Evidence map›Paper›PMID 34092548›Full record

ArticleJMIR formative research2021

Artificial Intelligence-Based Chatbot for Anxiety and Depression in University Students: Pilot Randomized Controlled Trial.

Maria Carolina Klos, Milagros Escoredo, Angela Joerin, Viviana Noemí Lemos, Michiel Rauws, Eduardo L Bunge

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR formative research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 13 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

59 citing papers in PubMed, 13 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Pooled it
  13. Pooled it
  14. Trial
  15. Trial
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors.

Maria Carolina Klos *Interdisciplinary Center for Research in Health and Behavioral Sciences (CIICSAC), Universidad Adventista del Plata (UAP)., National Scientific and Technical Research Council (CONICET)., Libertador San Martín, Entre Ríos, Argentina.ORCID https://orcid.org/0000-0002-5108-4692
Milagros Escoredo *X2AI inc., San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-6698-8750
Angela Joerin *X2AI inc., San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-3667-9636
Viviana Noemí Lemos *Interdisciplinary Center for Research in Health and Behavioral Sciences (CIICSAC), Universidad Adventista del Plata (UAP)., National Scientific and Technical Research Council (CONICET)., Libertador San Martín, Entre Ríos, Argentina.ORCID https://orcid.org/0000-0002-8855-2293
Michiel Rauws *X2AI inc., San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-5931-7702
Eduardo L Bunge *Department of Psychology, Palo Alto University, Palo Alto, CA, United States.ORCID https://orcid.org/0000-0002-1487-7618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence-based chatbots are emerging as instruments of psychological intervention; however, no relevant studies have been reported in Latin America.

objectiveThe objective of the present study was to evaluate the viability, acceptability, and potential impact of using Tess, a chatbot, for examining symptoms of depression and anxiety in university students.

methodsThis was a pilot randomized controlled trial. The experimental condition used Tess for 8 weeks, and the control condition was assigned to a psychoeducation book on depression. Comparisons were conducted using Mann-Whitney U and Wilcoxon tests for depressive symptoms, and independent and paired sample t tests to analyze anxiety symptoms.

resultsThe initial sample consisted of 181 Argentinian college students (158, 87.2% female) aged 18 to 33. Data at week 8 were provided by 39 out of the 99 (39%) participants in the experimental condition and 34 out of the 82 (41%) in the control group. On an average, 472 (SD 249.52) messages were exchanged, with 116 (SD 73.87) of the messages sent from the users in response to Tess. A higher number of messages exchanged with Tess was associated with positive feedback (F

conclusionsThe students spent a considerable amount of time exchanging messages with Tess and positive feedback was associated with a higher number of messages exchanged. The initial results show promising evidence for the usability and acceptability of Tess in the Argentinian population. Research on chatbots is still in its initial stages and further research is needed.

Indexed as

anxietyartificial intelligencechatbotscollege studentsconversational agentsdepressionmental health

Identifiers

PMID34092548
PMCPMC8391753

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.