Evidence mapPaperPMID 30806625Full record

ArticleJMIR mHealth and uHealth2019

Patient Adherence to a Mobile Phone-Based Heart Failure Telemonitoring Program: A Longitudinal Mixed-Methods Study.

Patrick Ware, Mala Dorai, Heather J Ross, Joseph A Cafazzo, Audrey Laporte, Chris Boodoo, Emily Seto

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03358303 (Effect of a Mobile Phone-based Telemonitoring Program on the Outcome of Heart Failure Patients After an Incidence of Acute Decompensation), which is not on this map. Cited by 59 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 6 pooled it
28.9field-weighted citation impact, top 1% 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.

NCT03358303 naactive not recruitingnot on this map

Effect of a Mobile Phone-based Telemonitoring Program on the Outcome of Heart Failure Patients After an Incidence of Acute Decompensation

TypeinterventionalSponsorUniversity Health Network, TorontoRan2018 to 2026Enrolled90ConditionsHeart FailureArmsMedly
3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 6 syntheses or guidelines pooled it, 108 citations in OpenAlex.

  1. Pooled it
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  13. Developing a Patient Experience Questionnaire for the Man Van Mobile Clinical Unit.Health expectations : an international journal of public participation in health care and health policy · 2025
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  17. Proceedings of the 2024 Transplant AI Symposium.Frontiers in transplantation · 2024
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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

7 authors at 2 institutions in 1 country.

Patrick WareInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, Toronto, Toronto, ON, Canada.ORCID 0000-0002-5325-9871
Mala DoraiCentre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-1155-2383
Heather J RossTed Rogers Centre for Heart Research, University Health Network, Toronto, ON, Canada.ORCID 0000-0003-4384-3027
Joseph A CafazzoInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, Toronto, Toronto, ON, Canada.ORCID 0000-0002-3114-4440
Audrey LaporteInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, Toronto, Toronto, ON, Canada.ORCID 0000-0002-5667-9206
Chris BoodooInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, Toronto, Toronto, ON, Canada.ORCID 0000-0002-5733-7697
Emily SetoInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, Toronto, Toronto, ON, Canada.ORCID 0000-0002-8723-5915
University Health Network · CAPublic Health Ontario · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemonitoring (TM) can improve heart failure (HF) outcomes by facilitating patient self-care and clinical decision support. However, these outcomes are only possible if patients consistently adhere to taking prescribed home readings.

objectiveThe objectives of this study were to (1) quantify the degree to which patients adhered to taking prescribed home readings in the context of a mobile phone-based TM program and (2) explain longitudinal adherence rates based on the duration of program enrollment, patient characteristics, and patient perceptions of the TM program.

methodsA mixed-methods explanatory sequential design was used to meet the 2 research objectives, and all explanatory methods were guided by the unified theory of acceptance and use of technology 2 (UTAUT2). Overall adherence rates were calculated as the proportion of days patients took weight, blood pressure, heart rate, and symptom readings over the total number of days they were enrolled in the program up to 1 year. Monthly adherence rates were also calculated as the proportion of days patients took the same 4 readings over each 30-day period following program enrollment. Next, simple and multivariate regressions were performed to determine the influence of time, age, sex, and disease severity on adherence rates. Additional explanatory methods included questionnaires at 6 and 12 months probing patients on the perceived benefits and ease of use of the TM program, an analysis of reasons for patients leaving the program, and semistructured interviews conducted with a purposeful sampling of patients (n=24) with a range of adherence rates and demographics.

resultsOverall average adherence was 73.6% (SD 25.0) with average adherence rates declining over time at a rate of 1.4% per month (P<.001). The multivariate regressions found no significant effect of sex and disease severity on adherence rates. When grouping patients' ages by decade, age was a significant predictor (P=.04) whereby older patients had higher adherence rates over time. Adherence rates were further explained by patients' perceptions with regard to the themes of (1) performance expectancy (improvements in HF management and peace of mind), (2) effort expectancy (ease of use and technical issues), (3) facilitating conditions (availability of technical support and automated adherence calls), (4) social influence (support from family, friends, and trusted clinicians), and (5) habit (degree to which taking readings became automatic).

conclusionsThe decline in adherence rates over time is consistent with findings from other studies. However, this study also found adherence to be the highest and most consistent over time in older age groups and progressively lower over time for younger age groups. These findings can inform the design and implementation of TM interventions that maximize patient adherence, which will enable a more accurate evaluation of impact and optimization of resources. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.9911.

Indexed as

AgedAged, 80 and overBlood PressureBody WeightCell PhoneFemaleHeart FailureHeart RateHome Care ServicesHumansLongitudinal StudiesMaleMiddle AgedMobile ApplicationsMonitoring, PhysiologicPatient Acceptance of Health Careadherenceheart failuremHealthtelemonitoring

Identifiers

PMID30806625
PMCPMC6412156
OpenAlexW2913446730

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 Socratic graph.