Bibliographic record
Abstract
For a long time, patients were seen as weak and passive recipients of care, whose only role was to provide information and comply with doctors' orders. This is beginning to change, and patients are more seen as autonomous, active, and involved collaborators in care, co-creating value with service providers and others. In parallel, the healthcare sector is changing due to an aging population, advances in technology, medical knowhow, and the prevalence of chronic diseases, which all call for a more involved patient. During the last decade, patient involvement in healthcare has been recognized as important to provide more efficient, integrated, patient-focused healthcare. Despite this recent gain in attention, there is a gap between rhetoric's and practice, since the meaning and benefits of patient involvement are unclear both in theory and practice. This thesis takes an alternate perspective on patient involvement, departing from service theory on value creation and customer involvement. It aims to understand and explore patient involvement and how patients can be involved in both the use, and development, of healthcare services. This thesis is based on three different studies using both qualitative and quantitative research methods. The first study is a systematic literature review of healthcare research, addressing the topic of patient involvement and related concepts. Based on a total of 125 reviewed empirical articles, this study serves as an introduction and orientation to the diverse field. It aims to contribute to the knowledge base in the growing research field of patient involvement. The second study addresses and explores lead-user theory as a method to identify highly innovative patients who can be suitable for involvement in healthcare development. The third study explores how patients, depending on disease, care process and context, can take different roles in healthcare development.
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.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".