No abstract

This monograph addresses the hypotheses that preschool children benefit most strongly when early care and education (ECE) is at or above a threshold of quality, has specific quality features, and/or is of longer duration. These issues are pivotal in recent policies designed to improve the quality of ECE, especially for children from low-income families. Evidence of quality thresholds in which ECE quality has stronger impacts in settings with moderate to high levels of quality than in settings with low quality would inform policy initiatives in which monetary incentives or consequences are allocated to ECE settings based on their level of quality. Evidence that specific features of quality, such as quality of teacher-child interactions and of literacy and mathematics instruction, are predictors of gains in child outcomes could help inform quality improvement efforts. Evidence that more time spent in center-based ECE or in instruction in specific content areas predict larger gains among preschoolers could be useful in designing public preschool programs such as Head Start or prekindergarten. Secondary data analyses of eight large studies of preschool children in center-based ECE were conducted. Analyses focused on quality thresholds and quality features examined the extent to which three types of quality measures predicted gains in children's language, literacy, mathematics, and social skills. The measures comprised (1) global quality measures that provide an overall or global rating of quality, focusing on interactions as well as on physical features of the environment, activities, and routines; (2) interaction-specific measures that focus in depth on the quality of interactions between teachers and children with respect to instructional and emotional support; and (3) domain-specific measures that focus on the quality of instruction and stimulation in specific content areas such as early language and literacy. The goal was to provide replicated analyses with data from several projects in order to address each question. Multilevel analyses that controlled for entry skills were conducted, and results were combined by using meta-analysis, nonlinear and nonparametric analyses, and propensity score analyses. With respect to thresholds, the analyses suggest that increases in the quality of instruction are related to larger gains in language and literacy outcomes, but only in higher quality classrooms. Results point to stronger associations between quality and child outcomes in higher versus lower quality classrooms for measures of the instructional quality of teacher-child interactions and of the quality of specific activities thought to promote early literacy, such as teaching phonemic skills and book reading. In addition, the items focusing on quality of interactions on the global measure also predicted acquisition of language and social skills in higher but not in lower quality classrooms. With respect to quality features, interaction-specific and especially domain-specific measures of quality remained significant pr...

Background and purpose: Skilled nursing facilities (SNFs) are penalized for hospital readmissions within 30 days. Medication errors often precipitate hospital returns. The Centers for Medicare and Medicaid Services mandates that health care providers must determine whether medications pose significant risks and implement corrective actions. Federal restrictions exist regarding nurse practitioners (NPs) in long-term care; however, NPs are efficient in the health care of patients requiring a SNF, including completing thorough medication reconciliation and correcting deficiencies. Local Problem: A needs assessment of a 90-bed SNF revealed inadequate medical coverage and no formalized program to reduce hospital readmissions, including a mandated medication reconciliation process. The problem contributed to an average 30-day readmission rate of 24.15%. Methods: The investigators sought to determine whether an NP-led medication reconciliation on admission would reduce hospital readmissions from a SNF. A pre- and postimplementation design was used to compare 30-day hospital readmission rates over a 30-day project period. Interventions: An evidence-based workflow process for systematic medication reconciliation was designed. A full-time NP used the workflow process to complete stabilization visits with medication reconciliation on each facility admission. Results: Results revealed a hospital readmission rate of 19.2% preimplementation and 13.5% postimplementation, reflecting a 29.7% decrease in the rate of hospital readmissions within a 30-day period. Conclusion: A chi-square analysis conveyed no statistical significance; yet, the positive benefits of NP intervention included reduced hospitalizations, increased revenue, improved quality measures and survey results, and preparation for the Centers for Medicare and Medicaid Services mandates. Implications for practice: Nurse practitioners have the necessary education and skills to provide quality care as well as achieving CMS mandates and improving quality measures in SNF settings.

Jumping to conclusions during probabilistic reasoning is a cognitive bias reliably observed in psychosis, and linked to delusion formation. Although the reasons for this cognitive bias are unknown, one suggestion is that psychosis patients may view sampling information as more costly. However, previous computational modelling has provided evidence that patients with chronic schizophrenia jump to conclusion because of noisy decision making. We developed a novel version of the classical beads-task, systematically manipulating the cost of information gathering in four blocks. For 31 individuals with early symptoms of psychosis and 31 healthy volunteers, we examined the numbers of ‘draws to decision’ when information sampling had no, a fixed, or an escalating cost. Computational modelling involved estimating a cost of information sampling parameter and a cognitive noise parameter. Overall patients sampled less information than controls. However, group differences in numbers of draws became less prominent at higher cost trials, where less information was sampled. The attenuation of group difference was not due to floor effects, as in the most costly block participants sampled more information than an ideal Bayesian agent. Computational modelling showed that, in the condition with no objective cost to information sampling, patients attributed higher costs to information sampling than controls (Mann-Whiney U=289, p=0.007), with marginal evidence of differences in noise parameter estimates (t=1.86 df=60, p=0.07). In patients, individual differences in severity of psychotic symptoms were statistically significantly associated with higher cost of information sampling (rho=0.6, p=0.001) but not with more cognitive noise (rho=0.27, p=0.14); in controls cognitive noise predicted aspects of schizotypy (preoccupation and distress associated with delusion-like ideation on the Peters Delusion Inventory). Using a psychological manipulation and computational modelling, we provide evidence that early psychosis patients jump to conclusions because of attributing higher costs to sampling information, not because of being primarily noisy decision makers.

Jumping to conclusions during probabilistic reasoning is a cognitive bias reliably observed in psychosis and linked to delusion formation. Although the reasons for this cognitive bias are unknown, one suggestion is that psychosis patients may view sampling information as more costly. However, previous computational modeling has provided evidence that patients with chronic schizophrenia jump to conclusions because of noisy decision-making. We developed a novel version of the classical beads task, systematically manipulating the cost of information gathering in four blocks. For 31 individuals with early symptoms of psychosis and 31 healthy volunteers, we examined the numbers of “draws to decision” when information sampling had no, a fixed, or an escalating cost. Computational modeling involved estimating a cost of information sampling parameter and a cognitive noise parameter. Overall, patients sampled less information than controls. However, group differences in numbers of draws became less prominent at higher cost trials, where less information was sampled. The attenuation of group difference was not due to floor effects, as in the most costly block, participants sampled more information than an ideal Bayesian agent. Computational modeling showed that, in the condition with no objective cost to information sampling, patients attributed higher costs to information sampling than controls did, Mann–Whitney U = 289, p = 0.007, with marginal evidence of differences in noise parameter estimates, t(60) = 1.86, p = 0.07. In patients, individual differences in severity of psychotic symptoms were statistically significantly associated with higher cost of information sampling, ρ = 0.6, p = 0.001, but not with more cognitive noise, ρ = 0.27, p = 0.14; in controls, cognitive noise predicted aspects of schizotypy (preoccupation and distress associated with delusion-like ideation on the Peters Delusion Inventory). Using a psychological manipulation and computational modeling, we provide evidence that early-psychosis patients jump to conclusions because of attributing higher costs to sampling information, not because of being primarily noisy decision makers.