SEARCH · PubMed Health

Results for “Structural equation modeling”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources

PubMed2003

Family harmony as a protective factor against adolescent tobacco and alcohol use in Wuhan, China.

PURPOSE: To investigate the association between family harmony (FH) and tobacco and alcohol use (TAU) in Chinese adolescents. METHODS: Participants completed a survey in 1998 as part of a larger study of adolescent health in Wuhan, China. Analyses were performed on subjects for whom complete data were available (n = 183; 50.8% male; mean age = 13.17 yrs, std dev = 0.59). Structural equation modeling was utilized to quantify the relationships between the FH, TAU, depression, and academic aptitude factors. RESULTS: The conceptualized structural equation model was found to have a good fit to the data (CFI = 0.995; chi2 = 39.57 df = 38; p = 40). FH was a significant predictor of TAU (beta = -0.42, p < 0.05) and was protective. FH' was also negatively related to depression (r = -0.24, p < 0.05) and positively related to academic achievement/aptitude (r = 0.35, p < 0.05). CONCLUSIONS: These central findings highlight the value and importance placed on FH within the Chinese culture. Future prevention programs may benefit by taking into account FH as a potential mediator of TAU in adolescents in China.

Achievement↗

PubMed1998

Methods of evaluation in outcomes research.

UNLABELLED: This activity is designed for pharmacists, physicians, physician assistants, nurses, and other healthcare team members; payers for health services; and healthcare executives. GOAL: To provide basic information on the methods used and computer software available for evaluating invariant factorial structures, such as those found in health status measurement tools. OBJECTIVES: 1. Discuss why comparison of mean scores may not be appropriate when interpreting humanistic outcomes results. 2. Identify alternative methods for evaluating data from health status measurement tools, such as the SF-36. 3. Define validity, reliability, and structure. 4. Understand the value of structural equation modeling when using health status measurement tools, such as the SF-36. 5. Describe the statistical software used to perform structural equation modeling.

Data Interpretation, Statistical↗

PubMed2005

Tumour matrilysin expression predicts metastatic potential of stage I (pT1) colon and rectal cancers.

BACKGROUND AND AIMS: Nodal metastases are indisputable determinants of prognosis for colon and rectal cancer. Using classical histological criteria, many attempts to predict nodal metastasis have failed, preventing the adequate management of stage I (pT1) cancer. We investigated the role of tumour matrilysin in predicting metastatic potential, and discuss its potential use in individualising treatment of pT1 colon and rectal cancer. METHODS: The gene signature associated with nodal metastasis was investigated by cDNA array in 24 colon and rectal cancers. We studied 494 colon and rectal cancer patients to identify risk factors for nodal metastasis and evaluated the potential to predict nodal metastasis by either the logistic regression model or the Bayesian neural network model with built-in matrilysin. We then inferred possible causality of nodal metastasis from structural equation modelling. RESULTS: cDNA array revealed that matrilysin was maximally upregulated in the metastasis signature identified. Tumour matrilysin expression emerged as a stage independent risk factor for nodal metastasis, resulting in a similar predictive performance in receiver operating characteristic curve analysis in the two models. A Bayesian approach called automatic relevance determination identified matrilysin as one of the most relevant predictors examined. Structural equation modelling suggested possible direct causality between matrilysin and nodal metastasis. CONCLUSIONS: We have provided evidence that tumour matrilysin expression is a promising biomarker predicting nodal metastasis of colon and rectal cancer. Analysis of tumour matrilysin expression would help clinicians achieve the goal of individualised cancer treatment based on the metastatic potential of pT1 colon and rectal cancer.

Adenocarcinoma↗

PubMed1987

Individual differences in cognitive arithmetic.

Unities in the processes involved in solving arithmetic problems of varying operations have been suggested by studies that have used both factor-analytic and information-processing methods. We designed the present study to investigate the convergence of mental processes assessed by paper-and-pencil measures defining the Numerical Facility factor and component processes for cognitive arithmetic identified by using chronometric techniques. A sample of 100 undergraduate students responded to 320 arithmetic problems in a true-false reaction-time (RT) verification paradigm and were administered a battery of ability measures spanning Numerical Facility, Perceptual Speed, and Spatial Relations factors. The 320 cognitive arithmetic problems comprised 80 problems of each of four types: simple addition, complex addition, simple multiplication, and complex multiplication. The information-processing results indicated that regression models that included a structural variable consistent with memory network retrieval of arithmetic facts were the best predictors of RT to each of the four types of arithmetic problems. The results also verified the effects of other elementary processes that are involved in the mental solving of arithmetic problems, including encoding of single digits and carrying to the next column for complex problems. The relation between process components and ability measures was examined by means of structural equation modeling. The final structural model revealed a strong direct relation between a factor subsuming efficiency of retrieval of arithmetic facts and of executing the carry operation and the traditional Numerical Facility factor. Furthermore, a moderate direct relation between a factor subsuming speed of encoding digits and decision and response times and the traditional Perceptual Speed factor was also found. No relation between structural variables representing cognitive arithmetic component processes and ability measures spanning the Spatial Relations factor was found. Results of the structural modeling support the conclusion that information retrieval from a network of arithmetic facts and execution of the carry operation are elementary component processes involved uniquely in the mental solving of arithmetic problems. Furthermore, individual differences in the speed of executing these two elementary component processes appear to underlie individual differences on ability measures that traditionally span the Numerical Facility factor.(ABSTRACT TRUNCATED AT 400 WORDS)

Cognition↗

PubMed1997

[A new wave of behavior genetic modeling using covariance structure analysis].

A number of useful methods for analyzing covariance structure have been proposed in the studies of human behavior genetics, reflecting the fact that the behavior genetic studies are one of the main origins of covariance structure model. In this paper, I review recent progress on methodology for behavior genetic studies of twins and families from the standpoint of the structural equation modeling. Especially, genetic ACE (additive genetic, common environment and random environment) model, multivariate ACE model, genetic factor analysis model and twin-parent model are focused upon. This review also discusses how to construct applied structural equation models which are useful for psychological research.

Factor Analysis, Statistical↗

PubMed2026

Effect of a pharmacist-led mHealth app on adherence, quality of life, and glycaemic control in diabetes: A multicentre RCT.

AIMS: To evaluate whether CareAide®, a pharmacist-driven mHealth application, improves medication adherence, health-related quality of life (HRQoL), and glycaemic control in diabetes mellitus using structural equation modelling. METHODS: Pre-specified secondary analysis of the type 2 diabetes mellitus cohort from a 6-month multicentre open-label randomised controlled trial (N = 663) across three Malaysian hospitals. Adherence was assessed by MMAS-8 (subjective) and Proportion of Days Covered (PDC; pharmacy-verified). HRQoL was measured by AQoL-6D and EQ-5D-5 L. Structural equation modelling (SEM), Necessary Condition Analysis, and Importance-Performance Map Analysis (cIPMA) were applied. RESULTS: CareAide® produced large adherence gains (MMAS-8: 7.31 vs 5.55, d = 1.64; PDC ≥ 80%: 81.6% vs 33.0%; both p < 0.001). Early 3-month adherence was the strongest predictor of sustained 6-month adherence in both models (β std = 0.567 and 0.688; p < 0.001). AQoL-6D utility improved significantly (0.669 vs 0.618; d = 0.353, p < 0.001), driven by coping (d = 0.447) and relationships (d = 0.254) domains. HRQoL did not mediate adherence; gains were a direct independent benefit. The intervention effect on HbA1c was not statistically significant in the PDC-based SEM model (β =  - 0.333, p = 0.065); a group difference was, however, supported by baseline-adjusted ANCOVA (β =  - 0.41%, p = 0.002), and the complete-case comparison was non-significant (p = 0.153), so glycaemic findings warrant cautious interpretation. cIPMA identified the intervention as the primary optimisation target. CONCLUSIONS: CareAide® significantly improves medication adherence and psychosocial quality of life. Evidence for glycaemic benefit came from baseline-adjusted analysis (ANCOVA), though findings should be interpreted with caution given incomplete HbA1c data at one site. The first three months are the most critical period for pharmacist support. In this dataset, PDC appeared more sensitive than MMAS-8 to the HbA1c signal within 6 months, but this finding requires confirmation in longer studies with more complete HbA1c data. TRIAL REGISTRATION: ClinicalTrials.gov NCT06068309.

Aged↗

PubMed1999

Self-efficacy and social support as mediators in the relation between disease severity and quality of life in patients with epilepsy.

PURPOSE: This study examined the influence of two psychosocial variables mediating between disease severity and quality of life (QoL) in epilepsy; social support and mastery (measured by locus of control and self-efficacy). A model placing these two variables as mediators between disease severity and QoL was tested with structural equation modeling. METHODS: Eighty-nine patients with epilepsy (58% men, age 36+/-12 years) were given the following instruments: Liverpool Seizure Severity Scale, Interpersonal Support Evaluation List, Epileptic Self-Efficacy Scale, Locus of Control scale, and the World Health Organization's Quality of Life Questionnaire, the WHOQOL. RESULTS: Structural equation modeling showed good fit between the research model and the data (Bentler-Bonett Normalized Index of fit, 0.96; LISREL GFI, 0.95). Ninety percent of the variance of the WHOQOL was explained by a combination of disease severity, self-efficacy in epilepsy, social support, and locus of control. Mastery was found to mediate the correlation between disease severity and QoL, and social support was found to act as a mediator between disease severity and mastery. CONCLUSIONS: The study findings emphasize the possibility of improving QoL among patients with epilepsy by counseling and treatment aimed at reinforcing their self-efficacy and locus of control, as well as by improving their SoS.

Adult↗

PubMed2002

The mixed or multilevel model for behavior genetic analysis.

We propose the mixed model or multilevel model as a general alternative approach to existing behavior genetic analysis-an alternative to correlation analysis, the DeFries-Fulker analysis, and structural equation modeling. The mixed or multilevel model handles readily families of behavioral genetic data, which include paired sibling data (e.g., pairs of MZ and DZ twins) and clustered sibling data (e.g., a family of more than two biological siblings) as special cases. Not only can a family of behavioral genetic data have more than two siblings, it can also contain multiple types of siblings (e.g., a pair of MZ twins, a pair of DZ twins, a full sibling, and a half sibling). In contrast to the traditional approaches, the mixed or multilevel model is insensitive to the order of the siblings in a sibling cluster. We apply our approach to a large, nationally representative behavior genetic sample collected recently by the Add Health Study. We demonstrate the approach through several applications using both clustered and family complex behavioral genetic data: conventional variance decomposition analysis, analysis of interactions between genetic and environmental influences, and analysis of the possible genetic basis for friendship selection. We compare results from the mixed or multilevel model, Pearson's correlation analysis, and the structural equation model.

Adolescent↗

PubMed2002

Modeling condom-use stage of change in low-income, single, urban women.

This study was undertaken to identify and test a model of the cognitive antecedents to condom use stage of change in low-income, single, urban women. A convenience sample of 537 women (M=30 years old) attending two urban primary health care settings in western New York State anonymously completed questionnaires based primarily on two leading social-cognitive models, the transtheoretical model and the information-motivation-behavioral skills model. We used structural equation modeling to examine the direct and indirect effects of HIV-related knowledge, social norms of discussing HIV risk and prevention, familiarity with HIV-infected persons, general readiness to change sexual behaviors, perceived vulnerability to HIV, and pros and cons of condom use on condom-use stage of change. The results indicated two models that differ by partner type. Condom-use stage of change in women with steady main partners was influenced most by social norms and the pros of condom use. Condom-use stage of change in women with "other" types (multiple, casual, or new) of sexual partners was influenced by HIV-related knowledge, general readiness to change sexual behaviors, and the pros of condom use. These findings suggest implications for developing gender-relevant HIV-prevention interventions.

Adolescent↗

PubMed2001

The Role of Personality Traits and Goal Orientations in Strategy Use.

The aim of this study was to contribute to the development of an integrated theory on individual learning differences. To that end, theories on learning styles, personality, and achievement motivation were combined in an explanatory model (tested with structural equation modelling). Goal orientations play an important role in this model, situated between personality traits and theories of intelligence, on the one hand, and learning strategy constructs (surface learning and deep learning), on the other. Surface-level strategies were related to entity theory beliefs and ego orientation as well as to conscientiousness, agreeableness, and effort orientation. Deep-level strategies were only directly related to task orientation and intellect. The relations found shed more light on what individual differences in learning consist of and help explain regularities in learning behavior. Copyright 2001 Academic Press.

Journal Article↗

PubMed2026

Virtual reality physical education and adolescents' exercise interest and physical fitness: An explanatory sequential mixed-methods randomized trial with exploratory pathway analysis.

Traditional physical education (PE) faces declining student interest and limited fitness gains. Virtual reality (VR) offers immersive, gamified experiences, but evidence regarding its effectiveness and explanatory pathways remains limited. This explanatory sequential mixed-methods randomized trial assigned 360 adolescents (aged 13-16) from three middle schools to either VR-supported PE (n = 180) or conventional PE (n = 180) for 12 weeks, with a 4-week follow-up. Outcomes included exercise interest (validated scale), physical fitness (coordination via MABC-2, cardiorespiratory endurance via the 20-m shuttle run, explosive power via the standing long jump, and speed via the 10-m sprint), and accelerometer-measured physical activity. The qualitative component involved 38 unique students: 32 completed individual semi-structured interviews, and six additional students participated only in focus groups. Three-level linear mixed-effects models and exploratory structural equation modeling were used. The VR group showed significantly greater improvements in exercise interest (d = 0.78), coordination (d = 0.62), cardiorespiratory endurance (d = 0.55), and speed (d = 0.48) than the control group (all p < 0.001), but not in explosive power (d = 0.12, p = 0.148). Effects were partially retained at follow-up (interest d = 0.65, coordination d = 0.48, endurance d = 0.42, and speed d = 0.30), a pattern not fully consistent with a purely novelty-driven explanation. Exploratory mediation identified exercise interest as a statistically compatible explanatory pathway (indirect effect = 0.34, 95% CI [0.22, 0.46]), although the timing of measurement precludes causal interpretation. Qualitative findings contextualized these results by highlighting immersion, feedback, self-efficacy, and perceived transfer. VR-supported PE may enhance adolescents' exercise interest and selected fitness dimensions, but its limited effect on explosive power and possible novelty contribution indicate that it should complement, rather than replace, conventional PE. Longer-term studies are needed.

Humans↗

PubMed2005

The Readiness for Interprofessional Learning Scale: a possible more stable sub-scale model for the original version of RIPLS.

The original version of the Readiness for Interprofessional Learning Scale (RIPLS) was published by Parsell and Bligh (1999). Three sub-scales with acceptable or high internal consistencies were suggested, however two publications suggested different sub-scales. An investigation into how to improve the reliability for use of the RIPLS instrument with undergraduate health-care students commenced. Content analysis on the original 19 items involving experienced health-care staff resulted in four sub-scales. These sub-scales were then used to formulate a possible model within a structural equation model. The goodness of fit was assessed using a sample (n = 308) of new first year undergraduate students from 8 different health and social care programmes. The same data was fitted to each of the two original sub-scale models suggested by Parsell and Bligh (1999) and the results compared. The fit of the new four sub-scale model appears superior to either of the original models. The new four factor model was then tested on subsequent data (n = 247) obtained from the same students at the end of their first year. The fit was seen to be even better at the end of the academic year.

Humans↗

PubMedDate not supplied

Testing a theoretical model of exercise behavior for older adults.

BACKGROUND: Although there are many known benefits to exercise, only 10-30% of older adults report regular exercise. Understanding the factors that explain exercise behavior in older adults will help structure interventions that motivate these individuals to initiate and adhere to regular exercise. OBJECTIVE: The purpose of this study was to test the impact of components from two theoretical perspectives that explain exercise behavior, social cognitive theory, and the transtheoretical model. METHODS: This was a descriptive study using a sample of 179 older adults living independently in an East Coast continuing care retirement community (CCRC). A single one-time interview was completed and included: (a) stage of change for exercise, (b) self-efficacy and outcome expectations, (c) health status, (d) fear of falling, and (e) exercise activity. Model testing used structural equation modeling. RESULTS: Testing of the hypothesized model showed that 11 of the 22 paths were statistically significant. Health status and social support influenced self-efficacy and outcome expectations which directly influenced stage of change and exercise. Social support likewise directly influenced stage of change. Together the variables in the model explained 64% of exercise behavior in older adults. There was a poor fit of the hypothesized model to the data with a chi2 of 144.7, degrees of freedom (df) of 23 and a ratio of 6.3. The revised model fit the data better chi2 = 80.5, df = 19, p <.05, chi2/df = 4.2) and there was improved fit when compared to the hypothesized model (chi2 difference of 64.0, df difference of 4, p < or = l. DISCUSSION: The combined testing of the mediating components of the theory of self-efficacy as well as the incorporation of the stage of change to explain exercise behavior in older adults suggests that both of these approaches are useful. Stage of change may be particularly useful to help determine the most appropriate intervention to increase activity and exercise in older adults.

Aged↗

PubMed2003

Comparative study of the FAIR technique of perfusion quantification with the hydrogen clearance method.

Arterial spin labeling magnetic resonance methods, including flow-sensitive alternating inversion recovery (FAIR), are becoming increasingly common for the noninvasive quantification of cerebral blood flow (CBF). This report compares the FAIR method with hydrogen clearance. The latter is an established, invasive technique for CBF measurement in animals. Paired readings of CBF were obtained in gerbils to maximize the degree of spatial and temporal correspondence between methods. Flow-sensitive alternating inversion recovery (50 averages, 6.7-minute measurement time) and hydrogen clearance measurements were made concurrently. Cerebral blood flow values measured by both techniques displayed an initial decrease because of the injurious effects of electrode insertion and subsequent recovery. Mixed model regression analysis, structural equations modeling, and a simple concordance correlation coefficient analysis were performed. No evidence of a marked systematic bias in the FAIR measurements was found; mixed model regression analysis yielded relative bias estimates of 0.4 (confidence interval: 3.0, 3.9) mL. 100 g-1. min-1 and -3.7 (-12.1, 4.7) mL. 100 g-1. min-1 at 20 and 100 mL. 100 g-1. min-1, respectively. The principal limitation of the FAIR technique was the magnitude of the random measurement error (imprecision), which had a standard deviation on the order of 10 mL. 100 g-1. min-1.

Animals↗

PubMed1994

Alternative analytical methods for detecting matching effects in treatment outcomes.

Project MATCH presented a unique opportunity for a team of statisticians, data analysts and content experts to come together and explore the strengths and weaknesses of the application of various statistical models to the data of the type being collected in this large trial. The following models were evaluated: multilevel models, event history models, multiple were structural equation modeling, time series models, ordinal repeated measures designs and generalized estimating equations. No one model was found to be the perfect solution and each seemed to have something to recommend it. Future research on these methods will shed light on many issues raised. It is hoped that alcohol researchers will find useful guidelines within this chapter as they plan and carry out their studies.

Alcoholism↗

PubMed2001

How shared are age-related influences on cognitive and noncognitive variables?

Several theories have suggested that age-related declines in cognitive processing are due to a pervasive unitary mechanism, such as a decline in processing speed. Structural equation model tests have shown some support for such common factor explanations. These results, however, may not be as conclusive as previously claimed. A further analysis of 4 cross-sectional data sets described in Salthouse, Hambrick, and McGuthry (1998) and Salthouse and Czaja (2000) found that although the best fitting model included a common factor in 3 of the data sets, additional direct age paths were significant, indicating the presence of specific age effects. For the remaining data set, a factor-specific model fit at least as well as the best fitting common factor model. Three simulated data sets with known structure were then tested with a sequence of structural equation models. Common factor models could not always be falsified--even when they were false. In contrast, factor-specific models were more easily falsified when the true model included a unitary common factor. These results suggest that it is premature to conclude that all age-related cognitive declines are due to a single mechanism. Common factor models may be particularly difficult to falsify with current analytic procedures.

Adolescent↗

PubMed2005

Hypertension--a possible vulnerability marker for depression in patients with end-stage renal disease.

OBJECTIVE: This study explored the association of hypertension and psychiatric morbidity in patients with end-stage renal disease (ESRD) under adjusted personality characteristics and parental attachment. METHODS: The mental health of 121 patients with ESRD in a general teaching hospital was evaluated using the 12-item version of the Chinese Health Questionnaire (CHQ). Only 40 males and 49 females completed all the questionnaires. Ten of the 40 males and 21 of the 49 females had high scores (> or = 4) and were allotted to the case group (n = 31). The remaining 58 patients constituted the control group (CHQ < 4). RESULTS: The logistic regression model showed that hypertension, gender, and neuroticism are statistically significant covariates. Hypertension, especially, was strongly associated with depressive vulnerability (odds ratio of hypertension versus without hypertension = 9.07:1). Structural equation modeling revealed that gender difference and hypertension directly influenced the individuals' mental health status and that the influence of hypertension on mental health was highly variable. CONCLUSION: A parsimonious structural equation model provided considerable evidence that hypertension could have an important effect on depression in ESRD patients, when predisposing factors, such as personality characteristics and parental attachment, gender, duration of hemodialysis and other medical diseases were adjusted. Hence, hypertension might be a mediating factor of depressive vulnerability in ESRD patients underling genetic and environmental problems.

Aged↗

PubMed2003

Early predictors of long-term disability after injury.

BACKGROUND: Improving outcomes after serious injury is important to patients, patients' families, and healthcare providers. Identifying early risk factors for long-term disability after injury will help critical care providers recognize patients at risk. OBJECTIVES: To identify early predictors of long-term disability after injury and to ascertain if age, level of disability before injury, posttraumatic psychological distress, and social network factors during hospitalization and recovery significantly contribute to long-term disability after injury. METHODS: A prospective, correlational design was used. Injury-specific information on 63 patients with serious, non-central nervous system injury was obtained from medical records; all other data were obtained from interviews (3 per patient) during a 2 1/2-year period. A model was developed to test the theoretical propositions of the disabling process. Predictors of long-term disability were evaluated using path analysis in the context of structural equation modeling. RESULTS: Injuries were predominately due to motor vehicle crashes (37%) or violent assaults (21%). Mean Injury Severity Score was 13.46, and mean length of stay was 12 days. With structural equation modeling, 36% of the variance in long-term disability was explained by predictors present at the time of injury (age, disability before injury), during hospitalization (psychological distress), or soon after discharge (psychological distress, short-term disability after injury). CONCLUSIONS: Disability after injury is due partly to an interplay between physical and psychological factors that can be identified soon after injury. By identifying these early predictors, patients at risk for suboptimal outcomes can be detected.

Accidents, Traffic↗