The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach
ABSTRACT Objective The purpose of this research was to ascertain how university students' eating addiction was impacted by their early experiences, picky eating, and hedonic hunger. Methods This descriptive cross‐sectional study involved 681 university students and was carried out between April...
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Wiley
2025-07-01
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| Series: | Brain and Behavior |
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| Online Access: | https://doi.org/10.1002/brb3.70667 |
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| author | Muhammet Ali Aydin Ceren Karabulutlu Izzet Ulker Metin Yildiz |
| author_facet | Muhammet Ali Aydin Ceren Karabulutlu Izzet Ulker Metin Yildiz |
| author_sort | Muhammet Ali Aydin |
| collection | DOAJ |
| description | ABSTRACT Objective The purpose of this research was to ascertain how university students' eating addiction was impacted by their early experiences, picky eating, and hedonic hunger. Methods This descriptive cross‐sectional study involved 681 university students and was carried out between April and June 2024. A sociodemographic characteristics information form, Childhood Positive and Negative Experiences Scale, Picky Eating Scale, Yale Food Addiction Scale, and Power of Food Scale were utilized to collect data. G*Power 3.1, the SPSS 22 software, and the R programming language 4.1.3 were utilized in the study's analysis. Results Hierarchical regression analysis produced a significant and applicable model for this investigation (F(4,676) = 61.193, p = 0.001). A total of 26.6% (R2 = 0.266) of the variance in the degree of eating addiction was explained by the levels of Picky Eating, Negative Childhood Experiences, Positive Childhood Experiences, and Power of Food Scales. When the t‐test results for the regression coefficient's significance were examined in the regression model, it was found that the level of “Eating Addiction” increased statistically in response to increases in the levels of Negative Childhood Experiences Scale (t = 7.699, p < 0.001), Picky Eating Scale (t = 6.625, p < 0.001), and Food Power Scale (t = 9.532, p < 0.001). Eating addiction was found to be unaffected by the degree of positive childhood experiences (p = −0.566). Hedonic hunger was found to be the most significant variable in predicting the eating addiction variable in the machine learning technique. Conclusion In our study, childhood experiences, picky eating status, and hedonic hunger status were found to affect eating addiction. Longitudinal studies on eating addiction in young people are recommended. |
| format | Article |
| id | doaj-art-459ce24de1404607a4c4140ad0e83834 |
| institution | Kabale University |
| issn | 2162-3279 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Brain and Behavior |
| spelling | doaj-art-459ce24de1404607a4c4140ad0e838342025-08-20T03:58:48ZengWileyBrain and Behavior2162-32792025-07-01157n/an/a10.1002/brb3.70667The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning ApproachMuhammet Ali Aydin0Ceren Karabulutlu1Izzet Ulker2Metin Yildiz3Department of Nursing, Faculty of Health Sciences Erzurum Technical University Erzurum TurkeyDepartment of Nutrition and Dietetics, Institute of Health Sciences Ataturk University Erzurum TurkeyDepartment of Nutrition and Dietetics, Faculty of Health Sciences Erzurum Technical University Erzurum TurkeyDepartment of Midwifery, Faculty of Health Sciences Sakarya University Sakarya TurkeyABSTRACT Objective The purpose of this research was to ascertain how university students' eating addiction was impacted by their early experiences, picky eating, and hedonic hunger. Methods This descriptive cross‐sectional study involved 681 university students and was carried out between April and June 2024. A sociodemographic characteristics information form, Childhood Positive and Negative Experiences Scale, Picky Eating Scale, Yale Food Addiction Scale, and Power of Food Scale were utilized to collect data. G*Power 3.1, the SPSS 22 software, and the R programming language 4.1.3 were utilized in the study's analysis. Results Hierarchical regression analysis produced a significant and applicable model for this investigation (F(4,676) = 61.193, p = 0.001). A total of 26.6% (R2 = 0.266) of the variance in the degree of eating addiction was explained by the levels of Picky Eating, Negative Childhood Experiences, Positive Childhood Experiences, and Power of Food Scales. When the t‐test results for the regression coefficient's significance were examined in the regression model, it was found that the level of “Eating Addiction” increased statistically in response to increases in the levels of Negative Childhood Experiences Scale (t = 7.699, p < 0.001), Picky Eating Scale (t = 6.625, p < 0.001), and Food Power Scale (t = 9.532, p < 0.001). Eating addiction was found to be unaffected by the degree of positive childhood experiences (p = −0.566). Hedonic hunger was found to be the most significant variable in predicting the eating addiction variable in the machine learning technique. Conclusion In our study, childhood experiences, picky eating status, and hedonic hunger status were found to affect eating addiction. Longitudinal studies on eating addiction in young people are recommended.https://doi.org/10.1002/brb3.70667childhood experienceseating addictionhedonic hungerpicky eating |
| spellingShingle | Muhammet Ali Aydin Ceren Karabulutlu Izzet Ulker Metin Yildiz The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach Brain and Behavior childhood experiences eating addiction hedonic hunger picky eating |
| title | The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach |
| title_full | The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach |
| title_fullStr | The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach |
| title_full_unstemmed | The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach |
| title_short | The Effect of Childhood Experiences, Picky Eating, and Hedonic Hunger on Eating Addiction in University Students: Analyzed by Machine Learning Approach |
| title_sort | effect of childhood experiences picky eating and hedonic hunger on eating addiction in university students analyzed by machine learning approach |
| topic | childhood experiences eating addiction hedonic hunger picky eating |
| url | https://doi.org/10.1002/brb3.70667 |
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