853 resultados para health behavior models


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This chapter will address psychodynamic, cognitive-behavioural, and developmental models in supervision by initially considering the historical underpinnings of each and then examining in turn some of the key processes that are evident in the supervisory relationships. Case studies are included where appropriate to highlight the application of theory to practice and several processes are fully elaborated over all models to enable a contemporary view of style and substance in the supervision context.

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A number of studies in relation to the place, impact and purpose of Wellness curricula provide insight into the perceived benefits of Wellness education in university environments. Of particular note is the recommendation by many authors that curriculum design fosters personal experiences, reflective practice and active self-managed learning approaches in order to legitimise (give permission for) the adoption of wellness as a personal lifestyle approach in the frenetic pace of student life. From a broader educational perspective, Wellness education provides opportunities for students to engage in learning self regulation skills both within and beyond the context of the Wellness construct.To realise the suggested potential of Wellness education in higher learning, it is necessary that curricula overlay the principles from the domains of both self-regulation and Wellness, to highlight authentic learning as a means to lifelong approaches. Currently, however, systematic development and empirical examination of the Wellness construct have received limited academic investigation. Despite having a multitude of intended purposes from the educative to the therapy oriented goals of the original authors, most wellness models appear to be limited to the “what” of Wellness. Investigations of the “how” and “why” aspects of Wellness may serve to enhance currently existing models by incorporating behaviour modification and learning approaches in order to create more comprehensive frameworks for health education and promotion.It is also important to note that none of the current Wellness models actually address the educative framework necessary for an individual to learn and thus become aware or understand and make choices about their own Wellness.The literature reviewed within this paper would suggest that learner success is optimised by giving learners authentic opportunities to develop and practice self regulation strategies. Such opportunities include learning experiences that: provide options for self determined outcomes; require skills development; recognise principles of successful learning as outlined by the APA; and are scaffolded according to learner needs rather than in generic ways. Thus, configuring a learner centred curriculum in Wellness Education would potentially benefit from overlaying principles from the domains of both SRL and Wellness to highlight authentic learning as a means to lifelong approaches, triggered by undergraduate experiences.Student perceptions are a rich and significant data base for the measurement of their experiences, activities, practices and behaviours. Wellness undergraduate education, such as the “Fitness, Health and Wellness” unit offered by Queensland University of Technology, offers a context in which to confirm possibilities suggested by the literature reviewed in this paper in a practical, Australian context.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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Cooking skills are emphasized in nutrition promotion but their distribution among population subgroups and relationship to dietary behavior is researched by few population-based studies. This study examined the relationships between confidence to cook, sociodemographic characteristics, and household vegetable purchasing. This cross-sectional study of 426 randomly selected households in Brisbane, Australia, used a validated questionnaire to assess household vegetable purchasing habits and the confidence to cook of the person who most often prepares food for these households. The mutually adjusted odds ratios (ORs) of lacking confidence to cook were assessed across a range of demographic subgroups using multiple logistic regression models. Similarly, mutually adjusted mean vegetable purchasing scores were calculated using multiple linear regression for different population groups and for respondents with varying confidence levels. Lacking confidence to cook using a variety of techniques was more common among respondents with less education (OR 3.30; 95% confidence interval [CI] 1.01 to 10.75) and was less common among respondents who lived with minors (OR 0.22; 95% CI 0.09 to 0.53) and other adults (OR 0.43; 95% CI 0.24 to 0.78). Lack of confidence to prepare vegetables was associated with being male (OR 2.25; 95% CI 1.24 to 4.08), low education (OR 6.60; 95% CI 2.08 to 20.91), lower household income (OR 2.98; 95% CI 1.02 to 8.72) and living with other adults (OR 0.53; 95% CI 0.29 to 0.98). Households bought a greater variety of vegetables on a regular basis when the main chef was confident to prepare them (difference: 18.60; 95% CI 14.66 to 22.54), older (difference: 8.69; 95% CI 4.92 to 12.47), lived with at least one other adult (difference: 5.47; 95% CI 2.82 to 8.12) or at least one minor (difference: 2.86; 95% CI 0.17 to 5.55). Cooking skills may contribute to socioeconomic dietary differences, and may be a useful strategy for promoting fruit and vegetable consumption, particularly among socioeconomically disadvantaged groups.

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Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

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Exposure of the skin to sunlight can cause skin cancer and is also necessary for cutaneous vitamin D production. Media reports have highlighted the purported health benefits of vitamin D. Our aim was to examine attitudes and behaviours related to sun protection and vitamin D. A cross-sectional study of 2,001 residents in Queensland, Australia aged 20-70 years was undertaken. Information collected included: skin cancer risk factors; perceptions about levels of sun exposure required to maintain vitamin D; belief that sun protection increases risk of vitamin D deficiency; intention, and actual change in sun protection practices for adults and children. Multivariate models examined predictors of attitudinal and behavioural change. One-third (32%) believed a fair-skinned adult, and 31% thought a child required at least 30 minutes per day in summer sun to maintain vitamin D levels. Reductions in sun protection were reported by 21% of adults and 14% of children. Factors associated with belief that sun protection may result in not obtaining enough vitamin D included aged ≥ 60 years (OR=1.35, 95% CI 1.09-1.66) and having skin that tanned easily (OR=1.96, 95% CI 1.38-2.78). Participants from low income households, and those who frequently used sun protective clothing were more likely to have reduced sun protection practices (OR=1.33, 95% CI 1.10-1.73 and OR=1.73, 95% CI 1.36-2.20, respectively). This study provides evidence of reductions in sun protection practices in a population living in a high UV environment. There is an urgent need to re-focus messages regarding sun exposure and for continued sun protection practices.

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Survey-based health research is in a boom phase following an increased amount of health spending in OECD countries and the interest in ageing. A general characteristic of survey-based health research is its diversity. Different studies are based on different health questions in different datasets; they use different statistical techniques; they differ in whether they approach health from an ordinal or cardinal perspective; and they differ in whether they measure short-term or long-term effects. The question in this paper is simple: do these differences matter for the findings? We investigate the effects of life-style choices (drinking, smoking, exercise) and income on six measures of health in the US Health and Retirement Study (HRS) between 1992 and 2002: (1) self-assessed general health status, (2) problems with undertaking daily tasks and chores, (3) mental health indicators, (4) BMI, (5) the presence of serious long-term health conditions, and (6) mortality. We compare ordinal models with cardinal models; we compare models with fixed effects to models without fixed-effects; and we compare short-term effects to long-term effects. We find considerable variation in the impact of different determinants on our chosen health outcome measures; we find that it matters whether ordinality or cardinality is assumed; we find substantial differences between estimates that account for fixed effects versus those that do not; and we find that short-run and long-run effects differ greatly. All this implies that health is an even more complicated notion than hitherto thought, defying generalizations from one measure to the others or one methodology to another.

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The current study sought to understand adolescent protective behavior in friendship using a Theory of Planned Behavior framework. In particular, the study sought to consider a young persons’ direct and active intervention to inhibit their friends’ risky behavior or to assist them when the behavior leads to injury. The role of attitudes regarding the consequences, norms and control about protective behavior were examined both qualitatively through focus groups (n= 50) and quantitatively through surveys from a sample of 540 Year 9 students (13-14 years old). There was some support for the theory with attitudes regarding the consequences of the behavior and norms predicting intended protective behavior. A path analysis was conducted with a sub-sample of 140 students which showed that intentions to be protective and perceived control to undertake protective behavior directly predicted such behavior after a 3 month interval. Attitudes towards the consequences and norms only indirectly predicted protective behavior via intention. The findings provide important applied information for interventions designed to increase adolescent protective behavior in their friendships.

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This chapter describes an evidence-based programme called the Resourceful Adolescent Program (RAP), which has been successful in building resilience in young people to prevent depressive symptoms developing.The programme adopts a strengths-focused approach. It aims to build a range of coping resources that foster teenagers’ abilities to maintain a positive sense of self and regulate emotions in the face of the vicissitudes of everyday struggles and difficult life events.This groupbased programme can be implemented routinely in schools or by counselling professionals as an early intervention or prevention programme. While there is no universal definition, ‘resilience’ generally means the process of avoiding the negative trajectories associated with exposure to risk factors (Fergus and Zimmerman, 2005). Current models of resilience are also very clear that there ‘are many pathways to resilience’ (Bonanno, 2004) and there is no

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Seasonal patterns have been found in a remarkable range of health conditions, including birth defects, respiratory infections and cardiovascular disease. Accurately estimating the size and timing of seasonal peaks in disease incidence is an aid to understanding the causes and possibly to developing interventions. With global warming increasing the intensity of seasonal weather patterns around the world, a review of the methods for estimating seasonal effects on health is timely. This is the first book on statistical methods for seasonal data written for a health audience. It describes methods for a range of outcomes (including continuous, count and binomial data) and demonstrates appropriate techniques for summarising and modelling these data. It has a practical focus and uses interesting examples to motivate and illustrate the methods. The statistical procedures and example data sets are available in an R package called ‘season’. Adrian Barnett is a senior research fellow at Queensland University of Technology, Australia. Annette Dobson is a Professor of Biostatistics at The University of Queensland, Australia. Both are experienced medical statisticians with a commitment to statistical education and have previously collaborated in research in the methodological developments and applications of biostatistics, especially to time series data. Among other projects, they worked together on revising the well-known textbook "An Introduction to Generalized Linear Models," third edition, Chapman Hall/CRC, 2008. In their new book they share their knowledge of statistical methods for examining seasonal patterns in health.

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Background: The effect of patient education on reducing stroke has had mixed effects, raising questions about how to achieve optimal benefit. Because past evaluations have typically lacked an appropriate theoretical base, the design of past research may have missed important effects. --------- Method: This study used a social cognitive framework to identify variables that might change in response to education. A mixed design was used to evaluate two approaches to an intervention, both of which included education. Fifty seniors completed a measure of stroke knowledge and beliefs twice: before and after an intervention that was either standard (educational brochure plus activities that were not about stroke) or enhanced (educational brochure plus activities designed to enhance beliefs about stroke). Outcome measures were health beliefs, intention to exercise to reduce stroke, and stroke knowledge. --------- Results: Selected beliefs changed significantly over time but not differentially across conditions. Beliefs that changed were (a) perceived susceptibility to stroke and (b) perceived benefit of exercise to reduce risk. Benefit beliefs, in particular, were strongly and positively associated with intention to exercise. -------- Conclusion: Findings suggest that basic approaches to patient education may influence health beliefs. More effective stroke prevention programs may result from continued consideration of the role of health beliefs in such programs.

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This naturalistic study investigated the mechanisms of change in measures of negative thinking and in 24-h urinary metabolites of noradrenaline (norepinephrine), dopamine and serotonin in a sample of 43 depressed hospital patients attending an eight-session group cognitive behavior therapy program. Most participants (91%) were taking antidepressant medication throughout the therapy period according to their treating Psychiatrists' prescriptions. The sample was divided into outcome categories (19 Responders and 24 Non-responders) on the basis of a clinically reliable change index [Jacobson, N.S., & Truax, P., 1991. Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12–19.] applied to the Beck Depression Inventory scores at the end of the therapy. Results of repeated measures analysis of variance [ANOVA] analyses of variance indicated that all measures of negative thinking improved significantly during therapy, and significantly more so in the Responders as expected. The treatment had a significant impact on urinary adrenaline and metadrenaline excretion however, these changes occurred in both Responders and Non-responders. Acute treatment did not significantly influence the six other monoamine metabolites. In summary, changes in urinary monoamine levels during combined treatment for depression were not associated with self-reported changes in mood symptoms.

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Analytical and computational models of the intervertebral disc (IVD) are commonly employed to enhance understanding of the biomechanics of the human spine and spinal motion segments. The accuracy of these models in predicting physiological behaviour of the spine is intrinsically reliant on the accuracy of the material constitutive representations employed to represent the spinal tissues. There is a paucity of detailed mechanical data describing the material response of the reinforced­ground matrix in the anulus fibrosus of the IVD. In the present study, the ‘reinforced­ground matrix’ was defined as the matrix with the collagen fibres embedded but not actively bearing axial load, thus incorporating the contribution of the fibre-fibre and fibre-matrix interactions. To determine mechanical parameters for the anulus ground matrix, mechanical tests were carried out on specimens of ovine anulus, under unconfined uniaxial compression, simple shear and biaxial compression. Test specimens of ovine anulus fibrosus were obtained with an adjacent layer of vertebral bone/cartilage on the superior and inferior specimen surface. Specimen geometry was such that there were no continuous collagen fibres coupling the two endplates. Samples were subdivided according to disc region - anterior, lateral and posterior - to determine the regional inhomogeneity in the anulus mechanical response. Specimens were loaded at a strain rate sufficient to avoid fluid outflow from the tissue and typical stress-strain responses under the initial load application and under repeated loading were determined for each of the three loading types. The response of the anulus tissue to the initial and repeated load cycles was significantly different for all load types, except biaxial compression in the anterior anulus. Since the maximum applied strain exceeded the damage strain for the tissue, experimental results for repeated loading reflected the mechanical ability of the tissue to carry load, subsequent to the initiation of damage. To our knowledge, this is the first study to provide experimental data describing the response of the ‘reinforced­ground matrix’ to biaxial compression. Additionally, it is novel in defining a study objective to determine the regionally inhomogeneous response of the ‘reinforced­ground matrix’ under an extensive range of loading conditions suitable for mechanical characterisation of the tissue. The results presented facilitate the development of more detailed and comprehensive constitutive descriptions for the large strain nonlinear elastic or hyperelastic response of the anulus ground matrix.