Evidence map›Paper›PMID 38805259›Full record

Trial reportJMIR mental health2024

Effects of a Chatbot-Based Intervention on Stress and Health-Related Parameters in a Stressed Sample: Randomized Controlled Trial.

Christine Schillings, Echo Meißner, Benjamin Erb, Eileen Bendig, Dana Schultchen, Olga Pollatos

Abstract readRandomized Controlled TrialMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in JMIR mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Observational
  6. Review
  7. Review
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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

6 authors.

Christine SchillingsDepartment of Clinical and Health Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany.ORCID 0000-0002-8807-9547
Echo MeißnerInstitute of Distributed Systems, Ulm University, Ulm, Germany.ORCID 0000-0002-2937-6306
Benjamin ErbInstitute of Distributed Systems, Ulm University, Ulm, Germany.ORCID 0000-0002-5432-4989
Eileen BendigDepartment of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, Ulm University, Ulm, Germany.ORCID 0000-0001-6727-1751
Dana SchultchenDepartment of Clinical and Health Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany.ORCID 0000-0001-5623-535X
Olga PollatosDepartment of Clinical and Health Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany.ORCID 0000-0002-0512-565X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStress levels and the prevalence of mental disorders in the general population have been rising in recent years. Chatbot-based interventions represent novel and promising digital approaches to improve health-related parameters. However, there is a lack of research on chatbot-based interventions in the area of mental health.

objectiveThe aim of this study was to investigate the effects of a 3-week chatbot-based intervention guided by the chatbot ELME, specifically with respect to the ability to reduce stress and improve various health-related parameters in a stressed sample.

methodsIn this multicenter two-armed randomized controlled trial, 118 individuals with medium to high stress levels were randomized to the intervention group (n=59) or the treatment-as-usual control group (n=59). The ELME chatbot guided participants of the intervention group through 3 weeks of training based on the topics stress, mindfulness, and interoception, with practical and psychoeducative elements delivered in two daily interactive intervention sessions via a smartphone (approximately 10-20 minutes each). The primary outcome (perceived stress) and secondary outcomes (mindfulness; interoception or interoceptive sensibility; subjective well-being; and emotion regulation, including the subfacets reappraisal and suppression) were assessed preintervention (T1), post intervention (T2; after 3 weeks), and at follow-up (T3; after 6 weeks). During both conditions, participants also underwent ecological momentary assessments of stress and interoceptive sensibility.

resultsThere were no significant changes in perceived stress (β

conclusionsTo gain insight into how the intervention can be improved to achieve its full potential for stress reduction, besides a longer intervention duration, specific sample subgroups should be considered. The chatbot-based intervention seems to have the potential to improve mindfulness and emotion regulation in a stressed sample. Future chatbot-based studies and interventions in health care should be designed based on the latest findings on the efficacy of rule-based and artificial intelligence-based chatbots.

trial registrationGerman Clinical Trials Register DRKS00027560; https://drks.de/search/en/trial/DRKS00027560. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-doi.org/10.3389/fdgth.2023.1046202.

Indexed as

MindfulnessStress, PsychologicalAdultEmotional RegulationFemaleHumansInteroceptionMaleMiddle Agedchatbotemotion regulationinteroceptioninteroceptive sensibilityinterventionmindfulnessrandomized controlled trialRCTstress

Identifiers

PMID38805259
PMCPMC11167325

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Registered trials

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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.