| Literature DB >> 31892122 |
Chengyan Zhu1, Xiaolin Xu1, Wei Zhang2, Jianmin Chen2, Richard Evans3.
Abstract
During the last two decades, social media has immersed itself into all facets of our personal and professional lives. The healthcare sector is no exception, with public health departments now capitalizing on the benefits that social media offers when delivering healthcare education and communication with citizens. Provincial Health Committees (PHCs) in China have begun to adopt the micro-video sharing platform, Tik Tok, to engage with local residents and communicate health-related information. This study investigates the status quo of official Tik Tok accounts managed by PHCs in mainland China. In total, 31 PHC accounts were analyzed during August 2019, while the top 100 most liked micro-videos were examined using content analysis. Coding included three major aspects: Quantified Impact, Video Content, and Video Form. 45.2% (n = 14) of PHCs had official Tik Tok accounts. A limited number of accounts (n = 2) were yet to upload a micro-video, while most (n = 9) had uploaded their first micro-video during 2019. For the top 100 most liked micro-videos, a sharp difference was observed in terms of number of Likes, Comments and Reposts. Videos containing cartoons or documentary-style content were most frequently watched by citizens. Similarly, content that promoted professional health or provided knowledge of diseases was frequently viewed. Content containing original music, formal mandarin language, subtitles, and which lasted less than 60 s, were most frequently followed. It is considered a missed opportunity that most PHCs struggle to take advantage of the Tik Tok platform, especially given its growing popularity and daily increase in account creation.Entities:
Keywords: China; Provincial Health Committee; Tik Tok; healthcare; micro-video; social media
Mesh:
Year: 2019 PMID: 31892122 PMCID: PMC6981526 DOI: 10.3390/ijerph17010192
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1The coding framework for the top 100 most liked micro-videos run by Provincial Health Committees (PHCs).
The coding scheme for video analysis.
| Index | Explanation |
|---|---|
| Number of Likes | Total number of Likes by 20 August 2019 |
| Number of Comments | Total number of Comments received by 20 August 2019 |
| Number of Reposts | Total number of Reposts by 20 August 2019 |
| Video Type | Refers to the different types of health communication, divided into five categories, including: cartoon, documentary, situation comedy, excerpt from TV program, excerpt from news report. |
| Video Theme | Refers to the major topic involved in the micro-video, encompassing disease knowledge, daily diet, health professionals’ image promotion, healthcare info, and health reforms. |
| Emotion | Refers to the major emotion involved; classified as excited, moved, humor or no specific emotion. |
| Character | Refers to the character playing the leading role or being shown most during the micro-video; divided into health professionals, public figures and general public (with patients included). |
| Background Music | Refers to the background music used, including no music, music selected from the Tik Tok music library, and original music. |
| Language Feature | Refers to the language used, including mandarin, and other local dialects. |
| Emphasized theme (Ending) | Refers to the technique of re-emphasizing the theme at the end of the micro-video. |
| Length | Refers to the length of the micro-video. |
| Subtitles | Refers to the technique of using subtitles to display the words spoken in the micro-video as written text. |
Basic information of Tik Tok accounts run by PHCs.
| Province | Region | First Time Video Uploaded | Number of Followers | Number of Uploaded Videos | Number of Updates | Total Number of Likes | Number of Top 100 most liked Micro-Videos |
|---|---|---|---|---|---|---|---|
| Tianjin | East | Never | 26 | 0 | 0 | 0 | 0 |
| Shanghai | East | Never | 4 | 0 | 0 | 0 | 0 |
| Shanxi | Central | 21 June 2018 | 5145 | 133 | 133 | 31,000 | 11 |
| Jilin | Central | 19 April 2019 | 13,000 | 74 | 75 | 127,000 | 14 |
| Jiangxi | Central | 12 May 2019 | 614 | 19 | 19 | 2808 | 1 |
| Henan | Central | 4 April 2019 | 190 | 5 | 5 | 367 | 0 |
| Hubei | Central | 5 May 2019 | 8566 | 121 | 121 | 45,000 | 5 |
| Hunan | Central | 10 July 2019 | 58 | 5 | 5 | 140 | 0 |
| Guangdong | East | 4 September 2018 | 132,000 | 478 | 527 | 651,000 | 53 |
| Hainan | East | 30 November 2018 | 274 | 9 | 9 | 580 | 0 |
| Sichuan | West | 23 January 2019 | 38,000 | 97 | 105 | 196,000 | 16 |
| Guizhou | West | 19 August 2019 | 54 | 12 | 12 | 51 | 0 |
| Inner Mongolia | West | 25 April 2019 | 38 | 6 | 6 | 13 | 0 |
| Ning Xia | West | 16 August 2019 | 11 | 3 | 3 | 27 | 0 |
| Total | 197,980 | 962 | 1,015 | 1,053,986 | 100 |
The distribution of the Quantified Impact dimension.
| Quantified Impact | Min | Max | Median | Sum |
|---|---|---|---|---|
| Number of Likes | 667 | 177,000 | 7,752.56 | 775,256 |
| Number of Comments | 0 | 6815 | 135.97 | 13,597 |
| Number of Reposts | 0 | 20,000 | 595.68 | 59,568 |