Evidence map›Paper›PMID 41057603›Full record

ArticleScientific reports2025

The role of prompt, voice, and personality factors in the acceptance and evaluation of AI-generated mindfulness exercises.

Diel Alexander, Bäuerle Alexander, Teufel Martin, Jansen Christoph

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

4 authors.

Diel AlexanderClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg-Essen, Essen, Germany. alexander.diel@lvr.de.
Bäuerle AlexanderClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Teufel MartinClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Jansen ChristophClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI-generated mindfulness exercises have the potential to provide tailored mindfulness interventions. However, the role of quality of AI-generated mindfulness exercises on their acceptance and evaluation is as of yet underexplored. The present work investigates effects of prompting (tailored versus non-tailored versus human), voice (trained versus non-trained versus human), and matching voice personality factors on the uncanniness, human likeness, and acceptance of AI-generated mindfulness exercises. In two experiments, n = 143 participants rated real and different variations of AI-generated mindfulness exercises. It was found that trained AI voices significantly improve the evaluation of AI-generated mindfulness exercises comparable to human controls, while no significant effects of prompting were found. A categorization task further showed that exercises by trained AI voices were indistinguishable from human mindfulness exercises. Furthermore, a mismatch of voice personality and setting (mindfulness) significantly decreased voice evaluation. The results demonstrate the importance of using trained and matching AI voices for the implementation of AI-generated mindfulness interventions.

Indexed as

Artificial IntelligenceMindfulnessPersonalityVoiceAdultFemaleHumansMaleMiddle AgedYoung AdultDigital healthe-mental healthGenerative AIMeditationUncanny valley

Identifiers

PMID41057603
PMCPMC12504707

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.