Patients’ Experiences of Using Smartphone Apps to Support Self-Management and Improve Medication Adherence in Hypertension: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Worldwide, hypertension control rates remain suboptimal despite clinically effective antihypertensive drug therapy. Patient failure to take medication as prescribed (ie, nonadherence) is the most important factor contributing to poor control. Smartphone apps can facilitate the delivery of evidence-based behavior change techniques to improve adherence and may provide a scalable, usable, and feasible method to deliver self-management support. OBJECTIVE: The aim of this study is to explore patients' experiences of the usability and feasibility of smartphone apps to support self-management and improve medication adherence in hypertension. METHODS: A qualitative descriptive study was conducted. A total of 11 people living with hypertension from the West of Ireland were sampled purposively and interviewed about their experience of using a self-management app for a 4-week period, which included two key functionalities: self-monitoring of blood pressure (BP) and medication reminders. Thematic analysis was carried out on the semistructured interview data. RESULTS: Participants' age ranged from 43 to 74 years (mean 62 years, SD 9.13). Three themes were identified: digital empowerment of self-management, human versus digital systems, and digital sustainability. Although patients' experience of using the technology to self-monitor BP was one of empowerment, characterized by an enhanced insight and understanding into their condition, control, and personal responsibility, the reminder function was only feasible for patients who reported unintentional nonadherence to treatment. Patients experienced the app as a sustainable tool to support self-management and found it easy to use, including those with limited technological competence. CONCLUSIONS: The study's findings provide new insights into the experience of using apps to support medication adherence in hypertension. Overall, the data support apps as a usable and feasible method to aid self-management of hypertension and highlight the need for personalized functionality, particularly with regard to medication adherence reminder strategies. The study's findings challenge the perspective that the use of these technologies to support self-management can inevitably add to the burden of treatment experienced by patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".