社交媒体帖子健康信念模型建构评价项目的心理测量分析:Rasch测量模型的应用

IF 2.5 3区 心理学 Q2 PSYCHOLOGY, MULTIDISCIPLINARY Behavioral Sciences Pub Date : 2025-02-13 DOI:10.3390/bs15020204
Xiaofeng Jia, Soyeon Ahn
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引用次数: 0

摘要

社交媒体是健康交流的重要工具,因为它提供了一个即时、广泛的平台来分享信息、纠正错误信息和促进健康行为。健康信念模型(HBM)为设计更有效的社交媒体信息提供了一种结构化的方法,它采用独特的结构来预测健康行为,如严重程度、易感性、益处、障碍和自我效能。虽然之前的研究已经探索了健康信息中的HBM结构,但大多数研究收集的调查数据都缺乏强有力的心理测量证据,特别是在评估社交媒体帖子时。本研究通过使用Rasch测量理论(RMT)分析HBM项目评估社交媒体宣传COVID-19疫苗接种的心理测量特性,解决了这一空白。研究结果表明,严重性、益处和障碍是社交媒体帖子中最可靠的HBM结构,而易感性和自我效能在社交媒体健康信息中未得到充分利用。此外,维度分析证实了不同的模式,但无法解释的差异表明,还有其他因素影响疫苗信息传递,这引起了有效性问题。这些结果强调需要通过强调被忽视的构念和提高项目有效性来改进基于hbm的信息策略。本研究通过建立全面的心理测量属性,特别是在社交媒体环境中应用,为在社交媒体中使用hbm相关措施提供了指导。它还提出了设计和评估社交媒体健康信息的实用指南,确保他们有效地利用HBM结构来促进积极的健康行为。未来的研究应该探索测量不变性和内容创作者对HBM结构的重视,利用高参与度的推文,同时扩展到不同的视角,以获得更广泛的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Psychometric Analysis of Items Evaluating Health Belief Model Constructs in Social Media Posts: Application of Rasch Measurement Model.

Social media is a crucial tool for health communication as it provides an immediate, wide-reaching platform to share information, correct misinformation, and promote health behaviors. The Health Belief Model (HBM) offers a structured approach for designing more effective social media messages by employing unique constructs predicting health behaviors, such as severity, susceptibility, benefits, barriers, and self-efficacy. While prior research has explored HBM constructs in health messages, most studies have collected the survey data with items lacking robust psychometric evidence, particularly in evaluating social media posts. This study addresses this gap by using Rasch Measurement Theory (RMT) to analyze the psychometric properties of HBM items evaluating social media posts promoting COVID-19 vaccination. The findings indicate that severity, benefits, and barriers are the most reliable HBM constructs in social media posts, while susceptibility and self-efficacy are underutilized in health messaging for social media. Also, dimensionality analysis confirms distinct patterns, but unexplained variance suggests that additional factors influence vaccine messaging, raising validity concerns. These results underscore the need to refine HBM-based message strategies by emphasizing overlooked constructs and improving item effectiveness. This study provides guidelines for using HBM-related measures in social media by establishing comprehensive psychometric properties, especially when applied in social media contexts. It also presents practical guidelines for designing and evaluating social media health messages, ensuring they effectively utilize HBM constructs to promote positive health behaviors. Future research should explore measurement invariance and content creators' emphasis on HBM constructs, leveraging high-engagement tweets while expanding to diverse perspectives for broader applicability.

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来源期刊
Behavioral Sciences
Behavioral Sciences Social Sciences-Development
CiteScore
2.60
自引率
7.70%
发文量
429
审稿时长
11 weeks
期刊最新文献
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