ArticleBMC health services research2020
Scoping review and bibliometric analysis of Big Data applications for Medication adherence: an explorative methodological study to enhance consistency in literature.
Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Mobile-Health based physical activities co-production policies towards cardiovascular diseases prevention: findings from a mixed-method systematic review.BMC health services research · 2022Pooled it
- Contexts and Mechanisms Related to the Efficacy of Digital Medication Adherence Interventions to Support Medication Adherence Among Adults With Chronic Diseases: Realist Review.Interactive journal of medical research · 2026Review
- Understanding Responsible Development in AI-Based Clinical Prediction Models for Mortality: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- Integration of artificial intelligence in orthodontic imaging: A bibliometric analysis of research trends and applications.Imaging science in dentistry · 2025Review
- Emerging trends and hot spots on electrical impedance tomography extrapulmonary applications.Heliyon · 2022Article
- Emerging Trends and Hot Spots of Electrical Impedance Tomography Applications in Clinical Lung Monitoring.Frontiers in medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMedication adherence has been studied in different settings, with different approaches, and applying different methodologies. Nevertheless, our knowledge and efficacy are quite limited in terms of measuring and evaluating all the variables and components that affect the management of medication adherence regimes as a complex phenomenon. The study aim is mapping the state-of-the-art of medication adherence measurement and assessment methods applied in chronic conditions. Specifically, we are interested in what methods and assessment procedures are currently used to tackle medication adherence. We explore whether Big Data techniques are adopted to improve decision-making procedures regarding patients' adherence, and the possible role of digital technologies in supporting interventions for improving patient adherence and avoiding waste or harm.
methodsA scoping literature review and bibliometric analysis were used. Arksey and O'Malley's framework was adopted to scope the review process, and a bibliometric analysis was applied to observe the evolution of the scientific literature and identify specific characteristics of the related knowledge domain.
resultsA total of 533 articles were retrieved from the Scopus academic database and selected for the bibliometric analysis. Sixty-one studies were identified and included in the final analysis. The Morisky medication adherence scale (36%) was the most frequently adopted baseline measurement tool, and cardiovascular/hypertension disease, the most investigated illness (38%). Heterogeneous findings emerged from the types of study design and the statistical methodologies used to assess and compare the results.
conclusionsOur findings reveal a lack of Big Data applications currently deployed to address or measure medication adherence in chronic conditions. Our study proposes a general framework to select the methods, measurements and the corpus of variables in which the treatment regime can be analyzed.
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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.