Evidence map›Paper›PMID 35226152›Full record

ArticlePsychological research2023

Happiness feels light and sadness feels heavy: introducing valence-related bodily sensation maps of emotions.

Matthias Hartmann, Bigna Lenggenhager, Kurt Stocker

Abstract read
In one paragraph

Article in Psychological research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. What is Balance? A Vital Mechano-Regulation Paradigm.Open mind : discoveries in cognitive science · 2025
    Article
  6. Article
  7. Article
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Matthias HartmannFaculty of Psychology, UniDistance Suisse, Ueberlandstrasse 12, 3900, Brig, Switzerland. Matthias.hartmann@fernuni.ch.ORCID http://orcid.org/0000-0003-1132-1339
Bigna LenggenhagerDepartment of Psychology, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-0418-9931
Kurt StockerFaculty of Psychology, UniDistance Suisse, Ueberlandstrasse 12, 3900, Brig, Switzerland.ORCID http://orcid.org/0000-0002-6161-7114

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung PP00P1_170511
6 · The paper itself

Abstract

Bodily sensation mapping (BSM) is a recently developed self-report tool for the assessment of emotions in which people draw their sensations of activation in a body silhouette. Following the circumplex model of affect, activity and valence are the underling dimensions of every emotional experience. The aim of this study was to introduce the neglected valence dimension in BSM. We found that participants systematically report valence-related sensations of bodily lightness for positive emotions (happiness, love, pride), and sensations of bodily heaviness in response to negative emotions (e.g., anger, fear, sadness, depression) with specific body topography (Experiment 1). Further experiments showed that both computers (using a machine learning approach) and humans recognize emotions better when classification is based on the combined activity- and valence-related BSMs compared to either type of BSM alone (Experiments 2 and 3), suggesting that both types of bodily sensations reflect distinct parts of emotion knowledge. Importantly, participants found it clearer to indicate their bodily sensations induced by sadness and depression in terms of bodily weight than bodily activity (Experiment 2 and 4), suggesting that the added value of valence-related BSMs is particularly relevant for the assessment of emotions at the negative end of the valence spectrum.

Indexed as

HappinessSadnessAngerEmotionsHumansSensation

Identifiers

PMID35226152
PMCPMC9873729

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.