Öz

AGE AND EXPERIENCE BASED NEUROCOGNITIVE PERFORMANCE OF SEAFARERS

Öz

The main purpose of this study to assess the age-related cognitive decline rates and cognitive performances of the seafarers who belongs the different experience levels and age groups. ANAM4^R computerized cognitive test batteries were applied to determine the cognitive competencies and performances of the seafarers. Results were examined separately for each test using descriptive tables, one-way ANOVA test and The Tukey post-hoc test. Significant differences were found among groups in terms of cognitive abilities (p<.05). In all tests, oceangoing masters have the lowest mean accuracy score and represent the highest risk group for the possibility of human induced errors occurrence due to cognitive impairment. A direct relationship between cognitive performance decline and aging was detected in all cognitive tests.

Anahtar Kelimeler

• Cognition,Seafarers,Neurocognitive Tests,Maritime,Cognitive Abilities

Kaynakça

1. 1. Macrae, C., (2009). Human Factors at Sea: Common Patterns of Error in Groundings and Collisions. Maritime Policy & Management, 36(1), 21-38.
2. 2. Chidambaram, P., (2016). Perspectives on Human Factors in a Shifting Operational Environment. Journal of Loss Prevention in the Process Industries, 44, 112-118.
3. 3. Koester, T., (2001). Human Factors and Everyday Routine in the Maritime Work Domain. In Human Factors in Transportation, Communication, Health, and the Workplace. Human Factors and Ergonomics Society Europe Chapter Annual Meeting.
4. 4. Wiegmann, D. and Shappell, S., (1999). Human Error and Crew Resource Management Failures in Naval Aviation Mishaps: A review of U.S. Naval Safety Center data, 1990-96. Aviation, Space, and Environmental Medicine, 70, pp:1147-51.
5. 5. Tac, U., Tavacioglu L., Bolat, P., Kora, K., and Bolat, F., (2014). Monitoring Seafarers Cognitive Performance during a Voyage by Automated Neurological Assessment Metrics, Constanta Maritime University Annals, Vol:2, pp:299-311.
6. 6. Burgoyne, A.P., Sala, G., Gobet, F., Macnamara, B.N., Campitelli, G., and Hambrick, D.Z., (2016). The Relationship Between Cognitive Ability and Chess Skill: A comprehensive Meta-analysis. Intelligence, 59, 72-83.
7. 7. Salthouse, T.A., (2009). When Does Age-Related Cognitive Decline Begin? Neurobiology of Aging, 30(4), 507-514.
8. 8. Plassman, B.L., Welsh, K.A., Helms, M., Brandt, J., Page, W.F., and Breitner, J.C.S., (1995). Intelligence and Education as Predictors of Cognitive State in Late Life: A 50-year Follow-Up. Neurology 45, 1446–1450.

9. 9. Deary, I.J., Corley, J., Harris, S.E., Houlihan, L.M., Marioni, R.E., Penke, L., Rafnsson, S.B., and Starr, J.M., (2009). Age-Associated Cognitive Decline, British Medical Bulletin, Vol:92, No:1, pp:135-152, 12.2009,.
10. 10. Park, D.C. and Reuter-Lorenz, P., (2009). The Adaptive Brain: Aging and Neurocognitive Scaffolding. Annu Rev Psychol, 60, 173–196.
11. 11. Van Horik, J.O., Langley, E.J., Whiteside, M.A., and Madden, J.R., (2017). Differential Participation in Cognitive Tests is Driven by Personality, Sex, Body Condition and Experience. Behavioural processes, 134, 22-30. 12. ANAM4R System Quick Start Guide, (2016). Automated Neuropsychological Assessment Metrics.
12. 13. Johnson, D.R., Vincent, A.S., Johnson, A.E., Gilliland, K., and Schlegel, R.E., (2008). Reliability and Construct Validity of the Automated Neuropsychological Assessment Metrics (ANAM) Mood Scale. Archives of Clinical Neuropsychology, 23(1), 73-85.