Examining the effect of future time perspective on goal adjustment in long distance runners: The mediating role of grit
Bibliographic record
Abstract
Pursuit of personal goals is an adaptive aspect of self-regulation in physical activity. The way in which individuals perceive their future has implications for goal-striving, such that goals may optimize long- or short-term pleasures as per tenets of socioemotional selectivity theory (SST). Individuals with an expansive time perspective are likely to pursue goals while those with limited time perspective are likely to disengage from unattainable goals. Currently, examination of goal adjustment within tenets of SST in athletes is limited. Moreover, exploring factors that contribute to relationship between time perspective and goal adjustment is needed. Grit may mediate this relationship as it is a personality trait that involves pursuit of long-term goals despite failure. Long-distance runners (N = 126; 75% female; Mage = 38 + 11 years) completed self-report measures assessing future time perspective (FTP; Carstensen & Lang, 1996), grit (Duckworth & Quinn, 2009), and goal adjustment (Wrosch et al., 2013). Correlations were significant (p < .05) for FTP and grit (r = .41), and grit and goal disengagement (r = -.27). Mediation models, controlling for age, were estimated separately for goal disengagement and reengagement. Grit mediated relationship between FTP and goal disengagement (point estimate = -0.32, BCa CI= -0.76 to -0.02). In this sample, expansive FTP is not associated with pursuit of long-term goals, which is inconsistent with SST; however, further research is warranted to determine the generalizability of this finding. Further, runners with higher grit may not disengage in goal pursuits, which may affect maladaptive self-regulation processes when goals become unattainable.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".