Evidence map›Paper›PMID 42211179›Full record

ArticleFrontiers in artificial intelligence2026

Between innovation and risk: artificial intelligence and data protection in digital Mexico.

Emilio J Medrano-Sánchez, Elizabeth Ruiz-Ramírez, Mariela L Ayllon

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 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.

Emilio J Medrano-SánchezUniversidad San Ignacio de Loyola, Lima, Peru.
Elizabeth Ruiz-RamírezUniversidad Nacional Autónoma de México, Mexico City, Mexico.
Mariela L AyllonUniversidad Tecnológica del Perú, Ica, Peru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At a global level, the rapid adoption of artificial intelligence (AI) brings significant risks to data privacy, prompting the development of legal frameworks. In Latin America, including Mexico, where such frameworks remain emergent, the issue gains particular relevance. This study analyzed how perceptions of AI are associated with perceptions of personal data protection among university-educated professionals residing in Mexico City in 2025, based on privacy theory, the Technology Acceptance Model (TAM), and their extensions. A quantitative, non-experimental, correlational, and cross-sectional approach was employed. Data were collected from 101 university-educated professional participants residing in Mexico City using an expert-validated, 24-item Likert-type questionnaire. Data analysis was conducted in SPSS using non-parametric correlation tests (Spearman and Kendall). Results indicated that a more favorable perception of AI was associated with more favorable perceptions of personal data protection and its dimensions. The correlations demonstrated a moderate and significant positive association (

Indexed as

artificial intelligencecitizen trustdigital public policypersonal data protectionsocial perception

Identifiers

PMID42211179
PMCPMC13212271

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.