Evidence map›Paper›PMID 39314814›Full record

ArticleDigital health

Exploring community pharmacists' attitudes in Thailand towards ChatGPT usage: A pilot qualitative investigation.

Nuntapong Boonrit, Kornchanok Chaisawat, Chanakarn Phueakong, Nantitha Nootong, Warit Ruanglertboon

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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

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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.

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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

5 authors.

Nuntapong BoonritDepartment of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Prince of Songkla University, Hatyai, Songkhla, Thailand.
Kornchanok ChaisawatDepartment of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Prince of Songkla University, Hatyai, Songkhla, Thailand.
Chanakarn PhueakongDepartment of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Prince of Songkla University, Hatyai, Songkhla, Thailand.
Nantitha NootongDepartment of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Prince of Songkla University, Hatyai, Songkhla, Thailand.
Warit RuanglertboonDiscipline of Pharmacology, Division of Health and Applied Sciences, Faculty of Science, Prince of Songkla University, Hatyai, Songkhla, Thailand.ORCID https://orcid.org/0000-0003-0540-7427

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: ChatGPT has recently emerged as a disruptive technology, potentially impacting various societal dimensions, including pharmacy practices. In Thailand, community pharmacists are navigating transitions as patients increasingly rely on digital tools for healthcare recommendations. This study explores the attitudes of community pharmacists in Hatyai, one of Thailand's most populated cities, towards the integration of ChatGPT in pharmacy services. Method: ChatGPT-3.5 was used to generate responses to three questions concerning the use of medicine in special populations in the Thai language. These responses were then incorporated into a questionnaire and evaluated using a Likert scale from 1 to 5. Participants who consented were asked to rate the responses and participate in an in-depth interview. Results: The majority of participants rated the responses favorably, with scores of 4 and 5 accounting for at least 60% of the ratings. Only a small proportion of responses received doubtful ratings (score of 3) or was in disagreement, ranging from 20% to 40%. Moreover, open opinions extracted from the interviews suggested that participants viewed ChatGPT as a capable assistant, as it provided fast yet reasonably accurate information in the Thai language. Conclusion: The findings indicate that community pharmacists view ChatGPT as a capable assistant, albeit noting the need for further refinements. The study underscores the importance for pharmacists to proactively adapt to technological advancements, particularly those affecting patient safety, to enhance healthcare delivery and optimize treatment outcomes.

Indexed as

ChatGPTcommunity pharmacypharmacy servicespublic health

Identifiers

PMID39314814
PMCPMC11418248

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LicenceCC BY-NC
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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.