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Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health
BACKGROUND: The quantum increases in home Internet access and available online health information with limited control over information quality highlight the necessity of exploring decision making processes in accessing and using online information, specifically in relation to children who do not ma...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3529696/ https://www.ncbi.nlm.nih.gov/pubmed/23228171 http://dx.doi.org/10.1186/1472-6947-12-144 |
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author | Walsh, Anne M Hyde, Melissa K Hamilton, Kyra White, Katherine M |
author_facet | Walsh, Anne M Hyde, Melissa K Hamilton, Kyra White, Katherine M |
author_sort | Walsh, Anne M |
collection | PubMed |
description | BACKGROUND: The quantum increases in home Internet access and available online health information with limited control over information quality highlight the necessity of exploring decision making processes in accessing and using online information, specifically in relation to children who do not make their health decisions. The aim of this study was to understand the processes explaining parents’ decisions to use online health information for child health care. METHODS: Parents (N = 391) completed an initial questionnaire assessing the theory of planned behaviour constructs of attitude, subjective norm, and perceived behavioural control, as well as perceived risk, group norm, and additional demographic factors. Two months later, 187 parents completed a follow-up questionnaire assessing their decisions to use online information for their child’s health care, specifically to 1) diagnose and/or treat their child’s suspected medical condition/illness and 2) increase understanding about a diagnosis or treatment recommended by a health professional. RESULTS: Hierarchical multiple regression showed that, for both behaviours, attitude, subjective norm, perceived behavioural control, (less) perceived risk, group norm, and (non) medical background were the significant predictors of intention. For parents’ use of online child health information, for both behaviours, intention was the sole significant predictor of behaviour. The findings explain 77% of the variance in parents’ intention to treat/diagnose a child health problem and 74% of the variance in their intentions to increase their understanding about child health concerns. CONCLUSIONS: Understanding parents’ socio-cognitive processes that guide their use of online information for child health care is important given the increase in Internet usage and the sometimes-questionable quality of health information provided online. Findings highlight parents’ thirst for information; there is an urgent need for health professionals to provide parents with evidence-based child health websites in addition to general population education on how to evaluate the quality of online health information. |
format | Online Article Text |
id | pubmed-3529696 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35296962013-01-03 Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health Walsh, Anne M Hyde, Melissa K Hamilton, Kyra White, Katherine M BMC Med Inform Decis Mak Research Article BACKGROUND: The quantum increases in home Internet access and available online health information with limited control over information quality highlight the necessity of exploring decision making processes in accessing and using online information, specifically in relation to children who do not make their health decisions. The aim of this study was to understand the processes explaining parents’ decisions to use online health information for child health care. METHODS: Parents (N = 391) completed an initial questionnaire assessing the theory of planned behaviour constructs of attitude, subjective norm, and perceived behavioural control, as well as perceived risk, group norm, and additional demographic factors. Two months later, 187 parents completed a follow-up questionnaire assessing their decisions to use online information for their child’s health care, specifically to 1) diagnose and/or treat their child’s suspected medical condition/illness and 2) increase understanding about a diagnosis or treatment recommended by a health professional. RESULTS: Hierarchical multiple regression showed that, for both behaviours, attitude, subjective norm, perceived behavioural control, (less) perceived risk, group norm, and (non) medical background were the significant predictors of intention. For parents’ use of online child health information, for both behaviours, intention was the sole significant predictor of behaviour. The findings explain 77% of the variance in parents’ intention to treat/diagnose a child health problem and 74% of the variance in their intentions to increase their understanding about child health concerns. CONCLUSIONS: Understanding parents’ socio-cognitive processes that guide their use of online information for child health care is important given the increase in Internet usage and the sometimes-questionable quality of health information provided online. Findings highlight parents’ thirst for information; there is an urgent need for health professionals to provide parents with evidence-based child health websites in addition to general population education on how to evaluate the quality of online health information. BioMed Central 2012-12-10 /pmc/articles/PMC3529696/ /pubmed/23228171 http://dx.doi.org/10.1186/1472-6947-12-144 Text en Copyright ©2012 Walsh et al.; licensee BioMed Central Ltd. 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 is properly cited. |
spellingShingle | Research Article Walsh, Anne M Hyde, Melissa K Hamilton, Kyra White, Katherine M Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
title | Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
title_full | Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
title_fullStr | Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
title_full_unstemmed | Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
title_short | Predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
title_sort | predictive modelling: parents’ decision making to use online child health information to increase their understanding and/or diagnose or treat their child’s health |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3529696/ https://www.ncbi.nlm.nih.gov/pubmed/23228171 http://dx.doi.org/10.1186/1472-6947-12-144 |
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