Inteligencia emocional, calidad de vida y alexitimia en personas mayores institucionalizadas
Bibliographic record
Abstract
At the stage of old age it is important the study of emotions and how these affect to adaptation and quality of life of older people. Some authors show up the importance of emotional intelligence and quality of life. Alexithymia refers to the difficulty to understand and identify feelings and those of others and externally oriented thinking. The aim is study the relationship between emotional intelligence, quality of life and alexithymia in a group of elderly. The participants were 25 elderly in an institutionalized center of Murcia; there were 12 men. The questionnaires were used: The brief inventory of emotional intelligence for major (EQ-I-M20), the questionnaire of qualit evaluation of life in residential context (CECAVIR) and The brief scale of alexitimia of Toronto (TAS-20). It found significant positive correlations between: the difficulty to identify feelings and the social and familiar relations; the difficulty to identify feelings and satisfaction with the life; the difficulty to describe feelings and the social and familiar relations as well as a significant negative correlation between difficulty to describe feelings and adaptability. The results will allow to advance in the implantation of activities that promote the emotional development of the elderly institutionalized persons in favor of his quality of life.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".