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Cost-effectiveness analysis for health communication programs.

This article describes methods for analyzing the cost-effectiveness of health communication programs, focusing in particular on estimating program effectiveness with econometric methods that address experimental and quasi-experimental designs (and their absence), national or subnational program coverage, and endogenously targeting of programs. Experimental designs provide a gold standard for assessing effectiveness but are seldom feasible for large-scale health communication programs. Even in the absence of such designs, however, fairly simple methods can be used to examine intermediate objectives, such as program reach, which in turn can be linked to program costs to estimate cost effectiveness. When moving beyond program reach to behavioral or other outcome measures, such as contraceptive use or fertility, or when faced with full-coverage national programs, more elaborate data and methods are required. We discuss data requirements and assumptions necessary in each case, focusing on single-equation multiple regression models, structural equations models, and fixed effects estimators for use with longitudinal data, and then describing how cost information can be incorporated into econometric models so as to get measures of the cost-effectiveness of communication interventions.

Cost-Benefit Analysis↗

Comparative stigma of HIV/AIDS, SARS, and tuberculosis in Hong Kong.

This study compares public stigma towards three types of infectious diseases- human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), severe acute respiratory syndrome (SARS), and tuberculosis (TB)-tests an attribution model of stigma, and explores the relationships between stigma and public attitudes towards government policies in Hong Kong. Using a population-based telephone survey, 3011 Hong Kong Chinese adults were randomly assigned to one of the three disease conditions and were interviewed about their attitudes and beliefs towards the assigned disease. Findings showed that public stigma was the highest towards HIV/AIDS, followed by TB and SARS. Using multi-sample model structural equation modeling, we found that the attributions of controllability, personal responsibility, and blame were applicable in explaining stigma across three disease types. Knowledge about the disease had no significant effect on stigma. Participants with less stigmatizing views had significantly more favorable attitudes towards government policies related to the diseases. The study is an important attempt in understanding the attributional mechanisms of stigma towards infectious diseases. Implications for stigma reduction and promotion of public awareness and disease prevention are discussed.

Acquired Immunodeficiency Syndrome↗

Relations of positive and negative affectivity to anxiety and depression in children: evidence from a latent variable longitudinal study.

The tripartite model of anxiety and depression has been studied with adults; however, support is still emerging with children concerning measurement and relations between positive (PA) and negative (NA) affect and psychopathology. In this longitudinal study of 270 4th- to 11th-grade children (mean age = 12.9 years, SD = 2.23). confirmatory factor analysis supported a 2-factor orthogonal model of children's self-reported affect and revealed that the concurrent relations of NA and PA to anxiety and depression symptoms were consistent with the tripartite model. Structural equation modeling demonstrated moderate cross-time stability of trait PA and NA, consistent with a temperament view of these factors, as well as partial support for the role of NA and PA in the development of anxiety and depression symptoms in children.

Anxiety Disorders↗

Testing a four-factor model of psychopathy and its association with ethnicity, gender, intelligence, and violence.

Although a 2-factor model has advanced research on the psychopathy construct, a 3-factor model was recently developed that emphasized pathological personality and eliminated antisocial behavior. However, dropping antisocial behavior from the psychopathy construct may not be advantageous. Using a large sample of psychiatric patients from the MacArthur Risk Assessment Study (J. Monahan & H. J. Steadman, 1994), the authors used confirmatory factor analysis to test a 4-factor model of psychopathy, which included interpersonal, affective, and behavioral impulsivity dimensions and an antisocial behavior dimension. Model fit was good for this 4-factor model, even when ethnicity, gender, and intelligence variables were included in the model. Structural equation modeling was used to compare the 3- and 4-factor models in predicting proximal (violence) and distal (intelligence) correlates of psychopathy.

Adult↗

A measurement model of medication adherence to highly active antiretroviral therapy and its relation to viral load in HIV-positive adults.

This study compared a multiple method measurement model of highly active antiretroviral therapy (HAART) adherence with single-method models to determine optimal validity in predicting HIV viral load. Repeated measures of antiretroviral adherence were collected over a 15-month period using three different measurement methods: a self-report questionnaire, an adherence interview item, and electronic medication monitoring. The participants included HIV-positive men and women (n = 323) who were currently prescribed HAART. Single-factor models composed of multiple measurements over time were developed for each adherence method and HIV viral load. The three adherence methods were then combined in a second order factor measurement model. Structural equation modeling was used to test the models. Mean adherence, defined as percent of doses taken, was 92%, 90%, and 57% by self-report, interview, and electronic monitoring, respectively. Reliability of individual measurements of adherence was low. Four or seven assessments were needed to attain acceptable stability, depending on the method. The second-order factor model of adherence fit the data and explained 45% of the variability in HIV viral load. Models including only one method of assessing adherence explained between 20% and 24% of the variability. Models that included both self-report and electronic monitoring optimized predictive validity. Using at least two different methods of adherence measurement, each assessed at multiple times is recommended to derive reliable and valid measurement of medication adherence, which is predictive of biological outcomes such as HIV viral load.

Adolescent↗

Heritability of neck pain: a population-based study of 33,794 Danish twins.

OBJECTIVES: To determine the heritability of neck pain in a large population-based study of twins. METHODS: Data on lifetime prevalence of neck pain from a population-based cross-sectional survey of Danish twins were used. To assess twin similarity, the probandwise concordance rates, zygosity-specific odds ratios and tetrachoric correlations were calculated and compared for monozygotic and dizygotic twins. Using biometric modelling (structural equation modelling), the genetic and environmental contributions of the liability to neck pain were estimated. RESULTS: A total of 33,794 twins (response rate 73%) answered the questions regarding neck pain. Probandwise concordance rates, zygosity-specific odds ratios and tetrachoric correlations showed a significant genetic effect on neck pain. An overall additive genetic component of 44% was found. The genetic effect decreased with age, accounting for only 10% in the oldest male group and 0% in the oldest female group. There was a statistically significant difference in heritability between males and females (34 vs 52%, P<0.0001). CONCLUSIONS: Genes play a significant role in neck pain, particularly in women. However, the genetic influence becomes gradually less important with increasing age, and environmental factors dominate almost completely in the older age groups.

Adult↗

Social support and depressive symptomatology among HIV-positive women: the mediating role of self-esteem and mastery.

Women constitute an increasing proportion of individuals contracting HIV in the United States and, once diagnosed, are living longer lives since the advent of combination antiretroviral therapies. HIV-positive women, who are disproportionately ethnic minority, face unique challenges to their psychosocial adaptation. Findings from a survey of 373 mainly indigent African-American and Puerto Rican women living with HIV/AIDS in the New York City area indicated high levels of depressive symptomatology, which were inversely related to HIV-related social support from friends, relatives, partner, and groups/ organizations. In line with the Cognitive Adaptation Model, structural equation modeling indicated that psychological resourcefulness (i.e., self-esteem and mastery) mediated the effects of social support on depressive symptomatology. Findings suggest the need to assess HIV-positive women for social isolation and depression and to provide them with interventions such as support groups that capitalize on their existing strengths, including their psychological resourcefulness.

Acquired Immunodeficiency Syndrome↗

A multimethod assessment of social intervention effects on narcotics use and property crime.

Log-linear modeling, structural equation modeling, repeated measures analysis of variance, and time series analysis are discussed for their utility in evaluating the temporal effects of social interventions. Methods are illustrated by applications examining the independent and joint temporal effects of methadone maintenance treatment and legal supervision on narcotics use and property crime among narcotics addicts. Convergent results from a multimethod assessment of the issue show that methadone maintenance has long-term and short-term suppressive effects on narcotics use and property crime. More complicated but complementary findings have been found in evaluating the effectiveness of legal supervision.

Analysis of Variance↗

Multilevel models for censored and latent responses.

Multilevel models were originally developed to allow linear regression or ANOVA models to be applied to observations that are not mutually independent. This lack of independence commonly arises due to clustering of the units of observations into 'higher level units' such as patients in hospitals. In linear mixed models, the within-cluster correlations are modelled by including random effects in a linear model. In this paper, we discuss generalizations of linear mixed models suitable for responses subject to systematic and random measurement error and interval censoring. The first example uses data from two cross-sectional surveys of schoolchildren to investigate risk factors for early first experimentation with cigarettes. Here the recalled times of the children's first cigarette are likely to be subject to both systematic and random measurement errors as well as being interval censored. We describe multilevel models for interval censored survival times as special cases of generalized linear mixed models and discuss methods of estimating systematic recall bias. The second example is a longitudinal study of mental health problems of patients nested in clinics. Here the outcome is measured by multiple questionnaires allowing the measurement errors to be modelled within a linear latent growth curve model. The resulting model is a multilevel structural equation model. We briefly discuss such models both as extensions of linear mixed models and as extensions of structural equation models. Several different model structures are examined. An important goal of the paper is to place a number of methods that readers may have considered as being distinct within a single overall modelling framework.

Adolescent↗

Network analysis of cortical visual pathways mapped with PET.

Brain metabolic mapping techniques, such as positron emission tomography (PET), can provide information about the functional interactions within entire neural systems. With the large quantity of data that can accumulate from a mapping study, a network analysis, which makes sense of the complex interactions among neural elements, is necessary. A network analysis was performed on data obtained from a PET study that examined both the changes in regional cerebral blood flow (rCBF) and interregional correlations among human cortical areas during performance of an object vision (face matching) and spatial vision (dot-location matching) task. Brain areas for the network were selected based on regions showing significant rCBF or interregional correlations between tasks. Anterior temporal and frontal lobe regions were added to the network using a principal components analysis. Interactions among selected regions were quantified with structural equation modeling. In the structural equation models, connections between brain areas were based on known neuroanatomy and the interregional correlations were used to calculate path coefficients representing the magnitude of the influence of each directional path. The combination of the anatomical network and interregional correlations created a functional network for each task. The functional network for the right hemisphere showed that in the object vision task, dominant path influences were among occipitotemporal areas, while in the spatial vision task, occipitoparietal interactions were stronger. The network for the spatial vision task also had a strong feedback path from area 46 to occipital cortex, an effect that was absent in the object vision task. There were strong interactions between dorsal and ventral pathways in both networks. Functional networks for the left hemisphere did not differ between tasks. Networks for the interhemispheric interactions showed that the dominant pathway in the right hemisphere also had stronger effects on homologous left hemisphere areas and are consistent with a hypothesis that intrahemispheric interactions were greater in the right hemisphere in both tasks, and that these influences were transmitted callosally to the left hemisphere.

Adult↗

Effects of empowerment on pharmacists' organizational behaviors.

OBJECTIVE: To investigate the effects of power factors, need for achievement, and empowerment on commitment, loyalty, identification, and job turnover intention among pharmacists. DESIGN: Cross-sectional study. SETTING: United States. PARTICIPANTS: 447 licensed pharmacists nationwide. INTERVENTION: Self-administered questionnaire. MAIN OUTCOME MEASURES: Structural equation modeling was used to assess the fit of the theoretical model and examine the effects of empowerment on pharmacists' behaviors within their organizations using pharmacists' self-reports. RESULTS: An overall response rate of 42.2% was obtained. The test of the hypothesized model using structural equation modeling resulted in a satisfactory fit. The effects of power factors and need for achievement on psychological empowerment (gamma11 = .75, gamma12 = .27) and structural empowerment (gamma21 = .81, gamma22 = .20) were examined. Also, the effects of psychological empowerment and structural empowerment on loyalty (beta31 = .05, beta32 = .69), commitment (beta41 = - .09, beta42 = .92), and identification (beta51 = .05, beta52 = .78) were analyzed. Finally, the effects of loyalty (beta63 = -.24), commitment (beta64 = -.74), and identification (beta65 = .35) on job turnover intention were assessed. CONCLUSION: Kanter's theory, which maintains that structures within organizations have an impact on organizational behaviors, was supported by our findings. Pharmacists' organizational behaviors such as commitment, loyalty, identification, and job turnover intention are influenced by structural empowerment. Given the pharmacist supply-and-demand imbalances of the past few years, organizations should make every effort to retain the pharmacists currently in their employ.

Cross-Sectional Studies↗

Structural modeling of dynamic changes in memory and brain structure using longitudinal data from the normative aging study.

This is an application of new longitudinal structural equation modeling techniques to time-dependent associations of memory and brain structure measurements. There were 225 participants aged 30-80 years at baseline who were measured again after a 7-year interval on both the lateral ventricular size and Wechsler memory score. Multiple regression analyses show nonlinear associations with age but no relationships among longitudinal changes. Mixed-effects latent growth curve analyses and analyses based on latent difference scores indicate that longitudinal changes in both variables are reasonably well described by an exponential or dual change model. Bivariate dynamic structural equation modeling analyses indicate age-lagged changes operate in a coupled-over-time fashion, with the brain measure (lateral ventricular size) as a leading indicator in time of memory (Wechsler memory score) declines.

Adult↗

Instruments for causal inference: an epidemiologist's dream?

The use of instrumental variable (IV) methods is attractive because, even in the presence of unmeasured confounding, such methods may consistently estimate the average causal effect of an exposure on an outcome. However, for this consistent estimation to be achieved, several strong conditions must hold. We review the definition of an instrumental variable, describe the conditions required to obtain consistent estimates of causal effects, and explore their implications in the context of a recent application of the instrumental variables approach. We also present (1) a description of the connection between 4 causal models-counterfactuals, causal directed acyclic graphs, nonparametric structural equation models, and linear structural equation models-that have been used to describe instrumental variables methods; (2) a unified presentation of IV methods for the average causal effect in the study population through structural mean models; and (3) a discussion and new extensions of instrumental variables methods based on assumptions of monotonicity.

Bias↗

Mapping cognition to the brain through neural interactions.

Brain imaging methods, such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), provide a unique opportunity to study the neurobiology of human memory. As these methods can measure most of the brain, it is possible to examine the operations of large-scale neural systems and their relation to cognition. Two neuroimaging studies, one concerning working memory and the other episodic memory retrieval, serve as examples of application of two analytic methods that are optimised for the quantification of neural systems, structural equation modelling, and partial least squares. Structural equation modelling was used to explore shifting prefrontal and limbic interactions from the right to the left hemisphere in a delayed match-to-sample task for faces. A feature of the functional network for short delays was strong right hemisphere interactions between hippocampus, inferior prefrontal, and anterior cingulate cortices. At longer delays, these same three areas were strongly linked, but in the left hemisphere, which was interpreted as reflecting change in task strategy from perceptual to elaborate encoding with increasing delay. The primary manipulation in the memory retrieval study was different levels of retrieval success. The partial least squares method was used to determine whether the image-wide pattern of covariances of Brodmann areas 10 and 45/47 in right prefrontal cortex (RPFC) and the left hippocampus (LGH) could be mapped on to retrieval levels. Area 10 and LGH showed an opposite pattern of functional connectivity with a large expanse of bilateral limbic cortices that was equivalent for all levels of retrieval as well as the baseline task. However, only during high retrieval was area 45/47 included in this pattern. The results suggest that activity in portions of the RPFC can reflect either memory retrieval mode or retrieval success depending on other brain regions to which it is functionally linked, and imply that regional activity must be evaluated within the neural context in which it occurs. The general hypothesis that learning and memory are emergent properties of large-scale neural network interactions is discussed, emphasising that a region can play a different role across many functions and that role is governed by its interactions with anatomically related regions.

Brain↗

The world economic system and international migration in less developed countries: an ecological approach.

"This paper analysed net migration within the context of [the] world economic system and urban ecological framework using the structural equation model." The author "employs linear structural equation modelling to examine determinants of international migration, using data from the World Bank World Tables, World Development Reports and the World Bank." (SUMMARY IN FRE AND SPA)

Agriculture↗

An overview of relations among causal modelling methods.

This paper provides a brief overview to four major types of causal models for health-sciences research: Graphical models (causal diagrams), potential-outcome (counterfactual) models, sufficient-component cause models, and structural-equations models. The paper focuses on the logical connections among the different types of models and on the different strengths of each approach. Graphical models can illustrate qualitative population assumptions and sources of bias not easily seen with other approaches; sufficient-component cause models can illustrate specific hypotheses about mechanisms of action; and potential-outcome and structural-equations models provide a basis for quantitative analysis of effects. The different approaches provide complementary perspectives, and can be employed together to improve causal interpretations of conventional statistical results.

Causality↗

On the relation between brain images and brain neural networks.

The relationship between brain images observed by PET and fMRI and the underlying neural activity is analysed using recent results on the detailed nature of averaged and synchronised activity of coupled neural networks and on a simplifying model of the level of blood flow caused by neural activity. The conditions on the coupled neural systems are specified that lead to structural equation models, giving support to analysis of the covariance structural equation modelling of brain imaging data. The relation between the resulting models and possible neural codes are analysed. Furthermore, a new form of structural equation model is derived, in which all neuronal activity arises as hidden variables. We discuss how the results of such analyses can be transported back to the domain of coupled temporally dynamic neural systems in the brain appropriate to EEG and MEG observations.

Brain↗

The health and well-being of caregivers of children with cerebral palsy.

OBJECTIVE: Most children enjoy healthy childhoods with little need for specialized health care services. However, some children experience difficulties in early childhood and require access to and utilization of considerable health care resources over time. Although impaired motor function is the hallmark of the cerebral palsy (CP) syndromes, many children with this development disorder also experience sensory, communicative, and intellectual impairments and may have complex limitations in self-care functions. Although caregiving is a normal part of being the parent of a young child, this role takes on an entirely different significance when a child experiences functional limitations and possible long-term dependence. One of the main challenges for parents is to manage their child's chronic health problems effectively and juggle this role with the requirements of everyday living. Consequently, the task of caring for a child with complex disabilities at home might be somewhat daunting for caregivers. The provision of such care may prove detrimental to both the physical health and the psychological well-being of parents of children with chronic disabilities. It is not fully understood why some caregivers cope well and others do not. The approach of estimating the "independent" or "direct" effects of the care recipient's disability on the caregiver's health is of limited value because (1) single-factor changes are rare outside the context of constrained experimental situations; (2) assumptions of additive relationships and perfect measurements rarely hold; and (3) such approaches do not provide a complete perspective, because they fail to examine indirect pathways that occur between predictor variables and health outcomes. A more detailed analytical approach is needed to understand both direct and indirect effects simultaneously. The primary objective of the current study was to examine, within a single theory-based multidimensional model, the determinants of physical and psychological health of adult caregivers of children with CP. METHODS: We developed a stress process model and applied structural equation modeling with data from a large cohort of caregivers of children with CP. This design allowed the examination of the direct and indirect relationships between a child's health, behavior and functional status, caregiver characteristics, social supports, and family functioning and the outcomes of caregivers' physical and psychological health. Families (n = 468) of children with CP were recruited from 19 regional children's rehabilitation centers that provide outpatient disability management and supports in Ontario, Canada. The current study drew on a population available to the investigators from a previous study, the Ontario Motor Growth study, which explored patterns of gross motor development in children with CP. Data on demographic variables and caregivers' physical and psychological health were assessed using standardized, self-completed parent questionnaires as well as a face-to-face home interview. Structural equation modeling was used to test specific hypotheses outlined in our conceptual model. This analytic approach involved a 2-step process. In the first step, observed variables that were hypothesized to measure the underlying constructs were tested using confirmatory factor analysis; this step led to the so-called measurement model. The second step tested hypotheses about relationships among the variables in the structural model. All of the hypothesized paths in the conceptual model were tested and included in the structural model. However, only paths that were significant were shown in the final results. The direct, indirect, and total effects of theoretical constructs on physical and psychological health were calculated using the structural model. RESULTS: The most important predictors of caregivers' well-being were child behavior, caregiving demands, and family function. A higher level of behavior problems was associated with lower levels of both psychological (beta = -.22) and physical health (beta = -.18) of the caregivers, whereas fewer child behavior problems were associated with higher self-perception (beta = -.37) and a greater ability to manage stress (beta = -.18). Less caregiving demands were associated with better physical (beta = .23) and psychological (beta = .12) well-being of caregivers, respectively. Similarly, higher reported family functioning was associated with better psychological health (beta = .33) and physical health (beta = .33). Self-perception and stress management were significant direct predictors of caregivers' psychological health but did not directly influence their physical well-being. Caregivers' higher self-esteem and sense of mastery over the caregiving situation predicted better psychological health (beta = .23). The use of more stress management strategies was also associated with better psychological health of caregivers (beta = .11). Gross income (beta = .08) and social support (beta = .06) had indirect overall effects only on psychological health outcome, whereas self-perception (beta = .22), stress management (beta = .09), gross income (beta = .07), and social support (beta = .06) had indirect total effects only on physical health outcomes. CONCLUSIONS: The psychological and physical health of caregivers, who in this study were primarily mothers, was strongly influenced by child behavior and caregiving demands. Child behavior problems were an important predictor of caregiver psychological well-being, both directly and indirectly, through their effect on self-perception and family function. Caregiving demands contributed directly to both the psychological and the physical health of the caregivers. The practical day-to-day needs of the child created challenges for parents. The influence of social support provided by extended family, friends, and neighbors on health outcomes was secondary to that of the immediate family working closely together. Family function affected health directly and also mediated the effects of self-perception, social support, and stress management. In families of children with CP, strategies for optimizing caregiver physical and psychological health include supports for behavioral management and daily functional activities as well as stress management and self-efficacy techniques. These data support clinical pathways that require biopsychosocial frameworks that are family centered, not simply technical and short-term rehabilitation interventions that are focused primarily on the child. In terms of prevention, providing parents with cognitive and behavioral strategies to manage their child's behaviors may have the potential to change caregiver health outcomes. This model also needs to be examined with caregivers of children with other disabilities.

Adaptation, Psychological↗