NEIGHBORHOOD DISORDER AND INDIVIDUAL COMMUNITY CAPACITY: HOW INCIVILITIES INFORM THREE DOMAINS OF PSYCHOSOCIAL ASSESSMENT

This article examines contextual models to bring together the disorder and community capacity perspectives, since both are grounded in social (dis)organization theory and cumulative causation. We analyze how individual and neighborhood characteristics, social and physical disorder, and crime affect three individual community capacity outcomes: city quality of life, neighborhood safety, and household moving intentions. The “broken windows” downward spiral suggests that neighborhood incivilities may decrease multiple psychosocial assessments, or, individual community capacities. Consistent with prior research, we find that social and physical disorder decreases all three outcomes. Second, we find that both disorders also mediate neighborhood effects, including socioeconomic status and residential stability. Third, these direct and indirect disorder effects are not altered by prior victimization or neighborhood crime rates. Reducing disorder will, in turn, improve three distinct domains and geographic scales of individual community capacity, and can also reduce the adverse effects of other local area capacity deficits.     

The Issue of Consent in Research that Administers Drugs of Addiction to Addicted Persons

In addiction, impaired control over drug use raises questions about the capacity of addicted persons to consent to participate in research studies in which they are given their drug of addiction. We review the case for doing such research, and the arguments that addiction does, and does not, prevent addicted persons from consenting to such research. We argue for a more nuanced view that acknowledges that while in some situations addiction impairs decision-making capacity, it does not eliminate such capacity. We conclude with some suggestions for recruiting addicted subjects and designing experiments in ways to obtain free and informed consent.     

Integrating Process Interventions into a School-Based Curriculum Group

ABSTRACT

Manualized approaches are widely used in work with aggressive, impulsive, and oppositional behaviors to improve their peer relations, school behavior, and interactions with adults, including their teachers. When group-work principles and interventions are not applied to the live spontaneous group situations that arise, however, workers miss opportunities to further help members understand, incorporate, and practice the very behaviors being offered in the curriculum. This article describes a curriculum-based group experience and the successes and limitations of the work that was done and identifies areas in which the integration of more traditional group process interventions could have increased the effectiveness of the cognitive-behavioral curriculum-oriented approach.     

The benefits of a nap during prolonged work and wakefulness

Abstract

Prolonged work scenarios with demands for sustained performance are increasingly common. Because sleep loss inevitably compromises functioning in such situations, napping has been proposed as a countermeasure. The optimal timing of the nap relative to its benefits for performance and mood is not known, however. To address this issue, 41 healthy adults were permitted a two-hour nap at one of five times during a 56-hour period of intermittent work, with no other sleep. Naps were placed 12 hours apart, near the circadian peak (P) or trough (T), and were preceded by 6(P), 18(T), 30(P), 42(T), or 54(P) hours of wakefulness. Work test bouts occurred every few hours and consisted of a variety of psychomotor and cognitive tasks as well as mood scales completed at the beginning, middle and end of each bout. A total of eight performance and 24 mood parameters were derived from the bouts and compared between groups at all test points prior to and following the naps. An estimate of the extent to which each nap condition differed from the control (P54) condition was derived by totalling the proportion of test points that yielded statistically significant results relative to the total number of tests conducted both before and after naps.

Although all performance and most mood parameters displayed a circadian-modulated deterioration as the protocol progressed, a nap appeared to attentuate the extent of this change in all performance parameters but not in mood parameters. Overall, the timing of the nap across days and within the circadian cycle was irrelevant to its effect on performance, suggesting that it diminished the intrusion of sleepiness into behavioural functioning, even though subjects were phenomenally unaware of this benefit.     

Testing for the maximum mean in a mixture of normals

We consider the test of the null hypothesis that the largest mean in a mixture of an unknown number of normal components is less than or equal to a given threshold. This test is motivated by the problem of assessing whether the Soviet Union has been operating in compliance with the Nuclear Test Ban Treaty. In our analysis, the number of normal components is determined using Akaike's Information Criterion while the hypothesis test itself is based on asymptotic results given by Behboodian for a mixture of two normal components. A bootstrap approach is also considered for estimating the standard error of the largest estimated mean. The performance of the testa are examined through the use of simulation.     

Undercoverage of Wavelet-Based Resampling Confidence Intervals

The decorrelating property of the discrete wavelet transformation (DWT) appears valuable because one can avoid estimating the correlation structure in the original data space by bootstrap resampling of the DWT. Several authors have shown that the wavestrap approximately retains the correlation structure of observations. However, simply retaining the same correlation structure of original observations does not guarantee enough variation for regression parameter estimators. Our simulation studies show that these wavestraps yield undercoverage of parameters for a simple linear regression for time series data of the type that arise in functional MRI experiments. It is disappointing that the wavestrap does not even provide valid resamples for both white noise sequences and fractional Brownian noise sequences. Thus, the wavestrap method is not completely valid in obtaining resamples related to linear regression analysis and should be used with caution for hypothesis testing as well. The reasons for these undercoverages are also discussed. A parametric bootstrap resampling in the wavelet domain is introduced to offer insight into these previously undiscovered defects in wavestrapping.     

CHOICE-CONSTRAINED CONJOINT ANALYSIS

Choice-constrained conjoint analysis (CCCA) is a new method for metric conjoint analysis studies. It computes part-worth utility functions that account for “revealed preference”—those products a respondent actually selects in an independent choice situation. CCCA uses an iterative penalty function estimation procedure that successively modifies initial regressionderived part worths so that respondent choices (either actual or intended) of real brands are predicted as accurately as possible. The paper first describes the motivation and rationale for CCCA and presents the mathematics of the algorithm. As an illustration, it applies the CCCA model and penalty function estimation procedure to a limited set of synthetic data. A second application of the technique is presented that uses data obtained by a major telecommunications firm that used conjoint analysis to examine the importance of several features of residential communication devices. The paper also discusses potential extensions of the CCCA model and the kinds of marketing applications for which it might be useful.