Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study
Background: The integration of genetic testing into eHealth applications holds great promise for the personalization of disease prevention guidelines. However, relatively little is known about the impact of eHealth applications on an individual's behavior.Aim: The aim of the pilot study was to...
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Frontiers Media S.A.
2021-02-01
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doaj-c32d9f59becc43c99824eeed2bb416f82021-02-09T17:26:48ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2021-02-01210.3389/fdgth.2020.567656567656Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot StudyKerti Alev0Andres Kütt1Margus Viigimaa2Digital Health, Tallinn University of Technology (TalTech), Tallinn, EstoniaInformation Technology and Communication Technologies, Information Technology Department, Tallinn University of Technology (TalTech), Tallinn, EstoniaNorth Estonia Medical Center, Tallinn University of Technology, Tallinn, EstoniaBackground: The integration of genetic testing into eHealth applications holds great promise for the personalization of disease prevention guidelines. However, relatively little is known about the impact of eHealth applications on an individual's behavior.Aim: The aim of the pilot study was to investigate the effect of the personalized eHealth application approach to behavior change in a 1-month follow-up period on groups with previously known and unknown caffeine impacts.Method: We created a direct-to-consumer approach that includes providing relevant information and personalized reminders and goals on the digital device regarding the caffeine intake for two groups of individuals: the intervention group (IG) with the genetic raw data available and the control group (CG) to test the impact of the same content (article about caffeine metabolism) on participants without the genetic test. Study participants were all Estonians (n = 160).Results: The study suggests that eHealth applications work for short-term behavior change. Participants in the genetic IG tended to increase caffeine intake if they were informed about caffeine not being harmful. They reported feeling better physically and/or mentally after their behavioral change decision during the period of the study.Conclusions: Our pilot study revealed that eHealth applications may have a positive effect for short-term behavior change, regardless of a prior genetic test. Further studies among larger study groups are required to achieve a better understanding about behavior change of individuals in the field of personalized medicine and eHealth interventions.https://www.frontiersin.org/articles/10.3389/fdgth.2020.567656/fullmHealthpharmacogeneticsbehavior changeCaffeineeHealthdecision support |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kerti Alev Andres Kütt Margus Viigimaa |
spellingShingle |
Kerti Alev Andres Kütt Margus Viigimaa Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study Frontiers in Digital Health mHealth pharmacogenetics behavior change Caffeine eHealth decision support |
author_facet |
Kerti Alev Andres Kütt Margus Viigimaa |
author_sort |
Kerti Alev |
title |
Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study |
title_short |
Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study |
title_full |
Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study |
title_fullStr |
Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study |
title_full_unstemmed |
Disclosing Pharmacogenetic Feedback of Caffeine via eHealth Channels, Assessment of the Methods and Effects to Behavior Change: A Pilot Study |
title_sort |
disclosing pharmacogenetic feedback of caffeine via ehealth channels, assessment of the methods and effects to behavior change: a pilot study |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Digital Health |
issn |
2673-253X |
publishDate |
2021-02-01 |
description |
Background: The integration of genetic testing into eHealth applications holds great promise for the personalization of disease prevention guidelines. However, relatively little is known about the impact of eHealth applications on an individual's behavior.Aim: The aim of the pilot study was to investigate the effect of the personalized eHealth application approach to behavior change in a 1-month follow-up period on groups with previously known and unknown caffeine impacts.Method: We created a direct-to-consumer approach that includes providing relevant information and personalized reminders and goals on the digital device regarding the caffeine intake for two groups of individuals: the intervention group (IG) with the genetic raw data available and the control group (CG) to test the impact of the same content (article about caffeine metabolism) on participants without the genetic test. Study participants were all Estonians (n = 160).Results: The study suggests that eHealth applications work for short-term behavior change. Participants in the genetic IG tended to increase caffeine intake if they were informed about caffeine not being harmful. They reported feeling better physically and/or mentally after their behavioral change decision during the period of the study.Conclusions: Our pilot study revealed that eHealth applications may have a positive effect for short-term behavior change, regardless of a prior genetic test. Further studies among larger study groups are required to achieve a better understanding about behavior change of individuals in the field of personalized medicine and eHealth interventions. |
topic |
mHealth pharmacogenetics behavior change Caffeine eHealth decision support |
url |
https://www.frontiersin.org/articles/10.3389/fdgth.2020.567656/full |
work_keys_str_mv |
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