ASSOCIATIONS BETWEEN SENSE OF PURPOSE, NEGATIVE AFFECT, AND CORTISOL: EVIDENCE FROM REPEATED DAILY ASSESSMENTS
Bibliographic record
Abstract
Abstract A growing literature suggests that having a sense of purpose in life is key to supporting optimal aging outcomes. One proposed mechanism for such benefits posits that having strong sense of purpose facilitates better management of and less reactivity to daily negative experiences, which over time may impact health. However, there remains a paucity of research investigating sense of purpose, affective experiences, and biological stress markers as individuals engage in their daily life routines. The present study sought to examine everyday associations between sense of purpose in life, negative affect, and salivary cortisol using repeated daily life assessments. A sample of 170 older adults aged 60 to 87 (M =71.18 years, SD=6.06) completed affect ratings and provided concurrent salivary cortisol samples 4 times per day over 7 consecutive days. Multilevel growth modeling was used to examine whether trait sense of purpose in life moderated within-day associations between negative affect and log-transformed cortisol levels (nmol/L), adjusting for relevant demographic information and factors that may impact cortisol (e.g., time since waking, caffeine intake). Analyses revealed that sense of purpose was indeed associated with lower daily negative affect, but it did not predict everyday cortisol and was also not moderating the within-person couplings between everyday negative affect and cortisol. Our results suggest that purpose in life shapes daily affect dynamics of older adults, yet not through modulating the physiological implications of negative affect. Follow-up analyses will explore whether these findings generalize to vulnerable groups of very old adults and those in poor health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".