Evidence map›Paper›PMID 41401443›Full record

ArticleJMIR mHealth and uHealth2025

Exploring the Fit Between the Outputs of Freely Available Medication Adherence Apps and Users' Needs: Mixed Methods Study.

Kirstin Messner, Vanessa Sutter, Samuel Allemann, Isabelle Arnet

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Article in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Kirstin MessnerDepartment Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0009-0003-8146-1553
Vanessa SutterDepartment Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0009-0001-6256-3381
Samuel AllemannDepartment Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0003-4067-9401
Isabelle ArnetDepartment Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0001-7591-4104

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedication nonadherence is a significant barrier to therapy success. Smartphone apps represent reasonable tools for simple adherence-enhancing interventions. Many adherence apps are available in app stores with diverse content, quality, and outputs. We define "output of an adherence app" as the processing and visualization of data recorded by the user and related to adherence. In 2016, Santo et al defined 5 desirable features in the output of adherence apps: tracking history, charts, statistics, rewards, and an exportable file. With this, a reference point to evaluate outputs of adherence apps was delivered. Identifying and fulfilling users' needs are essential when developing an adherence app for patients' self-management and professional adherence services, such as therapy support provided by health care professionals (HCPs).

objectiveWe aimed to investigate the smartphone app market regarding desirable features in the outputs, explore the users' needs, and evaluate the concordance.

methodsWe searched for smartphone adherence apps in the 2 largest commercial app repositories by using keywords. Search results were screened for eligibility by applying inclusion and exclusion criteria. Eligible, freely available apps were tested regarding desirable features in their output. We conducted 2 focus groups and a cross-sectional online survey to explore users' needs. Survey participants rated their desire for features on a 7-point Likert scale. Focus groups were analyzed using the previously reported framework method. Descriptive statistics were calculated by median and IQR or mean and SD. We compared survey subgroups with a 2-tailed t test. A P value <.05 was considered statistically significant.

resultsWe screened 80 apps for eligibility and included 9 in our analyses. All desirable features were present, with tracking history being the most frequent feature (in 8/9 apps). Other desirable features were observed in 3 or fewer of the apps. Eight individuals participated in the 2 focus groups. During the focus groups, a total of 13 categories of desired features emerged. All 5 desirable features were rated as important in adherence apps. Three additional features were mentioned: (1) professional feedback regarding therapy or intake course, (2) additional recommendations based on intake course, and (3) option to discuss the data with an HCP. A total of 42 individuals participated in the online survey. Tracking history was the most desired (mean rating of 5.29) and rewards the least desired feature (mean rating of 2.81) in the output. There was ambivalence regarding professional feedback, statistics, and charts. Participants with or without regular medication use showed no significant differences.

conclusionsThe outputs delivered by freely available smartphone adherence apps only partly match users' needs. Users showed a special interest in the interpretation of their data with an HCP. Therefore, adherence apps cannot substitute for the HCP but can be used to enhance current patient care.

Indexed as

Medication AdherenceMobile ApplicationsNeeds AssessmentAdultCross-Sectional StudiesFemaleFocus GroupsHumansMaleMiddle AgedQualitative ResearchSurveys and Questionnairesdesirable featuresimplementationmedication adherencemHealthneeds assessmentoutputsusers’ perspective

Identifiers

PMID41401443
PMCPMC12754584

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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.