Evidence map›Paper›PMID 42238161›Full record

ReviewCureus2026

AI-Enabled or Digitally Augmented Adherence Systems for Chronic Care: Smart Pillboxes and Personalized Medication Reminders.

Raja Waqas, Kiranjot Kaur, Haleema Sadia, Onyia Nnaemeka Chidobu

Abstract readReview
In one paragraph

Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Raja WaqasRegulatory Sciences and Health Safety, Arizona State University, Tempe, USA.
Kiranjot KaurMedicine, United States Navy, United States Military, North Chicago, USA.
Haleema SadiaSurgery, Allama Iqbal Medical College, Multan, PAK.
Onyia Nnaemeka ChidobuGeneral Medicine, NES Healthcare, Norwich, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This systematic review included seven studies (randomized controlled trials and observational studies) evaluating AI-enabled and digitally augmented medication adherence interventions in chronic disease populations. A structured search was conducted across PubMed, Embase, Scopus, and Cochrane Library up to February 2026. Due to heterogeneity in interventions and outcome measures, a narrative synthesis was performed. Across studies, adherence improvements were reported in several interventions, although findings were inconsistent, and one large randomized trial showed no significant benefit. Evidence for clinical and system-level outcomes was limited and variably reported. These findings suggest potential benefits of digitally supported adherence interventions, but conclusions are constrained by small sample sizes, heterogeneity, and moderate-to-high risk of bias.

Indexed as

artificial intelligencechronic diseasedigital healthmedication adherencepatient safetyquality improvementsmart pillbox

Identifiers

PMID42238161
PMCPMC13229088

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.