Evidence map›Paper›PMID 37887453›Full record

ArticleBehavioral sciences (Basel, Switzerland)2023

Investigating the Effect of Cognitive-Behavioral, Mindful-Based, Emotional-Based Intervention and Professional Training on Teachers' Job Burnout: A Meta-Analysis.

Jian Li, Eryong Xue, Yunshu He

Open access · goldAbstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

Jian LiChina Institute of Education Policy, Faculty of Education, Beijing Normal University, Beijing 100875, China.
Eryong XueChina Institute of Education Policy, Faculty of Education, Beijing Normal University, Beijing 100875, China.
Yunshu HeChina Institute of Education Policy, Faculty of Education, Beijing Normal University, Beijing 100875, China.
Beijing Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Teachers are more likely to experience occupational burnout; intervention for their job burnout has been paid more and more attention by the academic community. However, there is not enough evidence to support the interventions' effect. This study adopts the meta-analysis method and makes a statistical analysis of the interventions' effect on teachers' job burnout based on 29 papers in the literature of randomized controlled experiments. It mainly presents the basic external characteristics of the research literature; besides, based on the results of software CMA.V3, this paper also analysed the overall intervention effect and the separate effect of four types of intervention, namely, cognitive-behavioral interventions (CBI), mindfulness-based interventions (MBI), professional training (PT), and emotional-based intervention (EBI). The results showed that CBI had the best effect, and mindfulness-based intervention had the second-best effect. Professional training also showed a good intervention effect, while the intervention effect of emotional-based intervention remains to be verified. In addition, it was found that only the effect of cognitive-behavioral intervention (CBI) was significant and had a strong effect (g = 0.876, 95% CI-1.06, 2.814,

Indexed as

cognitive–behavioral intervention (CBI)interventionsmeta-analysismindfulness-based intervention (MBI)teachers’ job burnout

Identifiers

PMID37887453
PMCPMC10604072
OpenAlexW4387132329

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.