Evidence map›Paper›PMID 40278718›Full record

ArticleSports (Basel, Switzerland)2025

ChatGPT-4o-Generated Exercise Plans for Patients with Type 2 Diabetes Mellitus-Assessment of Their Safety and Other Quality Criteria by Coaching Experts.

Samir Akrimi, Leon Schwensfeier, Peter Düking, Thorsten Kreutz, Christian Brinkmann

Abstract read
In one paragraph

Article in Sports (Basel, Switzerland), 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
  2. Review
  3. 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

5 authors.

Samir AkrimiDepartment of Preventive and Rehabilitative Sport Medicine, Institute of Cardiovascular Research and Sport Medicine, German Sport University Cologne, 50933 Cologne, Germany.
Leon SchwensfeierDepartment of Preventive and Rehabilitative Sport Medicine, Institute of Cardiovascular Research and Sport Medicine, German Sport University Cologne, 50933 Cologne, Germany.
Peter DükingDepartment of Sports Science and Movement Pedagogy, TU Braunschweig, 38106 Braunschweig, Germany.
Thorsten KreutzDepartment of Fitness & Health, IST University of Applied Sciences, 40233 Düsseldorf, Germany.
Christian BrinkmannDepartment of Preventive and Rehabilitative Sport Medicine, Institute of Cardiovascular Research and Sport Medicine, German Sport University Cologne, 50933 Cologne, Germany.ORCID 0000-0001-8419-7565

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this discussion paper based on preliminary data, the safety and other quality criteria of ChatGPT-4o-generated exercise plans for patients with type 2 diabetes mellitus (T2DM) are evaluated. The study team created three fictional patient profiles varying in sex, age, body mass index, secondary diseases/complications, medication, self-rated physical fitness, weekly exercise routine and personal exercise preferences. Three distinct prompts were used to generate three exercise plans for each fictional patient. While Prompt 1 was very simple, Prompt 2 and Prompt 3 included more detailed requests. Prompt 3 was optimized by ChatGPT itself. Three coaching experts reviewed the exercise plans for safety and other quality criteria and discussed their evaluations. Some of the exercise plans showed serious safety issues, especially for patients with secondary diseases/complications. While most exercise plans incorporated key training principles, they showed some deficits, e.g., insufficient feasibility. The use of more detailed prompts (Prompt 2 and Prompt 3) tended to result in more elaborate exercise plans with better ratings. ChatGPT-4o-generated exercise plans may have safety issues for patients with T2DM, indicating the need to consult a professional coach for feedback before starting a training program.

Indexed as

diabetesdigital healthexercisehealth benefitstraining

Identifiers

PMID40278718
PMCPMC12031090

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.