Cognitive adaptation and mental health: A motivational analysis
Bibliographic record
Abstract
Abstract The present study tested a motivational model where the beneficial impact that processes of cognitive adaptation have on mental health takes place through self‐determined motivation. The model proposes that the components of cognitive adaptation theory (positive self‐perceptions, perceptions of control, and optimism) foster a self‐determined motivation. In turn, self‐determined motivation predicts positive indices of mental health. In addition, the model posits that the beneficial role of cognitive adaptation on mental health is mediated by motivational processes. The model was tested using a 1‐year prospective design with a random sample from the general population. Results from structural equation modelling analysis provided empirical support for the proposed model. Results are discussed with regards to Taylor's ( 1983 ) cognitive adaptation theory, self‐determination theory (Deci & Ryan, 1991 ), and the Hierarchical Model of Intrinsic and Extrinsic Motivation (Vallerand, 1997 ). Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".