Quantifying the Quality of Web-Based Health Information on Student Health Center Websites Using a Software Tool: Design and Development Study.

adolescents automated quantification tool digital health health information health information websites health websites infodemiology information quality metrics online health online health information quality public health student health center websites

Journal

JMIR formative research
ISSN: 2561-326X
Titre abrégé: JMIR Form Res
Pays: Canada
ID NLM: 101726394

Informations de publication

Date de publication:
02 Feb 2022
Historique:
received: 24 07 2021
accepted: 28 11 2021
revised: 29 10 2021
entrez: 2 2 2022
pubmed: 3 2 2022
medline: 3 2 2022
Statut: epublish

Résumé

The internet has become a major source of health information, especially for adolescents and young adults. Unfortunately, inaccurate, incomplete, or outdated health information is widespread on the web. Often adolescents and young adults turn to authoritative websites such as the student health center (SHC) website of the university they attend to obtain reliable health information. Although most on-campus SHC clinics comply with the American College Health Association standards, their websites are not subject to any standards or code of conduct. In the absence of quality standards or guidelines, monitoring and compliance processes do not exist for SHC websites. Thus, there is no oversight of the health information published on SHC websites by any central governing body. The aim of this study is to develop, describe, and validate an open-source software that can effectively and efficiently assess the quality of health information on SHC websites in the United States. Our cross-functional team designed and developed an open-source software, QMOHI (Quantitative Measures of Online Health Information), that assesses information quality for a specified health topic from all SHC websites belonging to a predetermined list of universities. The tool was designed to compute 8 different quality metrics that quantify various aspects of information quality based on the retrieved text. We conducted and reported results from 3 experiments that assessed the QMOHI tool in terms of its scalability, generalizability in health topics, and robustness to changes in universities' website structure. Empirical evaluation has shown the QMOHI tool to be highly scalable and substantially more efficient than manually assessing web-based information quality. The tool's runtime was dominated by network-related tasks (98%), whereas the metric computations take <2 seconds. QMOHI demonstrated topical versatility, evaluating SHC website information quality for four disparate and broad health topics (COVID, cancer, long-acting reversible contraceptives, and condoms) and two narrowly focused topics (hormonal intrauterine device and copper intrauterine device). The tool exhibited robustness, correctly measuring information quality despite changes in SHC website structure. QMOHI can support longitudinal studies by being robust to such website changes. QMOHI allows public health researchers and practitioners to conduct large-scale studies of SHC websites that were previously too time- and cost-intensive. The capability to generalize broadly or focus narrowly allows a wide range of applications of QMOHI, allowing researchers to study both mainstream and underexplored health topics. QMOHI's ability to robustly analyze SHC websites periodically promotes longitudinal investigations and allows QMOHI to be used as a monitoring tool. QMOHI serves as a launching pad for our future work that aims to develop a broadly applicable public health tool for web-based health information studies with potential applications far beyond SHC websites.

Sections du résumé

BACKGROUND BACKGROUND
The internet has become a major source of health information, especially for adolescents and young adults. Unfortunately, inaccurate, incomplete, or outdated health information is widespread on the web. Often adolescents and young adults turn to authoritative websites such as the student health center (SHC) website of the university they attend to obtain reliable health information. Although most on-campus SHC clinics comply with the American College Health Association standards, their websites are not subject to any standards or code of conduct. In the absence of quality standards or guidelines, monitoring and compliance processes do not exist for SHC websites. Thus, there is no oversight of the health information published on SHC websites by any central governing body.
OBJECTIVE OBJECTIVE
The aim of this study is to develop, describe, and validate an open-source software that can effectively and efficiently assess the quality of health information on SHC websites in the United States.
METHODS METHODS
Our cross-functional team designed and developed an open-source software, QMOHI (Quantitative Measures of Online Health Information), that assesses information quality for a specified health topic from all SHC websites belonging to a predetermined list of universities. The tool was designed to compute 8 different quality metrics that quantify various aspects of information quality based on the retrieved text. We conducted and reported results from 3 experiments that assessed the QMOHI tool in terms of its scalability, generalizability in health topics, and robustness to changes in universities' website structure.
RESULTS RESULTS
Empirical evaluation has shown the QMOHI tool to be highly scalable and substantially more efficient than manually assessing web-based information quality. The tool's runtime was dominated by network-related tasks (98%), whereas the metric computations take <2 seconds. QMOHI demonstrated topical versatility, evaluating SHC website information quality for four disparate and broad health topics (COVID, cancer, long-acting reversible contraceptives, and condoms) and two narrowly focused topics (hormonal intrauterine device and copper intrauterine device). The tool exhibited robustness, correctly measuring information quality despite changes in SHC website structure. QMOHI can support longitudinal studies by being robust to such website changes.
CONCLUSIONS CONCLUSIONS
QMOHI allows public health researchers and practitioners to conduct large-scale studies of SHC websites that were previously too time- and cost-intensive. The capability to generalize broadly or focus narrowly allows a wide range of applications of QMOHI, allowing researchers to study both mainstream and underexplored health topics. QMOHI's ability to robustly analyze SHC websites periodically promotes longitudinal investigations and allows QMOHI to be used as a monitoring tool. QMOHI serves as a launching pad for our future work that aims to develop a broadly applicable public health tool for web-based health information studies with potential applications far beyond SHC websites.

Identifiants

pubmed: 35107423
pii: v6i2e32360
doi: 10.2196/32360
pmc: PMC8851325
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e32360

Informations de copyright

©Anagha Kulkarni, Mike Wong, Tejasvi Belsare, Risha Shah, Diana Yu Yu, Bera Coskun, Carrie Holschuh, Venoo Kakar, Sepideh Modrek, Anastasia Smirnova. Originally published in JMIR Formative Research (https://formative.jmir.org), 02.02.2022.

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Auteurs

Anagha Kulkarni (A)

Department of Computer Science, San Francisco State University, San Francisco, CA, United States.

Mike Wong (M)

Department of Computer Science, San Francisco State University, San Francisco, CA, United States.

Tejasvi Belsare (T)

Department of Computer Science, San Francisco State University, San Francisco, CA, United States.

Risha Shah (R)

Department of Computer Science, San Francisco State University, San Francisco, CA, United States.

Diana Yu Yu (D)

Department of Computer Science, San Francisco State University, San Francisco, CA, United States.

Bera Coskun (B)

Department of Computer Science, San Francisco State University, San Francisco, CA, United States.

Carrie Holschuh (C)

School of Nursing, San Francisco State University, San Francisco, CA, United States.

Venoo Kakar (V)

Department of Economics, San Francisco State University, San Francisco, CA, United States.

Sepideh Modrek (S)

Department of Economics, San Francisco State University, San Francisco, CA, United States.

Anastasia Smirnova (A)

Department of English Language and Literature, San Francisco State University, San Francisco, CA, United States.

Classifications MeSH