Evidence map›Paper›PMID 42756415›Full record

ArticleFrontiers in psychology2026

Writing self-efficacy, achievement emotions, and engagement among Chinese EFL learners: a variable- and person-centered investigation based on control-value theory.

Hong Lei, Quanwang Zhan

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. 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
–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

0 citing papers in PubMed.

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

2 authors.

Hong LeiCenter for University Foreign Language Education, Anhui University, Hefei, China.
Quanwang ZhanSchool of Foreign Studies, Anhui University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drawing on the Control-Value Theory (CVT), this study adopts a dual-analytical approach to investigate the interplay of writing self-efficacy, emotions (enjoyment, anxiety, boredom), and engagement among 1,879 Chinese EFL learners. The variable-centered analysis identified writing self-efficacy as a key correlate of both behavioral and cognitive engagement, showing significant direct associations with engagement as well as indirect associations through the differentiated mediating roles of the three emotions. Notably, boredom emerged as the emotional correlate of behavioral engagement, whereas all three emotions were associated with cognitive engagement, suggesting that the role of emotions in engagement may not be uniform across engagement dimensions. Complementing these findings, the person-centered analysis identified four distinct latent profiles ranging from High Efficacy and Enjoyment to Lowest Efficacy and High Distress, which differed systematically in engagement outcomes. While behavioral engagement was comparatively insensitive to differences in emotional intensity once self-efficacy was low, cognitive engagement showed a clearer hierarchical pattern across profiles. The identification of a subgroup exhibiting concurrent high anxiety and high boredom alongside severely diminished self-efficacy illustrated a level of emotional complexity that variable-centered analyses would be unlikely to capture. Synthesizing these findings, the study suggests the potential value of considering both general associative patterns and learner-specific heterogeneity in future research and instructional practice on L2 writing.

Indexed as

control-value theoryL2 writing emotionsL2 writing engagementL2 writing self-efficacylatent profile analysis

Identifiers

PMID42756415
PMCPMC13582565

What OpenQuestion holds

Textmetadata
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.