Coping Strategies and Social Participation in Older Adults
Bibliographic record
Abstract
BACKGROUND: Social participation refers to daily activities, such as personal care and mobility, and social roles, such as interpersonal relationships and leisure. Although restrictions in participation in normal aging have been recognized, little research has been done to study the coping strategies used to alleviate those restrictions. OBJECTIVE: The objective of the present study was to explore the relationships between cognitive and behavioural coping strategies and the social participation of community-dwelling older adults. METHODS: The Assessment of Life Habits (LIFE-H) and the Inventory of Coping Strategies Used by the Elderly (ICSUE) were used to document social participation and coping strategies of 350 randomly recruited older adults living at home independently. Sociodemographic and health-related characteristics were also assessed. Regression analyses were performed to evaluate the relationship between social participation, coping strategies and the other variables. RESULTS: Behavioural coping strategies were the most important factor associated with daily activities, social roles and total participation, followed by the type of living environment and age. These variables explained 33% (p=0.04), 13% (p=0.02), and 28% (p=0.00) of the variance of the models, respectively. The absence of any relationship between the cognitive coping strategies and social participation was a striking result. CONCLUSION: Our study suggests expanding current geriatric approaches to integrate knowledge on useful, safe and appropriate behavioural changes and to help older people acquire such strategies when they are lacking.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".