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Health e‐mavens: identifying active online health information users

BACKGROUND: Given the rapid increase of Internet use for effective health communication, it is important for health practitioners to be able to identify and mobilize active users of online health information across various web‐based health intervention programmes. We propose the concept ‘health e‐ma...

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Detalles Bibliográficos
Autores principales: Sun, Ye, Liu, Miao, Krakow, Melinda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054841/
https://www.ncbi.nlm.nih.gov/pubmed/26296041
http://dx.doi.org/10.1111/hex.12398
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author Sun, Ye
Liu, Miao
Krakow, Melinda
author_facet Sun, Ye
Liu, Miao
Krakow, Melinda
author_sort Sun, Ye
collection PubMed
description BACKGROUND: Given the rapid increase of Internet use for effective health communication, it is important for health practitioners to be able to identify and mobilize active users of online health information across various web‐based health intervention programmes. We propose the concept ‘health e‐mavens’ to characterize individuals actively engaged in online health information seeking and sharing activities. OBJECTIVES: This study aimed to address three goals: (i) to test the factor structure of health e‐mavenism, (ii) to assess the reliability and validity of this construct and (iii) to determine what predictors are associated with health e‐mavenism. METHODS: This study was a secondary analysis of nationally representative data from the 2010 Health Tracking Survey. We assessed the factor structure of health e‐mavenism using confirmatory factor analysis and examined socio‐demographic variables, health‐related factors and use of technology as potential predictors of health e‐mavenism through ordered regression analysis. RESULTS: Confirmatory factor analyses showed that a second‐order two‐factor structure best captured the health e‐maven construct. Health e‐mavenism comprised two second‐order factors, each encompassing two first‐order dimensions: information acquisition (consisting of information tracking and consulting) and information transmission (consisting of information posting and sharing). Both first‐order and second‐order factors exhibited good reliabilities. Several factors were found to be significant predictors of health e‐mavenism. DISCUSSION AND CONCLUSION: This study offers a starting point for further inquiries about health e‐mavens. It is a fruitful construct for health promotion research in the age of new media technologies. We conclude with specific recommendations to further develop the health e‐maven concept through continued empirical research.
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spelling pubmed-50548412016-10-19 Health e‐mavens: identifying active online health information users Sun, Ye Liu, Miao Krakow, Melinda Health Expect Original Research Papers BACKGROUND: Given the rapid increase of Internet use for effective health communication, it is important for health practitioners to be able to identify and mobilize active users of online health information across various web‐based health intervention programmes. We propose the concept ‘health e‐mavens’ to characterize individuals actively engaged in online health information seeking and sharing activities. OBJECTIVES: This study aimed to address three goals: (i) to test the factor structure of health e‐mavenism, (ii) to assess the reliability and validity of this construct and (iii) to determine what predictors are associated with health e‐mavenism. METHODS: This study was a secondary analysis of nationally representative data from the 2010 Health Tracking Survey. We assessed the factor structure of health e‐mavenism using confirmatory factor analysis and examined socio‐demographic variables, health‐related factors and use of technology as potential predictors of health e‐mavenism through ordered regression analysis. RESULTS: Confirmatory factor analyses showed that a second‐order two‐factor structure best captured the health e‐maven construct. Health e‐mavenism comprised two second‐order factors, each encompassing two first‐order dimensions: information acquisition (consisting of information tracking and consulting) and information transmission (consisting of information posting and sharing). Both first‐order and second‐order factors exhibited good reliabilities. Several factors were found to be significant predictors of health e‐mavenism. DISCUSSION AND CONCLUSION: This study offers a starting point for further inquiries about health e‐mavens. It is a fruitful construct for health promotion research in the age of new media technologies. We conclude with specific recommendations to further develop the health e‐maven concept through continued empirical research. John Wiley and Sons Inc. 2015-08-21 2016-10 /pmc/articles/PMC5054841/ /pubmed/26296041 http://dx.doi.org/10.1111/hex.12398 Text en © 2015 The Authors. Health Expectations. Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Papers
Sun, Ye
Liu, Miao
Krakow, Melinda
Health e‐mavens: identifying active online health information users
title Health e‐mavens: identifying active online health information users
title_full Health e‐mavens: identifying active online health information users
title_fullStr Health e‐mavens: identifying active online health information users
title_full_unstemmed Health e‐mavens: identifying active online health information users
title_short Health e‐mavens: identifying active online health information users
title_sort health e‐mavens: identifying active online health information users
topic Original Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054841/
https://www.ncbi.nlm.nih.gov/pubmed/26296041
http://dx.doi.org/10.1111/hex.12398
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