Assessing enablement in clinical practice: a systematic review of available instruments
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Enablement is an intervention by which the health care provider recognizes, promotes and enhances patients' ability to control their health and life. An abundant health literature suggests that enablement is associated with good outcomes. In this review, we aimed at identifying and comparing instruments that assess enablement in the health care context. METHOD: We conducted a systematic literature review using Medline, Embase, Cochrane, Cinahl and PsycINFO databases, 1980 through March 2009, with specific search strategy for each database. Citations were included if they reported: (1) development and/or validation of an instrument; (2) evaluation of enablement in a health care context; and (3) quantitative results following administration of the instrument. The quality of each main retained citation was assessed using a modified version of the Standards for Reporting of Diagnostic Accuracy. RESULTS: Of 3135 citations identified, 53 were retrieved for detailed evaluation. Four articles were included. Two instruments were found: the Patient Empowerment Scale (PES) and the Empowering Speech Practices Scale (ESPS). Both instruments assessed enablement in hospital setting, one from the inpatient's perspective (PES) and the other from both perspectives (ESPS). CONCLUSION: Two instruments assess enablement in hospital setting. No instrument is currently available to assess enablement in an ambulatory care context.
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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 | 0.042 | 0.157 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.021 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".