Social support differentially moderates the impact of neuroticism and extraversion on mental wellbeing among community-dwelling older adults
Bibliographic record
Abstract
BACKGROUND: Personality affects psychological wellbeing, and social support networks may mediate this effect. This may be particularly pertinent in later life, when social structures change significantly, and can lead to a decline in psychological wellbeing. AIM: To examine, in an older population, whether the relationships between neuroticism and extraversion and mental wellbeing are moderated by available social support networks. METHOD: We gathered information from 536 community-dwelling older adults, regarding personality, social support networks, depressive symptomatology, anxiety and perceived stress, as well as controlling for age and gender. RESULTS: Neuroticism and extraversion interacted with social support networks to determine psychological wellbeing (depression, stress and anxiety). High scores on the social support networks measure appear to be protective against the deleterious effects of high scores on the neuroticism scale on psychological wellbeing. Meanwhile, individuals high in extraversion appear to require large social support networks in order to maintain psychological wellbeing. CONCLUSION: Large familial and friendship social support networks are associated with good psychological wellbeing. To optimise psychological wellbeing in older adults, improving social support networks may be differentially effective for different personality types.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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 teacher head, 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".