Self–Compassion is Best Measured as a Global Construct and is Overlapping with but Distinct from Neuroticism: A Response to Pfattheicher, Geiger, Hartung, Weiss, and Schindler (2017)
Why this work is in the frame
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Bibliographic record
Abstract
Pfattheicher and colleagues recently published an article entitled ‘Old Wine in New Bottles? The Case of Self–compassion and Neuroticism’ that argues the negative items of the Self–compassion Scale (SCS), which represent reduced uncompassionate self–responding, are redundant with neuroticism (especially its depression and anxiety facets) and do not evidence incremental validity in predicting life satisfaction. Using potentially problematic methods to examine the factor structure of the SCS (higher–order confirmatory factor analysis), they suggest a total self–compassion score should not be used and negative items should be dropped. In Study 1, we present a reanalysis of their data using what we argue are more theoretically appropriate methods (bifactor exploratory structural equation modelling) that support use of a global self–compassion factor (explaining 94% of item variance) over separate factors representing compassionate and reduced uncompassionate self–responding. While self–compassion evidenced a large correlation with neuroticism and depression and a small correlation with anxiety, it explained meaningful incremental validity in life satisfaction compared with neuroticism, depression, and anxiety. Findings were replicated in Study 2, which examined emotion regulation. Study 3 established the incremental validity of negative items with multiple well–being outcomes. We conclude that although self–compassion overlaps with neuroticism, the two constructs are distinct. © 2018 European Association of Personality Psychology
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it