Future Time Perspective and Gratitude in Daily Life: A Micro–Longitudinal Study
Bibliographic record
Abstract
Preliminary cross–sectional evidence suggests that future time perspective (FTP) is associated with dispositional gratitude, but research on daily perceptions of FTP and their relations to daily gratitude is lacking. In this study, we addressed this gap by examining how FTP and gratitude jointly unfold in daily life and how these relations vary within and across individuals. A micro–longitudinal design ( N = 331, adults aged 18–77) with daily assessments over two workweeks was employed to examine the relations between gratitude and two components of FTP (remaining opportunities and time). Three important results from random intercepts cross–lagged panel models stand out. First, we found evidence for within–person day–to–day carry–over effects in FTP and gratitude. Second, FTP and gratitude were systematically related within and across individuals. Third, age and dispositional forms of FTP and gratitude predicted between–person differences in FTP and gratitude in daily life. Finally, exploratory multilevel analyses have shown that the associations between daily FTP and gratitude vary across ages at the between–person level but not at the within–person level. Overall, these findings advance our understanding of perceptions of FTP in daily life and their associations with gratitude in adulthood. © 2019 European Association of Personality Psychology
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".