Evidence map›Paper›PMID 33978593›Full record

ArticleJMIR research protocols2021

Improving Medication Adherence Through Adaptive Digital Interventions (iMedA) in Patients With Hypertension: Protocol for an Interrupted Time Series Study.

Kobra Etminani, Carina Göransson, Alexander Galozy, Margaretha Norell Pejner, Sławomir Nowaczyk

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% 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.

NCT04413500 naunknown statusnot on this map

iMedA: Improving MEDication Adherence Through Person Centered Care and Adaptive Interventions

TypeinterventionalSponsorHalmstad UniversityRan2020 to 2021Enrolled32ConditionsHypertensionArmsReminder, Educational message, Motivational messages, showing trends
NCT05555095 recruitingnot on this mapstarted 2022, after this paper: background citation

The Medicaid Innovation Collaborative (MIC) Experience: Transforming Care Through Digital Health: A Mixed Methods Analysis

TypeobservationalSponsorOSF Healthcare SystemRan2022 to 2028Enrolled19,331ConditionsHypertension, Diabetes Mellitus, Maternal HealthArmsdigital health delivered multicomponent intervention
3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  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

5 authors at 1 institution in 1 country.

Kobra EtminaniCenter for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden.ORCID https://orcid.org/0000-0003-2006-6229
Carina GöranssonCenter for Research on Welfare, Health and Sport, Halmstad University, Halmstad, Sweden.ORCID https://orcid.org/0000-0001-6215-2032
Alexander GalozyCenter for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden.ORCID https://orcid.org/0000-0002-7453-9186
Margaretha Norell PejnerCenter for Research on Welfare, Health and Sport, Halmstad University, Halmstad, Sweden.ORCID https://orcid.org/0000-0002-1174-2523
Sławomir NowaczykCenter for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden.ORCID https://orcid.org/0000-0002-7796-5201
Halmstad University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a strong need to improve medication adherence (MA) for individuals with hypertension in order to reduce long-term hospitalization costs. We believe this can be achieved through an artificial intelligence agent that helps the patient in understanding key individual adherence risk factors and designing an appropriate intervention plan. The incidence of hypertension in Sweden is estimated at approximately 27%. Although blood pressure control has increased in Sweden, barely half of the treated patients achieved adequate blood pressure levels. It is a major risk factor for coronary heart disease and stroke as well as heart failure. MA is a key factor for good clinical outcomes in persons with hypertension.

objectiveThe overall aim of this study is to design, develop, test, and evaluate an adaptive digital intervention called iMedA, delivered via a mobile app to improve MA, self-care management, and blood pressure control for persons with hypertension.

methodsThe study design is an interrupted time series. We will collect data on a daily basis, 14 days before, during 6 months of delivering digital interventions through the mobile app, and 14 days after. The effect will be analyzed using segmented regression analysis. The participants will be recruited in Region Halland, Sweden. The design of the digital interventions follows the just-in-time adaptive intervention framework. The primary (distal) outcome is MA, and the secondary outcome is blood pressure. The design of the digital intervention is developed based on a needs assessment process including a systematic review, focus group interviews, and a pilot study, before conducting the longitudinal interrupted time series study.

resultsThe focus groups of persons with hypertension have been conducted to perform the needs assessment in a Swedish context. The design and development of digital interventions are in progress, and the interventions are planned to be ready in November 2020. Then, the 2-week pilot study for usability evaluation will start, and the interrupted time series study, which we plan to start in February 2021, will follow it.

conclusionsWe hypothesize that iMedA will improve medication adherence and self-care management. This study could illustrate how self-care management tools can be an additional (digital) treatment support to a clinical one without increasing burden on health care staff.

trial registrationClinicalTrials.gov NCT04413500; https://clinicaltrials.gov/ct2/show/NCT04413500. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24494.

Indexed as

artificial intelligencedigital interventionhypertensionmedication adherencemHealth

Identifiers

PMID33978593
PMCPMC8156113
OpenAlexW3138107713

What OpenQuestion 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 OpenQuestion graph.