Understanding the Relationship Between Emotional Intelligence, Eating disorders, Blood group and Cognitive functioning among Asian and African University Students
Bibliographic record
Abstract
Abstract Introduction - The overall purpose of the study was to examine the relationship between emotional intelligence, eating disorders, blood group and cognitive functioning among Asian and African university students in India. That’s how emotional intelligence and blood group type serves as aetiological factors for eating disorders and the degree to which these three Variables influence cognitive functioning among university students. Objectives - The first aim of the study was to determine if any relationship exist between emotional intelligence, eating disorders, blood groups and cognitive functioning among Asian and African Students. Our second aim was to investigate the impact of eating disorders, emotional intelligence and blood groups on cognitive functioning, as well as to find the role of blood groups on aetiology of eating disorders. And finally, to also investigate the role of cultural differences on emotional intelligence, eating disorders and cognitive functioning Methods and Material - The study considered sample size of 120 African and Asian university students at National forensic sciences university (NFSU) who were residing in India and continuing their studies from undergraduate to PhD in all academic streams during the time of the study with ratio of equal African and Asian as well as male to female. Tools used in the study were eating disorders diagnostic scale by Stice, E., Fisher, M., & Martinez, E. (2004), Schutte Self Report Emotional Intelligence Test (SSEIT) and Montreal cognitive assessment (MOCA). Results – We found positive correlation between blood group and cognitive functioning with correlation value of .241** at 0.01 significant level. Blood group was also found to be negatively correlated to eating disorders with correlation value of -237** at 0.01 significant level and positively correlated with emotional intelligence with correlation value of .187* at 0.01 significant level. We also found that, cognitive functioning was negatively correlated to eating disorders with correlation value of -.842** and positively correlated to emotional intelligence with correlation value of .781. ** This reveals that, people who are having eating disorders are more likely to perform poorly in cognitive functioning. Our results also shows that, emotional intelligence was negatively correlated to eating disorders with correlation value of -.745.** This can be interpreted as people who have high emotional intelligence are of low risk of developing eating disorders compare to those with low emotional intelligence. Finally, we also found significant difference between Asian and African students on the basis of emotional intelligence level, cognitive functioning and eating disorders. Conclusion - In conclusion, the result of this study shows that, there is a correlation between emotional intelligence, eating disorders, blood groups and cognitive functions. Also, Asian and African students differ on emotional intelligence level, cognitive functioning and eating disorders. But emotional intelligence, eating disorders and cognitive functioning is not dependent on different academic level. That’s no significant difference was found between different academic level, that’s undergraduate, post-graduate and PhD on eating disorders, emotional intelligence and cognitive task Keywords: Emotional intelligence, blood group, eating disorders, cognitive functioning, Asian and African student
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".