Health Hybrid Concept Analysis in Old People
Bibliographic record
Abstract
BACKGROUND: It seems necessary to study the health status of this age group to promote their health and prevent disease as well as care planning. In order to achieve this goal, a clear definition of the concept of elderly health is essential. METHOD: Hybrid concept analysis, our research design, utilizes both theoretical analysis of literature and empirical observation to define a concept. We chose the hybrid concept analysis method because its inclusion of old people perspectives enriches the limited health research literature. The method consists of three phases: theory, fieldwork, and analysis. RESULTS: In comparison, we can conclude that health in the elderly people is something more than the absence of illness and 4 physical, mental, social and spiritual domains which are referred to in the definition of a theoretical stage are supported by the findings. The relative health was also proposed against the complete welfare and comfort for the elderly and it showed that their expectations are less than their ages. In addition, the elderly have expressed the family as a preference and the researcher believes that this theme is context based because it has emerged following the interview. Since the family has a special place according to the Iranian culture and religion and the family health is a priority in their health. In addition, the daily activities have been raised as a major theme that can be considered as the physical health but the elderly have expressed it apart from the physical health. CONCLUSION: Health among the old is a concept that is affected by genetic, environmental, healthcare services and lifestyle-related factors and involves proportional physical, mental, social, familial, spiritual, and economical welfare along with the ability to handle daily life activities which is measurable through medical and functional approaches.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".