Symptoms of chronic stress at work in NGO workers

Working in a NGO often involves providing life saving resources (food, medicine, equipment, water, etc) to needy populations around the globe. Such duty requires highly dedicated employees and humanitarian workers are said to face a hign degree of pressure in their daily work. Despite the evidence of taxing work demands, and a high potential for stress related problems, very few studies on occupational chronic stress have specifically looked at NGO workers. Assuming that "field stress" can relay to workers at headquarters, we carried out an exploratory study about occupational health among employees of a NGO's headquarters. We sent a questionnaire to all employees (N=130) of a NGO headquarters located in Switzerland. We used the TST questionnaire (French version of the Langner's questionnaire on psychiatric symptoms) to identify cases with potential mental health problems. We also included in the questionnaire some items about motivation, acknowledgment, work-life balance, job demand, and autonomy. A total of 75 employees answered our questionnaire (57% response rate). 44% of our sample were men (n=33) and 56% were women (n=42). The mean age was of 40 years (SD=7.6). 56% were working at the headquarters of the NGO in questions as of 2 years or less. Not surprisingly, a majority of respondents reported to be highly motivated (74%) and the meaning of work was important for 80% of them. However, 35% indicated having problems in conciliating their private and professional life. Most frequent reported symptoms included feeling "weak all over" (81%), having "trouble getting asleep often" (35%), "clogging in nose" (35%), feeling "nervous often" (33%), and "memory not all right" (33%). The score for psychiatric symptoms was high in 8 (11%) employees whose health might therefore be at risk. In comparison, other sudies showed that this proportion was 9% for French teachers and 16% for sales personnel1. Results show that symptoms of mental health problems do occur among NGO workers. Some of these symptoms are known to be linked to occupational stress. Chronic stress manifests itself first in non-specific symptoms (e.g. fatigue) and later in specific pathologies. This could explain the relatively low proportion of cases with a high score in Langner's scale than was expected. Therefore, we hypothesize a healthy worker effect. The fact that our sample is 40 years old in average, and that the turnover is quite high can also support this hypothesis. Further research is needed in order to better understand occupational stress in this specific population. An upcoming study will investigate the role of organizational factors associated with health complaints. Therefore, a longitudinal survey including quantitative and qualitative methods is appropriate.

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.