Free Article Review About Odor Identification Ability Predicts Changes In Symptoms Of Psychopathology Following

Published: 2021-06-21 23:39:24
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Psychology
Studies show that odor perception is directly related to the condition and functioning of the orbitofrontal cortex. The olfactory abilities of an otherwise normal human being can be largely impaired by neurological diseases as well as brain injuries. Moreover, scientists have also found that the ability to identify smells is often closely linked to functional brain activity levels. Killgore and Associates (2007) conducted a study to showcase the effectiveness of odor detection tests in predicting susceptibility to sleep deprivation as measured through Personality Tests. This experiment sought to prove that a small olfactory test can be a good predictor of emotional and cognitive performance of sleep deprived subjects.
Hypotheses
Data
Participants were 22 (17 male and 5 female) healthy military personnel of age 24.9±3.9 years. The participants were pre-screened for nicotine use, caffeine users, history of depression, neurological, or psychological problems. The independent variable of the study was the ability to correctly identify and distinguish twenty different odors from self-administered Smell Identification Test (SIT). The dependent variable was the performance of the participants on a Personality Assessment Inventory (PAI). The PAI test consisted of 344 statements with each having four possible responses such as, “False, not at all true”, “slightly true”, “mainly true”, and “very true”. The PAI inventory has 11 scales, of which nine were used for the purpose of the present study.
Results
Broader Implication
The results of this study clearly shows that Smell Identification Test can be a good indicator of susceptibility to behavioral problems when subjects are sleep deprived. The hypotheses of the study was proved; however, an additional exploratory analyses showed that higher baseline SIT performance was associated with higher Manic Irritability in sleep deprived subjects. The authors believe that the linear relationship between low SIT performance, depressive affective symptoms, and perception of negative interpersonal relationships maybe a mechanism to protect the brain from adverse effects of sleep deprivation.
Limitations of the study
The primary limitation of the study was the low number of participants followed by a significant gender bias (only 5 female and 17 males), which could have been a confounding factor in the study. Authors only established correlations between the SIT scores and PAI results and ignored the fact that correlation and causation are not similar. The study collected Quantitative data from SIT and compared it with qualitative inputs from the Personality Assessment Inventory, if the authors had chosen a quantitative test such as measurements of IQ, they could have shown actual relationship through linear regression analysis. Only one scale of measurement was used to detect the effects of sleep deprivation and these were self-reported, the authors did not control for the lack of motivation in the participants after sleep deprivation.
Follow up study
The study by Killgore and associates (2007) looked at the predictive powers of SIT performance of 22 subjects (17 males, and 5 females) based on the Personality Assessment Inventory scale. The study was well-designed and effectively carried out, however, there is scope to improve upon the study design to draw out more information about the predictive capabilities of SIT. I propose to conduct a study to measure the SIT performance of 50 individuals (25male, and 25 female) and see how the results are correlated with IQ test Performance, Visual Attention, and spatial memory. In the previous study, the authors compared the quantitative independent variable with a qualitative dependent variable (PAI measures), which were self-reported by subjects. To improve the credibility of the test results, I will compare the results of SIT with quantitative variables derived from IQ tests and Visual attention tests. While the study by Killgore and associates (2007) looked at the effects of sleep deprivation on the PAI scores of participants pre-tested with SIT; my study will see how cognitive functions are affected by sleep deprivation, and how well SIT can predict the effect. Through this study, I can also better showcase the predictive powers of SIT on the cognitive abilities of subjects before and after sleep deprivation.
Hypotheses
The first hypothesis for this study will be that subjects scoring High on SIT will fare better on IQ tests and visual attention tests, since a higher score of SIT is associated with better functioning of oribito-frontal and prefrontal cortex regions of brain. The second hypothesis will be that following sleep deprivation, subjects with higher initial SIT will score better on IQ and visual attention tests than the rest of the participants. The third hypothesis is that subjects with initial high SIT performance will be able to maintain the similar level of performance after sleep deprivation compared to subjects, who scored low on SIT initially.
Study subjects and Methodology
50 individuals from a college (between ages of 24-25) will be chosen at random. I want to conduct the study on 25 male, and 25 female participants. The participants will be screened for a history of substance abuse, psychological disorders in the subject or the family, the subjects will be tested for ADHD (Attention Deficit Hyperactivity Disorder). Participants who consume more than 300mg of caffeine per day, or have consumed similar amounts in last two years will be excluded. Participants will be tested for signs of depression using the Beck Depression Inventory, individuals scoring above 9 will be excluded. The subjects will be extrinsically motivated with cash rewards for scoring better in each test(Duckworth, Quinn, Lynam, Loeber, & Stouthamer-Loeber, 2011). The cash reward will be the same after the sleep deprivation to ensure that the subjects do not underperform because they do not feel motivated enough to take the test.
The test participants will first undergo a Smell Identification Test for 10 different smells, which will form the baseline information for the study. Subsequently, the subjects will be administered a standard Stanford Binet IQ test (Couzens, Cuskelly, & Haynes, 2011). The subjects will be exposed to a Computer Administered Visual Attention Test (CA-VAT) as described in Arthur, Strong, & Williamson, (1994), in this test the response time of the subjects will be measured in seconds. Following this initial tests, subjects will give monetary awards based on their scores and asked to stay awake for 60 hours. The next phase of testing will start from 56th hour and subjects will be administered the same tests in the same order, this time however the SIT will be conducted on 10 new smells.
Predictions
Since the subjects will be motivated to perform well in the study, we can safely assume that the test results of the subjects will be close to their abilities. If SIT is a good predictor for brain functioning, then participants with initial low scores on SIT will score low on visual attention, and IQ tests both before and after the sleep deprivation. On the other hand, SIT scores of previously low-performing participants will go lower after sleep deprivation. Subjects with higher than average SIT scores are more likely to outperform other participants (with lower than average SIT scores) in visual attention and IQ test both before and after the sleep deprivation experiment.
Limitations
This study can be further improved by incorporating FMRI scans of the brains of subjects before and after the sleep deprivation experiments to understand the effect of sleep deprivation on the functionality of the prefrontal cortex and other associated regions. The predictive powers of the SIT scores can be better evaluated by comparing the scores with real time FMRI scans. A larger sample size of 200-500 individuals can give the necessary confidence required to assert the predictive powers of SIT scores.
References
Arthur, W., Strong, M. H., & Williamson, J. (1994). Validation of a visual attention test as a predictor of driving accident involvement. Journal of Occupational and Organizational Psychology, 67(2), 173–182.
Couzens, D., Cuskelly, M., & Haynes, M. (2011). Cognitive development and Down syndrome: age-related change on the Stanford-Binet test. American Journal on Intellectual and Developmental Disabilities, 116(3), 181–204.
Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., & Stouthamer-Loeber, M. (2011). Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences of the United States of America, 108(19), 7716–20. doi:10.1073/pnas.1018601108
Killgore, W. D. S., Killgore, D. B., Mcbride, S. a., Kamimori, G. H., & Balkin, T. J. (2007). Odor Identification Ability Predicts Changes in Symptoms of Psychopathology Following 56 H of Sleep Deprivation. Journal of Sensory Studies, 23(1), 35–51. doi:10.1111/j.1745-459X.2007.00139.x

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