Measuring Stress and Coping in Later Adulthood: Examining the Psychometric Properties of the Revised Stress Assessment Inventory for Older Adults
Bibliographic record
Abstract
BACKGROUND: Cognitive and behavioral factors contribute to the mitigation of stress-related health outcomes in later life. Given that stress management interventions for older adults are an important target for healthcare, there is a need for a relatively short and standardized assessment tool to comprehensively measure stress and coping in later adulthood while minimizing the burden on participants. The Stress Assessment Inventory (SAI), a 123-item measure designed to assess stress and coping resources in younger adults. OBJECTIVE: The objective of this study was to examine the psychometric properties of the SAI in 294 older adults. METHODS: The SAI was evaluated on its dimensionality, reliability, and validity. FINDINGS: A shortened SAI is proposed for older adults, with good internal consistency and criterion validity. The Revised SAI was found to have a three-factor model that captures Adaptive Cognitive Resources, Maladaptive Behavioral and Cognitive Habits, and Adaptive Health Habits. DISCUSSION: The current study supports the use of the Revised SAI in community-dwelling older adult populations as a comprehensive tool to assess stress and coping for use by researchers and healthcare professionals.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".