Data collection costs in industrial environments for three occupational posture exposure assessment methods

BMC Medical Research Methodology

关键词: Ergonomics;    Posture;    Inclinometer;    Observation;    Questionnaire;   

DOI  :  10.1186/1471-2288-12-89

来源: DOAJ

【 摘 要 】

Abstract

Background

Documentation of posture measurement costs is rare and cost models that do exist are generally naïve. This paper provides a comprehensive cost model for biomechanical exposure assessment in occupational studies, documents the monetary costs of three exposure assessment methods for different stakeholders in data collection, and uses simulations to evaluate the relative importance of cost components.

Methods

Trunk and shoulder posture variables were assessed for 27 aircraft baggage handlers for 3 full shifts each using three methods typical to ergonomic studies: self-report via questionnaire, observation via video film, and full-shift inclinometer registration. The cost model accounted for expenses related to meetings to plan the study, administration, recruitment, equipment, training of data collectors, travel, and onsite data collection. Sensitivity analyses were conducted using simulated study parameters and cost components to investigate the impact on total study cost.

Results

Inclinometry was the most expensive method (with a total study cost of € 66,657), followed by observation (€ 55,369) and then self report (€ 36,865). The majority of costs (90%) were borne by researchers. Study design parameters such as sample size, measurement scheduling and spacing, concurrent measurements, location and travel, and equipment acquisition were shown to have wide-ranging impacts on costs.

Conclusions

This study provided a general cost modeling approach that can facilitate decision making and planning of data collection in future studies, as well as investigation into cost efficiency and cost efficient study design. Empirical cost data from a large field study demonstrated the usefulness of the proposed models.

【 授权许可】

Unknown