Physical exercise,employee fitness and the management of health at work

Abstract

This paper presents some recent data on why organizations invest in exercise and physical fitness programmes for their stiff. These data suggest that, owing to a lack of evaluation studies, organizations act mainly on the basis of assumption and belief. However, from a subsequent review of the available literature on the personal and organizational effects of such programmes, it appears that these assumptions and beliefs are not altogether unfounded. The paper concludes by discussing the ways in which exercise and employee fitness programmes might help die individual and their organization in terms of the management of health at work.     

Women's Critical Responses to Sexually Explicit Material: The Role of Hyperfemininity and Processing Style

Previous research on women's responses to male-targeted sexually explicit material (SEM) suggests that women may be critical toward such content. However, women's critical responses to SEM have not been explained empirically. The present study had two goals: (1) to investigate whether women's critical responses to male-targeted SEM depend on individual differences in gender role orientation (i.e., hyperfemininity) and (2) to explain the effect of hyperfemininity on critical responses to SEM by looking at the way sexual material is processed. In an online experiment among women aged 18 to 30 (N = 195), both the type of SEM (a male- versus female-targeted erotic story) and processing style (stimulus- versus response-focused) were manipulated. In addition, participants were divided into three groups based on low, moderate, or high hyperfemininity. When using stimulus-focused processing (i.e., attending to the characters and situational context of the story), women were more critical toward male-targeted SEM (relative to female-targeted material), but only when they had low and moderate degrees of hyperfemininity.     

Optimal Forecasts from Markov Switching Models

We derive forecasts for Markov switching models that are optimal in the mean square forecast error (MSFE) sense by means of weighting observations. We provide analytic expressions of the weights conditional on the Markov states and conditional on state probabilities. This allows us to study the effect of uncertainty around states on forecasts. It emerges that, even in large samples, forecasting performance increases substantially when the construction of optimal weights takes uncertainty around states into account. Performance of the optimal weights is shown through simulations and an application to U.S. GNP, where using optimal weights leads to significant reductions in MSFE. Supplementary materials for this article are available online.