996 resultados para Random utility


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Objective. Comorbid mental illness amongst methadone maintenance therapy clients may be common and screening may be warranted. The Mood Disorders Questionnaire (MDQ) is a screening tool for bipolar disorder that has been validated in other treatment settings. Its utility for patients with substance use disorders is assessed in this study.

Methods. Clients of a methadone maintenance program were invited to complete the MDQ when they attended a public Drug and Alcohol Service for their regular scheduled appointments. Information about their history of substance use was also collected.

Results. Eighty clients (43 females, 37 males) aged 35 8.0 years (mean SD) participated in the study. Seventy-four clients completed the MDQ of which 36 (48.6%) obtained a positive screen. A check of client fi les suggested that only three of the 74 participants had a current working diagnosis of bipolar disorder. These three participants had screened positive on the MDQ.

Conclusions. There was a high prevalence of manic symptoms reported by participants, suggesting that screening for bipolar disorder in this population may be warranted. However, there is a risk of false positives with the MDQ, as it does not clearly differentiate between symptoms of mania and drug intoxication.

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Background The quality of behaviour support plans (BSPs) can be an important influence on the quality of the support provided to people with disability who show challenging behaviours. The Behavior Support Plan Quality Evaluation Guide II (BSP-QE II) is one tool that may be useful in assessing the quality of behaviour support plans. It has previously been used to assess BSPs to support children in schools in the USA. In this preliminary study, we examined the utility of the BSP-QE II for assessing behaviour support plans designed for adults with an intellectual disability in community support services in Australia.

Method  Experienced practitioners were surveyed concerning the relevance of BSP-QE II components to the evaluation of BSPs in Australia, and an audit was conducted of randomly selected BSPs submitted as a statutory requirement to the Office of the Senior Practitioner.

Results  The BSP-QE II showed evidence of acceptable construct validity and interrater reliability. There was evidence of a need for substantial improvement in the quality of BSPs, consistent with previous findings conducted using other audit tools.

Conclusions The findings support the utility of the BSP-QE II, to inform and evaluate service planning in supporting adults with intellectual disability who show challenging behaviour.

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Introduction and Aims. Despite considerable success in tobacco control, many teenagers in Australia and other industrialised countries still smoke tobacco. There is mixed evidence on the relative influence of proximal social networks (parents/siblings/peers) on pre- and early-teen smoking, and no research has examined how these influences compare after accounting for school- and community-level effects.The aim of this study was to compare the relative influences of parents, siblings and peers, after accounting for school- and community-level variation in smoking.

Design and Methods.
A cross-sectional fixed and random effects model of smoking prevalence was used, with individuals (n = 7314) nested within schools (n = 231) nested within communities (n = 30). Grade 6 and 8 students (modal ages 11 and 13 years) completed an on-line survey. Key variables included parent/sibling/peer use. Controls included alcohol involvement, sensation seeking, pro-social beliefs, laws/norms about substance use and school commitment.

Results.There was significant variation in smoking at both the school and community levels, supporting the need for a multilevel model. Individual-level predictors accounted for much of the variance at higher levels. The strongest effects were for number of friends who smoke, sibling smoking and alcohol involvement. Smaller significant effects were found for parent smoking. At the community level, socioeconomic disadvantage was significant, but community-level variance in pro-social and drug-related laws/norms was not related to smoking.

Discussion and Conclusions. Cross-level interactions were generally non-significant. Early teenage smoking was best explained by sibling and peer smoking, and individual risks largely accounted for the substantial variation observed across schools and communities. In terms of future tobacco control, findings point to the utility of targeting families in disadvantaged communities.[Kelly AB, O'Flaherty M, Connor JP, Homel R, Toumbourou JW, Patton GC, Williams J. The influence of parents, siblings and peers on pre- and early-teen smoking: A multilevel model.

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Objective : To explore the relationship between overweight/obesity and utility in adolescents.

Methods : Data were collected from 2890 adolescents attending 13 secondary schools in the state of Victoria, Australia. The Assessment of Quality of Life 6-Dimension (AQoL-6D) questionnaire was used to measure individual utility. Adolescent's height and weight were measured and weight status categories assigned according to the World Health Organization adolescent growth standards. Multivariate linear regression analyses were undertaken for the whole population and subpopulations of boys and girls to estimate the mean differences in utility scores between 1) overweight and healthy weight and 2) obese and healthy weight adolescents, while controlling for demographic and socioeconomic status variables.

Results : The mean age of adolescents was 14.6 years, 56.2% were boys, 22.2% were overweight, and 9.4% were obese. The mean utility of healthy weight adolescents was 0.860. After adjustments, the overweight and obese groups reported significantly lower mean utility scores (differences: −0.018 and −0.059, respectively, relative to the healthy weight group). This can be interpreted as equivalent to a stated willingness to sacrifice 1.8% and 5.9% of a life in perfect health or 2.3% and 6.8% of a life at healthy weight. A significant utility difference associated with overweight was only experienced by girls (−0.039, P = 0.003). Both sexes experienced significant utility differences associated with obesity, but the magnitude was double for girls (−0.084, P < 0.001) relative to boys (−0.041, P = 0.022).

Conclusion : Utility is lower among overweight and more so among obese adolescents.

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The focus of this paper is on the community impact of education research, as conceived specifically within a changing context of research assessment in Australia, first mooted by the previous Federal Coalition (conservative) Government within a new Research Quality Framework (RQF), and now to be reworked by the Excellence in Research for Australia (ERA) initiated by the incoming Federal Labour (progressive) Government. Convinced that a penchant for the utility of research will not go away, irrespective of the political orientations of government, our interest is in exploring: the assumption that research, particularly in areas such as education, should have an impact in the community (as this was first defined within the RQF); the difficulties much education research (despite its “applied” characterisation) has in complying with this ideal; and what a community impact requirement means for the kinds of education research that will be privileged in the future. In particular, we are concerned about the potential narrowing of education research directed at or by community impact and what is lost in the process. One potential loss or weakening is in the positional autonomy of higher education to conduct independent education research.

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Automatic human action recognition has been a challenging issue in the field of machine vision. Some high-level features such as SIFT, although with promising performance for action recognition, are computationally complex to some extent. To deal with this problem, we construct the features based on the Distance Transform of body contours, which is relatively simple and computationally efficient, to represent human action in the video. After extracting the features from videos, we adopt the Conditional Random Field for modeling the temporal action sequences. The proposed method is tested with an available standard dataset. We also testify the robustness of our method on various realistic conditions, such as body occlusion or intersection.

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Background: Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia.

Methods
: An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables.

Results
: Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (p<0.05). Perceiving cycling to be a cheap or a convenient form of transport were associated with utility cycling (p<0.05).

Conclusions
: The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.

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Fracture risk is determined by bone mineral density (BMD). The T-score, a measure of fracture risk, is the position of an individual's BMD in relation to a reference range. The aim of this study was to determine the magnitude of change in the T-score when different sampling techniques were used to produce the reference range. Reference ranges were derived from three samples, drawn from the same region: (1) an age-stratified population-based random sample, (2) unselected volunteers, and (3) a selected healthy subset of the population-based sample with no diseases or drugs known to affect bone. T-scores were calculated using the three reference ranges for a cohort of women who had sustained a fracture and as a group had a low mean BMD (ages 35-72 yr; n = 484). For most comparisons, the T-scores for the fracture cohort were more negative using the population reference range. The difference in T-scores reached 1.0 SD. The proportion of the fracture cohort classified as having osteoporosis at the spine was 26, 14, and 23% when the population, volunteer, and healthy reference ranges were applied, respectively. The use of inappropriate reference ranges results in substantial changes to T-scores and may lead to inappropriate management.

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This paper challenges the assumption within Economics that the relationship between money and subjective wellbeing is determined by processes of cognitive comparison. An alternative explanation for such well known phenomena as the Easterlin Paradox and Decreasing Marginal Utility are provided through a consideration of affect. The theoretical basis for such explanations relies on theory from Psychology usually overlooked by Economists, such as affect heuristics and Subjective Wellbeing Homeostasis. The presented evidence for this alternative source of explanation melds psychological theory with empirical data. It is concluded that affective processes offer a coherent alternative explanation for the phenomena under discussion.

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Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov random field (MRF), known as the dynamic conditional random field (DCRF). Parameter estimation in general MRFs using maximum likelihood is known to be computationally challenging (except for extreme cases), and thus we propose an efficient boosting-based algorithm AdaBoost.MRF for this task. Distinct from most existing work, our algorithm can handle hidden variables (missing labels) and is particularly attractive for smarthouse domains where reliable labels are often sparsely observed. Furthermore, our method works exclusively on trees and thus is guaranteed to converge. We apply the AdaBoost.MRF algorithm to a home video surveillance application and demonstrate its efficacy.