The experience of living with stroke: a qualitative meta-synthesis
Bibliographic record
Abstract
OBJECTIVE: The effects of stroke on stroke survivors are profound and cannot adequately be understood from a single approach or point of view. Use of qualitative study, in addition to quantitative research, provides a comprehensive picture of the consequences of stroke grounded in the experience of stroke survivors. The purpose of the present study was to examine the contribution of the published qualitative literature to our understanding of the experience of living with stroke. DESIGN: Qualitative meta-synthesis. METHOD: A literature search was conducted to identify qualitative studies focused on the experience of living with stroke. Themes and supporting interpretations from each study were compiled and reviewed independently by 2 research assistants in order to identify recurring themes and facilitate interpretation across studies. RESULTS: From 9 qualitative studies, 5 inter-related themes were identified as follows: (i) Change, Transition and Transformation, (ii) Loss, (iii) Uncertainty, (iv) Social Isolation, (v) Adaptation and Reconciliation. CONCLUSION: The present synthesis suggests the sudden, overwhelming transformation of stroke forms a background for loss, uncertainty and social isolation. However, stroke survivors may move forward through adaptation towards recovery. Meta-synthesis of qualitative research is needed to promote the inclusion of what we know about patient preferences and values in evidence-based practice.
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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 | 0.060 | 0.136 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| 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".