Online Health Information Consumers’ Learning across Health-Related Search Tasks from the Perspective of Retrieval Platform Switching (Preprint)

Author:

Chen YijingORCID,Lin HanmingORCID,Zhang JinORCID,Zhao YimingORCID

Abstract

BACKGROUND

Online health information retrieval has been a top choice for acquiring health information and knowledge by millions worldwide.

OBJECTIVE

This study aims to investigate consumers’ modification of retrieval platform switch paths across health-related search tasks and learning via such a change.

METHODS

A lab user experiment was designed to obtain data on consumers’ health information search behavior. Participants accomplished health-related information search tasks. Screen movements were recorded by EV screen-recording software. The participants underwent in-depth interviews immediately after finishing the tasks. Screen recordings and interview data were both coded and analyzed.

RESULTS

Three types of learning, including the similar transfer learning, optimizing learning, and SERP-guided learning were identified based on five change patterns of retrieval platform switch paths adopted by health information consumers from task 1 to task 2. Health information consumers’ retrieval platform switch based on information usefulness evaluation. And they accessed different amounts and types of health knowledge from different retrieval platforms.

CONCLUSIONS

The results suggest that health information consumers exhibit learning both through retrieval platform switching and the knowledge they consume during the search process. This facilitates the assessment of a certain retrieval platform’s usefulness by measuring the amount and types of health knowledge in each search result. This study also contributes to the enhancement of consumers’ health information retrieval abilities, and to helping optimize health information retrieval platforms by increasing their exposure to consumers and increasing the matching degree between knowledge types and consumer needs.

Publisher

JMIR Publications Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3