Bibliographic record
Abstract
Introduction: Animal models have been used in many areas of research to provide insights into mechanisms and treatments for various disorders and diseases. For example, animals are often used in other areas of psychology, such as learning, with examples such as Pavlov’s dogs and Skinner’s rats. Further, animals have also been noted to exhibit psychiatric disorders that are frequently observed in humans, such as depression and anxiety. However, the use of animal models in other less studied fields of psychiatric research is unclear. This poses the questions: is the use of animals effective in studies of common mental health disorders? If so, what aspects of common mental health disorders do current studies focus on? Further, can disorders that have lower prevalence rates also be studied with the use of animals? This paper reviews the use of animals in the study of obsessive-compulsive related disorders of addiction, eating disorders, and trichotillomania (a disorder of compulsive hair-pulling) to answer these questions. Methods: Addiction, eating disorders, and trichotillomania were examined based on ease of study in non-human animals, and sufficient available literature. Nine articles for each disorder were examined to determine types of animals used, and the purpose of animal models in the study. Results: Research shows animal models are often used to study the etiology, genetics, mechanisms, and neurochemistry of psychiatric disorders. Animal models have high validity and translate well to humans. However, treatments of psychiatric disorders are less studied using animal models. Discussion: The review of the current literature suggests animal models are effective in studies of addiction, eating disorders, and trichotillomania. Animal models can be developed to inform various aspects of psychiatric disorders and should be expanded to include studies examining treatments as well. Further, food addiction also should be further assessed using animal models. Conclusion: Overall, animal models are useful in studying various aspects of psychiatric disorders and should continue to be used for those less commonly studied. Future studies with animal models should focus on psychiatric disorders that involve compulsive, repetitive behaviours.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".