Evidence map›Paper›PMID 37545778›Full record

ArticleInternational journal of nursing sciences2023

The development and evaluation of a social media-based HIV knowledge dissemination platform in China.

Shuyu Han, Hui Li, Ke Li, Zhiwen Wang

Abstract read
In one paragraph

Article in International journal of nursing sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

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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

4 authors.

Shuyu HanSchool of Nursing, Peking University, Beijing, China.
Hui LiCenter for Disease Control and Prevention in Jinan Shizhong District, Jinan, China.
Ke LiDepartment of Emergency, Peking University First Hospital, Beijing, China.
Zhiwen WangSchool of Nursing, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to introduce the development of a social media-based HIV knowledge dissemination platform and evaluate its dissemination effects, users' feedback, and preferences. Methods: A social media-based HIV knowledge dissemination platform ("Lihui Space") was developed as a WeChat Official Account (WOA) to disseminate HIV-related information and knowledge to the public and answer subscribers' questions. A cross-sectional study was conducted on 784 platform subscribers between July 2021 and September 2021 to evaluate users' experiences with and preferences for the platform. This platform included three content levels about HIV-related information and knowledge: individual level (health self-management), community level (social function), and society level (news and policy), and dissemination information through texts, pictures, videos, and websites. A descriptive analysis was conducted to estimate the dissemination effects of the platform and evaluation scores. Results: As of September 16, 2021, this platform's WeChat Communication Index (WCI) score was 923.60, the total number of users was 100,008, and the total views in one month was more than 724,000. Participants reported a high level of satisfaction with this platform in terms of overall evaluation (23.36 ± 3.06), readability (18.46 ± 2.63), function evaluation (13.93 ± 1.92), design and structure (22.96 ± 3.36), and interactivity (12.56 ± 2.69). Conclusion: This social media-based platform is currently available in the WeChat application. It is a promising tool for HIV knowledge dissemination and addressing disparities in accessing health care resources.

Indexed as

Acquired immunodeficiency syndromeHIVKnowledgeTelemedicine

Identifiers

PMID37545778
PMCPMC10401336

What OpenQuestion holds

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Registered trials

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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.