Evidence map›Paper›PMID 42325352›Full record

ArticleFrontiers in psychology2026

Multimodal perceptual curation for cognitive autonomy in Generation Z decision making.

Zhean Zhu, Kai Wang

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.

Zhean ZhuSchool of Data Science, Zhejiang University of Finance and Economics, Hangzhou, China.
Kai WangSchool of Management, Zhejiang University of Finance and Economics, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recommendation algorithms increasingly shape the perceptual environments through which young users encounter information, evaluate options, and form preferences. Although prior studies have mainly examined algorithmic exposure as a problem of content filtering, less is known about how multimodal digital cues influence perceptual attention, intuitive judgment, and decision autonomy. This study proposes an Algorithmic Cognitive Colonization framework to explain how sustained exposure to personalized recommendation systems may progressively affect attentional selection, preference formation, and self-related decision processes. Two behavioral studies were conducted with educated Chinese undergraduate participants. Study 1 used a 14-day information diet field experiment in which participants switched from personalized recommendation feeds to chronological or social-graph-based feeds while maintaining normal platform use. The intervention was associated with increased reported content-exposure breadth, a U-shaped adjustment pattern in perceived decision autonomy, and a short-term return of content-exposure breadth toward baseline after personalized feeds were resumed. Study 2 used a dual-process decision paradigm to compare rapid consumer choices with deliberative opinion formation. Algorithmic recommendation labels produced stronger conformity in speeded consumer-choice conditions than in more deliberative opinion-formation conditions. Moreover, metacognitive awareness of algorithmic influence was not significantly associated with actual behavioral resistance, supporting a literacy paradox. These findings suggest that personalized recommendation systems may function as perceptual choice architectures that influence digital decision-making primarily by reducing decision friction and guiding intuitive responses. Rather than providing direct neural or physiological evidence, the present studies offer behavioral evidence for how algorithmically curated multimodal environments may shape attention-related choices, state-level preferences, and perceived autonomy. The results, therefore, provide a behavioral foundation for future multimodal neuroscience and perception research using eye-tracking, psychophysiological, neuroimaging, or cross-modal attention measures.

Indexed as

algorithmic cognitive colonizationchoice architectureconsumption diversitydecision autonomydual-process theoryGeneration Zinformation dietrecommendation algorithm

Identifiers

PMID42325352
PMCPMC13275461

What OpenQuestion holds

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Registered trials

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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.