What can be expected of information and communication technologies in terms of patient empowerment in health?
Bibliographic record
Abstract
PURPOSE: Implementing information and communication technologies (ICT) is often mentioned as a strategy that can foster public involvement and responsibility in health. The purpose of this paper is to provide a better understanding of the possibilities and issues afforded by the social uses of ICT for personal empowerment in health. DESIGN/METHODOLOGY/APPROACH: The paper discusses evidence from four case studies that characterize current computerization and networking processes in health. The studies shared a global framework comprising four interpretative paradigms of personal empowerment: the professional, technocratic, consumerist and democratic paradigms. FINDINGS: The results show the coexistence of four empowerment logics in ICT use. Two trends proved dominant: a strengthening of the control and standardization processes tied to the typical power relationships in health, and a reinforcement of personal autonomy and self-assertion processes, either through commercial relationships or through the social relationships that are also present. PRACTICAL IMPLICATIONS: The paper supports the argument that in order to understand the opportunities for personal empowerment offered by ICT the logic underlying user practices in their respective contexts must be examined. ORIGINALITY/VALUE: The paper uses data from four case studies to illustrate the contradictory logics shaping the personal empowerment process. Under these logics, an ICT user may play roles as patient, client, consumer, or citizen.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.012 | 0.025 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".