Interactive effects of perfectionism on competitive golf performance: A multi-level analysis
Bibliographic record
Abstract
Perfectionism is a multidimensional personality characteristic comprised of two higher-order factors termed perfectionistic strivings (PS) and perfectionistic concerns (PC). Research has typically found perfectionistic strivings to be related to better sport performance, while concerns are usually unrelated. However, many of the tests of this relationship use non-athletes, contrived tasks, and one-off performances, and have also focused on the separate, rather than interactive, effects of PS and PC. The present study was designed to address these limitations by testing the interactive effect of indicators of PS and PC in predicting performance across two rounds of competitive golf. Eighty-nine male golf athletes ( M age = 28.42 years, SD = 11.87) completed measures of perfectionism and then competed in a regional golf competition. Their cumulative score, relative to par, across two rounds determined their performance. Hierarchical linear modelling, nesting performances within individuals, holes, and rounds, showed a significant three-way interaction between self-oriented performance perfectionism (indicator of PS), socially prescribed performance perfectionism (indicator of PC), and round ( b = 0.36, SE = 0.17, p = .039). At low levels of socially prescribed performance perfectionism, self-oriented performance perfectionism predicted improved performance; however, at high levels of socially prescribed performance perfectionism, self-oriented performance perfectionism predicted poorer performance. Findings highlight the importance of assessing the relationship between perfectionism and sport performance in real-world competitive contexts over time, while accounting for the interplay between indicators of PS and PC. • Perfectionism significantly predicted performance in competitive golf. • Perfectionism dimensions interact with time to differentially influence performance. • Socially prescribed performance perfectionism undermines golf performance. • Findings differ as a function of the instrument used to measure perfectionism.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".