Evidence map›Paper›PMID 41477544›Full record

ArticleClinical neuropsychiatry2025

Algorithmic Entrapment the Silent Erosion of User Autonomy and Mental Health.

Leon Donadoni, Donatella Marazziti, Federico Mucci

Abstract read
In one paragraph

Article in Clinical neuropsychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Leon DonadoniAtlantic Institute, Rome.
Donatella MarazzitiDepartment of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, Pisa, Italy.
Federico MucciDepartment of Mental Health, Lucca Zone, Azienda USL Toscana Nord Ovest, Lucca, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent developments in the study of highly visual social media have highlighted that, far from being neutral conduits, adolescents' online environments might be curated by recommender systems that learn from behaviour. On this view, risk and benefit may depend less on time spent online than on patterns of exposure ‒ what reaches young people, how they meet it, and when in development contact occurs. For instance, in large adolescent cohorts, only 10-15% of users account for most of the association between use and distress, underscoring the relevance of heterogeneity. Similar feeds might support connection and care while, in susceptible users, amplifying appearance-centred comparison, compulsive use and contact with harmful material. A public-health perspective treats personalisation as an upstream determinant and invites proportionate responsibilities, namely transparency, independent audit and safety-by-design. Clinically, brief assessments that separate time from type of engagement, paired with low-burden, mechanism-focused interventions, could offer practical steps. Taken together, a precautionary and balanced stance should aim at keeping what is valuable online while reducing foreseeable harm through accountable design.

Indexed as

algorithmic exposureethicsmental healthpublic healthrecommender systemssafety-by-designsocial-media

Identifiers

PMID41477544
PMCPMC12752921

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.