The Impact of Neighboring on Changes in Sense of Community Over Time: A Latent Transition Analysis

Sense of community (SOC) is associated with the quality of community life and the building of social capital. While its linkage to informal social behavior, such as neighboring, is inherent in discussions regarding theory, empirical evidence remains scarce. Moreover, the degree to which neighboring behavior influences SOC over time is largely unknown. Using a latent transition analysis, the effect of neighboring on SOC was investigated over a 5-year span from 2006 to 2011 among a sample of adults (n?=?165) in Arizona. Initially, a latent class analysis identified two SOC subgroups: Low SOC and High SOC. The likelihood of shifts in SOC class membership over 5 years was generally stable, with most individuals staying in the same group (82.3% Low SOC; 92.4% High SOC). Neighboring behavior and socio-demographic covariates impacted the likelihood that individuals changed classes, with 25.3% of Low SOC individuals transitioning to High SOC in 2011 and 55.4% of High SOC individuals moving to Low SOC in 2011. Specifically, having an income greater than $60,000 and visiting with neighbors lessened the likelihood of being in the Low SOC class in 2006; and length of residence and exchanging favors with neighbors lessened the likelihood of being in the Low SOC class in 2011. These findings have implications for both community design and community development practice. Design and development interventions that promote greater social interaction may help build and sustain SOC over time.

     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

NATURAL HEALTH DISCOURSES AND THE THERAPEUTIC PRODUCTION OF CONSUMER RESISTANCE

Social critics of the natural health movement charge that it indoctrinates consumers in a therapeutic consumerist ideology. This "dominated consumer" thesis ignores that socially situated individuals must negotiate a plethora of institutionally specific power structures aiming to classify and govern their identities. Accordingly, resistance toward specific institutional constructions of identity can be produced through marketplace ideologies. I explore this understudied ideological effect by analyzing the narratives of women who are using natural health alternatives to resist their ascribed medico-administrative identities. Natural health's therapeutic ideology enables these women to contest the degenerative implications of their medical diagnoses and, conversely, to reconstruct their chronic illnesses as an opportunity for discovering their inner regenerative potential and expanding their spiritual horizons. This analysis has implications for prior studies suggesting that resistance toward the technocratic and bureaucratic aspects of conventional medicine exemplifies a Foucauldian "care of the self." I argue that a postmodern adaptation of Foucauldian theory is needed to address the complex interrelationships among the care of the self, medical consumerism, and the therapeutic ideology of the natural health marketplace.     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Ideologies about work: An exploratory study

This paper focuses upon an as yet under-explored factor believed to underlie most managerial and organizational behavior variables—work ideology. Work ideologies are surveyed for several convenience samples of students and managers to show their ability to be studied and that patterned differences may be discovered. In addition, the historical origins and meanings of four major work ideologies are discussed.     

Anti-Poverty Action and Research in the U.K.

This paper briefly reviews the deteriorating position of the poor in the UK in recent years; summarizes the range of action and research initiatives that has developed to address the problem of poverty; and suggests an agenda of principles to inform further action and research.     

Implementation and process evaluation of a student "school-as-community" group. A component of a school-based drug abuse prevention program

Little documentation exists regarding the functioning of formalized adolescent groups as drug abuse prevention agents. Two studies are described that were conducted at high schools whose students are at high risk for drug abuse. Twenty-one schools were randomly assigned to one of three conditions: (a) standard care, (b) classroom drug abuse education only, or (c) classroom plus school-as-community. Results of the first study indicated that the school-as-community component--which involved weekly meetings and periodic events at seven schools--was implemented as planned, drug abused focused, and perceived as productive in discouraging drug abuse. In the second study, staff in the classroom plus school-as-community condition self-reported involvement in the greatest number of community activities across the school year, compared with staff from the other two conditions. These two studies support the feasibility of formalized groups of high-risk youth to promote drug-free events.