Evidence map›Paper›PMID 28725103›Full record

ArticleSex roles

Will I Fit in and Do Well? The Importance of Social Belongingness and Self-Efficacy for Explaining Gender Differences in Interest in STEM and HEED Majors.

Una Tellhed, Martin Bäckström, Fredrik Björklund

Open access · hybridAbstract read
In one paragraph

Article in Sex roles. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
17.7field-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

19 citing papers in PubMed, 225 citations in OpenAlex.

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  8. Mind the gender gap: The social neuroscience of belonging.Frontiers in human neuroscience · 2023
    Review
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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

3 authors at 1 institution in 1 country.

Una TellhedDepartment of Psychology, Lund University, Box 213, SE-221 00 Lund, Sweden.ORCID 0000-0002-7283-6021
Martin BäckströmDepartment of Psychology, Lund University, Box 213, SE-221 00 Lund, Sweden.
Fredrik BjörklundDepartment of Psychology, Lund University, Box 213, SE-221 00 Lund, Sweden.
Lund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Throughout the world, the labor market is clearly gender segregated. More research is needed to explain women's lower interest in STEM (Science, Technology, Engineering and Mathematics) majors and particularly to explain men's lower interest in HEED (Health care, Elementary Education, and the Domestic spheres) majors. We tested self-efficacy (competence beliefs) and social belongingness expectations (fitting in socially) as mediators of gender differences in interest in STEM and HEED majors in a representative sample of 1327 Swedish high school students. Gender differences in interest in STEM majors strongly related to women's lower self-efficacy for STEM careers and, to a lesser degree, to women's lower social belongingness expectations with students in STEM majors. Social belongingness expectations also partly explained men's lower interest in HEED majors, but self-efficacy was not an important mediator of gender differences in interest in HEED. These results imply that interventions designed to lessen gender segregation in the labor market need to focus more on the social belongingness of students in the gender minority. Further, to specifically increase women's interest in STEM majors, we need to counteract gender stereotypical competence beliefs and assure women that they have what it takes to handle STEM careers.

Indexed as

BelongingnessGenderHEEDInterestSelf-efficacySTEM

Identifiers

PMID28725103
PMCPMC5486898
OpenAlexW2542575430

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.