708 resultados para Health Beliefs Model
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Applying the competing--risks model to multi--cause mortality,this paper provides a theoretical and empirical investigation of the positive complementarities that occur between disease--specific policy interventions. We argue that since an individual cannot die twice, competing risks imply that individuals will not waste resources on causes that are not the most immediate, but will make health investments so as to equalize cause--specific mortality. However, equal mortality risk from a variety of diseases does not imply that disease--specific public health interventions are a waste. Rather, a cause--specific intervention produces spillovers to other disease risks, so that the overall reduction in mortality will generally be larger than the direct effect measured on the targeted disease. The assumption that mortality from non--targeted diseases remains the same after a cause--specific intervention under--estimates the true effect of such programs, since the background mortality is also altered as a result of intervention. Analyzing data from one of the most important public health programs ever introduced, the Expanded Program on Immunization (EPI) of the United Nations, we find evidence for the existence of such complementarities, involving causes that are not biomedically, but behaviorally, linked.
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CONTEXT: Previous studies may have underestimated the contribution of health behaviors to social inequalities in mortality because health behaviors were assessed only at the baseline of the study. OBJECTIVE: To examine the role of health behaviors in the association between socioeconomic position and mortality and compare whether their contribution differs when assessed at only 1 point in time with that assessed longitudinally through the follow-up period. DESIGN, SETTING, AND PARTICIPANTS: Established in 1985, the British Whitehall II longitudinal cohort study includes 10 308 civil servants, aged 35 to 55 years, living in London, England. Analyses are based on 9590 men and women followed up for mortality until April 30, 2009. Socioeconomic position was derived from civil service employment grade (high, intermediate, and low) at baseline. Smoking, alcohol consumption, diet, and physical activity were assessed 4 times during the follow-up period. MAIN OUTCOME MEASURES: All-cause and cause-specific mortality. RESULTS: A total of 654 participants died during the follow-up period. In the analyses adjusted for sex and year of birth, those with the lowest socioeconomic position had 1.60 times higher risk of death from all causes than those with the highest socioeconomic position (a rate difference of 1.94/1000 person-years). This association was attenuated by 42% (95% confidence interval [CI], 21%-94%) when health behaviors assessed at baseline were entered into the model and by 72% (95% CI, 42%-154%) when they were entered as time-dependent covariates. The corresponding attenuations were 29% (95% CI, 11%-54%) and 45% (95% CI, 24%-79%) for cardiovascular mortality and 61% (95% CI, 16%-425%) and 94% (95% CI, 35%-595%) for noncancer and noncardiovascular mortality. The difference between the baseline only and repeated assessments of health behaviors was mostly due to an increased explanatory power of diet (from 7% to 17% for all-cause mortality, respectively), physical activity (from 5% to 21% for all-cause mortality), and alcohol consumption (from 3% to 12% for all-cause mortality). The role of smoking, the strongest mediator in these analyses, did not change when using baseline or repeat assessments (from 32% to 35% for all-cause mortality). CONCLUSION: In a civil service population in London, England, there was an association between socioeconomic position and mortality that was substantially accounted for by adjustment for health behaviors, particularly when the behaviors were assessed repeatedly.
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In this article we examine the potential effect of market structureon hospital technical efficiency as a measure of performance controlled byownership and regulation. This study is relevant to provide an evaluationof the potential effects of recommended and initiated deregulation policiesin order to promote market reforms in the context of a European NationalHealth Service. Our goal was reached through three main empirical stages.Firstly, using patient origin data from hospitals in the region of Cataloniain 1990, we estimated geographic hospital markets through the Elzinga--Hogartyapproach, based on patient flows. Then we measured the market level ofconcentration using the Herfindahl--Hirschman index. Secondly, technicaland scale efficiency scores for each hospital was obtained specifying aData Envelopment Analysis. According to the data nearly two--thirds of thehospitals operate under the production frontier with an average efficiencyscore of 0.841. Finally, the determinants of the efficiency scores wereinvestigated using a censored regression model. Special attention waspaid to test the hypothesis that there is an efficiency improvement in morecompetitive markets. The results suggest that the number of competitors inthe market contributes positively to technical efficiency and there is someevidence that the differences in efficiency scores are attributed toseveral environmental factors such as ownership, market structure andregulation effects.
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This paper shows how recently developed regression-based methods for thedecomposition of health inequality can be extended to incorporateindividual heterogeneity in the responses of health to the explanatoryvariables. We illustrate our method with an application to the CanadianNPHS of 1994. Our strategy for the estimation of heterogeneous responsesis based on the quantile regression model. The results suggest that thereis an important degree of heterogeneity in the association of health toexplanatory variables which, in turn, accounts for a substantial percentageof inequality in observed health. A particularly interesting finding isthat the marginal response of health to income is zero for healthyindividuals but positive and significant for unhealthy individuals. Theheterogeneity in the income response reduces both overall health inequalityand income related health inequality.
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In many research areas (such as public health, environmental contamination, and others) one deals with the necessity of using data to infer whether some proportion (%) of a population of interest is (or one wants it to be) below and/or over some threshold, through the computation of tolerance interval. The idea is, once a threshold is given, one computes the tolerance interval or limit (which might be one or two - sided bounded) and then to check if it satisfies the given threshold. Since in this work we deal with the computation of one - sided tolerance interval, for the two-sided case we recomend, for instance, Krishnamoorthy and Mathew [5]. Krishnamoorthy and Mathew [4] performed the computation of upper tolerance limit in balanced and unbalanced one-way random effects models, whereas Fonseca et al [3] performed it based in a similar ideas but in a tow-way nested mixed or random effects model. In case of random effects model, Fonseca et al [3] performed the computation of such interval only for the balanced data, whereas in the mixed effects case they dit it only for the unbalanced data. For the computation of twosided tolerance interval in models with mixed and/or random effects we recomend, for instance, Sharma and Mathew [7]. The purpose of this paper is the computation of upper and lower tolerance interval in a two-way nested mixed effects models in balanced data. For the case of unbalanced data, as mentioned above, Fonseca et al [3] have already computed upper tolerance interval. Hence, using the notions persented in Fonseca et al [3] and Krishnamoorthy and Mathew [4], we present some results on the construction of one-sided tolerance interval for the balanced case. Thus, in order to do so at first instance we perform the construction for the upper case, and then the construction for the lower case.
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Objective The aim is to analyze and compare individual BMI growth patterns of adults from Switzerland and the U.S. Methods The analyses are based on data from two population representative longitudinal household surveys, one from Switzerland, the other from the U.S. Each data set contains up to four data points for each adult individual. We use multilevel models for growth. Results It can be shown that growth patterns are different in different cohorts in the two countries: there are only small growth differences in the youngest and oldest, but large differences in the middle ages. The individual BMI increase of the middle age Swiss amounts to only half of that in the comparable U.S. individuals. Conclusion Given the much higher BMI level especially in the youngest cohort, this points to severe obesity problems in the U.S. middle aged population in the near future. A positive correlation between individual BMI level and growth may aggravate this fact.
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The purpose of this paper is to study the diffusion and transformation of scientific information in everyday discussions. Based on rumour models and social representations theory, the impact of interpersonal communication and pre-existing beliefs on transmission of the content of a scientific discovery was analysed. In three experiments, a communication chain was simulated to investigate how laypeople make sense of a genetic discovery first published in a scientific outlet, then reported in a mainstream newspaper and finally discussed in groups. Study 1 (N=40) demonstrated a transformation of information when the scientific discovery moved along the communication chain. During successive narratives, scientific expert terminology disappeared while scientific information associated with lay terminology persisted. Moreover, the idea of a discovery of a faithfulness gene emerged. Study 2 (N=70) revealed that transmission of the scientific message varied as a function of attitudes towards genetic explanations of behaviour (pro-genetics vs. anti-genetics). Pro-genetics employed more scientific terminology than anti-genetics. Study 3 (N=75) showed that endorsement of genetic explanations was related to descriptive accounts of the scientific information, whereas rejection of genetic explanations was related to evaluative accounts of the information.
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Practice of psychiatric hospitalization has considerably changed: deinstitutionnalization, brief hospitalizations, opened units, partnership with patients and complementarity with community mental health services. These changes appear simultaneously in most of industrialized countries. They are the result of social changes, evolution of mental health care, and a sharper perception of deinsertion risks through long term hospitalizations. Values of psychiatric hospital were based on a closed and protective place, where community life prepared to life in the community; they are now founded on an opened place where care aims at resolving crisis and keeping closely in touch with the community. These modifications imply to rethink hospital psychiatric care and their connections with environment. This paper describe a model of care developed in a first admission psychiatric unit.
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A form produced by Elder Affairs about what a elderly person wants and does not want when close to death.
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BACKGROUND: There is an emerging knowledge base on the effectiveness of strategies to close the knowledge-practice gap. However, less is known about how attributes of an innovation and other contextual and situational factors facilitate and impede an innovation's adoption. The Healthy Heart Kit (HHK) is a risk management and patient education resource for the prevention of cardiovascular disease (CVD) and promotion of cardiovascular health. Although previous studies have demonstrated the HHK's content validity and practical utility, no published study has examined physicians' uptake of the HHK and factors that shape its adoption. OBJECTIVES: Conceptually informed by Rogers' Diffusion of Innovation theory, and Theory of Planned Behaviour, this study had two objectives: (1) to determine if specific attributes of the HHK as well as contextual and situational factors are associated with physicians' intention and actual usage of the HHK kit; and (2), to determine if any contextual and situational factors are associated with individual or environmental barriers that prevent the uptake of the HHK among those physicians who do not plan to use the kit. METHODS: A sample of 153 physicians who responded to an invitation letter sent to all family physicians in the province of Alberta, Canada were recruited for the study. Participating physicians were sent a HHK, and two months later a study questionnaire assessed primary factors on the physicians' clinical practice, attributes of the HHK (relative advantage, compatibility, complexity, trialability, observability), confidence and control using the HHK, barriers to use, and individual attributes. All measures were used in path analysis, employing a causal model based on Rogers' Diffusion of Innovations Theory and Theory of Planned Behaviour. RESULTS: 115 physicians (follow up rate of 75%) completed the questionnaire. Use of the HHK was associated with intention to use the HHK, relative advantage, and years of experience. Relative advantage and the observability of the HHK benefits were also significantly associated with physicians' intention to use the HHK. Physicians working in solo medical practices reported experiencing more individual and environmental barriers to using the HHK. CONCLUSION: The results of this study suggest that future information innovations must demonstrate an advantage over current resources and the research evidence supporting the innovation must be clearly visible. Findings also suggest that the innovation adoption process has a social element, and collegial interactions and discussions may facilitate that process. These results could be valuable for knowledge translation researchers and health promotion developers in future innovation adoption planning.
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Many interventions promoting physical activity (PA) are effective in preventing disease onset, and although studies have found a positive relationship between health-related quality of life (HRQL) and PA, most of these studies have focused on older adults and those with chronic conditions. Less is known regarding the association between PA level and HRQL among healthy adults. Our objective was to analyse the relationship between PA level and HRQL among a sample of 573 employees aged 20-68 taking part in a workplace intervention to promote PA. Measures included HRQL (using a single item) and PA (i.e. Godin Leisure-Time Questionnaire). The Modified Canadian Aerobic Fitness Test (MCAFT) was also completed by 10% of the employees. MET-minute scores (assessing energy expenditure over one week) were compared across HRQL categories using ANOVA. A multiple linear regression analysis was conducted to further examine the relationship between HRQL and PA, controlling for potential covariates. Participants in the higher health status categories were found to report higher levels of energy expenditure (one-way ANOVA, p < 0.001). In the multiple linear regression model, each unit increase in health status level translated in a mean increase of 356 MET-minutes in energy expenditure (p < 0.001). This single-item assessment of health status explained six percent of the variance in energy expenditure. The study concludes that higher energy expenditure through PA among an adult workplace population is positively associated with increased health status, and it also suggests that a single-item HRQL measure is suitable for community- and population-based studies, reducing response burden and research costs.
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Objective: Health status measures usually have an asymmetric distribution and present a highpercentage of respondents with the best possible score (ceiling effect), specially when they areassessed in the overall population. Different methods to model this type of variables have beenproposed that take into account the ceiling effect: the tobit models, the Censored Least AbsoluteDeviations (CLAD) models or the two-part models, among others. The objective of this workwas to describe the tobit model, and compare it with the Ordinary Least Squares (OLS) model,that ignores the ceiling effect.Methods: Two different data sets have been used in order to compare both models: a) real datacomming from the European Study of Mental Disorders (ESEMeD), in order to model theEQ5D index, one of the measures of utilities most commonly used for the evaluation of healthstatus; and b) data obtained from simulation. Cross-validation was used to compare thepredicted values of the tobit model and the OLS models. The following estimators werecompared: the percentage of absolute error (R1), the percentage of squared error (R2), the MeanSquared Error (MSE) and the Mean Absolute Prediction Error (MAPE). Different datasets werecreated for different values of the error variance and different percentages of individuals withceiling effect. The estimations of the coefficients, the percentage of explained variance and theplots of residuals versus predicted values obtained under each model were compared.Results: With regard to the results of the ESEMeD study, the predicted values obtained with theOLS model and those obtained with the tobit models were very similar. The regressioncoefficients of the linear model were consistently smaller than those from the tobit model. In thesimulation study, we observed that when the error variance was small (s=1), the tobit modelpresented unbiased estimations of the coefficients and accurate predicted values, specially whenthe percentage of individuals wiht the highest possible score was small. However, when theerrror variance was greater (s=10 or s=20), the percentage of explained variance for the tobitmodel and the predicted values were more similar to those obtained with an OLS model.Conclusions: The proportion of variability accounted for the models and the percentage ofindividuals with the highest possible score have an important effect in the performance of thetobit model in comparison with the linear model.
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Despite clear evidence of correlations between financial and medical statuses and decisions, most models treat financial and health-related choices separately. This article bridges this gap by proposing a tractable dynamic framework for the joint determination of optimal consumption, portfolio holdings, health investment, and health insurance. We solve for the optimal rules in closed form and capitalize on this tractability to gain a better understanding of the conditions under which separation between financial and health-related decisions is sensible, and of the pathways through which wealth and health determine allocations, welfare and other variables of interest such as expected longevity or the value of health. Furthermore we show that the model is consistent with the observed patterns of individual allocations and provide realistic estimates of the parameters that confirm the relevance of all the main characteristics of the model.
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Abstract This thesis presents three empirical studies in the field of health insurance in Switzerland. First we investigate the link between health insurance coverage and health care expenditures. We use claims data for over 60 000 adult individuals covered by a major Swiss Health Insurance Fund, followed for four years; the data show a strong positive correlation between coverage and expenditures. Two methods are developed and estimated in order to separate selection effects (due to individual choice of coverage) and incentive effects ("ex post moral hazard"). The first method uses the comparison between inpatient and outpatient expenditures to identify both effects and we conclude that both selection and incentive effects are significantly present in our data. The second method is based on a structural model of joint demand of health care and health insurance and makes the most of the change in the marginal cost of health care to identify selection and incentive effects. We conclude that the correlation between insurance coverage and health care expenditures may be decomposed into the two effects: 75% may be attributed to selection, and 25 % to incentive effects. Moreover, we estimate that a decrease in the coinsurance rate from 100% to 10% increases the marginal demand for health care by about 90% and from 100% to 0% by about 150%. Secondly, having shown that selection and incentive effects exist in the Swiss health insurance market, we present the consequence of this result in the context of risk adjustment. We show that if individuals choose their insurance coverage in function of their health status (selection effect), the optimal compensations should be function of the se- lection and incentive effects. Therefore, a risk adjustment mechanism which ignores these effects, as it is the case presently in Switzerland, will miss his main goal to eliminate incentives for sickness funds to select risks. Using a simplified model, we show that the optimal compensations have to take into account the distribution of risks through the insurance plans in case of self-selection in order to avoid incentives to select risks.Then, we apply our propositions to Swiss data and propose a simple econometric procedure to control for self-selection in the estimation of the risk adjustment formula in order to compute the optimal compensations.