250 resultados para neighborhood change


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The aim of this study was the validation of a brief form of the Perceived Neighborhood Social Cohesion questionnaire using data from 5065 men from the "Cohort Study on Substance-Use Risk Factors." A 9-item scale covering three factors was proposed. Excellent indices of internal consistency were measured (α = .93). The confirmatory factor analyses resulted in acceptable fit indices supporting measurement invariance across French and German forms. Significant correlations were found between the brief form of the Perceived Neighborhood Social Cohesion questionnaire, and satisfaction and self-reported health, providing evidence of the concurrent validity of the scale. Perceived neighborhood social cohesion, and depression and suicide attempts were negatively associated, sustaining the protective effect of perceived social cohesion.

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This study main purpose was the validation of both French and German versions of a Perceived Neighborhood Social Cohesion Questionnaire. The sample group comprised 5065 Swiss men from the "Cohort Study on Substance Use Risk Factors." Multigroup Confirmatory factor analysis showed that a three-factor model fits the data well, which substantiates the generalizability of Perceived Neighborhood Social Cohesion Questionnaire factor structure, regardless of the language. The Perceived Neighborhood Social Cohesion Questionnaire demonstrated excellent homogeneity (α = 95) and split-half reliability (r = .96). The Perceived Neighborhood Social Cohesion Questionnaire was sensitive to community size and participants' financial situation, confirming that it also measures real social conditions. Finally, weak but frequent correlations between Perceived Neighborhood Social Cohesion Questionnaire and alcohol, cigarette, and cannabis dependence were measured.

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OBJECTIVE: Client change talk has been proposed as a mechanism of change in motivational interviewing (MI) by mediating the link between therapist MI-consistent behaviors (MICO) and client behavioral outcomes. We tested under what circumstances this mechanism was supported in the context of a clinical trial of brief MI for heavy drinking among nontreatment seeking young men. METHOD: We conducted psycholinguistic coding of 174 sessions using the MI Skill Code 2.1 and derived the frequency of MICO and the strength of change talk (CTS) averaged over the session. CTS was examined as a mediator of the relationship between MICO and a drinking composite score measured at 3-month follow-up, controlling for the composite measure at baseline. Finally, we tested therapist gender and MI experience as well as client readiness to change and alcohol problem severity as moderators of this mediation model. RESULTS: CTS significantly predicted outcome (higher strength related to less drinking), but MICO did not predict CTS. However, CTS mediated the relationship between MICO and drinking outcomes when therapists had more experience in MI and when clients had more severe alcohol problems (i.e., significant conditional indirect effects). CONCLUSIONS: The mechanism hypothesized by MI theory was operative in our brief MI with heavy drinking young men, but only under particular conditions. Our results suggest that attention should be paid to therapist selection, training, and/or supervision until they reach a certain level of competence, and that MI might not be appropriate for nontreatment seeking clients drinking at a lower level of risk. (PsycINFO Database Record

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The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

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Mountain ecosystems have been less adversely affected by invasions of non-native plants than most other ecosystems, partially because most invasive plants in the lowlands are limited by climate and cannot grow under harsher high-elevation conditions. However, with ongoing climate change, invasive species may rapidly move upwards and threaten mid- then high-elevation mountain ecosystems. We evaluated this threat by predicting current and future potential distributions of 48 invasive plant species distributed in Switzerland (CH) and New South Wales (NSW), two areas where climate interacts differently with the elevation gradient. Using a species distribution modeling approach combining two scales, which builds on high-resolution data (< 250 m) but accounts for the global climatic niche of species, we found that different environmental drivers limit the elevation range of invasive species in the two regions, leading to region-specific species responses to climate change. Whereas the optimal suitability for plant invaders is predicted to markedly shift from the lowland to the montane or subalpine zone in CH, such an upward shift is far less pronounced in NSW where montane and subalpine elevations are currently already suitable. Non-native species able to invade the upper reaches of mountains in a future climate will be cold-tolerant in the Swiss Alps but preferring wet soils in the Australian Alps. Other plant traits were only marginally associated with elevation limits. These results demonstrate that a more systematic consideration of future distributions of invasive species is required in conservation plans of not yet invaded mountainous ecosystems.

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While ecological effects on short-term population dynamics are well understood, their effects over millennia are difficult to demonstrate and convincing evidence is scant. Using coalescent methods, we analysed past population dynamics of three lizard species (Psammodromus hispanicus, P. edwardsianus, P. occidentalis) and linked the results with climate change data covering the same temporal horizon (120 000 years). An increase in population size over time was observed in two species, and in P. occidentalis, no change was observed. Temporal changes in temperature seasonality and the maximum temperature of the warmest month were congruent with changes in population dynamics observed for the three species and both variables affected population density, either directly or indirectly (via a life-history trait). These results constitute the first solid link between ecological change and long-term population dynamics. The results moreover suggest that ecological change leaves genetic signatures that can be retrospectively traced, providing evidence that ecological change is a crucial driver of genetic diversity and speciation.

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Climate change affects the rate of insect invasions as well as the abundance, distribution and impacts of such invasions on a global scale. Among the principal analytical approaches to predicting and understanding future impacts of biological invasions are Species Distribution Models (SDMs), typically in the form of correlative Ecological Niche Models (ENMs). An underlying assumption of ENMs is that species-environment relationships remain preserved during extrapolations in space and time, although this is widely criticised. The semi-mechanistic modelling platform, CLIMEX, employs a top-down approach using species ecophysiological traits and is able to avoid some of the issues of extrapolation, making it highly applicable to investigating biological invasions in the context of climate change. The tephritid fruit flies (Diptera: Tephritidae) comprise some of the most successful invasive species and serious economic pests around the world. Here we project 12 tephritid species CLIMEX models into future climate scenarios to examine overall patterns of climate suitability and forecast potential distributional changes for this group. We further compare the aggregate response of the group against species-specific responses. We then consider additional drivers of biological invasions to examine how invasion potential is influenced by climate, fruit production and trade indices. Considering the group of tephritid species examined here, climate change is predicted to decrease global climate suitability and to shift the cumulative distribution poleward. However, when examining species-level patterns, the predominant directionality of range shifts for 11 of the 12 species is eastward. Most notably, management will need to consider regional changes in fruit fly species invasion potential where high fruit production, trade indices and predicted distributions of these flies overlap.