互联网使用对HIV阴性检测者健康焦虑影响的探索性研究

发布时间：2018-04-21 14:39

本文选题：HIV阴性检测 + 健康焦虑　；参考：《大连医科大学》2013年硕士论文

【摘要】：目的：考察艾滋病自愿检测（HIV Voluntary Counseling and Testing，VCT）门诊中HIV检测结果为阴性的人群健康与疾病相关网络使用情况、健康焦虑、躯体症状以及抑郁水平与社区人群、门诊患者之间的差异，探索互联网使用对HIV阴性检测人群健康焦虑的影响，并对其相关影响因素的作用方式和途径进行初步探讨。方法：1、对象：有效被试620人，其中HIV阴性检测者157人，门诊对照组157人，社区对照组306人，年龄在15~60岁。2、问卷：采用一般情况表、健康相关网络搜索行为调查表、易感性心理因素调查表、健康焦虑问卷（HAQ）、病人健康问卷躯体症状量表（PHQ-15）、病人健康问卷抑郁量表（PHQ-9）、健康相关网络使用问卷（HIUQ）分别对社区组、门诊组和HIV阴性检测组人群进行调查，各量表的得分分组比较采用F检验、两因素方差分析、采用分层回归分析和检验健康焦虑和抑郁的影响因素；应用路径分析验证网络使用对健康焦虑的中介作用模型。结果：1、三组人群健康相关网络使用情况不同，社区组中使用网络的人数所占比例最高84.0%（257人）；门诊对照组中在网上搜索健康信息的人数所占比例最高73.9%（116人）；使用即时通讯工具如论坛、QQ群等交流健康与疾病相关信者中HIV阴性检测组的比例最高45.9%（45人）。 2、HIV阴性检测组与社区、门诊对照组人群在躯体症状、健康焦虑、抑郁得分上差异显著HIV阴性检测组的躯体症状得分显著高于社区组(P0.01)，但与门诊组差异不显著（P0.05）；在健康焦虑及抑郁得分上均显著高于社区和门诊组。 3、网络使用对健康焦虑的主效应显著F（2，377）=15.13， p0.01，随着网络使用频率的增多，健康焦虑水平呈上升的趋势；易感性对健康焦虑的主效应显著，F（2，377）=8.34，p0.01；易感性与网络使用的交互作用显著，说明网络使用因素对不同易感性人群的影响不同，易感性高的个体频繁进行健康或疾病相关的网络搜索时更容易产生健康焦虑，而网络作用对低易感性个体的健康焦虑影响不明显；性别与网络使用的交互作用显著。 4、采用Pearson相关分析，躯体症状、健康焦虑抑郁均与网络使用频率存在着显著的正相关（p0.01）。其中健康焦虑、抑郁、躯体症状与网络使用频率的相关系数分别为0.36、0.25、0.15，健康焦虑与网络使用的关系最为密切，此外，健康焦虑与抑郁、躯体症状之间也存在着较强的相关性，相关系数分别为0.66、0.54、0.64。 5、对健康焦虑的影响因素进行多元分层回归分析，结果显示基本情况中性别对健康焦虑的预测作用显著，组别和易感性作为原因变量对预测健康焦虑的作用显著，做出了新的贡献，解释力增加了31%，网络使用对健康焦虑的预测作用显著解释力增加了5.1%。 6、通过路径分析看出：从易感性出发指向健康焦虑和网络使用的路径系数分别为0.38和0.28，均达到了显著性水平，从易感性指向躯体症状、抑郁的路径系数没有达到了显著性水平；从健康焦虑出发指向躯体症状、抑郁的路径系数分别为0.48和0.55，达到了显著性水平。结论： 1、 HIV阴性检测者使用互联网交流健康或疾病信息的比例高于对照组。 2、HIV阴性检测者的躯体症状水平与门诊组相近；健康焦虑抑郁水平显著高于门诊和社区对照组。 3、易感性个体随着健康相关网络使用的频率增加容易产生健康焦虑，，而对于非易感性个体网络使用对健康焦虑的影响不明显。 4、易感性心理因素是健康焦虑的主要的预测因素，网络使用是易感性因素预测健康焦虑的重要中介因素。即网络使用激发了个体潜隐的易感性素质导致焦虑的发生。 5、本次“阴性艾滋病”事件的爆发，可能就是在网络的影响作用下，高易感性个体间HIV相关健康焦虑的传播与强化。
[Abstract]:Objective: To investigate the health and disease related network use, health anxiety, somatomatic symptoms and depression levels between the community population and outpatients in the HIV Voluntary Counseling and Testing (VCT) outpatient clinic, which are negative for HIV detection results, and explore the health of the Internet using HIV negative detection population health. The influence of anxiety and the ways and means of influencing factors are discussed.
Methods: 1 subjects: 620 effective subjects, including 157 HIV negative test, 157 outpatient control group, 306 community control group and 15~60 year old.2, questionnaire: health related network search behavior questionnaire, susceptibility psychological factor questionnaire, health anxiety questionnaire (HAQ), patient health questionnaire somatic symptom scale (PH) Q-15), the patient health questionnaire Depression Scale (PHQ-9), the health related network use questionnaire (HIUQ) was used to investigate the community group, the outpatient group and the HIV negative test group. The scores of each scale were compared with the F test, two factor variance analysis, and the stratified regression analysis and test of the influencing factors of health anxiety and depression; the application path was used. The mediating effect of Internet use on health anxiety was analyzed and verified.
Results: 1, three groups of people had different health related network usage.
The highest percentage was 84% (257); the proportion of people searching for health information on the Internet in the outpatient control group was the highest (116), and the ratio of HIV negative test groups such as instant messaging tools such as forum, QQ group and other communication health and disease related believers was the highest (45).
2, there were significant differences in somatic symptoms, health anxiety and depression scores between the HIV negative test group and the community and the outpatient control group. The scores of somatic symptoms in the HIV negative test group were significantly higher than those in the community group (P0.01), but there was no significant difference between the out-patient group and the out-patient group (P0.05), and the scores in the health anxiety and depression were significantly higher than those in the community and the out-patient groups.
3, the main effect of network use on health anxiety is significant F (2377) =15.13, P0.01, with the increase of network use frequency, the level of health anxiety is rising, the main effect of susceptibility to health anxiety is significant, F (2377) =8.34, P0.01, and the interaction between susceptibility and network use is significant, indicating the factors of network use to different susceptibility people. The influence of the group is different. The individuals with high susceptibility to frequent health or disease related network search are more likely to produce health anxiety, and the effect of the network on the health anxiety of the low susceptibility individuals is not obvious, and the interaction between sex and network use is significant.
4, Pearson correlation analysis, somatic symptoms, health anxiety and depression have significant positive correlation with network use frequency (P0.01). The correlation coefficient of health anxiety, depression, somatic symptoms and network use frequency is 0.36,0.25,0.15, and the relationship between health anxiety and network use is most closely, in addition, health anxiety and depression, body There was also a strong correlation between body symptoms, and the correlation coefficients were 0.66,0.54,0.64.
5, multiple stratified regression analysis on the influencing factors of health anxiety was carried out. The results showed that gender was significant in predicting health anxiety in the basic situation. Group and susceptibility as the cause variable had significant effect on predicting health anxiety, made new contributions, the explanatory power increased by 31%, and the predictive effect of network use on health anxiety was significant. The explanatory power is increased by 5.1%.
6, through the path analysis, we can see that the path coefficients from the susceptibility to the health anxiety and the network use are 0.38 and 0.28 respectively, and all reach the significant level. From the susceptibility to somatic symptoms, the path coefficient of depression has not reached a significant level; from the health anxiety to the somatic symptoms, the path coefficient of depression is respectively 0.48 and 0.55, reaching a significant level.
Conclusion:
1, the proportion of HIV negative test users using Internet to communicate health or disease information is higher than that of the control group.
2, the level of somatic symptoms of HIV negative test group was similar to that of outpatient group, and the level of health anxiety and depression was significantly higher than that of outpatient and community control group.
3, susceptible individuals tend to generate health anxiety with increasing frequency of health related networks, while the use of non susceptible individuals is not significantly affected by health anxiety.
4, the psychological factors of susceptibility are the main predictors of health anxiety. Network use is an important intermediary factor for predicting health anxiety by susceptibility factors. That is, network use stimulates the individual latent susceptibility to anxiety.
5, the outbreak of the "negative AIDS" incident may be the transmission and enhancement of HIV related health anxiety among highly susceptible individuals under the influence of the Internet.

【学位授予单位】：大连医科大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：R512.91

【参考文献】