Factors that influence heart failure self-management of community dwelling individuals
Bibliographic record
Abstract
Heart failure (HF) affects 350,000 Canadians, and is the third most common primary diagnosis for a hospitalization in Canada. People with HF experience periods of stability interspersed with exacerbations requiring hospitalization. During the fiscal year 2000-01, 85,679 patients were admitted to hospitals in Canada accruing a cost of over $1 billion per year for inpatient hospital services alone. These statistics indicate that in addition to the considerable influence on the lives of many Canadians, the burden of the problem is significant on the current and future health care system. This thesis examines factors that influence HF self-management as well as the profile characteristics of community dwelling individuals. The results of a systematic review and findings of a study that combines a mixed method approach including a quantitative secondary analysis, and a set of qualitative telephone interviews are presented. The qualitative data focuses on one factor, perception of social support, and how it relates to HF self-management. Finally, an integration of the information is presented. (Abstract shortened by UMI.)
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".