Evidence map›Paper›PMID 33898936›Full record

ArticleJAMIA open2021

Information needs and perceptions of chatbots for hypertension medication self-management: a mixed methods study.

Ashley C Griffin, Zhaopeng Xing, Sean P Mikles, Stacy Bailey, Saif Khairat, Jaime Arguello, Yue Wang, Arlene E Chung

Open access · goldAbstract read
In one paragraph

Article in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
5.2field-weighted citation impact, top 5% of its field
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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 25 citations in OpenAlex.

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  7. Patient Information Needs During Ambulatory Medication Changes: A Qualitative Study.Journal of patient-centered research and reviews · 2025
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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

8 authors at 2 institutions in 1 country.

Ashley C GriffinCarolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina, USA.ORCID https://orcid.org/0000-0002-1535-0797
Zhaopeng XingCarolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina, USA.
Sean P MiklesLineberger Comprehensive Cancer Outcomes Program, UNC, Chapel Hill, North Carolina, USA.
Stacy BaileyFeinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Saif KhairatCarolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina, USA.ORCID https://orcid.org/0000-0002-8992-2946
Jaime ArguelloSchool of Information & Library Science, UNC, Chapel Hill, North Carolina, USA.
Yue WangCarolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina, USA.
Arlene E ChungCarolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina, USA.
University of North Carolina at Chapel Hill · USNorthwestern University · US

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
An Interdisciplinary Program for Advanced Training in Health Data AnalyticsT15LM012500 · NLM · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MOSTAFA, JAVED · 2017 to 2021
$2.9M
NCATS NIH HHS UL1 TR002489NLM NIH HHS T15 LM012500
6 · The paper itself

Abstract

objectiveChatbots have potential to deliver interactive self-management interventions but have rarely been studied in the context of hypertension or medication adherence. The objective of this study was to better understand patient information needs and perceptions of chatbots to support hypertension medication self-management. MATERIALS AND

methodsMixed methods were used to assess self-management needs and preferences for using chatbots. We purposively sampled adults with hypertension who were prescribed at least one medication. Participants completed questionnaires on sociodemographics, health literacy, self-efficacy, and technology use. Semi-structured interviews were conducted, audio-recorded, and transcribed verbatim. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using applied thematic analysis.

resultsThematic saturation was met after interviewing 15 participants. Analysis revealed curiosity toward chatbots, and most perceived them as humanlike. The majority were interested in using a chatbot to help manage medications, refills, communicate with care teams, and for accountability toward self-care tasks. Despite general enthusiasm, there were concerns with chatbots providing too much information, making demands for lifestyle changes, invading privacy, and usability issues with deployment on smartphones. Those with overall positive perceptions toward chatbots were younger and taking fewer medications. DISCUSSION: Chatbot-related informational needs were consistent with existing self-management research, and many felt chatbots would be valuable if customizable and compatible with patient portals, pharmacies, or health apps.

conclusionAlthough most were not familiar with chatbots, patients were interested in interacting with them, but this varied. This research informs future design and functionalities of conversational interfaces to support hypertension self-management.

Indexed as

chatbotconversational agenthypertensionmobile healthself-management

Identifiers

PMID33898936
PMCPMC8054030
OpenAlexW3154184856

What OpenQuestion 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 OpenQuestion graph.