SynthesisAtencion primaria2021
[Mobile applications to improve drug adherence: Review and quality analysis].
Synthesis in Atencion primaria, 2021. 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
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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Sociodemographic and clinical predictors of adherence to antidepressants in depressive disorders: a systematic review with a meta-analysis.Frontiers in pharmacology · 2024Pooled it
- Effectiveness of interventions to improve adherence to antidepressant medication in patients with depressive disorders: a cluster randomized controlled trial.Frontiers in public health · 2024Trial
- Education and Symptom Reporting in an mHealth App for Patients With Cancer: Mixed Methods Development and Validation Study.JMIR human factors · 2025Article
- Medication beliefs and adherence during and after pregnancy among women at risk for gestational hypertensive disorders.Frontiers in drug safety and regulation · 2025Article
- Article
- Barriers and Facilitating Factors of Adherence to Antidepressant Treatments: An Exploratory Qualitative Study with Patients and Psychiatrists.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo review the mobile apps in the Spanish market to improve adherence to medications and evaluate their characteristics and quality to identify high-quality applications.
methodA review was carried out following a stepwise procedure similar to a systematic review of the scientific literature. Apple Apps Store and Google Play Store mobile application digital distribution platforms. Applications aimed at supporting self-management of treatment, which generate reminders, in Spanish, updated in the last 2 years and free. We evaluate the applications according to a set of characteristics considered desirable and the quality with the Mobile App Rating Scale tool.
resultsOut of 708 applications, 3 applications were selected. The Medisafe and Mytherapy applications had 89% and 78% of the desirable characteristics, respectively. Sergio Licea's application only had 56%. The highest global quality score was obtained by the MyTherapy application (3.79/5, IQR: 3-4), followed by Medisafe (3.72/5, (IQR: 3-4) and, finally, Sergio Licea (2.87/5, IQR: 2-4). The quality assessment coincides with the user assessment. There are many available applications, however, most did not meet the selection criteria.
conclusionsA systematic stepwise process was able to identify the quality application to be tested in a future study that will provide evidence on the use of a multicomponent intervention to improve medication adherence.
Indexed as
Identifiers
What OpenQuestion holds
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.