Confounding Bias In Comparative Effectiveness Research

Components of Forklifts

Discuss about the Confounding Bias in Comparative Effectiveness Research.

Forklifts refer to small industrial vehicles that have a forked platform that is operated by power and is attached at the front in a way that facilitates easy lowering or raising for insertion under cargo vehicles to move or lift them. In other words, forklifts are powered industrial trucks that are used for moving and lifting materials over small distances (Jacobus et al. 2015). These vehicles were developed in 20^th century and their use greatly expanded during the World War II. Thus, they became indispensable components of equipment in warehousing and manufacturing. However, forklift safety are subject to a plethora of standards worldwide. Brakes of a forklift have been found to result in a loss of load or tip over, when applied suddenly (Houf et al. 2013). This assignment will propose effective traffic management plan for forklift operators, to enhance their health and safety.

Forklifts consist of a variety of components that are necessary for handling their tasks effectively such as, truck frame, power source, counterweight, carriage, and mast. Research studies have elaborated on the entwining mechanisms of hydraulic cylinders, roller chain pulleys and controls in the operation of forklifts. An article stated that an estimated 50%of forklift accidents that resulted in injury of the operators occurred due to collisions in Victoria. It reported a significant reduction in the rates of forklift injury and fatality accidents over the past two decades (Saric et al. 2013). According to another study, crushing of the operator when falling off or tipping over the trucks contributed significantly to high death rates due to forklift accidents (Chae 2013). Other findings suggested that approximately 44% of the forklift accidents were found to involve pedestrians and led to 58% fatality in such cases. The study also stated that the traffic volume in a certain area where the forklift trucks are being operated and the number of pedestrians present at that time create a major impact on the accident rates (Rigby et al. 2013). Furthermore, it also took into account the fact that most forklift users have reconsidered the need for separating pedestrian and forklift traffic, with the aim of reducing accidents to the greatest possible extent. Reports also indicated that there occurred an estimated 110,000 accidents each year that involved forklift safety and as much as 94,750 injuries were found related to forklift accidents on an annual basis (Bragatto, Pirone and Gnoni 2014). This helped in identifying the need of devising an appropriate traffic management plan for reducing the rates of forklift accidents.

Forklift Safety

It will focus on determining the following things:

• The region where the forklift operators drive
• Type of surface that the forklift drivers work on
• The regions where the trucks load and unload
• The areas that the pedestrians require to access
• What traffic management approaches have been implemented
• What improvements have been observed

The study will be based on primary data collection process. Data will be gathered directly from original sources through direct observations and face-to-face interviews (SYLVIA 2018). Direct interaction will facilitate spotting the hazards that are associated with forklift movements, pedestrians and other vehicles. Interviews will also help in recording previous incidents of forklift accidents. The forklift drivers and other workers will also be contacted to assess their work environment and several aspects related to it.

The sample frame will be comprised of forklift operators, who have been working in the manufacturing industry for a minimum time period of two years and pedestrians. The method that would help in recruitment of the participants will be based on convenience sampling. This method is primarily a non-probability sampling form, where all participants will be selected based on their proximity and convenient accessibility (Emerson 2015). The sampling method will help in conducting a survey among people from the manufacturing workplaces and the nearby locality. The method is a relatively easier approach to recruit a sample, is inexpensive when compared to other methods and the participants would be readily available. 

Interviews and surveys will form the primary method of data collection (Lewis 2015) Interviews will encompass long conversations with the participants where they will be asked to elicit information that is essential for the research. The interviews will be conducted based on a personal approach where there will be scope of probing or asking follow-up questions. On the other hand, semi-structured questionnaires will also be distributed to the participants where the will be made to give responses to some questions in the form of yes or no and some that will be open-ended.

The qualitative data analysis will encompass a procedure where the responses collected from the workers at the manufacturing industry and the pedestrians will be collected and assembled into some kind of description or explanation. This will facilitate the interpretation of the situation (forklift accident) that will be investigated. Thus, the data analysis process will include gaining a sound understanding of specific patterns, which in turn would be followed by organizing the data into relevant themes.

Sampling bias might occur if the selected sample fails to represent the entire population. Efforts will be taken to ensure that the confounding variables do not ruin the results of an experiment. This bias will be removed by matching the participants according to their age and gender. Moreover, restriction procedure will help in ensuring that the confounding factors are distributed unequally (Haneuse 2016). Steps will be taken to avoid storage of sensitive data on forklift operations in machines that are connected to external networks. Data will not be sent via any file transfer technique or email, without proper encryption.

Data Collection Process

The inclusion criteria for selecting the workers will be:

• Minimum class 8^th educational qualification
• Must be 18 years of age
• Completed forklift driver training
• Must have the high risk work license
• Must be working as an operator for the last two years

The forklift operators will play the role of giving direct information about the places where they load and unload their trucks, those with high traffic, and impacts of traffic management. The pedestrians will provide information on account of encountering any forklift truck accident and the time when they find these trucks to operate most.

Showing respect for the autonomy of the workers and the pedestrians, while interacting with them during the interviews, if they refuse to provide answer to specific questions is required. The benefits of the research should be maximized, while reducing risks of any kind of physical or psychological harm. Furthermore, the participants will be selected from a group that will derive maximum benefits from the research conducted on knowing benefits of traffic management plan. One major ethical consideration will be the recruitment of human subjects (Ritchie et al. 2013). The Institutional Review Board (IRB) will be consulted for seeking an approval for the research. This will help in ensuring that no form of human rights are violated during the research. Issues of voluntary participation and informed consent shall also be taken into account where the workers and pedestrians will be provided the opportunity to participate in the research of their own fill, after they have been completely informed of the procedures, benefits and potential risks of the research process (Brinkmann 2014). Their participation will be free of all kinds of coercion. Anonymity and confidentiality will also be maintained while utilizing the interview and questionnaire responses for data analysis, and recommendations.

References

Bragatto, P.A., Pirone, A. and Gnoni, M.G., 2014. Application of RFID technology for supporting effective risk management in chemical warehouses. Safety, Reliability and Risk Analysis: Beyond the Horizon Taylor & Francis Group.

Brinkmann, S., 2014. Interview. In Encyclopedia of critical psychology (pp. 1008-1010). Springer New York.

Chae, J., 2013. A Study on Safety Improvement of Forklift Truck. Journal of the Korean Society of Safety, 28(4), pp.91-96.

Emerson, R.W., 2015. Convenience sampling, random sampling, and snowball sampling: How does sampling affect the validity of research?. Journal of Visual Impairment & Blindness (Online), 109(2), p.164.

Haneuse, S., 2016. Distinguishing selection bias and confounding bias in comparative effectiveness research. Medical care, 54(4), p.e23.

Houf, W.G., Evans, G.H., Ekoto, I.W., Merilo, E.G. and Groethe, M.A., 2013. Hydrogen fuel-cell forklift vehicle releases in enclosed spaces. International Journal of Hydrogen Energy, 38(19), pp.8179-8189.

Jacobus, C.J., Beach, G.J. and Rowe, S., Cybernet Systems Corp, 2015. Automated warehousing using robotic forklifts. U.S. Patent 8,965,561.

Lewis, S., 2015. Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), pp.473-475.

Rigby, M.P., Downs, G.M., Leyland, M.W.A. and Klumb, D.M., FLOW RITE SAFETY SOLUTIONS Inc, 2013. Warning device and collision avoidance system. U.S. Patent Application 13/773,458.

Ritchie, J., Lewis, J., Nicholls, C.M. and Ormston, R. eds., 2013. Qualitative research practice: A guide for social science students and researchers. sage.

Saric, S., Bab-Hadiashar, A., Hoseinnezhad, R. and Hocking, I., 2013. Analysis of forklift accident trends within Victorian industry (Australia). Safety science, 60, pp.176-184.

SYLVIA, M.L., 2018. Primary Data Collection. Clinical Analytics and Data Management for the DNP, p.87.