Perfectionism, Self-Image Goals and Compassionate Goals in Health and Mental Health: A Longitudinal Analysis
Bibliographic record
Abstract
This research focuses on ego-focused self-image goals as central to understanding the vulnerability inherent in perfectionism and the link that perfectionism has with poorer health and emotional well-being. The present study expands theory and research on perfectionism from a unique motivational perspective through a longitudinal investigation of perfectionism, the pursuit of self-image goals related to self-improvement, and mental and physical health among 187 university students. Our central finding was that trait and self-presentational perfectionism were associated longitudinally with self-image goals and poorer mental and physical health. Longitudinal analyses showed that perfectionistic self-presentation predicted subsequent self-image goals, controlling for initial self-image goals. Additionally, self-image goals were associated with worse mental and physical health and greater loneliness and social anxiety. Collectively, our results illustrate the benefits of assessing problematic personal goals in perfectionism and the need to revise existing motivational accounts by recognizing the important role ego-involved goals play in guiding much of what perfectionists do and how they act in their daily lives.
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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 | 0.003 | 0.005 |
| 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) | 0.001 | 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".