Evidence map›Paper›PMID 35059305›Full record

ArticleInternet interventions2022

Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness.

Hao Liu, Huaming Peng, Xingyu Song, Chenzi Xu, Meng Zhang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Internet interventions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 23 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 23 pooled it
33.9field-weighted citation impact, top 1% of its field
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

93 citing papers in PubMed, 23 syntheses or guidelines pooled it, 239 citations in OpenAlex.

  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. Pooled it
  15. Pooled it
  16. Pooled it
  17. Pooled it
  18. Pooled it
  19. Pooled it
  20. Pooled it

33 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 1 country.

Hao LiuSchool of Design, South China University of Technology, B11 Building, University Town Campus, South China University of Technology, Guangzhou Higher Education Mega Center, Panyu District, 510006 Guangzhou, China.
Huaming PengSchool of Design, South China University of Technology, B11 Building, University Town Campus, South China University of Technology, Guangzhou Higher Education Mega Center, Panyu District, 510006 Guangzhou, China.
Xingyu SongSchool of Psychology, Central China Normal University, The 8th Floor, Nanhu Complex Building, Central China Normal University, No. 152 Luoyu Road, Wuhan 430079, China.
Chenzi XuSocial Work Research Center, South China University of Technology, 5th Building, Wushan Campus, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou 510640, China.
Meng ZhangSocial Work Research Center, South China University of Technology, 5th Building, Wushan Campus, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou 510640, China.
South China University of Technology · CNCentral China Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression impacts the lives of a large number of university students. Mobile-based therapy chatbots are increasingly being used to help young adults who suffer from depression. However, previous trials have short follow-up periods. Evidence of effectiveness in pragmatic conditions are still in lack.

objectiveThis study aimed to compare chatbot therapy to bibliotherapy, which is a widely accepted and proven-useful self-help psychological intervention. The main objective of this study is to add to the evidence of effectiveness for chatbot therapy as a convenient, affordable, interactive self-help intervention for depression.

methodsAn unblinded randomized controlled trial with 83 university students was conducted. The participants were randomly assigned to either a chatbot test group (n = 41) to receive a newly developed chatbot-delivered intervention, or a bibliotherapy control group (n = 42) to receive a minimal level of bibliotherapy. A set of questionnaires was implemented as measurements of clinical variables at baseline and every 4 weeks for a period of 16 weeks, which included the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder scale (GAD-7), the Positive and Negative Affect Scale (PANAS). The Client Satisfaction Questionnaire-8 (CSQ-8) and the Working Alliance Inventory-Short Revised (WAI-SR) were used to measure satisfaction and therapeutic alliance after the intervention. Participants' self-reported adherence and feedback on the therapy chatbot were also collected.

resultsParticipants were all university students (undergraduate students (n = 31), postgraduate students (n = 52)). They were between 19 and 28 years old (mean = 23.08, standard deviation (SD) = 1.76) and 55.42% (46/83) female. 24.07% (20/83) participants were lost to follow-up. No significant group difference was found at baseline. In the intention-to-treat analysis, individuals in the chatbot test group showed a significant reduction in the PHQ-9 scores (F = 22.89;

conclusionsThe chatbot-delivered self-help depression intervention was proven to be superior to the minimal level of bibliotherapy in terms of reduction on depression, anxiety, and therapeutic alliance achieved with participants.

Indexed as

AI Artificial IntelligenceAI, Artificial IntelligenceANCONA, Analysis of CovarianceANOVA, Analysis of VarianceCBT, Cognitive Behavioral TherapyCSQ-8, the Client Satisfaction Questionnaires-8DPO, Dialogue Policy OptimizationDST, Dialogue Status TrackingGAD-7, the Generalized Anxiety Disorder Scale-7 (GAD-7)IPI, Internet-based Psychological InterventionsITT, Intent-to-TreatmHealthPANAS, the Positive and Negative Affect Schedule (PANAS) (Watson et al., 19s88)PHQ-9, the Patient Health Questionnaires-9Public health informaticsSD, Standard DeviationWAI-SR, the Working Alliance Inventory-Short Revised

Identifiers

PMID35059305
PMCPMC8760455
OpenAlexW4206687394

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.