regain or maintain control of their lives. METHOD: Based on a non-experimental research design, 138 patients to test a hypothesized model of functional status in patients with chronic obstructive pulmonary disease, using structural equation modelling, were recruited from a medical center. Data were collected using questionnaires, 6-minute walking distance measurement, and pulmonary function test results recorded in patients' medical records. The proposed functional status model incorporated the exogenous variables disease severity and dyspnoea, and the endogenous variables age, exercise tolerance, fatigue, depression, anxiety, health perception and functional performance. Structural equation modelling with the lisrel software was used to establish a functional status model with those exogenous and endogenous variables. RESULTS: The results indicated a good fit between the proposed functional status model and the data collected [chi(2) = 8.84, P = 0.64, chi(2)/d.f. = 0.80, Goodness of Fit Index (GFI) = 0.98, adjusted GFI (AGFI) = 0.95, root mean square residual (RMR) = 0.04, Critical N (CN) = 384.26]. Coefficients for paths in the functional status model all demonstrated statistical significance. CONCLUSION: The functional status model was shown to consist of functional performance, functional capacity and other concepts, including disease severity, dyspnoea, age, exercise tolerance, fatigue, depression, anxiety and health perception. These results can be used to develop a suitable functional status model for chronic obstructive pulmonary disease, and could act as a reference for formulating future strategies and intervention procedures for further development of functional status.

Activities of Daily Living↗

PubMed2004

Major psychological factors affecting acceptance of gene-recombination technology.

The purpose of this study was to verify the validity of a causal model that was made to predict the acceptance of gene-recombination technology. A structural equation model was used as a causal model. First of all, based on preceding studies, the factors of perceived risk, perceived benefit, and trust were set up as important psychological factors determining acceptance of gene-recombination technology in the structural equation model. An additional factor, "sense of bioethics," which I consider to be important for acceptance of biotechnology, was added to the model. Based on previous studies, trust was set up to have an indirect influence on the acceptance of gene-recombination technology through perceived risk and perceived benefit in the model. Participants were 231 undergraduate students in Japan who answered a questionnaire with a 5-point bipolar scale. The results indicated that the proposed model fits the data well, and showed that acceptance of gene-recombination technology is explained largely by four factors, that is, perceived risk, perceived benefit, trust, and sense of bioethics, whether the technology is applied to plants, animals, or human beings. However, the relative importance of the four factors was found to vary depending on whether the gene-recombination technology was applied to plants, animals, or human beings. Specifically, the factor of sense of bioethics is the most important factor in acceptance of plant gene-recombination technology and animal gene-recombination technology, and the factors of trust and perceived risk are the most important factors in acceptance of human being gene-recombination technology.

Adolescent↗