Strategies to improve the quality of life of persons post-stroke: protocol of a systematic review
Bibliographic record
Abstract
BACKGROUND: While many outcomes post-stroke (e.g., depression) have been previously investigated, there is no complete data on the impact of a variety of quality improvement strategies on the quality of life and physical and psychological well-being of individuals post-stroke. The current paper outlines a systematic review protocol on the impact of quality improvement strategies on quality of life as well as physical and psychological well-being of individuals with stroke. METHODS: MEDLINE, CINAHL, EMBASE, and PsycINFO databases will be searched. Two independent reviewers will conduct all levels of screening, data abstraction, and quality appraisal. Only randomized controlled trials that report on the impact of quality improvement strategies on quality of life outcomes in people with stroke will be included. The secondary outcomes will be physical and psychological well-being. Quality improvement strategies include audit and feedback, case management, team changes, electronic patient registries, clinician education, clinical reminders, facilitated relay of clinical information to clinicians, patient education, (promotion of) self-management, patient reminder systems, and continuous quality improvement. Studies published since 2000 will be included to increase the relevancy of findings. Results will be grouped according to the target group of the varying quality improvement strategies (i.e., health system, health care professionals, or patients) and/or by any other noteworthy grouping variables, such as etiology of stroke or by sex. DISCUSSION: This systematic review will identify those quality improvement strategies aimed at the health system, health care professionals, and patients that impact the quality of life of individuals with stroke. Improving awareness and utilization of such strategies may enhance uptake of stroke best practices and reduce inappropriate health care utilization costs. SYSTEMATIC REVIEW REGISTRATION: PROSPERO, CRD42017064141.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.027 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".