Book Reviews

Michael Seltzer, Christian Kullberg, Soren Peter Olesen, Ilmari Rostila (eds): Listening to the Welfare State. Aldershot, Ashgate, 2001. 267 pp, ISBN 0-7546-1565-0, £45.00     

Power, Politics, and the Framing of Environmental Illness

The medical community, along with other government agencies, has created its own frame of environmental illness. This frame has been generally accepted by the American public. In this paper we discuss framing in general and the factors related to how the environmental illness frame has been constructed and maintained. We offer a brief history of the medical institution and illustrate the frame with its definitions of environmental illness. Qualitative data from a study of Oak Ridge, a contaminated community located in Tennessee, are examined to analyze the consequences of challenging the environmental illness frame. Implications for future research are discussed.     

Linear Increments with Non‐monotone Missing Data and Measurement Error

Linear increments (LI) are used to analyse repeated outcome data with missing values. Previously, two LI methods have been proposed, one allowing non‐monotone missingness but not independent measurement error and one allowing independent measurement error but only monotone missingness. In both, it was suggested that the expected increment could depend on current outcome. We show that LI can allow non‐monotone missingness and either independent measurement error of unknown variance or dependence of expected increment on current outcome but not both. A popular alternative to LI is a multivariate normal model ignoring the missingness pattern. This gives consistent estimation when data are normally distributed and missing at random (MAR). We clarify the relation between MAR and the assumptions of LI and show that for continuous outcomes multivariate normal estimators are also consistent under (non‐MAR and non‐normal) assumptions not much stronger than those of LI. Moreover, when missingness is non‐monotone, they are typically more efficient.     

The effect of a novel ADL-based training program on performance of activities of daily living and physical fitness

The purpose of this study was to determine the degree to which a novel training program based on activities of daily living (ADL) would affect performance of ADLs, as well as the fitness of older adults. Fourteen individuals (mean age 82 years) took part in a 10-week control period followed by a 10-week ADL-based training program. Pre- and posttests included the Physical Performance Test (PPT), the Physical Functional Performance-10 (PFP-10), and the Senior Fitness Test (SFT). After the training period, improvements ranging from 7% to 33% (p<.05) were seen on the PPT and PFP-10 and on three items of the SFT. After conversion to standard scores, the magnitude of change in the PPT and the PFP10 was significantly greater (p<.05) than the magnitude of change in the SFT. These data support the idea that this novel ADL-based training program was able to facilitate improved performance of ADLs, as well as select measures of fitness among older adults.     

Reading your Counterpart: The Benefit of Emotion Recognition Accuracy for Effectiveness in Negotiation

Using meta-analysis, we find a consistent positive correlation between emotion recognition accuracy (ERA) and goal-oriented performance. However, this existing research relies primarily on subjective perceptions of performance. The current study tested the impact of ERA on objective performance in a mixed-motive buyer-seller negotiation exercise. Greater recognition of posed facial expressions predicted better objective outcomes for participants from Singapore playing the role of seller, both in terms of creating value and claiming a greater share for themselves. The present study is distinct from past research on the effects of individual differences on negotiation outcomes in that it uses a performance-based test rather than self-reported measure. These results add to evidence for the predictive validity of emotion recognition measures on practical outcomes.

Income Inequality across the Rural-Urban Continuum in the United States, 1970–2016*

The growth in macro-level income inequality in the United States is well established, but less is known about patterns of inequality at subnational scales and how they vary between and within rural and urban localities. Using data from the Decennial Census and American Community Survey, we produce estimates of within-county income inequality from 1970 to 2016 and analyze differences in inequality levels, the persistence of high (low) inequality, and populations' exposure to high (low) inequality across the rural-urban continuum. We find that income inequality has historically been higher in non-metropolitan than metropolitan counties, but inequality levels converged by 2016 due to growing inequality in metropolitan counties. Additionally, levels of inequality were generally persistent within counties over time, except that counties characterized by low inequality in 1970 were unlikely to remain as such in 2016. Third, non-trivial shares of the metropolitan population resided in low-inequality contexts in 1970, but virtually none of the U.S. population resided in such places by 2016. Residence in high-inequality counties is normative in rural and urban America. This statistical analysis provides an updated portrait of income inequality across the rural-urban continuum, and should spur additional research on stratification in rural America during an era of growing inequality.