Subjects: Psychology >> Applied Psychology Subjects: Medicine, Pharmacy >> Preventive Medicine and Hygienics submitted time 2024-03-17
Abstract： HPV vaccination is an effective way to prevent and treat cervical cancer, but the vaccination situation in our country is not optimistic, and many young people hesitate to vaccinate HPV vaccine. Research has shown that information persuasion is an effective means to increase vaccination rates. This study will focus on the content of persuasion information and explore the relationship between influencing factors and individual personality characteristics. To this end, we recruited 284 subjects online to conduct a questionnaire survey and analyzed the data using ANOVA. The results show that there are significant differences in the persuasive effect of information containing different influencing factors. It is necessary to select more effective influencing factors to produce the persuasive effect of promoting vaccination, and the big five personality characteristics of individuals will have a significant impact on the persuasive effect of information. This study can provide scientific basis and guidance for the promotion of vaccination, and has important theoretical and practical value for promoting public health.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2024-02-29
Abstract： HPV vaccination can not only effectively prevent the development of cervical cancer and its precancerous lesions, but also prevent other parts of the disease caused by HPV infection. However, the vaccination situation in China is not optimistic, and many young people are hesitant to get the HPV vaccine. Based on the planning theory model, this study aims to explore the influencing factors of HPV vaccination intention, compile a questionnaire with good reliability and validity to evaluate the importance of influencing factors of HPV vaccination intention, and explore the importance degree of influencing factors of different vaccination intention. In experiment 1, this study explored the influencing factors of individual HPV vaccination intention through semi-structured interview method, and obtained 25 influencing factors such as vaccine safety, vaccine effectiveness, vaccination convenience, professionalism, conformity and data. In experiment 2, through exploratory factor analysis, confirmatory factor analysis and reliability and validity test, a 17-question, 4-dimensional questionnaire was constructed to evaluate the importance of factors influencing HPV vaccination intention. Among them, confirmatory factor analysis supported the 4-factor model (χ²/df<3, RMR=0.059, RMSEA=0.054, GFI=0.928, TLI=0.914, IFI=0.929), showing good model fit. The Cronbach’s α coefficient of the questionnaire was 0.853, and the retest reliability at a 4-week interval was 0.804. It shows that our questionnaire has good reliability and validity. In addition, there are significant differences in the evaluation of the importance of different influencing factors, and there are also significant differences in the evaluation of the importance of factors among individuals with or without a family history of cancer and different levels of education. This study will provide valuable insights into vaccination promotion strategies and provide scientific basis and reference for developing targeted approaches.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2022-03-18
Abstract：
This paper introduces the big data research method in psychology in details, taking Ninety-Nine Articles website as an example. Using the collected textual data, we calculated word frequencies as features, then trained machine learning models, and used models to predict life satisfaction for texts crawled from Ninety-Nine Articles website, providing inspiration and help for beginners in big data research. This paper introduces text-based word frequency calculation using Python and sentiment dictionary through specific examples, and completes the training, testing and application of the machine learning model using Python's scikit-learn library. Furthermore, we uploaded the accompanying source program for direct operation. This paper introduces the big data research method of machine learning modeling via text-based word frequency. Our article emphasizes how to apply the technology, and thus we introduce the technology in a more basic way with less involvement of the technical principles.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2022-03-06
Abstract：
[Objective] This study aims to explore the relationship between staying up late, different development levels of cities and life satisfaction with the method of big data in Weibo, so as to increase the understanding of life satisfaction of contemporary people. [Method]The users in Weibo were divided into those who stayed up late and didn't stay up late in first-tier cities and other cities according to user’s information of blog posting. In addition, the statistical difference in life satisfaction between people who stayed up late and didn't stay up late in different areas was compared. [Results] (1) The life satisfaction of Weibo users who stayed up late was significantly higher than that of non-staying up late group (t = 11.768, p < 0.05); (2) Life satisfaction of Weibo users in first-tier cities was significantly lower than that of users in other cities (t =-4.135, p < 0.05); (3) The life satisfaction of staying up late in first-tier cities was significantly lower than that of staying up late in other cities (p < 0.05), and there was no statistically significant difference between non-staying up late in first-tier cities and non-staying up late in other cities (p > 0.05); (4) The life satisfaction of staying up late in first-tier cities was significantly higher than that of non-staying up late in first-tier cities (p < 0.05), and that of staying up late in other cities was significantly higher than that of non-staying up late (p < 0.05). [Conclusion] The staying up late behavior of contemporary Weibo users will improve their life satisfaction to a certain extent. However, the life satisfaction of Weibo users in first-tier cities is lower than that of Weibo users in other cities. "
Peer Review Status:Awaiting Review
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