Evidence map›Paper›PMID 35626794›Full record

ArticleChildren (Basel, Switzerland)2022

Gender Differences in Sex Education in China: A Structural Topic Modeling Analysis Based on Online Knowledge Community Zhihu.

Wen Shi, Yuxuan Lin, Zihan Zhang, Jing Su

Open access · goldAbstract read
In one paragraph

Article in Children (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
15.2field-weighted citation impact, top 1% 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

0 citing papers in PubMed, 18 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Wen ShiSchool of Journalism and Communication, Jinan University, Guangzhou 510632, China.
Yuxuan LinSchool of Journalism and Communication, Tsinghua University, Beijing 100084, China.
Zihan ZhangSchool of Journalism and Communication, Tsinghua University, Beijing 100084, China.
Jing SuSchool of Humanities, Tsinghua University, Beijing 100084, China.
Tsinghua University · CNJinan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Considering the traditional concept of sex in China's official discourse and lack of social support system for sex education in China, burgeoning Internet knowledge community serves as an important forum for unprepared Chinese young parents to discuss and improve sex education. In this study, we conducted a structural topic modeling analysis of sex education discussions on Zhihu, the biggest online knowledge community in China. We found attention towards sex education are biased in China, where basic sexual terminologies are mentioned, but other important topics such as reproductive health, emotional attachment, and gender identity are insufficient or even absent, failing to fulfill the goal of Comprehensive Sexuality Education (CSE). This study paid special attention to gender differences in discussants, expected educators, and expected receivers of sex education. Findings show that boys are not considered as important sex education objects as girls, although many of them suffered from sexual assault and sexual diseases. They are always mentioned as roles that offend women rather than promoting or protecting themselves through sexual knowledge. Most discussants and expected educators of sex education are women, reflecting men's lack of attention to sex education issues as both individuals and fathers.

Indexed as

health communicationonline knowledge communitysex educationstructural topic modeling

Identifiers

PMID35626794
PMCPMC9139772
OpenAlexW4225001651

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.