Development and evaluation of online medication support tools for older people: a systematic review
Bibliographic record
Abstract
BACKGROUND: Success of online medication support tools is contingent on how well they are designed and address the needs of users, especially older people. OBJECTIVE: To characterise existing online medication support tools for older people and describe their development and evaluation. METHODS: This systematic review was undertaken following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Five electronic databases (MEDLINE, EMBASE, CINAHL, Scopus and Web of Science) were searched from inception to October 2024 for studies describing the development and/or evaluation of online medication support tools for older people aged ≥65 years, or their informal caregivers. The mixed-methods appraisal tool was used for quality assessment. Extracted data were analysed descriptively. RESULTS: A total of 1621 studies were identified, and 29 studies met the inclusion criteria. Over 80% (n = 21) of the tools were mobile health apps or websites. The most common development approach involved user-centred design methodologies (comprising user needs assessments, focus groups, interviews and user experience workshops). Usability testing using questionnaires and surveys (n = 13 tools) were the most common evaluation techniques followed by think-aloud protocol (n = 9 tools), interviews and focus groups (n = 9 tools). Findings across 22 studies suggest that user satisfaction of the developed online tools was high. The remaining seven studies did not measure usability of the final prototype or explicitly report on usability. CONCLUSION: Findings reveal heterogeneity in the methods used to develop and evaluate online tools for older people. Overall, all methodologies were feasible and led to the development of tools that demonstrated good to excellent levels of usability. PROTOCOL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42024483579. https://www.crd.york.ac.uk/PROSPERO/view/CRD42024483579.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".