Evidence map›Paper›PMID 37936253›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2024

Introducing Quin: The Design and Development of a Prototype Chatbot to Support Smoking Cessation.

Hollie Bendotti, David Ireland, Sheleigh Lawler, David Oates, Coral Gartner, Henry M Marshall

Abstract read
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

6 authors.

Hollie BendottiThoracic Research Centre, Faculty of Medicine, University of Queensland, Chermside, Queensland, Australia.ORCID 0000-0001-5078-4809
David IrelandThe Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Herston, Queensland, Australia.ORCID 0000-0003-2189-4624
Sheleigh LawlerSchool of Public Health, Faculty of Medicine, University of Queensland, Herston, Queensland, Australia.ORCID 0000-0002-5771-0551
David OatesThe Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Herston, Queensland, Australia.
Coral GartnerNHMRC Centre of Research Excellence on Achieving the Tobacco Endgame, School of Public Health, University of Queensland, Herston, Queensland, Australia.ORCID 0000-0002-6651-8035
Henry M MarshallThoracic Research Centre, Faculty of Medicine, University of Queensland, Chermside, Queensland, Australia.ORCID 0000-0002-9626-8014

Funding

Commonwealth Scientific and Industrial Research OrganisationNational Health and Medical Research CouncilPrince Charles Hospital Foundation NI2021-31
6 · The paper itself

Abstract

introductionChatbots emulate human-like interactions and may usefully provide on-demand access to tailored smoking cessation support. We have developed a prototype smartphone application-based smoking cessation chatbot, named Quin, grounded in real-world, evidence-, and theory-based smoking cessation counseling sessions.

methodsConversation topics and interactions in Quitline counseling sessions (N = 30; 18 h) were characterized using thematic, content, and proponent analyses of transcripts. Quin was created by programming this content using a chatbot framework which interacts with users via speech to text. Reiterative changes and additions were made to the conversation structure and dialogue following regular consultation with a multidisciplinary team from relevant fields, and from evidence-based resources.

resultsChatbot conversations were encoded into initial and scheduled follow-up "appointments." Collection of demographic information, and smoking and quit history, informed tailored discussion about pharmacotherapy preferences, behavioral strategies, and social and professional support to form a quit plan. Follow-up appointments were programmed to check in on user progress, review elements of the quit plan, answer questions, and solve issues. Quin was programmed to include teachable moments and educational content to enhance health literacy and informed decision-making. Personal agency is encouraged through exploration and self-reflection of users' personal behaviors, experiences, preferences, and ideas.

conclusionsQuin's successful development represents a movement toward improving access to personalized smoking cessation support. Qualitative foundations of Quin provide greater insight into the smoking cessation counseling relationship and enhances the conversational ability of the technology. The prototype chatbot will be refined through beta-testing with end users and stakeholders prior to evaluation in a clinical trial. IMPLICATIONS: Our novel study provides transparent description of the translation of qualitative evidence of real-world smoking cessation counseling sessions into the design and development of a prototype smoking cessation chatbot. The successful iterative development of Quin not only embodies the science and art of health promotion, but also a step forward in expanding the reach of tailored, evidence based, in-pocket support for people who want to quit smoking.

Indexed as

CounselingSmoking CessationAdultFemaleHumansMaleMiddle AgedMobile ApplicationsSmartphone

Identifiers

PMID37936253
PMCPMC11033568

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LicenceCC BY-NC-ND
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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.