围产期妇女对数字媒体上孕产妇保健信息质量的感知:范围审查

IF 5.8 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Bowen Li, Ningning Jin, Yingli Wang, Xiaoni Hou, Jing Meng, Yihong Zhang
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引用次数: 0

摘要

背景:围产期妇女越来越多地转向数字媒体获取孕产妇保健信息;然而,对这些信息质量的担忧仍然存在。了解围产期妇女对信息质量的看法对于提高信息服务的有效性至关重要。目的:本综述旨在(1)识别围产期妇女在感知数字媒体孕产妇保健信息质量时关注的关键特征;(2)总结围产期妇女报告的数字媒体孕产妇保健信息质量问题。方法:采用PubMed、Web of Science、Embase、Scopus和ScienceDirect数据库(2000-2024),按照PRISMA-ScR(系统评价和荟萃分析扩展范围评价的首选报告项目)指南进行范围评价。搜索策略使用布尔运算符将以下四个概念聚类结合起来:(1)围产期人口术语(“孕妇”、“孕妇”和“围产期”),(2)信息相关术语(“信息”、“教育”和“资源”),(3)感知相关术语(“感知”、“经验”和“期望”),以及(4)数字媒体术语(“在线”、“社交媒体”和“应用程序”)。数据综合采用专题分析。结果:从5290条记录中,30篇(0.57%)文章被纳入本综述。信息的感知质量特征可以分为四个不同的方面:(1)信息提供者,包括透明度和权威性两个特征;(2)信息内容,包括可信度、证据性、时效性、全面性、需求相关性、实用性、动机模拟性、情感支持性和文化敏感性9个特征;(3)信息呈现,包括可理解性、吸引力和简洁性三个特征;(4)信息平台,包括用户友好导航、主动传递和交互性三大特征。此外,与这些方面相关的几个可感知的质量问题值得注意。具体而言,(1)信息提供者的质量问题主要与他们缺乏可信度有关;(2)与信息内容相关的质量问题包括信息量过大、不准确、缺乏科学证据、相互矛盾的信息普遍存在、广度和深度不足、内容与女性需求不匹配以及引发负面情绪的信息;(3)表述问题,表现为理解信息的困难;(4)信息平台的质量问题包括可用性差和商业化。结论:我们的综述确定了围产期妇女重视的各个维度的17个关键质量特征。虽然与一般保健资料中的质量指标有相似之处,但围产期人口的具体特征所形成的独特质量特征不容忽视。这些独特的特点突出了定制孕产妇保健信息以满足围产期妇女独特需求和偏好的重要性。尽管数字媒体信息服务提供了许多好处,但本研究表明,围产期妇女对现有孕产妇保健信息的质量不满意。显然,今后的努力应侧重于整合围产期妇女对信息质量的看法,以确保信息质量的持续改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perinatal Women's Perception of Maternal Health Information Quality on Digital Media: Scoping Review.

Background: Perinatal women are increasingly turning to digital media for maternal health information; however, concerns regarding the quality of this information persist. Understanding perinatal women's perceptions of information quality is essential for enhancing the effectiveness of information services.

Objective: This review aims to (1) identify the key features that perinatal women focus on when perceiving the quality of maternal health information on digital media and (2) summarize the quality issues with maternal health information on digital media that perinatal women have reported.

Methods: A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines using PubMed, Web of Science, Embase, Scopus, and ScienceDirect databases (2000-2024). The search strategy combined the following four conceptual clusters using Boolean operators: (1) perinatal population terms ("pregnant women," "expectant mothers," and "perinatal"), (2) information-related terms ("information," "education," and "resource"), (3) perception-related terms ("perception," "experience," and "expectation"), and (4) digital media terms ("online," "social media," and "app"). Thematic analysis was used for data synthesis.

Results: From 5290 records identified, 30 (0.57%) articles were selected for inclusion in this review. The perceived quality features of information can be categorized into four distinct aspects: (1) information providers, which encompasses 2 features, transparency and authority; (2) information content, consisting of 9 features, trustworthiness, evidence based, timeliness, comprehensiveness, need-based relevance, practicality, motivational simulation, emotional supportiveness, and cultural sensitivity; (3) information presentation, which includes 3 features, understandability, attractiveness, and conciseness; and (4) information platforms, comprising 3 features, user-friendly navigation, proactive delivery, and interactivity. Furthermore, several perceived quality issues associated with these aspects were noteworthy. Specifically, (1) quality issues regarding information providers primarily pertained to their lack of credibility; (2) quality issues related to information content encompassed an overwhelming volume of information, inaccuracies, lack of scientific evidence, prevalence of contradictory information, insufficient breadth and depth, a mismatch between content and the needs of women, and information that induces negative emotions; (3) presentation issues manifested as difficulties in understanding the information; and (4) quality issues regarding information platforms included poor usability and the commercialization of these platforms.

Conclusions: Our review identifies 17 key quality features across various dimensions that are valued by perinatal women. While there are similarities with quality indicators found in general health information, the unique quality features shaped by the specific characteristics of the perinatal population cannot be overlooked. These distinctive attributes highlight the importance of tailoring maternal health information to meet the unique needs and preferences of perinatal women. Although digital media information services offer many benefits, this study indicates that perinatal women are dissatisfied with the quality of existing maternal health information. Clearly, future efforts should focus on integrating perinatal women's perceptions of information quality to ensure ongoing improvements in information quality.

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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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