Evidence map›Paper›PMID 41049162›Full record

ArticleFrontiers in digital health2025

DISCOVER: a Data-driven Interactive System for Comprehensive Observation, Visualization, and ExploRation of human behavior.

Tobias Hallmen, Dominik Schiller, Antonia Vehlen, Steffen Eberhardt, Tobias Baur, Daksitha Withanage Don, Wolfgang Lutz, Elisabeth André

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in digital health, 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. Article
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

8 authors.

Tobias Hallmen *Chair for Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany.
Dominik Schiller *Chair for Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany.
Antonia VehlenDepartment of Psychology, Division of Clinical Psychology and Psychotherapy, University of Trier, Trier, Germany.
Steffen EberhardtDepartment of Psychology, Division of Clinical Psychology and Psychotherapy, University of Trier, Trier, Germany.
Tobias BaurChair for Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany.
Daksitha Withanage DonChair for Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany.
Wolfgang LutzDepartment of Psychology, Division of Clinical Psychology and Psychotherapy, University of Trier, Trier, Germany.
Elisabeth AndréChair for Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding human behavior is a fundamental goal of social sciences, yet conventional methodologies are often limited by labor-intensive data collection and complex analyses. Computational models offer a promising alternative for analyzing large datasets and identifying key behavioral indicators, but their adoption is hindered by technical complexity and substantial computational requirements. To address these barriers, we introduce

Indexed as

behavioral indicatorscomputational modelsdata explorationhuman behavior analysisinteractive systemmachine learningmultimodal analysispsychotherapy

Identifiers

PMID41049162
PMCPMC12492635

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.