Preliminary Reliability Study of Computerized Neurobehavioural Test Method

  • Norlida Shaari Jabatan Pendidikan Politeknik & Kolej Komuniti, Aras 5, Galeria PjH, Jalan P4w, Persiaran Perdana, Presint 4, 62100 W.P. Putrajaya
  • Azian Hariri Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor
  • Nuur Azreen Paiman Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor
  • Nurul Fitriah Nasir Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor
  • Normayati Nordin Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor
  • Ainun Rahmahwati Ainuddin Occupational Safety, Health and Environment Division, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor
  • Norasikin Mat Isa Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor
Keywords: NCTB, Computerized Neurobehavioural Test, Test–retest, ICC, Reliability

Abstract

The recently developed Neurobehavioural Risk Assessment Evaluation System 1.0 (NeuRAES 1.0) tool aims to assess the neurobehavioural performance in Malaysia. Prior to utilize the advantage of the developed NeuRAES 1.0 tool effectively, it is vital to evaluate its reliability. The study aimed to conduct test and retest of NeuRAES 1.0 and assess the reliability of the NeuRAES 1.0 tool among university students in Universiti Tun Hussein Onn Malaysia (UTHM). With that regard, the reliability of the tool was examined among 40 healthy university students using a test–retest of four computerized tests that are, Benton Visual Retention, Symbol Memory, Trail Making, and Pursuit Aiming, with the test and retest held two weeks apart. The reliability was analyzed for all test measures using the Pearson product-moment correlation coefficient (r) and the intraclass correlation coefficient (ICC). A two-way mixed effect model was applied in this study to determine the ICCs and their 95% confidence intervals. The finding of all parameter measures in all four tests for standard scores were significantly similar, and the improvements of scores were also detected at retest for raw scores. The test–retest scores were found to have the ICC values ranging from low to adequate (0.269 to 0.655). The low ICCs were detected on Memory Symbol Test (r = 0.264, ICC = 0.269), Trail Making Test (Section A: r = 0.377, ICC = 0.383; Section B: r = 0.445, ICC = 0.452), Benton Visual Retention Test (r = 0.511, ICC = 0.517), and Pursuit Aiming Test (Test B: r = 0.567, ICC = 0.574). An adequate ICC was found on Pursuit Aiming Test (Test A: r = 0.649, ICC = 0.655). This demonstrating that the instrument still have not achieved a condition where, a measurement process is capable to produce stable and consistent scores when repeated over time except for Pursuit Aiming Test (Test A). In conclusion, the findings extend our understanding of score changes due to repeat testing. A further review on the test measures with low ICC needs to be considered. Therefore, further studies with larger samples and varied group of populations would be valuable.

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Author Biographies

Norlida Shaari, Jabatan Pendidikan Politeknik & Kolej Komuniti, Aras 5, Galeria PjH, Jalan P4w, Persiaran Perdana, Presint 4, 62100 W.P. Putrajaya


Azian Hariri, Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor


Nuur Azreen Paiman, Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor

Published
19-11-2018
How to Cite
Shaari, N., Hariri, A., Paiman, N. A., Nasir, N. F., Nordin, N., Ainuddin, A. R., & Mat Isa, N. (2018). Preliminary Reliability Study of Computerized Neurobehavioural Test Method. International Journal of Integrated Engineering, 10(5). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/3036
Section
Special Issue 2018: Mechanical Engineering