The role of mindfulness and autonomous motivation for goal progress and goal adjustment: an intervention study
Bibliographic record
Abstract
Abstract Previous correlational studies showed the importance of mindfulness and autonomous goal motivation for goal pursuit, goal setting, and goal disengagement processes. The present study examined the role of mindfulness in goal regulation processes for self-selected personal goals in a randomized waitlist control group design. Participants (N = 228,M = 30.7 years, 18–78 years; 84% female) either received daily 9-12-minute audio mindfulness exercises online for four weeks or were placed on a waitlist. Participants in the intervention group (N = 113) reported more goal progress compared with the control group (N = 116) at the end of the intervention. Autonomous goal motivation for already set goals did not influence change in goal progress. However, autonomous goal motivation for newly set goals was higher in the intervention group than in the control group. Additionally, we tested the role of mindfulness in interaction with goal attainability and autonomous motivation for goal adjustment processes (in this case, reduction of goal importance). In the control group, lower goal attainability at baseline was associated with a greater reduction in goal importance for less autonomous goals. For more autonomous goals, change in goal importance was independent from baseline attainability. In contrast, in the intervention group, all goals were slightly devalued over time independently from autonomous motivation and goal attainability at T1. Moreover, changes in goal attainability were positively linked to changes in goal importance over time. This effect was moderated by mindfulness and autonomous motivation. Overall, the findings point to the relevance of mindfulness and autonomous motivation for goal regulation processes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".