Qualidade de Vida, Esperança, Autocompaixão e Otimismo em Pessoas de Idade Avançada que Frequentam a Academia Sénior
Bibliographic record
Abstract
Esta investigação teve como objetivo perceber a relação entre a qualidade de vida, o otimismo, a esperança e autocompaixão em pessoas seniores que frequentam as atividades da Universidade Sénior / Academia Sénior em meio rural e em meio urbano. A amostra foi composta por 89 pessoas (72 mulheres e 17 homens), com idades compreendidas entre os 65 e os 89 anos (M = 72,81; DP = 6,26). Os instrumentos de avaliação que utilizados foram: o Questionário Sociodemográfico, o Montreal Cognitive Assessment (MoCA), o World Health Organization Quality Of Life instrument (WHOQOL-Bref), o Self Compassion Scale (SELFCS), a Escala de Esperança e a Escala de Otimismo. Os resultados evidenciam que a amostra é maioritariamente do sexo feminino e tem escolaridade acima da média nacional para a mesma faixa etária. A qualidade de vida mostrou-se maior nas pessoas de idade avançada que frequentam a Academia sénior em meio rural. A qualidade de vida e o otimismo observaram-se maiores naqueles que auferem rendimentos superiores à média nacional nesta faixa etária. O estudo concluiu que existe uma relação positiva entre as variáveis qualidade de vida, otimismo, esperança e autocompaixão. / This investigation was aimed to understand the relationship between quality of life, optimism, hope and self-compassion in elder people who attend Senior Academy activities, both in rural and urban areas. The sample consisted of 89 people (72 women and 17 men), aged between 65 and 89 years old (M = 72,81; DP = 6,26). The psychometric instruments used were: the Sociodemographic Questionnaire, the Montreal Cognitive Assessment (MoCA), the World Health Organization Quality Of Life instrument (WHOQOL-Bref), the Self-Compassion Scale (SELFCS), the Scale Of Hope and the Scale of Optimism. The results showed the sample is mostly female and has above average education for the same age group. The quality of life was shown to be higher in elderly people who attend the Senior Academy in rural areas. The quality of life and optimism presented higher levels on those with higher income, above the average portuguese population at that age group. The study concluded that there is a positive relationship between the variables quality of life, optimism, hope and self-compassion.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".