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ASHABot: An LLM-Powered Chatbot to Support the Informational Needs of Community Health Workers

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arxiv 2409.10913 v3 pith:IFKC33D7 submitted 2024-09-17 cs.HC

classification cs.HC
keywords ashabotchwscommunityneedssupervisorschatbothealthhealthcare
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Community health workers (CHWs) provide last-mile healthcare services but face challenges due to limited medical knowledge and training. This paper describes the design, deployment, and evaluation of ASHABot, an LLM-powered, experts-in-the-loop, WhatsApp-based chatbot to address the information needs of CHWs in India. Through interviews with CHWs and their supervisors and log analysis, we examine factors affecting their engagement with ASHABot, and ASHABot's role in addressing CHWs' informational needs. We found that ASHABot provided a private channel for CHWs to ask rudimentary and sensitive questions they hesitated to ask supervisors. CHWs trusted the information they received on ASHABot and treated it as an authoritative resource. CHWs' supervisors expanded their knowledge by contributing answers to questions ASHABot failed to answer, but were concerned about demands on their workload and increased accountability. We emphasize positioning LLMs as supplemental fallible resources within the community healthcare ecosystem, instead of as replacements for supervisor support.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. WaLLM -- Insights from an LLM-Powered Chatbot deployment via WhatsApp

    cs.HC 2025-05 conditional novelty 6.0 of 10

    A six-month deployment of a WhatsApp-based LLM chatbot with 97 active users found that factual and health questions dominated, and that daily push questions and a leaderboard were associated with higher engagement.

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