Health-related quality of life after stroke: what are we measuring?
Bibliographic record
Abstract
As there is no single, accepted definition of health-related quality of life (HRQOL), it is assumed to be a broad, multidimensional construct referring to those aspects of people's lives that reasonably relate to their health. Although many scales are used to assess HRQOL, the operationalization of this construct within each tool is unclear. To clarify what each tool is measuring, this study reviewed eight scales commonly used to evaluate HRQOL after stroke. Two reviewers classified scale items from five generic and three stroke-specific scales within an established framework with nine dimensions; physical functioning, symptoms, global judgments of health, psychological well-being, social well-being, cognitive functioning, role activities, personal constructs, and satisfaction with care. All scales reviewed provide multidimensional assessment, but vary in number and combination of dimensions. All include assessment of physical functioning and most incorporate concepts, such as psychological well-being, social well-being, and role activities. One generic (Sickness Impact Profile) and two stroke-specific scales (Stroke Impact Scale and Stroke-Specific Quality of Life Scale) seemed most comprehensive. Evaluated against a common framework of dimensions, scales commonly used in the assessment of HRQOL after stroke provide varying multidimensional assessments of aspects of life function related to health. Whether any of these assessments are sufficient to describe HRQOL in its entirety is unclear.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".