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The multiple dimensions of dyspnea: Review and hypotheses
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Although dyspnea is a common and troubling symptom, our understanding of the neurophysiology of dyspnea is woefully incomplete. Most measurements of dyspnea treat it as a single entity. Although the multidimensional dyspnea concept has been mentioned for many decades, only recently has the concept been the subject of experimental tests. Emerging evidence has begun to favor the hypothesis that dyspnea comprises multiple dimensions or components that can be measured as different entities. Most recently, studies have begun to show that there is a separable 'affective dimension' (i.e. unpleasantness and emotional impact). Understanding of the multidimensional measurement of pain is far in advance of dyspnea, and has enabled progress in the neurophysiology of pain, including identification of separate neural structures subserving various elements of pain perception. We propose here a multidimensional model of dyspnea based on a state-of-the-art pain model, and review existing evidence in the light of this model.
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“The model of Lansing et al 21 for the perception of dyspnea proposed a sequence in which initially somatosensory areas assess the intensity and sensory quality (descriptors) of the breathlessness (somatic awareness), with a subsequent stage managed by the insula, dorsal anterior cingulate cortex, amygdala, and medial thalamus assessing the degree of unpleasantness/threat (affective awareness).22”
From Cognitive behavioral therapy for management of dyspnea: A pilot study (2015) · cites this paper as [21]
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“The findings of this pilot study appear to be consistent with this model if the feedback provided by BREVE program subjects (increased endurance, better breathlessness management, and reduced anxiety associated with exercise-related breathlessness) reflects a change in affective awareness facilitating an ability to increase their exercise capacity.”
From Cognitive behavioral therapy for management of dyspnea: A pilot study (2015) · cites this paper as [21]
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Self-citationHorton, R., Rocker, G. M., & Currow, D. C. (2010) · Current Opinion in Supportive and Palliative Care · doi:10.1097/spc.0b013e3283392788 · Cited by 8
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Management of Respiratory Symptoms in Those with Serious Illness
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Metadata
- Authors
- Lansing, R. W., Gracely, R. H., & Banzett, R. B.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Michigan Medicine (US)
- Corresponding author
- Banzett, Robert B.
- ORCID
- Banzett, Robert B.
- Venue
- Respiratory Physiology & Neurobiology
- Publisher
- Elsevier BV
- Published
- 2009-05
- Volume
- 167
- Issue
- 1
- Pages
- 53-60
- ISSN
- 1569-9048 (ISSN-L)
- PMC
- PMC2763422
- OpenAlex
- W2015408803
- Cited by
- 355
- References
- 114
- Citations by year
- 2026: 18 · 2025: 10 · 2024: 12 · 2023: 17 · 2022: 21 · 2021: 20 · 2020: 28 · 2019: 19 · 2018: 24 · 2017: 24 · 2016: 27 · 2015: 23 · 2014: 24 · 2013: 20 · 2012: 23
- FWCI
- 2.38
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Respiratory Physiology & Neurobiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01HL046690, HL-46690)
- National Institute of Nursing Research (R01NR010006, NR10006)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Respiratory and Cough-Related Research
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Neuroscience of respiration and sleep
- Health Sciences › Medicine › Physiology (medical) › Pain Mechanisms and Treatments
- Keywords
- dyspnea, unpleasantness, emotional impact, pain models, respiratory sensation
- MeSH terms
- Animals, Dyspnea, Humans, Models, Biological, Pain
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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