Evidence map›Paper›PMID 39652870›Full record

ArticleJMIR formative research2024

Rapid, Tailored Dietary and Health Education Through A Social Media Chatbot Microintervention: Development and Usability Study With Practical Recommendations.

Shahmir H Ali, Fardin Rahman, Aakanksha Kuwar, Twesha Khanna, Anika Nayak, Priyanshi Sharma, Sarika Dasraj, Sian Auer, Rejowana Rouf, Tanvi Patel and 1 more

Abstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

Shahmir H AliSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-0360-3507
Fardin RahmanSchool of Global Public Health, New York University, New York, NY, United States.ORCID 0009-0006-5376-3003
Aakanksha KuwarSchool of Global Public Health, New York University, New York, NY, United States.ORCID 0009-0009-4308-0876
Twesha KhannaSchool of Global Public Health, New York University, New York, NY, United States.ORCID 0009-0009-5398-9098
Anika NayakCollege of Computing, Data Science, and Society, University of California, Berkeley, Berkeley, CA, United States.ORCID 0000-0002-4778-8654
Priyanshi SharmaCollege of Computing, Data Science, and Society, University of California, Berkeley, Berkeley, CA, United States.ORCID 0000-0002-1789-5053
Sarika DasrajSchool of Global Public Health, New York University, New York, NY, United States.ORCID 0009-0004-1955-1475
Sian AuerSchool of Global Public Health, New York University, New York, NY, United States.ORCID 0000-0001-7164-9526
Rejowana RoufUniversity of Minnesota Medical School, Minneapolis, MN, United States.ORCID 0000-0001-7361-7640
Tanvi PatelSchool of Global Public Health, New York University, New York, NY, United States.ORCID 0009-0004-1203-0351
Biswadeep DharDepartment of Family and Community Medicine, University of Illinois College of Medicine Rockford, Rockford, IL, United States.ORCID 0000-0001-8143-9071

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is an urgent need to innovate methods of health education, which can often be resource- and time-intensive. Microinterventions have shown promise as a platform for rapid, tailored resource dissemination yet have been underexplored as a method of standardized health or dietary education; social media chatbots display unique potential as a modality for accessible, efficient, and affordable educational microinterventions.

objectiveThis study aims to provide public health professionals with practical recommendations on the use of social media chatbots for health education by (1) documenting the development of a novel social media chatbot intervention aimed at improving dietary attitudes and self-efficacy among South Asian American young adults and (2) describing the applied experiences of implementing the chatbot, along with user experience and engagement data.

methodsIn 2023, the "Roti" chatbot was developed on Facebook and Instagram to administer a 4-lesson tailored dietary health curriculum, informed by formative research and the Theory of Planned Behavior, to 18- to 29-year-old South Asian American participants (recruited through social media from across the United States). Each lesson (10-15 minutes) consisted of 40-50 prescripted interactive texts with the chatbot (including multiple-choice and open-response questions). A preintervention survey determined which lesson(s) were suggested to participants based on their unique needs, followed by a postintervention survey informed by the Theory of Planned Behavior to assess changes in attitudes, self-efficacy, and user experiences (User Experience Questionnaire). This study uses a cross-sectional design to examine postintervention user experiences, engagement, challenges encountered, and solutions developed during the chatbot implementation.

resultsData from 168 participants of the intervention (n=92, 54.8% Facebook; n=76, 45.2% Instagram) were analyzed (mean age 24.5, SD 3.1 years; n=129, 76.8% female). Participants completed an average of 2.6 lessons (13.9 minutes per lesson) and answered an average of 75% of questions asked by the chatbot. Most reported a positive chatbot experience (User Experience Questionnaire: 1.34; 81/116, 69.8% positive), with pragmatic quality (ease of use) being higher than hedonic quality (how interesting it felt; 88/116, 75.9% vs 64/116, 55.2% positive evaluation); younger participants reported greater hedonic quality (P=.04). On a scale out of 10 (highest agreement), participants reported that the chatbot was relevant (8.53), that they learned something new (8.24), and that the chatbot was helpful (8.28). Qualitative data revealed an appreciation for the cheerful, interactive messaging of the chatbot and outlined areas of improvement for the length, timing, and scope of text content. Quick replies, checkpoints, online forums, and self-administered troubleshooting were some solutions developed to meet the challenges experienced.

conclusionsThe implementation of a standardized, tailored health education curriculum through an interactive social media chatbot displayed strong feasibility. Lessons learned from challenges encountered and user input provide a tangible roadmap for future exploration of such chatbots for accessible, engaging health interventions.

Indexed as

Health EducationSocial MediaAdolescentAdultAsianDietFemaleHumansMaleSelf EfficacySurveys and QuestionnairesYoung AdultAsianchatbotconversational agentcurriculumdietdietary educationfeasibilityhealth educationinnovationinterventionmicrointerventionpublic health professionalsocial mediasocial media chatbotyoung adult

Identifiers

PMID39652870
PMCPMC11667145

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.