69 resultados para Latent class model

em Deakin Research Online - Australia


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Background Pre-school language impairment is common and greatly reduces educational performance. Population attempts to identify children who would benefit from appropriately timed intervention might be improved by greater knowledge about the typical profiles of language development. Specifically, this could be used to help with the early identification of children who will be impaired on school entry.

Methods This study applied longitudinal latent class analysis to assessments at 8, 12, 24, 36 and 48 months on 1113 children from a population-based study, in order to identify classes exhibiting distinct communicative developmental profiles.

Results Five substantive classes were identified: Typical, i.e. development in the typical range at each age; Precocious (late), i.e. typical development in infancy followed by high probabilities of precocity from 24 months onwards; Impaired (early), i.e. high probabilities of impairment up to 12 months followed by typical language development thereafter; Impaired (late), i.e. typical development in infancy but impairment from 24 months onwards; Precocious (early), i.e. high probabilities of precocity in early life followed by typical language by 48 months. The entropy statistic (0.84) suggested classes were fairly well defined, although there was a non-trivial degree of uncertainty in classification of children. That half of the Impaired (late) class was expected to have typical language at 4 years and 6% of the numerically large Typical class was expected to be impaired at 4 years illustrates this. Characteristics indicative of social advantage were more commonly found in the classes with improving profiles.

Conclusions Developmental profiles show that some pre-schoolers' language is characterized by periods of accelerated development, slow development and catch-up growth. Given the uncertainty in classifying children into these profiles, use of this knowledge for identifying children who will be impaired on school entry is not straightforward. The findings do, however, indicate greater need for language enrichment programmes among disadvantaged children.

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Relatively little examination of the meals that are prepared in households has been conducted, despite their well-defined properties and widespread community interest in their preparation. The purpose of the present study was to identify the patterns of main meal preparation among Australian adult household meal preparers aged 44 years and younger and 45 years and over, and the relationships between these patterns and likely socio-demographic and psychological predictors. An online cross-sectional survey was conducted by Meat and Livestock Australia among a representative sample of people aged 18–65 years in Australia in 2011. A total of 1076 usable questionnaires were obtained, which included categorical information about the main meal dishes that participants had prepared during the previous 6 months along with demographic information, the presence or absence of children at home, confidence in seasonal food knowledge and personal values. Latent class analysis was applied and four types of usage patterns of thirty-three popular dishes were identified for both age groups, namely, high variety, moderate variety, high protein but low beef and low variety. The meal patterns were associated differentially with the covariates between the age groups. For example, younger women were more likely to prepare a high or moderate variety of meals than younger men, while younger people who had higher levels of education were more likely to prepare high-protein but low-beef meals. Moreover, young respondents with higher BMI were less likely to prepare meals with high protein but low beef content. Among the older age group, married people were more likely to prepare a high or moderate variety of meals than people without partners. Older people who held strong universalist values were more likely to prepare a wide variety of meals with high protein but low beef content. For both age groups, people who had children living at home and those with better seasonal food knowledge were more likely to prepare a high variety of dishes. The identification of classes of meal users would enable health communication to be tailored to improve meal patterns. Moreover, the concept of meals may be useful for health promotion, because people may find it easier to change their consumption of meals rather than individual foods.

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High impulsivity is common to substance and gambling addictions. Despite these commonalities, there is still substantial heterogeneity on impulsivity levels within these diagnostic groups, and variations in impulsive levels predict higher severity of symptoms and poorer outcomes. We addressed the question of whether impulsivity scores can yield empirically driven subgroups of addicted individuals that will exhibit different clinical presentations and outcomes. We applied latent class analysis (LCA) to trait (UPPS-P impulsive behavior scale) and cognitive impulsivity (Stroop and d2 tests) scores in three predominantly male addiction diagnostic groups: Cocaine with Personality Disorders, Cocaine Non-comorbid, and Gambling and analyzed the usefulness of the resulting subgroups to differentiate personality beliefs and relevant outcomes: Craving, psychosocial adjustment, and quality of life. In accordance with impulsivity scores, the three addiction diagnostic groups are best represented as two separate classes: Class 1 characterized by greater trait impulsivity and poorer cognitive impulsivity performance and Class 2 characterized by lower trait impulsivity and better cognitive impulsivity performance. The two empirically derived classes showed significant differences on personality features and outcome variables (Class 1 exhibited greater personality dysfunction and worse clinical outcomes), whereas conventional diagnostic groups showed non-significant differences on most of these measures. Trait and cognitive impulsivity scores differentiate subgroups of addicted individuals with more versus less severe personality features and clinical outcomes.

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Background: Previous research on alcohol mixed with energy drinks (AmED) has shown that use is typically driven by hedonistic, social, functional, and intoxication-related motives, with differential associations with alcohol-related harm across these constructs. There has been no research looking at whether there are subgroups of consumers based on patterns of motivations. Consequently, the aims were to determine the typology of motivations for AmED use among a community sample and to identify correlates of subgroup membership. In addition, we aimed to determine whether this structure of motivations applied to a university student sample. Methods: Data were used from an Australian community sample (n = 731) and an Australian university student sample (n = 594) who were identified as AmED consumers when completing an online survey about their alcohol and ED use. Participants reported their level of agreement with 14 motivations for AmED use; latent classes of AmED consumers were identified based on patterns of motivation endorsement using latent class analysis. Results: A 4-class model was selected using data from the community sample: (i) taste consumers (31%): endorsed pleasurable taste; (ii) energy-seeking consumers (24%): endorsed functional and taste motives; (iii) hedonistic consumers (33%): endorse pleasure and sensation-seeking motives, as well as functional and taste motives; and (iv) intoxication-related consumers (12%): endorsed motives related to feeling in control of intoxication, as well as hedonistic, functional, and taste motives. The consumer subgroups typically did not differ on demographics, other drug use, alcohol and ED use, and AmED risk taking. The patterns of motivations for the 4-class model were similar for the university student sample. Conclusions: This study indicated the existence of 4 subgroups of AmED consumers based on their patterns of motivations for AmED use consistently structured across the community and university student sample. These findings lend support to the growing conceptualization of AmED consumers as a heterogeneous group in regard to motivations for use, with a hierarchical and cumulative class order in regard to the number of types of motivation for AmED use. Prospective research may endeavor to link session-specific motives and outcomes, as it is apparent that primary consumption motives may be fluid between sessions.

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BACKGROUND AND AIMS: Problem gamblers are not a homogeneous group and recent data suggest that subtyping can improve treatment outcomes. This study administered three readiness rulers and aimed to identify subtypes of gamblers accessing a national web-based counselling service based on these rulers. METHODS: Participants were 1204 gamblers (99.4% problem gamblers) who accessed a single session of web-based counselling in Australia. Measures included three readiness rulers (importance, readiness and confidence to resist an urge to gamble), demographics and the Problem Gambling Severity Index (PGSI). RESULTS: Gamblers reported high importance of change [mean = 9.2, standard deviation (SD) = 1.51] and readiness to change (mean = 8.86, SD = 1.84), but lower confidence to resist an urge to gamble (mean = 3.93, SD = 2.44) compared with importance and readiness. The statistical fit indices of a latent class analysis identified a four-class model. Subtype 1 was characterized by a very high readiness to change and very low confidence to resist an urge to gamble (n = 662, 55.0%) and subtype 2 reported high readiness and low confidence (n = 358, 29.7%). Subtype 3 reported moderate ratings on all three rulers (n = 139, 11.6%) and subtype 4 reported high importance of change but low readiness and confidence (n = 45, 3.7%). A multinomial logistic regression indicated that subtypes differed by gender (P < 0.001), age (P = 0.01), gambling activity (P < 0.05), preferred mode of gambling (P < 0.001) and PGSI score (P < 0.001). CONCLUSIONS: Problem gamblers in Australia who seek web-based counselling comprise four distinct subgroups based on self-reported levels of readiness to change, confidence to resist the urge to gamble and importance of change.

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BACKGROUND: Knowledge about the relationships between micro-scale environmental factors and older adults' walking for transport is limited and inconsistent. This is probably due to methodological limitations, such as absence of an accurate neighborhood definition, lack of environmental heterogeneity, environmental co-variation, and recall bias. Furthermore, most previous studies are observational in nature. We aimed to address these limitations by investigating the effects of manipulating photographs on micro-scale environmental factors on the appeal of a street for older adults' transportation walking. Secondly, we used latent class analysis to examine whether subgroups could be identified that have different environmental preferences for transportation walking. Thirdly, we investigated whether these subgroups differed in socio-demographic, functional and psychosocial characteristics, current level of walking and environmental perceptions of their own street.

METHODS: Data were collected among 1131 Flemish older adults through an online (n = 940) or an interview version of the questionnaire (n = 191). This questionnaire included a choice-based conjoint exercise with manipulated photographs of a street. These manipulated photographs originated from one panoramic photograph of an existing street that was manipulated on nine environmental attributes. Participants chose which of two presented streets they would prefer to walk for transport.

RESULTS: In the total sample, sidewalk evenness had by far the greatest appeal for transportation walking. The other environmental attributes were less important. Four subgroups that differed in their environmental preferences for transportation walking were identified. In the two largest subgroups (representing 86% of the sample) sidewalk evenness was the most important environmental attribute. In the two smaller subgroups (each comprising 7% of the sample), traffic volume and speed limit were the most important environmental attributes for one, and the presence of vegetation and a bench were the most important environmental attributes for the other. This latter subgroup included a higher percentage of service flat residents than the other subgroups.

CONCLUSIONS: Our results suggest that the provision of even sidewalks should be considered a priority when developing environmental interventions aiming to stimulate older adults' transportation walking. Natural experiments are needed to confirm whether our findings can be translated to real environments and actual transportation walking behavior.

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The “external structure” in an object oriented system refers here to the  graphs of objects and classes. The class structure graph or class model is derived from the object structure graph or object model, and in this operation structural information is lost, or never made explicit. Although object oriented programming languages capture the class model as declarations,  contradictory assumptions about object model properties may be made introducing faults into the design. Consistent assumptions about the object model can be specified in the code using assertions such as Eiffel’s  invariants, preconditions and postconditions. Three examples specifying the external structure are considered.

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The purpose of the study was to determine patterns of diet use among middle-aged Australian men and women and the relationships between these different usage patterns and demographic characteristics, health status and health habits. A cross-sectional mail survey was conducted among a random sample of 2975 people aged 40–71 years in Victoria, Australia. A total of 1031 usable questionnaires were obtained which included information about the use of diets (e.g. low-fat and low-salt) during the past 3 months along with demographic information, health status and health habits. Based on the responses about the use of thirteen diets for both sexes, latent class analysis was employed to identify the optimal number of use of diets and the assignment of participants to particular groups. Three types of diet uses were identified and provisionally named: diet use, selected diet use and non-diet use. This classification was associated with demographics, health status and health habits, and these associations differed between men and women. The findings suggest that nutrition education programmes should be tailored to the different needs of the diet use groups.

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This study has formulated a behavioral model of individual activity time allocation on weekends, and has extended it to incorporate the latent determinants of time use decisions during weekdays by using a latent variable model. The ultimate goals in developing this model are to improve the individual weekend activity time allocation model by introducing latent variables, and to estimate the value of activity time of different activity types. We conducted a pilot empirical investigation using a small data set regarding time use and expenditure both for weekdays and weekends, and a few indicators of the latent variables collected from individuals in Yokohama, Japan. The empirical findings suggest that the proposed model is valuable not only for modeling activity time allocation, but also in calculating the value of activity time.

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Analysis and fusion of social measurements is important to understand what shapes the public’s opinion and the sustainability of the global development. However, modeling data collected from social responses is challenging as the data is typically complex and heterogeneous, which might take the form of stated facts, subjective assessment, choices, preferences or any combination thereof. Model-wise, these responses are a mixture of data types including binary, categorical, multicategorical, continuous, ordinal, count and rank data. The challenge is therefore to effectively handle mixed data in the a unified fusion framework in order to perform inference and analysis. To that end, this paper introduces eRBM (Embedded Restricted Boltzmann Machine) – a probabilistic latent variable model that can represent mixed data using a layer of hidden variables transparent across different types of data. The proposed model can comfortably support largescale data analysis tasks, including distribution modelling, data completion, prediction and visualisation. We demonstrate these versatile features on several moderate and large-scale publicly available social survey datasets.