Outcomes For Street Children and Youth Under Multidisciplinary Care in a Drop-In Centre in Tegucigalpa, Honduras

BACKGROUND: There is little evidence to describe the feasibility and outcomes of services for the care of street children and youth in low-income countries. AIMS: To describe the outcomes of a multidisciplinary case management approach delivered in a drop-in centre for street children and youth. METHODS: A longitudinal study of street children and youth followed in an urban drop-in centre. Four hundred (400) street children and youth received a multidisciplinary case management therapeutic package based on the community reinforcement approach. The main outcomes were changes in psychological distress, substance abuse and social situation scores. RESULTS: The median follow-up time for the cohort was 18 months. There were reductions in the levels of psychological distress (p = 0.0001) and substance abuse (p ≤ 0.0001) in the cohort as well as an improvement in the social situation of street children and youth (p = 0.0001). There was a main effect of gender (p < 0.001) and a significant interaction of gender over time (p < 0.001) on improvements in levels of psychological distress. Survival analysis showed that the probability of remaining on substances at 12 months was 0.76 (95% CI: 0.69-0.81) and 0.51 (95% CI: 0.42-0.59) at 24 months. At 12 months, fewer female patients remained using substances compared to male (p < 0.01). CONCLUSION: To be most effective, programmes and strategies for children and youth in street situations in developing countries should target both their health and social needs

A bayesian multilevel modeling approach for data query in wireless sensor networks

In power-limited Wireless Sensor Network (WSN), it is important to reduce the communication load in order to achieve energy savings. This paper applies a novel statistic method to estimate the parameters based on the realtime data measured by local sensors. Instead of transmitting large real-time data, we proposed to transmit the small amount of dynamic parameters by exploiting both temporal and spatial correlation within and between sensor clusters. The temporal correlation is built on the level-1 Bayesian model at each sensor to predict local readings. Each local sensor transmits their local parameters learned from historical measurement data to their cluster heads which account for the spatial correlation and summarize the regional parameters based on level-2 Bayesian model. Finally, the cluster heads transmit the regional parameters to the sink node. By utilizing this statistical method, the sink node can predict the sensor measurements within a specified period without directly communicating with local sensors. We show that this approach can dramatically reduce the amount of communication load in data query applications and achieve significant energy savings

To think or to do: the impact of assessment and locomotion orientation on the Michelangelo phenomenon

This work examines how individual differences in assessment and locomotion shape goal pursuits in ongoing relationships. The Michelangelo phenomenon describes the role that close partners play in affirming versus disaffirming one another's pursuit of the ideal self. Using data from a longitudinal study of ideal goal pursuits among newly committed couples, we examined whether the action orientation that characterizes locomotion creates an optimal environment in which to give and receive affirmation, whereas the evaluative orientation that characterizes assessment creates a suboptimal environment for giving and receiving affirmation. Consistent with hypotheses, locomotion is positively associated with partner affirmation, movement toward the ideal self, and couple wellbeing, whereas parallel associations with assessment are negative. We also explore the behavioral mechanisms that may account for such associations

Emotional engagements predict and enhance social cognition in young chimpanzees

Social cognition in infancy is evident in coordinated triadic engagements, that is, infants attending jointly with social partners and objects. Current evolutionary theories of primate social cognition tend to highlight species differences in cognition based on human-unique cooperative motives. We consider a developmental model in which engagement experiences produce differential outcomes. We conducted a 10-year-long study in which two groups of laboratory-raised chimpanzee infants were given quantifiably different engagement experiences. Joint attention, cooperativeness, affect, and different levels of cognition were measured in 5- to 12-month-old chimpanzees, and compared to outcomes derived from a normative human database. We found that joint attention skills significantly improved across development for all infants, but by 12 months, the humans significantly surpassed the chimpanzees. We found that cooperativeness was stable in the humans, but by 12 months, the chimpanzee group given enriched engagement experiences significantly surpassed the humans. Past engagement experiences and concurrent affect were significant unique predictors of both joint attention and cooperativeness in 5- to 12-month-old chimpanzees. When engagement experiences and concurrent affect were statistically controlled, joint attention and cooperation were not associated. We explain differential social cognition outcomes in terms of the significant influences of previous engagement experiences and affect, in addition to cognition. Our study highlights developmental processes that underpin the emergence of social cognition in support of evolutionary continuity

On pancultural self-enhancement: well-adjusted Taiwanese self-enhance on personally valued traits

Taiwanese participants made better-than-average judgments on collectivistic and individualistic traits, evaluated the personal importance of those traits, and completed measures of psychological adjustment (depression, perceived stress, subjective well-being, and satisfaction with life). Replicating findings from other East Asian samples, participants self-enhanced (i.e., regarded the self as superior to peers) more on collectivistic than individualistic attributes and assigned higher personal importance to the former than the latter. Moreover, better adjusted participants manifested a stronger tendency to self-enhance on personally important attributes. These data are consistent with the view that self-enhancement is a universal human motive that is expressed tactically and at odds with the assertion that self-enhancement is a uniquely Western phenomenon. <br/

Within-Household Selection Methods: A Critical Review and Experimental Examination

Probability samples are necessary for making statistical inferences to the general population (Baker et al. 2013). Some countries (e.g. Sweden) have population registers from which to randomly select samples of adults. The U.S. and many other countries, however, do not have population registers. Instead, researchers (i) select a probability sample of households from lists of areas, addresses, or telephone numbers and (ii) select an adult within these sampled households. The process by which individuals are selected from sampled households to obtain a probability-based sample of individuals is called within-household (or within-unit) selection (Gaziano 2005).Within-household selection aims to provide each member of a sampled household with a known, nonzero chance of being selected for the survey (Gaziano 2005; Lavrakas 2008). Thus, it helps to ensure that the sample represents the target population rather than only those most willing and available to participate and, as such, reduces total survey error (TSE). In interviewer-administered surveys, trained interviewers can implement a prespecified within-household selection procedure, making the selection process relatively straightforward. In self-administered surveys, within-household selection is more challenging because households must carry out the selection task themselves. This can lead to errors in the selection process or nonresponse, resulting in too many or too few of certain types of people in the data (e.g. typically too many female, highly educated, older, and white respondents), and may also lead to biased estimates for other items. We expect the smallest biases in estimates for items that do not differ across household members (e.g. political views, household income) and the largest biases for items that do differ across household members (e.g. household division of labor). In this chapter, we review recent literature on within-household selection across survey modes, identify the methodological requirements of studying within-household selection methods experimentally, provide an example of an experiment designed to improve the quality of selecting an adult within a household in mail surveys, and summarize current implications for survey practice regarding within-household selection. We focus on selection of one adult out of all possible adults in a household; screening households for members who have particular characteristics has additional complications (e.g. Tourangeau et al. 2012; Brick et al. 2016; Brick et al. 2011), although designing experimental studies for screening follows the same principles

Growing Income Inequality Threatens American Education

The first of two articles in consecutive months describes the origins and nature of growing income inequality, and some of its consequences for American children. It documents the increased family income inequality that's occurred over the past 40 years and shows that the increased income disparity has been more than matched by an expanding gap between the amounts of money that low- and high-income parents spend on enrichment activities for their children. It also shows that the growth in income inequality has been accompanied by increasing gaps in academic achievement. The article draws from the first part of the author's recent book, Restoring Opportunity: The Crisis of Inequality and the Challenge for American Education (Harvard Education Press and the Russell Sage Foundation, 2014). The second part to the series, also drawn from Restoring Opportunity, describes ideas based on proven policy approaches that will enable the country to make progress on the enormous task of restoring the educational opportunities that children from low-income families need if they are to lead productive and fulfilling lives. © 2014

State and trait anger predicting creative process engagement – the role of emotion regulation.

Drawing on the specific emotion approach, and based on the emotional regulation theory and cognitive and activation perspectives on emotions, this study examined the differentiated impact of state and trait anger on creative process engagement (CPE) and the moderating influences of emotion reappraisal and suppression. Data were obtained from daily surveys (N = 422) of 98 employees from three consultancy companies. Hierarchical linear modeling analysis revealed that trait anger has a stronger impact on CPE than state anger does. Furthermore, the relationship between state anger and CPE is stronger when emotion reappraisal is lower, rather than higher, and the relationship between trait anger and CPE is also stronger when emotion suppression is lower, rather than higher