A daily diary study of self-compassion and adaptive coping behaviours in women with symptoms of bulimia nervosa
Bibliographic record
Abstract
BACKGROUND: Mental health is more than the absence of illness and includes the ability to cope adaptively with stress. To shed light on the factors that promote mental health in people with eating disorders, this daily diary study examined whether daily and trait levels of self-compassion predict adaptive coping behaviours in women with symptoms of bulimia nervosa (BN). METHODS: Women (N = 124) who met the DSM-5 criteria for BN completed 2 weeks of nightly measures assessing their daily level of self-compassion and their daily adaptive coping behaviours, namely, their use of problem-solving strategies, seeking and receiving of instrumental social support, and seeking and receiving of emotional social support. RESULTS: Multilevel modelling revealed that on days when self-compassion levels were higher than their personal mean level or than the preceding day's level, participants reported greater use of problem-solving strategies, greater seeking and receiving of instrumental social support, and greater receiving of emotional social support. Daily levels of self-compassion, but not increased self-compassion from the preceding day, were associated with emotional support sought. Further, higher trait self-compassion, as measured by participants' mean level of self-compassion over the 2 weeks, was associated with increased seeking and receiving of instrumental and emotional social support but not with problem-solving strategies. All models controlled for participants' daily and mean eating pathology over the 2 weeks, highlighting the unique contribution of self-compassion to adaptive coping behaviours. CONCLUSIONS: Results suggest that self-compassion may help individuals with symptoms of BN cope with challenges in their daily life more adaptively, an integral component of positive mental health. The present study is among the first to suggest that the benefits of self-compassion for individuals with eating disorder symptoms may lie not only in facilitating reduced eating pathology, as evidenced by prior research, but also in promoting positive mental health. More broadly, findings underscore the potential value of interventions designed to build self-compassion in individuals with eating disorder symptoms.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".