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Analysis on the literature communication path of new media integrating public mental health
The communication of mental health is an important branch of health communication, and it is also an important factor affecting people’s physical and mental health. With the increasing pressure of life, people’s mental health problems have huge challenges. Under the enormous pressure of economy and...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531954/ https://www.ncbi.nlm.nih.gov/pubmed/36204755 http://dx.doi.org/10.3389/fpsyg.2022.997558 |
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author | Liu, Shaojing |
author_facet | Liu, Shaojing |
author_sort | Liu, Shaojing |
collection | PubMed |
description | The communication of mental health is an important branch of health communication, and it is also an important factor affecting people’s physical and mental health. With the increasing pressure of life, people’s mental health problems have huge challenges. Under the enormous pressure of economy and life, people’s mental health problems are becoming increasingly prominent. This calls for attention to mental health issues. In the context of new media, knowledge about mental health can be disseminated through the Internet and mobile platforms. This approach will spread awareness of mental health prevention and basic issues. Mental health problems are also a manifestation of the lack of humanistic spirit. Excellent works related to humanistic spirit can promote the relief of mental health problems. Literature can contribute to the development of mental health problems. This research studies the communication of mental health issues in the context of new media using literary works as a carrier. At the same time, it also considers big data-related algorithms to mine the traditional characteristics of mental health problems. The research results show that new media technology can well assist the dissemination of mental health education, and literary works also contribute to the dissemination of mental health education knowledge. Collaborative filtering algorithm and atrous convolution algorithm can better predict the relevant characteristics in the process of mental health communication. For the CF algorithm, its maximum similarity index reached 0.987 when recommending mental health propagation paths using new media technology. For ACNN, the smallest prediction error is only 1.78%. |
format | Online Article Text |
id | pubmed-9531954 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95319542022-10-05 Analysis on the literature communication path of new media integrating public mental health Liu, Shaojing Front Psychol Psychology The communication of mental health is an important branch of health communication, and it is also an important factor affecting people’s physical and mental health. With the increasing pressure of life, people’s mental health problems have huge challenges. Under the enormous pressure of economy and life, people’s mental health problems are becoming increasingly prominent. This calls for attention to mental health issues. In the context of new media, knowledge about mental health can be disseminated through the Internet and mobile platforms. This approach will spread awareness of mental health prevention and basic issues. Mental health problems are also a manifestation of the lack of humanistic spirit. Excellent works related to humanistic spirit can promote the relief of mental health problems. Literature can contribute to the development of mental health problems. This research studies the communication of mental health issues in the context of new media using literary works as a carrier. At the same time, it also considers big data-related algorithms to mine the traditional characteristics of mental health problems. The research results show that new media technology can well assist the dissemination of mental health education, and literary works also contribute to the dissemination of mental health education knowledge. Collaborative filtering algorithm and atrous convolution algorithm can better predict the relevant characteristics in the process of mental health communication. For the CF algorithm, its maximum similarity index reached 0.987 when recommending mental health propagation paths using new media technology. For ACNN, the smallest prediction error is only 1.78%. Frontiers Media S.A. 2022-09-20 /pmc/articles/PMC9531954/ /pubmed/36204755 http://dx.doi.org/10.3389/fpsyg.2022.997558 Text en Copyright © 2022 Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Liu, Shaojing Analysis on the literature communication path of new media integrating public mental health |
title | Analysis on the literature communication path of new media integrating public mental health |
title_full | Analysis on the literature communication path of new media integrating public mental health |
title_fullStr | Analysis on the literature communication path of new media integrating public mental health |
title_full_unstemmed | Analysis on the literature communication path of new media integrating public mental health |
title_short | Analysis on the literature communication path of new media integrating public mental health |
title_sort | analysis on the literature communication path of new media integrating public mental health |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531954/ https://www.ncbi.nlm.nih.gov/pubmed/36204755 http://dx.doi.org/10.3389/fpsyg.2022.997558 |
work_keys_str_mv | AT liushaojing analysisontheliteraturecommunicationpathofnewmediaintegratingpublicmentalhealth |