Evidence map›Paper›PMID 39476370›Full record

ArticleJournal of medical Internet research2024

Characterization of Telecare Conversations on Lifestyle Management and Their Relation to Health Care Utilization for Patients with Heart Failure: Mixed Methods Study.

Mojisola Erdt, Sakinah Binte Yusof, Liquan Chai, Siti Umairah Md Salleh, Zhengyuan Liu, Halimah Binte Sarim, Geok Choo Lim, Hazel Lim, Nur Farah Ain Suhaimi, Lin Yulong and 10 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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. Article
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

20 authors.

Mojisola ErdtInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0003-2371-6768
Sakinah Binte YusofInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0009-0006-7370-4895
Liquan ChaiSchool of Informatics, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0009-0007-9448-5924
Siti Umairah Md SallehInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0009-0002-2029-319X
Zhengyuan LiuInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0001-6864-3094
Halimah Binte SarimChangi General Hospital, Singapore, Singapore.ORCID 0009-0000-3288-5622
Geok Choo LimChangi General Hospital, Singapore, Singapore.ORCID 0009-0008-3442-9688
Hazel LimInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0009-0008-7973-3472
Nur Farah Ain SuhaimiInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0009-0004-5833-5986
Lin YulongInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0009-0005-2753-3231
Yang GuoInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0002-4484-3160
Angela NgChangi General Hospital, Singapore, Singapore.ORCID 0009-0009-5497-359X
Sharon OngChangi General Hospital, Singapore, Singapore.ORCID 0009-0006-5059-7951
Bryan Peide ChooChangi General Hospital, Singapore, Singapore.ORCID 0000-0001-5602-8094
Sheldon LeeChangi General Hospital, Singapore, Singapore.ORCID 0000-0002-8750-6869
Huang WeiliangChangi General Hospital, Singapore, Singapore.ORCID 0000-0002-0702-0771
Hong Choon OhChangi General Hospital, Singapore, Singapore.ORCID 0000-0002-3086-7516
Maria Klara WoltersSchool of Informatics, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-3369-3558
Nancy F ChenInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0003-0872-5877
Pavitra KrishnaswamyInstitute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0001-5893-4306

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelehealth interventions where providers offer support and coaching to patients with chronic conditions such as heart failure (HF) and type 2 diabetes mellitus (T2DM) are effective in improving health outcomes. However, the understanding of the content and structure of these interactions and how they relate to health care utilization remains incomplete.

objectiveThis study aimed to characterize the content and structure of telecare conversations on lifestyle management for patients with HF and investigate how these conversations relate to health care utilization.

methodsWe leveraged real-world data from 50 patients with HF enrolled in a postdischarge telehealth program, with the primary intervention comprising a series of telephone calls from nurse telecarers over a 12-month period. For the full cohort, we transcribed 729 English-language calls and annotated conversation topics. For a subcohort (25 patients with both HF and T2DM), we annotated lifestyle management content with fine-grained dialogue acts describing typical conversational structures. For each patient, we identified calls with unusually high ratios of utterances on lifestyle management as lifestyle-focused calls. We further extracted structured data for inpatient admissions from 6 months before to 6 months after the intervention period. First, to understand conversational structures and content of lifestyle-focused calls, we compared the number of utterances, dialogue acts, and symptom attributes in lifestyle-focused calls to those in calls containing but not focused on lifestyle management. Second, to understand the perspectives of nurse telecarers on these calls, we conducted an expert evaluation where 2 nurse telecarers judged levels of concern and follow-up actions for lifestyle-focused and other calls (not focused on lifestyle management content). Finally, we assessed how the number of lifestyle-focused calls relates to the number of admissions, and to the average length of stay per admission.

resultsIn comparative analyses, lifestyle-focused calls had significantly fewer utterances (P=.01) and more dialogue acts (P

conclusionsOur approach and findings offer novel perspectives on the content, structure, and clinical associations of telehealth conversations on lifestyle management for patients with HF. Hence, our study could inform ways to enhance telehealth programs for self-care management in chronic conditions.

Indexed as

Heart FailureLife StyleTelemedicineAgedCommunicationDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedPatient Acceptance of Health Carebehaviorchronic diseaseconversationdialoguehealth care utilizationheart failurelifestyle managementmedical informaticsself-managementtelecaretelehealth

Identifiers

PMID39476370
PMCPMC11561433

What OpenQuestion holds

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LicenceCC BY
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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.