Defining Empowerment and Supporting Engagement Using Patient Views From the Citizen Health Information Portal: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The increasing presence of technology in health care has created new opportunities for patient engagement and with this, an intensified exploration of patient empowerment within the digital health context. While the use of technology, such as patient portals, has been positively received, a clear linkage between digital health solutions, patient empowerment, and health outcomes remains elusive. OBJECTIVE: The primary objective of this research was to explore the views of participants enrolled in an electronic health record portal access trial regarding the resultant influence of this technology on their feelings of patient empowerment. METHODS: The exploration of patient empowerment within a digital health context was done with participants in a tethered patient portal trial using interpretive description. Interpretive description is a qualitative methodology developed to pragmatically address clinical health questions. Patient demographics, self-reported health status, and self-identified technology adaptation contributed to the assessment of empowerment in this qualitative approach. RESULTS: This research produced a view of patient empowerment within the digital health context summarized in two overarching categories: (1) Being Heard and (2) Moving Forward. In each of these, two subcategories further delineate the aspects of empowerment, as viewed by these participants: Knowing More and Seeing What They See under Being Heard, and Owning Future Steps and Promoting Future Care under Moving Forward. This work also highlighted an ongoing interconnectedness between the concepts of patient empowerment, engagement, and activation and the need to further articulate the unique aspects of each of these. CONCLUSIONS: The results of this study contribute needed patient voice to the ongoing evolution of the concept of patient empowerment. In order to move toward more concrete and accurate measure of patient empowerment and engagement in digital health, there must be further consideration of what patients themselves identify as essential aspects of these complex concepts. This research has revealed relational and informational elements as two key areas of focus in the ongoing evolution of patient empowerment operationalization and measure.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".