Evidence map›Paper›PMID 41428138›Full record

ArticleCurrent heart failure reports2025

Interventions to Enhance Interoception and Symptom Attribution in Patients with Heart Failure: A Scoping Review.

Michelle M van Rijn, Tiny Jaarsma, Heleen Westland

Abstract readScoping Review
In one paragraph

Article in Current heart failure reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Michelle M van RijnJulius Center for Health Sciences and Primary Care, Department of General Practice and Nursing Science, University Medical Centre Utrecht, Universiteitsweg 100, Utrecht, The Netherlands.ORCID http://orcid.org/0009-0006-3678-3299
Tiny JaarsmaDepartment of Cardiology, University Medical Centre Utrecht, Utrecht, The Netherlands. tiny.jaarsma@liu.se.ORCID http://orcid.org/0000-0002-4197-4026
Heleen WestlandJulius Center for Health Sciences and Primary Care, Department of General Practice and Nursing Science, University Medical Centre Utrecht, Universiteitsweg 100, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0001-7366-5773

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewTimely recognition and interpretation of symptoms are crucial for effective self-care in heart failure (HF). However, many patients struggle to detect bodily sensations and interpret their meaning, leading to poor outcomes. Interoception and symptom attribution are central to this process but are often impaired. This scoping review aims to describe interventions and their characteristics aiming to enhance interoception and symptom attribution in patients with HF. RECENT

findingsRecent findings indicate that patients' attributions of the causes of their symptoms strongly influence self-care, and growing attention to interoception suggests that increased awareness of bodily sensations can improve self-care symptom management. Interventions targeting interoception and symptom attribution may help improving HF patients' symptom perception and self-care symptom management. Both constructs are closely connected and contribute to timely symptom management. The heterogeneity of interventions reflects the complexity of symptom perception in HF and highlights the need for personalized, multicomponent approaches to strengthen self-care and improve outcomes.

Indexed as

Heart FailureInteroceptionSelf CareHumans(4–6): InteroceptionHeart failureInterventionsSelf-careSymptom attributionSymptom management

Identifiers

PMID41428138
PMCPMC12722434

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Registered trials

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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.