Evidence mapPaperPMID 39655059Full record

ArticleDigital health

Integrating ChatGPT: Enhancing postpartum mental healthcare with artificial intelligence (AI) support.

Sultan Alam, Shahab Saquib Sohail

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

2 authors.

Sultan AlamSchool of Computing Science and Engineering, VIT Bhopal University, Sehore, India.ORCID https://orcid.org/0000-0003-2711-4860
Shahab Saquib SohailSchool of Computing Science and Engineering, VIT Bhopal University, Sehore, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We are writing to extend the discourse on the innovative work published in digital health on the feasibility of videoconferencing-based therapy groups for postpartum depression and anxiety. The pragmatic evaluation demonstrated promising outcomes in terms of acceptability, appropriateness, and group process, suggesting that this modality is a viable alternative to traditional in-person therapy, especially in addressing the challenges faced by new mothers. Building on this study, we propose considering the integration of artificial intelligence (AI)-driven tools such as ChatGPT2 into such group therapy settings. ChatGPT, a large language model developed by OpenAI, has demonstrated considerable potential in generating therapeutic dialogs, offering empathetic responses, and assisting in therapeutic guidance. It can be employed as a supplementary tool to enhance the therapeutic process by providing personalized, real-time responses during or between sessions.

Indexed as

AI integrationChatGPTDigital healthlarge language modelvideoconferencing therapy

Identifiers

PMID39655059
PMCPMC11626650

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.