Integration of a smart multidose blister package for medication intake: A mixed method ethnographic informed study of older adults with chronic diseases
Bibliographic record
Abstract
Smart adherence products are marketed to assist with medication management. However, little is known about their in-home integration by older adults. It is necessary to investigate the facilitators and barriers older adults face when integrating these products into their medication taking routines before effectiveness can be examined. The aim of this study was to (a) examine the integration of a smart multidose blister package and (b) understand medication intake behaviour of adults with chronic diseases using an integrated theoretical model comprised of the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and Capacity, Opportunity, Motivation and Behaviour (COM-B) Model. An ethnographic-informed study was conducted with older adults using the smart multidose blister package to manage their medications for eight weeks. Data was collected quantitatively and qualitatively using in-home observations, photo-elicitation, field notes, semi-structured interviews, system usability scale (SUS) and net promoter scale (NPS). The interview guide was developed with constructs from the TAM, TPB and COM-B Model. Data were analyzed using the Qualitative Analysis Guide of Leuven (QUAGOL) framework to generate themes and sub-themes which were mapped back to TAM, TBP and COM-B Model. Ten older adults with an average age of 76 years, of which 80% were female, participated in the study. On average, participants reported five medical conditions, while the average number of medications was 11.1. The mean SUS was 75.50 and overall NPS score was 0. Qualitative analysis identified three themes; (1) factors influencing medication intake behaviour (2) facilitators to the product use and, (3) barriers to the product use. The smart blister package was found to be easy to use and acceptable by older adults. Clinicians should assess an older adult's medication intake behavior as well as barriers and facilitators to product use prior to recommending an adherence product for managing medications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".