Assessment of musculoskeletal disorders among employees working office workplaces in the manufacturing sector.

BACKGROUND: The number of studies investigating the relationship between office employees and the development of musculoskeletal disorders (MSDs) is limited. Only a few focused on assessing workplace ergonomics of office employees. OBJECTIVE: This study aims to investigate the risk of MSDs and associated factors in the office workplaces of a large-size manufacturing company. METHODS: Data were gathered from 208 office employees from a manufacturing company via Rapid Office Strain Assessment (ROSA) and Cornell questionnaire. The collected data were analyzed to examine the relationship between ergonomic risk levels and MSDs reported by the office staff. RESULTS: The mean ROSA final score is 3.52 (std. dev. = 0.71), chair section is 3.30, monitor and telephone section is 2.18, and mouse and keyboard section is 2.69. Thirty-nine of 208 (18.8%) office workplaces are at risk. The most important factor to raise the risk level is found to be the height and depth of the chair. The Cornell questionnaire results highlight that the highest discomfort severity is related to the neck (32.26%), lower back (23.23%) and upper back (22.26%). The discomforts in the neck (r = 0.362), upper back (r = 0.404) and lower back (r = 0.368) are moderately and positively correlated according to the final ROSA score. The results indicate that the highest risked departments are Accounting, Sub Industry, Production Planning, and Manufacturing Management. CONCLUSION: The parameters associated with the chair section should be considered a priority for reducing and eliminating MSDs among office employees.

Classification of BCI Users Based on Cognition.

Brain-Computer Interfaces (BCI) are systems originally developed to assist paralyzed patients allowing for commands to the computer with brain activities. This study aims to examine cognitive state with an objective, easy-to-use, and easy-to-interpret method utilizing Brain-Computer Interface systems. Seventy healthy participants completed six tasks using a Brain-Computer Interface system and participants' pupil dilation, blink rate, and Galvanic Skin Response (GSR) data were collected simultaneously. Participants filled Nasa-TLX forms following each task and task performances of participants were also measured. Cognitive state clusters were created from the data collected using the K-means method. Taking these clusters and task performances into account, the general cognitive state of each participant was classified as low risk or high risk. Logistic Regression, Decision Tree, and Neural Networks were also used to classify the same data in order to measure the consistency of this classification with other techniques and the method provided a consistency between 87.1% and 100% with other techniques.

Job evaluation for clinical nursing jobs by implementing the NHS JE system.

AIM: The purpose of this paper was to evaluate locally all the clinical nursing jobs implementing the NHS JE system in four hospitals. BACKGROUND: The NHS JE was developed by the Department of Health in the UK in 2003-2004. METHODS: A job analysis questionnaire was designed to gather current job descriptions. It was distributed to each of 158 clinical nurses and supervisor nurses in 31 variety clinics at four hospitals in one city. The questionnaires were analysed to evaluate locally all the identified 94 nursing jobs. RESULTS: Fourteen of 19 nursing jobs in the medical and surgical clinics can be matched to the nurse national job in the NHS JE system. CONCLUSIONS: The results indicated that two new nursing jobs titled nurse B and nurse advanced B should be added to the list of national nursing jobs in the NHS JE system.

A revision of a job evaluation system.

AIMS: This paper reports a revision of the United Kingdom's National Health Service Job Evaluation System and tests the revised system in eight clinical nursing management jobs in four Turkish hospitals. BACKGROUND: A job evaluation system was developed in the United Kingdom in 2003-2004. Most studies have focused on how the whole system will be implemented in a health organization. No study investigating proficiency of the system in terms of factors and their level definitions was found. METHODS: The factors Knowledge, Training and experience and Working conditions were divided into five factors: Knowledge, Experience, Education, Environmental conditions and Hazards. To test the revised system, all the nursing management jobs in four hospitals were evaluated using a factor-based questionnaire including nurses' demographic information and 19 variables. The questionnaire was distributed to 57 supervisor nurses in 31 clinics at four hospitals in one Turkish city in 2005. All the questionnaires were analysed to evaluate the jobs. RESULTS: The job scores change depending on clinical conditions. Although the score range in the National Health Service Job Evaluation system has been determined as 405-465 points (band VI) for Nurse team leader and 469-536 points (band VII) for Nurse team manager jobs, the job scores in the present study were 363 (band V) - 557 points (band VIIIa) and 379 (band V) - 586 points (band VIIIa) respectively. CONCLUSION: Although this exploratory study was limited to four hospitals in one city in Turkey, the results indicated that two new jobs would be identified in the National Health Service system to match the jobs in the intensive care and emergency units.