Evidence map›Paper›PMID 42630163›Full record

ArticleFrontiers in psychology2026

Inconclusive mutually reinforcing effects between associative learning and fluid intelligence: simulated reanalyses and a comment on Ren et al. (2026).

Kimmo Sorjonen, Bo Melin, Marika Melin

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

3 authors.

Kimmo SorjonenDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Bo MelinDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Marika MelinDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on findings from analyses with the random-intercept cross-lagged panel model (RI-CLPM), Ren et al. concluded reinforcing longitudinal effects between associative learning and fluid intelligence. However, the RI-CLPM is susceptible to spurious findings. Here, we analyzed data simulated to resemble the data used by Ren et al. with alternative models and found discrepant increasing, decreasing, and null prospective effects between associative learning and fluid intelligence. Hence, the conclusions by Ren et al. appear not to be supported by their own data. It is important for researchers to bear in mind that correlations, including effects in the RI-CLPM, in observational (i.e., non-experimental) data may be spurious and do, consequently, not prove genuine (i.e., non-spurious) influence. We recommend researchers to fit alternative models to data and to base conclusions on an aggregation of findings.

Indexed as

associative learningfluid intelligencemutualism theory of intelligencerandom-intercept cross-lagged panel model (RI-CLPM)spurious effectsstatistical rigor

Identifiers

PMID42630163
PMCPMC13493240

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.