USER ENGAGEMENT IN HEALTHCARE LIVING LABS: A SCOPING REVIEW
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
User engagement in innovation processes is crucial for the development of sustainable healthcare. One promising user-centred approach used to integrate users’ experiential knowledge in the development of innovations is the Living Lab (LL). However, we lack a systematic understanding of the processes, methods and factors that lead to more effective user engagement. The objective of this scoping review is to map and systematically present current research on user engagement in Healthcare Living Labs (HLLs) to enhance understanding and inspire future research. Our review shows that the level of user engagement is still low given the limited use of methods tailored to support it and that HLL are predominantly used in technology and clinical innovation. We offer a clearer depiction and description of the methods innovation managers could use to foster greater user engagement in HLL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it