Evidence map›Paper›PMID 33800901›Full record

ArticleInternational journal of environmental research and public health2021

Variations in the Home Language Environment and Early Language Development in Rural China.

Yue Ma, Laura Jonsson, Tianli Feng, Tyler Weisberg, Teresa Shao, Zixin Yao, Dongming Zhang, Sarah-Eve Dill, Yian Guo, Yue Zhang and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
6.0field-weighted citation impact, top 4% 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

3 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
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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

12 authors at 3 institutions in 2 countries.

Yue MaRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Laura JonssonRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Tianli FengSchool of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China.ORCID 0000-0002-3051-1747
Tyler WeisbergRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Teresa ShaoRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Zixin YaoRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.ORCID 0000-0001-6815-977X
Dongming ZhangRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Sarah-Eve DillRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.ORCID 0000-0002-9321-6606
Yian GuoRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Yue ZhangChild Health Care Department, National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China.
Dimitris FriesenRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Scott RozelleRural Education Action Program, Freeman Spogli Institute for International Studies, Stanford University, Palo Alto, CA 94305-6055, USA.
Stanford University · USNational Center for Women and Children’s Health, China CDC · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The home language environment is critical to early language development and subsequent skills. However, few studies have quantitatively measured the home language environment in low-income, developing settings. This study explores variations in the home language environment and child language skills among households in poor rural villages in northwestern China. Audio recordings were collected for 38 children aged 20-28 months and analyzed using Language Environment Analysis (LENA) software; language skills were measured using the MacArthur-Bates Mandarin Communicative Developmental Inventories expressive vocabulary scale. The results revealed large variability in both child language skills and home language environment measures (adult words, conversational turns, and child vocalizations) with 5- to 6-fold differences between the highest and lowest scores. Despite variation, however, the average number of adult words and conversational turns were lower than found among urban Chinese children. Correlation analyses did not identify significant correlations between demographic characteristics and the home language environment. However, the results do indicate significant correlations between the home language environment and child language skills, with conversational turns showing the strongest correlation. The results point to a need for further research on language engagement and ways to increase parent-child interactions to improve early language development among young children in rural China.

Indexed as

LanguageLanguage DevelopmentAdultChildChild LanguageChild, PreschoolChinaHumansVocabularyYoung Adultchild developmenthome language environmentindividual differenceslanguage developmentrural China

Identifiers

PMID33800901
PMCPMC7967512
OpenAlexW3134086057

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.