Evidence map›Paper›PMID 38199786›Full record

Trial reportBMJ mental health2024

A chatbot to improve adherence to internet-based cognitive-behavioural therapy among workers with subthreshold depression: a randomised controlled trial.

Sakiko Yasukawa, Taku Tanaka, Kenji Yamane, Ritsuko Kano, Masatsugu Sakata, Hisashi Noma, Toshi A Furukawa, Takuya Kishimoto

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

Trial report in BMJ mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Sakiko YasukawaTechnology Development Laboratories, Sony Corporation, Tokyo, Japan.ORCID http://orcid.org/0000-0003-2375-609X
Taku TanakaTechnology Development Laboratories, Sony Corporation, Tokyo, Japan.ORCID http://orcid.org/0009-0004-5910-7387
Kenji YamaneTechnology Development Laboratories, Sony Corporation, Tokyo, Japan.ORCID http://orcid.org/0009-0005-1756-2987
Ritsuko KanoTechnology Development Laboratories, Sony Corporation, Tokyo, Japan.ORCID http://orcid.org/0009-0000-7273-4191
Masatsugu SakataDepartment of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan.ORCID http://orcid.org/0000-0002-5358-5263
Hisashi NomaDepartment of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan.ORCID http://orcid.org/0000-0002-2520-9949
Toshi A FurukawaDepartment of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan.ORCID http://orcid.org/0000-0003-2159-3776
Takuya KishimotoTechnology Development Laboratories, Sony Corporation, Tokyo, Japan takuya.kishimoto@sony.com.ORCID http://orcid.org/0009-0001-1624-0602

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInternet-based cognitive-behavioural therapy (iCBT) is effective for subthreshold depression. However, iCBT has problems with adherence, especially when unaccompanied by human guidance. Knowledge on how to enhance adherence to iCBT without human involvement can contribute to improving the effectiveness of iCBT.

objectiveThis is an implementation study to examine the effect of an automated chatbot to improve the adherence rate of iCBT.

methodsWe developed a chatbot to increase adherence to an existing iCBT programme, and a randomised controlled trial was conducted with two groups: one group using iCBT plus chatbot (iCBT+chatbot group) and one group not using the chatbot (iCBT group). Participants were full-time employees with subthreshold depression working in Japan (n=149, age mean=41.4 (SD=11.1)). The primary endpoint was the completion rate of the iCBT programme at 8 weeks.

findingsWe analysed data from 142 participants for the primary outcome. The completion rate of the iCBT+chatbot group was 34.8% (24/69, 95% CI 23.5 to 46.0), that of the iCBT group was 19.2% (14/73, 95% CI 10.2 to 28.2), and the risk ratio was 1.81 (95% CI 1.02 to 3.21).

conclusionsCombining iCBT with a chatbot increased participants' iCBT completion rate. CLINICAL IMPLICATIONS: Encouraging messages from the chatbot could improve participation in an iCBT programme. Further studies are needed to investigate whether chatbots can improve adherence to the programme in the long term and to assess their impact on depression, anxiety and well-being. TRIAL REGISTRATION NUMBER: UMIN000047621.

Indexed as

Cognitive Behavioral TherapyDepressionAnxietyAnxiety DisordersHumansInternetadult psychiatrydepressiondepression & mood disorderspsychiatry

Identifiers

PMID38199786
PMCPMC10806906

What OpenQuestion holds

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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.