Evidence map›Paper›PMID 40135005›Full record

ArticleCureus2025

Effect of the Use of Electronic Media on the Cognitive Intelligence, Attention, and Academic Trajectory of Medical Students.

Alejandro Hernández-Chávez, Liz Hamui-Sutton, Armando Muñoz-Comonfort, Raúl Sampieri-Cabrera

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

4 authors.

Alejandro Hernández-ChávezDepartment of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, MEX.
Liz Hamui-SuttonDepartment of Medical Education, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, MEX.
Armando Muñoz-ComonfortDepartment of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, MEX.
Raúl Sampieri-CabreraCenter for Complexity Sciences, National Autonomous University of Mexico, Mexico City, MEX.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Electronic media are an integral part of university students' academic and personal lives; however, their excessive use may interfere with the cognitive functions critical for learning. Intelligence can be assessed through crystallized intelligence (Gc), which reflects accumulated knowledge, and fluid intelligence (Gf), which is associated with problem solving and adaptability. Also, neurophysiological measurements like the event-related potentials (ERPs), particularly P300, provide high temporal resolution measures of cognitive processing, allowing an assessment of attention (neurophysiological measures) and memory functions. This study hypothesizes that excessive screen time negatively impacts attention, fluid and crystallized intelligence, and academic performance in medical students.  Materials and methods A total of 305 second-year medical students from a public university participated in the study (mean age: 20 years). Variables assessed included intelligence, attention, academic trajectory, and screen time. Intelligence was measured using the Shipley-2 test, and screen time was measured using a validated Screen Time Survey. For the neurophysiological measures, a subsample (n=30) underwent ERP recording with the P300 oddball paradigm for neurophysiological analysis. Academic performance was determined from standardized physiology test scores. Data were analyzed using IBM SPSS Statistics for Windows, Version 25.0 (2017; IBM Corp., Armonk, New York, United States), GraphPad Prism (Dotmatics, Boston, Massachusetts, United States), and Excel (Microsoft Corporation, Redmond, New York, United States) through descriptive and inferential statistics. Results A significant relationship emerged between screen time, cognitive performance, and academic achievement. Participants reported an average daily screen exposure of 7.1 ± 4.3 hours. A negative correlation was identified between screen time and standardized test scores (r = -0.24, p < 0.001), indicating that increased screen use was associated with lower academic performance. Cognitive intelligence assessments revealed that Gf (R² = 0.848) and general cognition (R² = 0.400) were significantly affected, while Gc remained stable (R² = 0.001). Neurophysiological measures showed average P300 latencies of 358.33 ± 45.6 ms and amplitudes of 259.63 ± 61.6 μV. Shorter N100 latencies (86.7 ± 24.6 ms) correlated with better academic performance (r = -0.45, R² = 0.199). Discussion Students with greater screen time exhibited lower standardized exam scores, suggesting that excessive digital exposure may deplete the cognitive resources essential for academic tasks. The decline in fluid and general cognitive intelligence suggests a diminished capacity for problem-solving and adaptability. Neurophysiological markers indicated prolonged latencies and reduced amplitudes of key ERPs (N100, N200, and P300), reflecting impaired attentional control and working memory in students with higher screen exposure. These findings suggest that prolonged screen use contributes to slower and less efficient cognitive processing. Conclusions Excessive screen time, particularly due to recreational electronic media use, negatively affects cognitive performance and academic outcomes in medical students. The observed decline appears to be mediated by deficits in attention and working memory along with a reduction in Gf, which may impair problem-solving skills and adaptability in complex academic settings.

Indexed as

intelligencelearningmedical educationmental cognitionp300 potential

Identifiers

PMID40135005
PMCPMC11936385

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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.