Systematic review of the use of pheromones for treatment of undesirable behavior in cats and dogs
Bibliographic record
Abstract
OBJECTIVE: To systematically review the scientific literature to identify, assess the quality of, and determine outcomes of studies conducted to evaluate the use of pheromones for treatment of undesirable behavior in cats and dogs. DESIGN: Systematic review. STUDY POPULATION: Reports of prospective studies published from January 1998 through December 2008. PROCEDURES: The MEDLINE and CAB Abstracts databases were searched with the following key terms: dog OR dogs OR canine OR cat OR cats OR feline AND pheromone OR synthetic pheromone OR facial pheromone OR appeasing pheromone. A date limit was set from 1998 through 2008. Identified reports for dogs (n = 7) and cats (7) were systematically reviewed. RESULTS: Studies provided insufficient evidence of the effectiveness of feline facial pheromone for management of idiopathic cystitis or calming cats during catheterization and lack of support for reducing stress in hospitalized cats. Only 1 study yielded sufficient evidence that dog-appeasing pheromone reduces fear or anxiety in dogs during training. Six studies yielded insufficient evidence of the effectiveness of dog-appeasing pheromone for treatment of noise phobia (2 reports), travel-related problems, fear or anxiety in the veterinary clinic, and stress- and fear-related behavior in shelter dogs as well as vocalizing and house soiling in recently adopted puppies. CONCLUSIONS AND CLINICAL RELEVANCE: 11 of the 14 reports reviewed provided insufficient evidence and 1 provided lack of support for effectiveness of pheromones for the treatment of undesirable behavior in cats and dogs.
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 | 0.009 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".