The meaning of patient satisfaction with prepaid primary health care in Israel

This paper reports the development of a self-administered Hebrew-language questionnaire for assessing patient satisfaction with primary care in Israel. Four scale measures of patient satisfaction were empirically constructed. These scales pertained to doctor conduct, doctor-patient communication, teamwork, and ease of access. In addition, a single direct question was used to measure overall satisfaction with the care. Ratings of all aspects of care were negatively skewed, with doctor-conduct and doctor-patient communication usually being the most satisfactory aspects and access the least satisfactory. It was shown that different practices, or the same practice at different points in time, can easily and meaningfully be compared, using mean satisfaction scores, measures of standard deviation, or percentages in each practice with ratings above (or below) the overall mean of all practices. The use of specific measures of patient satisfaction for comparison and intervention is discussed.     

Gaining Competitive Advantages in Higher Education: Analyzing the Gap between Expectations and Perceptions of Service Quality

The research findings have provided several implications for higher educational institutions, managers, and leaders of decision-making processes throughout the world. Service quality, customer satisfaction, and behavioral intentions are global issues that affect all organizations, large or small, profit or non-profit, global or local. We are all influenced or discouraged, satisfied or dissatisfied with positive loyalty behavioral intentions or negative complaining reactions, propelled by the level of service quality received. This revised version was published online in July 2006 with corrections to the Cover Date.     

Managerial Involvement and Perceptions of Strategy Process

Prior academic research attests to both positive and negative effects of involvement on the process of developing strategy. On the one hand, it has been argued that involvement strengthens shared vision, increases rationality and improves adaptiveness in strategy-making. On the other hand, involvement is said to lead to intense political behaviour, increased cultural inertia and more constraints in the strategy process. The purpose of this study is to investigate the relative importance of these effects. In a survey of over 6,000 managers, we find that their reported levels of involvement are positively associated with perceptions of strategy development processes that are more rational, more focused by a shared vision, and more adaptive. In addition, involvement is negatively associated with statements describing the process as top-down, influenced by politics and slowed by internal culture. Moreover, those who are more involved tend to see business and non-business constraints as less important in determining strategy. We argue that these associations between involvement and desirable features of strategy process are important because perceptions are the basis of managerial behaviour. Thus, managers who are more involved in strategy not only see the process in a more favourable light but also act in ways that make the process more effective. The main implication of these findings is that for most organisations increasing involvement improves the strategy process.     

What Drives Citizen Participation in Political Gatherings in Modern South Africa? A Quantitative Analysis of Self-Reported Behaviour

Social Indicators Research - Community and public gatherings are an important component of political participation in sub-Saharan Africa. Formal and informal community meetings and rallies are...     

Beyond the urban stream syndrome: organic matter budget for diagnostics and restoration of an impaired urban river

In response to water quality standard violations linked to excessive organic matter (OM) and a lack of sampling data informing the Total Maximum Daily Load (TMDL), an organic matter budget was created to quantify and identify sources of OM in the lower Jordan River (Salt Lake City, UT). By sampling dissolved, fine and coarse particulate OM, as well as measuring ecosystem metabolism at seven different sites, the researchers aimed to identify the origin of excess OM, and understand pathways by which different size classes of the OM pool are generated. The dissolved fraction (DOM; 94 %) was found to be the dominant form of OM transported within the river with fine particulate organic matter (FPOM; 6 %) the second most abundant, and coarse particulate organic matter (CPOM; 1 %) transport relatively insignificant in the overall OM budget. Primary production exceeded respiratory losses in the upper river, and this, along with OM inputs from two tributaries (where water reclamation facilities discharge into the river) delivered excess OM to the impaired lower reaches. Increasing stream metabolism index (SMI) with distance downstream (>1 in the lower river) further demonstrated that transport of excessive organic matter into the lower river was from upstream sources and not due to lateral inputs. This simple approach to characterizing the organic matter budget as it relates to water quality in the Jordan River was effective and could serve as a model for future studies attempting to quantify and identify sources of OM in urban ecosystems.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.