Cargando…

Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service

BACKGROUND: Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliabil...

Descripción completa

Detalles Bibliográficos
Autores principales: Bastl, Katharina, Berger, Uwe, Kmenta, Maximilian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5440733/
https://www.ncbi.nlm.nih.gov/pubmed/28483740
http://dx.doi.org/10.2196/jmir.7426
_version_ 1783238114900180992
author Bastl, Katharina
Berger, Uwe
Kmenta, Maximilian
author_facet Bastl, Katharina
Berger, Uwe
Kmenta, Maximilian
author_sort Bastl, Katharina
collection PubMed
description BACKGROUND: Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. OBJECTIVE: The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. METHODS: The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Today’s grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of ±2 and ±4 pollen per cubic meter. RESULTS: In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the “readiness to flower” for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. CONCLUSIONS: The quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to pollen allergy sufferers due to inadequate forecasts. The inclusion of information on reliability of provided forecasts and a similar handling regarding probabilistic weather forecasts should be considered.
format Online
Article
Text
id pubmed-5440733
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-54407332017-06-06 Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service Bastl, Katharina Berger, Uwe Kmenta, Maximilian J Med Internet Res Original Paper BACKGROUND: Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. OBJECTIVE: The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. METHODS: The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Today’s grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of ±2 and ±4 pollen per cubic meter. RESULTS: In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the “readiness to flower” for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. CONCLUSIONS: The quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to pollen allergy sufferers due to inadequate forecasts. The inclusion of information on reliability of provided forecasts and a similar handling regarding probabilistic weather forecasts should be considered. JMIR Publications 2017-05-08 /pmc/articles/PMC5440733/ /pubmed/28483740 http://dx.doi.org/10.2196/jmir.7426 Text en ©Katharina Bastl, Uwe Berger, Maximilian Kmenta. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.05.2017. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Bastl, Katharina
Berger, Uwe
Kmenta, Maximilian
Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service
title Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service
title_full Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service
title_fullStr Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service
title_full_unstemmed Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service
title_short Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service
title_sort evaluation of pollen apps forecasts: the need for quality control in an ehealth service
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5440733/
https://www.ncbi.nlm.nih.gov/pubmed/28483740
http://dx.doi.org/10.2196/jmir.7426
work_keys_str_mv AT bastlkatharina evaluationofpollenappsforecaststheneedforqualitycontrolinanehealthservice
AT bergeruwe evaluationofpollenappsforecaststheneedforqualitycontrolinanehealthservice
AT kmentamaximilian evaluationofpollenappsforecaststheneedforqualitycontrolinanehealthservice