Evidence map›Paper›PMID 38379636›Full record

ArticlePsychology research and behavior management2024

The Impact of Social Media on Users' Self-Efficacy and Loneliness: An Analysis of the Mediating Mechanism of Social Support.

Wei Jia, Lei Liu, Gang Peng

Abstract read
In one paragraph

Article in Psychology research and behavior management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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.

Wei JiaSchool of Politics and Public Administration, Qingdao University, Qingdao, Shandong, People's Republic of China.ORCID 0000-0002-8181-086X
Lei LiuSchool of Politics and Public Administration, Qingdao University, Qingdao, Shandong, People's Republic of China.ORCID 0009-0004-3369-0914
Gang PengSchool of Statistics, Southwestern University of Finance and Economics, Chengdu, Sichuan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The integration of social media into all areas of society has become a typical phenomenon of the Internet era. This study's core objective is to dissect the relationship between social media, self-efficacy and loneliness, especially emphasizing the mediating function of social support. Patients and Methods: The research data is derived from the pooled cross-sectional data combined from the four-period data of the China Family Panel Studies (CFPS). The study employs Ordinary Least Squares (OLS) regression as the basic research method, and utilizes Instrumental Variables (IV) and other methods to conduct robustness checks. Results: Social media usage frequency (SMUF) enhances self-efficacy and loneliness through social support. Social support promotes self-efficacy and alleviates users' loneliness. In self-efficacy, social support plays a fully mediating role. Moreover, education (human capital) has a significant moderating effect. There are noticeable differences in the response of different characteristics groups to SMUF. Conclusion: This study reveals how social media impacts self-efficacy and loneliness through social support. Based on the research results, avoiding prolonged usage of social media and improving digital literacy are the crucial means to exert the positive benefits of social media.

Indexed as

lonelinessmediation analysisself-efficacysocial mediasocial support

Identifiers

PMID38379636
PMCPMC10876441

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.