Evidence map›Paper›PMID 42421095›Full record

ArticleBMC psychology2026

Age differences in proactive and reactive control: valence asymmetries in the processing of complex emotional scenes.

Ni Zhang, Xuechuan Sun, Jingxin Wang

Abstract read
In one paragraph

Article in BMC 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
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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

3 authors.

Ni ZhangDepartment of Psychology, School of Law, Tianjin University of Commerce, Tianjin, 300134, China. zhangni1223@126.com.
Xuechuan SunFaculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.
Jingxin WangFaculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.

Funding

Annual Project of Tianjin Municipal Philosophy and Social Sciences Planning TJXLQN25-02
6 · The paper itself

Abstract

This study investigates age differences in proactive and reactive control during emotional scene processing, using complex scenes that require effortful top-down interpretation. Sixty-two participants (32 young and 30 older adults) completed an emotional AX-CPT task with positive, negative, and neutral scenes. Results revealed that the relative balance between proactive and reactive control in older adults was asymmetrically shaped by emotional valence when processing complex perceptually demanding stimuli. For positive scenes, older adults showed a relative reliance on proactive control, evidenced by higher Proactive Behavioral Index (PBI) scores. For negative scenes, they exhibited reduced proactive control, with higher error rates on neutral-negative sequences, whereas young adults showed the opposite pattern. Because the experimental design did not include a facial-expression comparison condition, conclusions about stimulus-type moderation are necessarily tentative. Nevertheless, these findings provide initial evidence that valence-specific control asymmetries are expressed under conditions of high conceptual and perceptual demand. Older adults appeared to differentially deploy control resources for positive versus negative stimuli under demanding conditions. This study provides new evidence that adaptive control is dynamically reshaped by the processing demands associated with complex emotional materials, offering a foundation for future research examining how stimulus complexity interacts with motivational priorities in aging.

Indexed as

AgingEmotionsAdultAgedAge FactorsFacial ExpressionFemaleHumansMaleMiddle AgedYoung AdultCognitive agingEmotional scenesProactive controlReactive controlStimulus complexity

Identifiers

PMID42421095
PMCPMC13536570

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.