Increasing stress resilience in older adults through a 6-week prevention program: effects on coping strategies, anxiety symptoms, and cortisol levels
Bibliographic record
Abstract
Introduction As people age, chronic stress, resulting in prolonged or repeated activation of the hypothalamic–pituitary–adrenal (HPA) axis, has been associated with long-term adverse health outcomes. Coping strategies and social support have been recognized as contributing to resilience to stress in older adults. Few studies have evaluated stress management training (SMT) interventions based on psychoneuroendocrinology that were designed to be delivered to healthy older adults in community settings. Methods In this study, a total of 170 older adults (mean age = 76.07, SD = 7.67) participated in a cluster-randomized trial designed to compare the delivery of an SMT intervention with a waitlist condition. Results The effect of SMT on coping strategies, stress, anxiety, and depression was measured 3 weeks and 3 months after the intervention. In addition, we tested the effect on basal cortisol secretion over 2 days from saliva samples upon awakening and the total diurnal cortisol output [area under the curve with respect to ground (AUCg)]. Results from repeated measures analyses of variance showed that participants who received the intervention demonstrated a significant increase in problem-solving coping strategies and a decrease in anxiety scores 3 weeks after the intervention compared to the waitlist group. STM participants also demonstrated lower cortisol levels on the AUCg index. At the 3-month follow-up, gains were maintained only on the AUCg index. Discussion This type of brief preventive program could reduce basal cortisol levels in older adults, which may be an important protective factor against health outcomes associated with chronic HPA activation. Our results provide sufficient evidence to warrant further research to improve the effectiveness of O’stress in different settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".