Depressive symptoms and goal pursuit: Between‐person and reciprocal within‐person effects in a multi‐wave longitudinal study
Bibliographic record
Abstract
INTRODUCTION: Depressive symptoms, goal progress, and goal characteristics are interrelated, but the directionality of these relationships is unclear. METHODS: In a 6-wave longitudinal study (N = 431; 2002 total surveys), we examine the bidirectionality of the relationships between depressive symptoms, goal characteristics (commitment, self-efficacy, and perception of other's support), and goal progress for academic and interpersonal goals at 2-week intervals. Separate random-intercept cross-lagged panel models were tested for each goal characteristic across both goals. RESULTS: At the within-person level, goal progress significantly positively predicted commitment, self-efficacy, and perception of others' support for the goal. Most of the other hypothesized paths were nonsignificant, including paths between depressive symptoms and progress. At the between-person level, all variables were significantly correlated, with some effects significantly larger for the interpersonal than the academic goal. DISCUSSION: The results suggest that when it comes to depressive symptoms and goal pursuit, general tendencies may be more important than variations over 2-week intervals.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".