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Grooming

Psychiatry and Psychology · NLM MeSH · updated 2026-11-04 · version 1

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 4 min read

An animal's cleaning and caring for the body surface.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (725 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

An animal's cleaning and caring for the body surface. This includes preening, the cleaning and oiling of feathers with the bill or of hair with the tongue.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Groomings; Preening; Preenings.

Where it fits in the MeSH classification

Broader topics
Appetitive Behavior

Research landscape

PubMed indexes 3,589 records tagged with the MeSH heading “Grooming” (counts retrieved 2026-10-31). 433 of them (12.1%) were published from 2020 onward, and the busiest period so far is through 1999 with 1,712 records.

Reviews account for 101 records (2.8%) and meta-analyses for 3. Randomized controlled trials number 8 (0.2%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.

PubMed records by publication periodthrough 1999: 1,712 records; 2000-2009: 596 records; 2010-2019: 848 records; 2020 onward: 433 records1,712through 19995962000-20098482010-20194332020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 19991,712
2000-2009596
2010-2019848
2020 onward433
Share of records by publication typeReviews: 2.8 percent; Meta-analyses: 0.1 percent; Randomized controlled trials: 0.2 percentReviews2.8% (101)Meta-analyses0.1% (3)Randomized controlled trials0.2% (8)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 3,589 PubMed records
TypeRecordsShare
Reviews1012.8%
Meta-analyses30.1%
Randomized controlled trials80.2%

Method: PubMed query "Grooming"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.

Reading the evidence in psychiatry and psychology

Research on mental health and behaviour relies on questionnaires, interviews and rating scales rather than physical measurements, so how a condition was defined and measured shapes every result. Many studies are observational or small, placebo responses can be large, and findings in one group or culture may not carry over to another. Nothing on this page is advice about diagnosis or treatment; anyone worried about their mental health should talk to a qualified clinician. Check how outcomes were measured, who took part and how long they were followed.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila
Seeds AM, Ravbar P, Chung P, Hampel S, Midgley FM, Mensh BD, et al.
2014Research article
Design not recorded in structured metadata
186cc by
PMID 25139955 · DOI · PMC4136539
DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels
Bohnslav JP, Wimalasena NK, Clausing KJ, Dai YY, Yarmolinsky DA, Cruz T, et al.
2021Research article
Design not recorded in structured metadata
183cc by
PMID 34473051 · DOI · PMC8455138
A neural command circuit for grooming movement control
Hampel S, Franconville R, Simpson JH, Seeds AM
2015Research article
Design not recorded in structured metadata
146cc by
PMID 26344548 · DOI · PMC4599031
Turn-taking in grooming interactions of sooty mangabeys (Cercocebus atys) in the wild
Tibesar P, Crockford C, Le Floch A, Pika S
2026Research article
Design not recorded in structured metadata
0cc by
PMID 41806232 · DOI · PMC13102903

A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila [1]

Research article Seeds AM, Ravbar P, Chung P, Hampel S, Midgley FM, Mensh BD, et al. · · 2014 · cited 186 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown.
Closing excerpt
This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (150 words)

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 25139955 · DOI · PMC4136539

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels [2]

Research article Bohnslav JP, Wimalasena NK, Clausing KJ, Dai YY, Yarmolinsky DA, Cruz T, et al. · · 2021 · cited 183 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies.
Closing excerpt
com/jbohnslav/deepethogram.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (163 words)

Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored manually, which is time-consuming, limited to few behaviors, and variable across researchers. We created DeepEthogram: software that uses supervised machine learning to convert raw video pixels into an ethogram, the behaviors of interest present in each video frame. DeepEthogram is designed to be general-purpose and applicable across species, behaviors, and video-recording hardware. It uses convolutional neural networks to compute motion, extract features from motion and images, and classify features into behaviors. Behaviors are classified with above 90% accuracy on single frames in videos of mice and flies, matching expert-level human performance. DeepEthogram accurately predicts rare behaviors, requires little training data, and generalizes across subjects. A graphical interface allows beginning-to-end analysis without end-user programming. DeepEthogram's rapid, automatic, and reproducible labeling of researcher-defined behaviors of interest may accelerate and enhance supervised behavior analysis. Code is available at: https://github.com/jbohnslav/deepethogram.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 34473051 · DOI · PMC8455138

A neural command circuit for grooming movement control [3]

Research article Hampel S, Franconville R, Simpson JH, Seeds AM · · 2015 · cited 146 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Animals perform many stereotyped movements, but how nervous systems are organized for controlling specific movements remains unclear.
Closing excerpt
As similar features underlie stimulus-induced movements in other animals, we infer the possibility of a common circuit organization for movement control that can be dissected in Drosophila.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (149 words)

Animals perform many stereotyped movements, but how nervous systems are organized for controlling specific movements remains unclear. Here we use anatomical, optogenetic, behavioral, and physiological techniques to identify a circuit in Drosophila melanogaster that can elicit stereotyped leg movements that groom the antennae. Mechanosensory chordotonal neurons detect displacements of the antennae and excite three different classes of functionally connected interneurons, which include two classes of brain interneurons and different parallel descending neurons. This multilayered circuit is organized such that neurons within each layer are sufficient to specifically elicit antennal grooming. However, we find differences in the durations of antennal grooming elicited by neurons in the different layers, suggesting that the circuit is organized to both command antennal grooming and control its duration. As similar features underlie stimulus-induced movements in other animals, we infer the possibility of a common circuit organization for movement control that can be dissected in Drosophila.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 26344548 · DOI · PMC4599031

Turn-taking in grooming interactions of sooty mangabeys (Cercocebus atys) in the wild [4]

Research article Tibesar P, Crockford C, Le Floch A, Pika S · · 2026

Abstract reading summary — source excerpts
Opening excerpt
Language is widely regarded as a uniquely human trait, rooted in mechanisms of social interaction such as conversational turn-taking.
Closing excerpt
These findings suggest that the fundamental structural principles of human conversation likely predate our species, offering valuable insight into the evolutionary history of language.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (263 words)

Language is widely regarded as a uniquely human trait, rooted in mechanisms of social interaction such as conversational turn-taking. It has been proposed that turn-taking may not be exclusive to humans but may represent an ancestral trait shared across primates and beyond. Early studies on great apes indicated a specialization in gestural forms of turn-taking, whereas monkeys appeared to rely more heavily on vocal exchanges. However, this ape–monkey difference may simply be due to a lack of research. To bridge this gap, the present study investigated turn-taking behaviors during grooming in an Afro-Eurasian monkey species, sooty mangabeys (Cercocebus atys). We addressed the following three key questions: (1) What turn-taking patterns, if any, characterize grooming interactions in sooty mangabeys? (2) Do sooty mangabeys preferentially use vocal turn-taking? (3) Which elements characterizing turn-taking patterns of sooty mangabeys are shared with human conversational turn-taking? We collected 105.3 h of video footage from 22 adult female sooty mangabeys in Taï National Park (between May 2022 and August 2023), yielding 428 female–female grooming videos, of which 71 were coded. An additional 595 grooming interactions were described directly in the field. Results showed that exchanges involving both actions and signals were the most frequent (e.g., a present gesture followed by grooming). The most common type of signal exchange was gestural turn-taking, a form previously reported only in great apes. The study identified key elements of conversational turn-taking: rapid responses, adjacency pair-like sequences, and participation frameworks. These findings suggest that the fundamental structural principles of human conversation likely predate our species, offering valuable insight into the evolutionary history of language.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41806232 · DOI · PMC13102903

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article Neurobiology of rodent self-grooming and its value for translational neuroscience [5]
    Kalueff AV, Stewart AM, Song C, Berridge KC, Graybiel AM, Fentress JC · Nat Rev Neurosci · 2016 · cited 671 times (Europe PMC)
  • Research article The social role of touch in humans and primates: behavioural function and neurobiological mechanisms [6]
    Dunbar RI · Neurosci Biobehav Rev · 2010 · cited 416 times (Europe PMC)
  • Research article Ethology and neurobiology of grooming behavior [7]
    Spruijt BM, van Hooff JA, Gispen WH · Physiol Rev · 1992 · cited 407 times (Europe PMC)
  • Research article ACTH-induced excessive grooming in the rat [8]
    Gispen WH, Isaacson RL · Pharmacol Ther · 1981 · cited 203 times (Europe PMC)
  • Research article The development of grooming and its expression in adult animals [9]
    Sachs BD · Ann N Y Acad Sci · 1988 · cited 98 times (Europe PMC)
  • Research article The hypothalamus: cross-roads of endocrine and behavioural regulation in grooming and aggression [10]
    Kruk MR, Westphal KG, Van Erp AM, van Asperen J, Cave BJ, Slater E, et al. · Neurosci Biobehav Rev · 1998 · cited 87 times (Europe PMC)

References

  1. Seeds AM, Ravbar P, Chung P, Hampel S, Midgley FM, Mensh BD, et al.. A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila. . 2014. PMID 25139955 · DOI · PMC4136539
  2. Bohnslav JP, Wimalasena NK, Clausing KJ, Dai YY, Yarmolinsky DA, Cruz T, et al.. DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels. . 2021. PMID 34473051 · DOI · PMC8455138
  3. Hampel S, Franconville R, Simpson JH, Seeds AM. A neural command circuit for grooming movement control. . 2015. PMID 26344548 · DOI · PMC4599031
  4. Tibesar P, Crockford C, Le Floch A, Pika S. Turn-taking in grooming interactions of sooty mangabeys (Cercocebus atys) in the wild. . 2026. PMID 41806232 · DOI · PMC13102903
  5. Kalueff AV, Stewart AM, Song C, Berridge KC, Graybiel AM, Fentress JC. Neurobiology of rodent self-grooming and its value for translational neuroscience. Nat Rev Neurosci. 2016. PMID 26675822 · DOI · PMC4840777
  6. Dunbar RI. The social role of touch in humans and primates: behavioural function and neurobiological mechanisms. Neurosci Biobehav Rev. 2010. PMID 18662717 · DOI
  7. Spruijt BM, van Hooff JA, Gispen WH. Ethology and neurobiology of grooming behavior. Physiol Rev. 1992. PMID 1320764 · DOI
  8. Gispen WH, Isaacson RL. ACTH-induced excessive grooming in the rat. Pharmacol Ther. 1981. PMID 6114501 · DOI
  9. Sachs BD. The development of grooming and its expression in adult animals. Ann N Y Acad Sci. 1988. PMID 3291663 · DOI
  10. Kruk MR, Westphal KG, Van Erp AM, van Asperen J, Cave BJ, Slater E, et al.. The hypothalamus: cross-roads of endocrine and behavioural regulation in grooming and aggression. Neurosci Biobehav Rev. 1998. PMID 9884110 · DOI

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-11-04; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-11-04.

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At a glance

3,589
PubMed records on this heading
12%
published since 2020
101
review articles
8
randomized trials
10
verified references below

Counts come from PubMed on 2026-10-31; they show how much has been written, not how strong the evidence is.

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