Evidence map›Paper›PMID 42077320›Full record

ArticleFrontiers in psychology2026

When stress meets the feed: algorithmic curation, digital stress relief, and academic amotivation in the attention economy.

Jing Jin, XiaCheng Song, Lu Sun, Xiqiong Yi, Quanyue Zheng

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Jing JinGuangdong University of Science and Technology, Dongguan, China.
XiaCheng SongGuangdong University of Science and Technology, Dongguan, China.
Lu SunXi'an Fanyi University, Xi'An, China.
Xiqiong YiDongguan Polytechnic, Dongguan, China.
Quanyue ZhengShinawatra University, Pathum Thani, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Algorithmically curated feeds have become a default layer of everyday life, offering rapid affect regulation under academic pressure while also reshaping attention and self-regulation. Moving beyond the generic "screen time" debate, this study examines a socio-technical pathway in which perceived pressure uncertainty is associated with academic amotivation through immersive escapism and self-regulatory fatigue. We surveyed 518 university students in China and measured pressure uncertainty, immersive escapism, self-regulatory fatigue, and academic amotivation. Using confirmatory factor analysis and latent structural equation modeling with ordinal indicators, while controlling demographics and entertainment-focused scrolling time, we found that pressure uncertainty was positively associated with immersive escapism. Immersive escapism, in turn, was positively associated with self-regulatory fatigue, which was associated with higher academic amotivation. Competing path models were more consistent with the hypothesized ordering than with alternative specifications. These findings suggest that platform-shaped digital relief may be linked to a depletion-oriented coping loop with educational consequences, pointing to intervention leverage points that are more actionable than broad calls to simply "use less." We discuss implications for higher education (digital wellbeing support, self-regulation scaffolding, and algorithm-related digital literacy) and for platform design and accountability (greater user control, transparency, and pacing mechanisms that may interrupt maladaptive loops).

Indexed as

academic amotivationalgorithmic curationimmersive escapismpressure uncertaintyself-regulatory fatigue

Identifiers

PMID42077320
PMCPMC13128543

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.