Rat tickling: A systematic review of applications, outcomes, and moderators
Bibliographic record
Abstract
INTRODUCTION: Rats initially fear humans which can increase stress and impact study results. Additionally, studying positive affective states in rats has proved challenging. Rat tickling is a promising habituation technique that can also be used to model and measure positive affect. However, current studies use a variety of methods to achieve differential results. Our objective was to systematically identify, summarize, and evaluate the research on tickling in rats to provide direction for future investigation. Our specific aims were to summarize current methods used in tickling experiments, outcomes from tickling, and moderating factors. METHODS: We systematically evaluated all articles about tickling identified from PubMed, Scopus, Web of Science, and PsychInfo. Our inclusion criteria were publication in a peer-reviewed journal and collection of original, empirical data on rats using the handling method of tickling. One researcher extracted information from each article. Bias was assessed by 2 investigators using the SYRCLE bias assessment tool. RESULTS: We identified 32 articles (56 experiments) published in peer-reviewed journals about rat tickling for inclusion. A wide variety of strains, sexes, and ages of rats were included. The most common method used for tickling was cycling through 15 seconds of tickling and 15 seconds of rest for 2 minutes for 3 to 5 days. Experiments with a control for tickling (N = 22) showed that tickling increases positive vocalization, approach behavior, decreases anxiety measures, improves handling, and in some cases decreases stress hormones. Tickling juvenile, individually housed rats with a trait predisposition to respond more positively to tickling, results in the most positive outcomes. Methods to reduce bias were insufficiently reported. CONCLUSIONS: We conclude that tickling is a promising method for improving rat welfare and investigating positive affect. However, the establishment of tickling best practices is essential as the outcomes from tickling can be moderated by several factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".