Evidence map›Paper›PMID 34602727›Full record

ArticleComputers in human behavior2022

More collaboration, less seriousness: Investigating new strategies for promoting youth engagement in government-generated videos during the COVID-19 pandemic in China.

Changyang He, Huan Liu, Lu He, Tun Lu, Bo Li

Open access · greenAbstract read
In one paragraph

Article in Computers in human behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
8.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 40 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 3 countries.

Changyang HeDepartment of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, China.
Huan LiuSchool of Computer Science, Fudan University, Shanghai, China.
Lu HeDepartment of Informatics, Donald Bren School of Information and Computer Science, University of California, Irvine, Irvine, CA, United States.
Tun LuSchool of Computer Science, Fudan University, Shanghai, China.
Bo LiDepartment of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, China.
Fudan University · CNHong Kong University of Science and Technology · HKUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effectively engaging citizens during crises is critical for governments to disseminate timely information and help the public to adjust to the constantly changing conditions. In particular, promoting youth engagement not only enhances crisis awareness and resilience among the young generation, but also has a positive impact on youths' social participation and responsibility. With the increasing popularity of online video services, leveraging online videos to disseminate authoritative information has become a method widely adopted by government. To enhance youth awareness and engagement, two new video-based crisis communication strategies have been utilized on a popular youth-targeted video platform Bilibili in China: creating recreational videos such as animation and music videos, and collaborating with individual video-uploaders in video making. However, their impacts and results are largely unknown, which motivates our study. Guided by Entertainment Education (EE) and Collaborative Governance (CG), we report, to our best knowledge, the first systematic study on how recreational video category and government-citizen collaboration would influence youth engagement focusing on 3347 COVID-19-related government-generated videos on Bilibili. This study reveals that recreational videos successfully promote youth engagement including interaction, feedback and sharing. Collaboration with individual uploaders in video making also has a substantially positive impact on youth engagement. Through an in-depth qualitative content analysis of user-generated commentaries, we further unpacked the unique values (e.g., trust work for youth participation) as well as latent limitations (e.g., imbalanced topic distribution) of the two new strategies. We discuss how the findings enrich EE and CG theoretically, and provide practical implications to effective and engaging communication strategies during crises.

Indexed as

Collaborative governanceCrisis communicationEntertainment educationGovernment-generated crisis videosYouth engagement

Identifiers

PMID34602727
PMCPMC8470152
OpenAlexW3199891962

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.