Evidence map›Paper›PMID 42311632›Full record

ArticleFrontiers in allergy2026

Potential of real-time pollen data: perceived needs and symptom management among seasonal allergic rhinitis patients.

Nora van Gaal, Christine Boomsma, Lisbeth F Hall, Jannie J van der Helm

Abstract read
In one paragraph

Article in Frontiers in allergy, 2026. 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
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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

4 authors.

Nora van GaalCentre for Environmental Safety and Security, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Christine BoomsmaCentre for Environmental Safety and Security, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Lisbeth F HallCentre for Environmental Safety and Security, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Jannie J van der HelmCentre for Environmental Safety and Security, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Seasonal allergic rhinitis (SAR) affects up to 20% of the Dutch population and significantly impacts daily functioning and quality of life. Despite behavioural measures and pharmacotherapy, many individuals experience suboptimal symptom control. Real-time pollen data are increasingly available and may support improved anticipation and management of symptoms. We examined its perceived value and intended use. Methods: A cross-sectional online questionnaire was conducted from April to June 2024 among 961 adults with self-reported or physician-diagnosed SAR, recruited via social media of the Dutch National Institute for Public Health and the Environment (RIVM). The questionnaire assessed symptoms, management strategies and effectiveness, perceived informational needs and usage, and demographic variables. Multinomial logistic regression identified factors associated with perceived informational needs. Results: Most participants used behavioural measures (58.1%) and medication (92.1%) to manage SAR symptoms, though perceived effectiveness varied. One in four expressed a need for more symptom management information. Younger age and moderate perceived impact on daily life were associated with increased informational needs on managing SAR. A third (35.4%) thought that real-time pollen data could contribute to managing SAR, with male gender and university education being associated with a perceived possible contribution. Real-time pollen data was valued for: confirmation of symptoms, limiting exposure to pollen and adjusting medication. Discussion: Findings indicate the potential for further optimisation of SAR symptom management and for fulfilling informational needs. Particularly men and those with university education thought that real-time pollen data could contribute to managing SAR. Information on the possible preventive use of pollen forecasts via accessible digital tools could enhance SAR self-management.

Indexed as

allergen avoidanceautomatic monitoringinformational needsreal-time pollen informationseasonal allergic rhinitis

Identifiers

PMID42311632
PMCPMC13269070

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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.