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: 3 complete abstracts (524 words), 9 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
Those factors which cause an organism to behave or act in either a goal-seeking or satisfying manner. They may be influenced by physiological drives or by external stimuli.
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: Motivations; Disincentives; Disincentive; Incentives; Incentive.
Where it fits in the MeSH classification
- Broader topics
- Behavior and Behavior Mechanisms; Emotional Intelligence
- Narrower topics
- Achievement; Aspirations, Psychological; Conflict, Psychological; Drive; Exploratory Behavior; Food Deprivation; Goals; Handling, Psychological; Instinct; Intention; Power, Psychological; Sense of Agency; Water Deprivation
- See also
- Cognitive Dissonance; Libido; Intention
Research landscape
PubMed indexes 215,803 records tagged with the MeSH heading “Motivation” (counts retrieved 2026-10-31). 45,903 of them (21.3%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 67,050 records.
Reviews account for 15,918 records (7.4%) and meta-analyses for 1,218. Randomized controlled trials number 10,651 (4.9%) as a share of all records on the topic.
Show the data
| Period | Records |
|---|---|
| through 1999 | 60,462 |
| 2000-2009 | 42,388 |
| 2010-2019 | 67,050 |
| 2020 onward | 45,903 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 15,918 | 7.4% |
| Meta-analyses | 1,218 | 0.6% |
| Randomized controlled trials | 10,651 | 4.9% |
Method: PubMed query "Motivation"[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 / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Neural and computational mechanisms of effort under the pressure of a deadline | 2026 | Research article Design not recorded in structured metadata | 2 | cc by PMID 42660916 · DOI · PMC13522516 |
| Foraging models explain human exploration in uncertain tasks | 2026 | Research article Design not recorded in structured metadata | 2 | cc by PMID 42669730 · DOI · PMC13526786 |
| Using Passive Sensing to Isolate a Biosignature for Craving Among Individuals in Early Alcohol Use Disorder Recovery | 2026 | Research article Design not recorded in structured metadata | 1 | cc by PMID 42575852 · DOI · PMC13456983 |
Neural and computational mechanisms of effort under the pressure of a deadline [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Deadlines fundamentally shape motivation.
- Closing excerpt
- These results reveal the neurocomputational mechanisms for how deadline pressure shapes motivation, and keep us on track with goals.
- 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)
Deadlines fundamentally shape motivation. Research examining effort-based choices finds effort is an avoided cost. However, this overlooks how making progress on longer-term goals to be reached before deadlines motivate people to exert high effort for little immediate reward. Here, we test a framework where motivation depends on deadline pressure (work remaining / time remaining). Across four studies we use computational modelling examining decisions when physical effort makes progress on goals with deadlines. In support of the hypotheses, deadline pressure significantly impacts decision-making, shifting people from avoiding effort, to seeking the progress it makes. Using ultra-high-field fMRI, we show that functionally connected putamen and midcingulate cortex sub-regions process and update estimates of deadline pressure, with distinct anterior cingulate and putamen sub-regions processing effort both when it is being avoided or sought. These results reveal the neurocomputational mechanisms for how deadline pressure shapes motivation, and keep us on track with goals.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42660916 · DOI · PMC13522516
Foraging models explain human exploration in uncertain tasks [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Different fields have fundamentally different models of how decisions are made.
- Closing excerpt
- These results suggest that humans use compare-to-threshold computations in more environments than were previously known.
- 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 (158 words)
Different fields have fundamentally different models of how decisions are made. Psychology and neuroscience tend to assume that decisions are made by calculating and comparing the values of all options. In ethology, conversely, decisions tend to be binary regardless of the number of options: Decision-makers calculate the value of continuing to exploit some option and explore only when this value drops below a threshold. Because these fields use incompatible methods, it remains unclear which view better describes human decision-making. We find that humans use compare-to-threshold computations even in classic compare-alternative tasks. Because the reinforcement-learning models typically used in the cognitive and brain sciences depend on compare-alternative computations, we also develop a compare-to-threshold foraging model. Compared to previous models, the foraging model better fits participant behavior, predicts the tendency to repeat choices, and predicts held-out participants that were almost impossible under traditional compare-alternative models. These results suggest that humans use compare-to-threshold computations in more environments than were previously known.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42669730 · DOI · PMC13526786
Using Passive Sensing to Isolate a Biosignature for Craving Among Individuals in Early Alcohol Use Disorder Recovery [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Craving is one of the most robust proximal predictors of both treatment dropout and relapse during early recovery for alcohol use disorder (AUD).
- Closing excerpt
- Findings highlight HRV as a viable target for passive monitoring in interventions aimed at supporting craving mitigation in early AUD recovery, particularly at the momentary level.
- 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 (217 words)
Craving is one of the most robust proximal predictors of both treatment dropout and relapse during early recovery for alcohol use disorder (AUD). Craving can onset rapidly, and the ability to accurately detect or modulate cravings varies significantly within- and between-persons. Because of this, craving management is a central feature of most current AUD treatment models. However, impaired interoceptive awareness, which is common in early AUD recovery, can stymie individuals' capacity to implement craving management strategies. Measurement and detection of craving through passive biosensor monitoring could support novel just-in-time adaptive interventions that can mitigate this vulnerability. This study sought to characterize the biosignatures of craving through the measurement of heart rate variability (HRV) using a combination of ambulatory electrocardiogram (ECG) monitoring and ecological momentary assessment (EMA) in individuals in the first year of a current AUD recovery attempt (N = 40, observations = 400). A multilevel negative binomial regression analysis was conducted to estimate correlations between craving and HRV. Results demonstrated that, at the within-person level, high-frequency HRV (HF-HRV; IRR = 1.01, p = 0.013) and SD1 (IRR = 0.97, p = 0.020) were associated with craving at the same moment. Findings highlight HRV as a viable target for passive monitoring in interventions aimed at supporting craving mitigation in early AUD recovery, particularly at the momentary level.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42575852 · DOI · PMC13456983
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 The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: A meta-analysis [4]
- Research article A meta-analysis of self-determination theory-informed intervention studies in the health domain: effects on motivation, health behavior, physical, and psychological health [5]
- Research article Food cue reactivity and craving predict eating and weight gain: a meta-analytic review [6]
- Research article Meta-Analysis of the Reasoned Action Approach (RAA) to Understanding Health Behaviors [7]
- Research article Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math [8]
- Research article Much ado about grit: A meta-analytic synthesis of the grit literature [9]
Full-text reviews on EvidenceLib
Open-access review articles about this topic, reproduced in full with authors, licence and references.
Dopamine, Erectile Function and Male Sexual Behavior from the Past to the Present: A Review
Maria Rosaria Melis, Fabrizio Sanna, Antonio Argiolas · Brain Sciences 2022 · CC BY 4.0
References
- Pisauro MA, Pollicino D, Fisher L, Apps MAJ. Neural and computational mechanisms of effort under the pressure of a deadline. . 2026. PMID 42660916 · DOI · PMC13522516
- Zid M, Laurie VJ, Ramírez-Ruiz J, Lavigne-Champagne A, Shourkeshti A, Harrell DC, et al.. Foraging models explain human exploration in uncertain tasks. . 2026. PMID 42669730 · DOI · PMC13526786
- Mei S, Emery NN, Eddie D. Using Passive Sensing to Isolate a Biosignature for Craving Among Individuals in Early Alcohol Use Disorder Recovery. . 2026. PMID 42575852 · DOI · PMC13456983
- Sheeran P, Maki A, Montanaro E, Avishai-Yitshak A, Bryan A, Klein WM, et al.. The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: A meta-analysis. Health Psychol. 2016. PMID 27280365 · DOI
- Ntoumanis N, Ng JYY, Prestwich A, Quested E, Quested E, Hancox JE, et al.. A meta-analysis of self-determination theory-informed intervention studies in the health domain: effects on motivation, health behavior, physical, and psychological health. Health Psychol Rev. 2021. PMID 31983293 · DOI
- Boswell RG, Kober H. Food cue reactivity and craving predict eating and weight gain: a meta-analytic review. Obes Rev. 2016. PMID 26644270 · DOI · PMC6042864
- McEachan R, Taylor N, Harrison R, Lawton R, Gardner P, Conner M. Meta-Analysis of the Reasoned Action Approach (RAA) to Understanding Health Behaviors. Ann Behav Med. 2016. PMID 27169555 · DOI · PMC4933736
- Theobald EJ, Hill MJ, Tran E, Agrawal S, Arroyo EN, Behling S, et al.. Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math. Proc Natl Acad Sci U S A. 2020. PMID 32152114 · DOI · PMC7104254
- Credé M, Tynan MC, Harms PD. Much ado about grit: A meta-analytic synthesis of the grit literature. J Pers Soc Psychol. 2017. PMID 27845531 · 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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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.