媒体暴露对大学生心理健康的影响：基于疫情双风险评估标准
文献类型：学位论文
| 作者 | 马 岩 |
| 答辩日期 | 2024-06 |
| 文献子类 | 硕士 |
| 授予单位 | 中国科学院大学 |
| 授予地点 | 中国科学院心理研究所 |
| 其他责任者 | 刘正奎 |
| 关键词 | 大学生心理健康 新冠疫情风险评估 潜在剖面分析 机器学习 媒体暴露 |
| 学位名称 | 应用心理硕士 |
| 学位专业 | 应用心理 |
| 其他题名 | Exploring the Impact of Media Exposure on College Students' Mental Health: An Analysis Based on the Dual Risk Assessment Criteria for Epidemics |
| 中文摘要 | The COVID-19 pandemic, a global public health crisis, has not only caused physical ailments among infected college students but has also profoundly affected the psychological well-being of both infected and uninfected student populations—an impact that may linger into the post-pandemic era. In light of the psychological health threats posed by such emergent public health challenges, the implementation of spatial risk management measures for timely interventions emerges as a crucial strategy for mitigating risks. However, existing research indicates that spatial risk assessment models designed to curtail the spread of the pandemic do not consistently mirror psychological health risks. In the era of digital proliferation, the role of media exposure related to the pandemic emerges as a significant determinant of the psychological health risks confronting college students during this crisis. Traditional research on media exposure often treats the consumption of epidemic-related media as a monolithic body, thus potentially overlooking the nuanced, bidirectional effects that various types of epidemic information can have on psychological health, both ameliorative and detrimental. Consequently, this study endeavors to elucidate the correlation between different COVID-19 risk assessment criteria and psychological health risks, delineate the variances in psychological health risks across media exposure subgroups under distinct risk assessment conditions, and unpack the influence of various types of media exposure content on psychological health during the pandemic. Such insights aim to refine our understanding of, and response to, the psychological health challenges posed by public health crises. This study comprises three distinct investigations. The first study aim to examine whether two different risk assessment criteria under the COVID-19 pandemic align with the psychological health risks of college students. Utilizing a convenience sampling approach, an online survey was administered to 77,197 students across 177 universities nationwide. This survey collected demographic and mental health status data. The results showed that the risk assessment using confirmed COVID-19 cases pinpointed the highest instances of depression and anxiety within the most critical areas, while paradoxically uncovering the lowest levels of these mental health concerns in areas deemed to be of the second-highest risk, thereby demonstrating a distinct ‘marginal zone effect’.A similar pattern was noted in the assessment based on geographic distance, suggesting discrepancies with actual psychological health risks. The second study investigates the differences in psychological health risks among different media exposure subgroups under spatial risk assessment criteria during the pandemic, aiming to understand whether various risk assessment criteria can identify the association between media exposure and psychological health risks. Latent profile analysis revealed potential categorizations among college students’ media exposure: ‘low media exposure group’, ‘medium media exposure group’, and ‘high media exposure group’. Resilience differed among media exposure subgroups in second-highest risk areas under both risk categorizations. Significant differences in depression and anxiety levels were found among media exposure subgroups in low-risk areas defined by the number of confirmed cases. In contrast, no significant associations in depression and anxiety were observed among media exposure subgroups in geographic distance-based groups, pointing to a lesser recognition by geographic space-based risk categorization of the correlation between media exposure and psychological health risks. The third segment of the study explored depression and anxiety levels across various COVID-19 risk categories using advanced machine learning methods, including polynomial logistic regression, random forest, support vector machine, and LightGBM. The LightGBM models proved superior in predicting mental health outcomes. The analysis also examined media exposure impact across these risk zones. Findings indicated that in high-risk areas, depression and anxiety were negatively impacted by epidemiological news and the tone of online discourse. However, local news coverage showed a positive effect on anxiety, whereas it negatively correlated with depression in these zones. In contrast, sub-high risk areas saw no significant media effect on depression, but positive online public opinions slightly raised anxiety levels. For sub-low risk groups, negative impacts were observed from online opinion on both mental states, while local news and public health information had a beneficial effect. Interestingly, authoritative commentary tended to reduce anxiety. In the lowest risk areas, media had little impact on depression, but coverage related to the epidemic was linked to increased anxiety. The study underscores the varied influence of media on mental health, with significant effects in high and sub-low risk areas and minimal impact on those in sub-high and low-risk zones. Through these three studies, this research examines the consistency between two spatial risk categorizations and psychological health risks under COVID-19, and through latent profile analysis and machine learning algorithms, analyzes the effect of media exposure on psychological health risks. This helps us understand the effectiveness of different risk categorizations in identifying the association between media exposure and psychological health risks during emergent public events, offering theoretical significance for supplementing media exposure risk research and providing crucial guidance for media dissemination practices in emergency management measures for psychological interventions during public health crises. |
| 英文摘要 | 新冠疫情（COVID-19）作为一场全球性的突发性公共卫生事件，不仅对确诊的大学生造成了身心伤害，也对未感染的大学生群体心理健康产生了深远的影响，这种影响甚至持续到后疫情时期。面对这类突发性公共卫生事件所引发的心理健康风险，采取空间层面的风险管理措施进行及时干预，是预防风险发生的有效策略。然而，以往的研究发现，用于应对疫情传播的空间风险评估标准并不总是与心理健康风险具有一致性。伴随数字时代的快速发展，疫情相关的媒体暴露被识别为大学生在疫情下面临的心理健康风险的潜在影响因素。此外，关于媒体暴露的研究通常是从广泛性接触所有疫情媒体信息的角度来进行，这可能导致无 法区分不同性质的疫情信息对心理健康正面或负面的双向影响。因此，研究不同的新冠疫情空间风险评估标准与心理健康风险的一致性，以及不同空间风险评估标准下媒体暴露子群体间的心理健康风险差异和不同类型媒体暴露内容对于疫情下心理健康的影响，从而为理解和应对公共卫生危机中的心理健康挑战提供更深入的见解。 本研究总共由三个研究构成。研究一旨在探讨新冠疫情下两个不同空间风险评估标准是否与大学生心理健康风险具有一致性。本研究采用方便抽样方法，对全国 177 所高校的 77197 名大学生进行在线问卷调查。问卷内容包括基本人口学信息和心理健康状况等。研究结果表明，确诊人数划分的风险评估标准分组的抑郁、焦虑呈现出高风险地区最高水平，而次高风险地区最低水平的“边缘带效应”。在基于地理距离的风险划分标准分组的抑郁、焦虑也呈现出不同类型的“边缘带效应”分布趋势；均表现出与心理健康风险的不一致性。 研究二探讨疫情下不同空间风险评估标准的媒体暴露子群体间的心理健康风险差异情况，旨在了解不同风险评估标准能否识别媒体暴露与心理健康风险的关联性。潜在剖面分析结果显示，大学生群体疫情媒体暴露程度存在潜在类别特征：“低媒体暴露组”、“中媒体暴露组”和“高媒体暴露组”。在两个区域风险划分标准下，次高风险地区媒体暴露子群体间的韧性均有差异性。确诊人数划分标准的低风险地区的媒体暴露子群体间的抑郁和焦虑水平存在差异。而在地理距离划分标准不同分组内媒体暴露子群体间的抑郁和焦虑并无显著关联，说明地理距离空间风险划分标准对媒体暴露与心理健康风险关联性的识别较小。 研究三采用机器学习对确诊人数风险评估标准分组的抑郁和焦虑分别对比多项式逻辑回归、随机森林、支持向量机、LightGBM 模型，结果发现抑郁、焦 虑 LightGBM 模型性能指标较佳。进一步使用不同媒体暴露内容预测不同分组内的抑郁、焦虑并进行事后分析，事后解释 SHAP 值结果发现，在高风险地区的抑郁、焦虑受到流行病学信息和网络舆论的负向影响，疫区情况报道负向预测高风险地区焦虑水平，本地疫情报道正向预测高风险地区焦虑水平；在次高风险地区，抑郁受到不同媒体暴露内容的影响作用较小，疫情网络舆论则是次高风险焦虑水平的正向影响因素；在次低风险地区，网络舆论是焦虑、抑郁的负向影响因素，本地疫情报道和公共卫生普及是抑郁的正向影响因素，权威解读是焦虑的负向影响因素，而流行病学调查负向预测了抑郁，但正向预测了焦虑；在低风险地区，不同媒体暴露内容对抑郁的影响较小，疫区情况报道则是焦虑的正向影响因素，总体来说，不同类型媒体暴露内容对高风险地区和次低风险地区大学生的影响较大，对次高风险地区和低风险地区的群体影响较小。 本研究通过三个研究对新冠疫情下两种空间风险划分标准与心理健康风险一致性进行探讨，并通过潜在剖面分析、机器学习算法分析媒体暴露对心理健康风险的影响作用，有助于我们了解突发公共事件下不同风险划分标准对于媒体暴露和心理健康风险关联性的识别有效性，对于补充媒体暴露风险研究具有理论意义，并对突发性公共卫生事件中心理干预的应急管理措施的媒体传播实践提供重要指导。 |
| 语种 | 中文 |
| 源URL | [http://ir.psych.ac.cn/handle/311026/48145]  |
| 专题 | 心理研究所_应用研究版块 |
| 推荐引用方式 GB/T 7714 | 马 岩. 媒体暴露对大学生心理健康的影响：基于疫情双风险评估标准[D]. 中国科学院心理研究所. 中国科学院大学. 2024. |
入库方式： OAI收割
来源：心理研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。