15. The Neural Basis of Eating Disorders and Potential Neurobiological and Psychotherapeutic Treatments in Young Adults
Bibliographic record
Abstract
Although the prevalence of eating disorders (anorexia nervosa, bulimia nervosa and binge eating) has increased among young adults - affecting women ten times more than men - a complete understanding of its underlying neural basis has yet to be reached. A common misconception is that these disorders stem from a superficial emphasis on food and weight, when actually environmental stressors coupled with neurobiological predispositions are major contributing factors to these compulsive, impulsive and sensation-seeking behaviors. This review presents a comprehensive look at theories on the neurobiological causes and effects of eating disorders: regulation of brain serotonin levels on mood and food intake, hypothalamic control of eating and weight, the allocentric lock hypothesis and finally similarities between the neurobiology of addiction and eating disorders. Understanding the pathology of the disorder may help elucidate why, despite achieving cognitive awareness of the disorder, treatment is difficult due to a disconnect between the neural factors controlling the disorder and a subsequent behavioral change. Why does cognitive awareness of their disorder not translate into a behavioral change? If the contributing neurobiological factors influencing the onset and persistence of the disorder can be understood, a multi-disciplinary treatment involving neuropharmacological and socio-emotional components could be implemented. The application of this research could be important for post-secondary institutions where environmental pressures and personal predispositions of individuals may align to onset eating-disorder behavior. Future studies on the physiology of eating and stress regulation and psychotherapeutic research may help develop treatments to target individuals at many stages of the disorder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".