A scoping review of shame, guilt, and pride in body image: Insights from the body and appearance self-conscious emotions scale
Bibliographic record
Abstract
The Body and Appearance Self-Conscious Emotions Scale (BASES; Castonguay et al., 2014) is a measure of shame, guilt, authentic pride, and hubristic pride self-conscious emotions. The scale has been widely used, yet details about implementation, outcomes, and contributions to the literature have not been summarized. This scoping review was designed to summarize and examine research utilizing the BASES to identify trends, findings, and gaps, providing recommendations for future research. A total of 2888 documents were reviewed, comprising records identified through database searching and those citing the BASES development article, resulting in 63 studies included in the final review. Data extraction focused on research objectives, scale applications, and key findings. Most studies used the BASES to explore relationships between self-conscious emotions and disordered eating, body ideals, and physical activity. Of the reviewed studies, 46 % used the full scale and 44 % used subscales, often using the authentic pride subscale in isolation or a combination of the shame and guilt subscales. The scale was frequently used in English (67 %), Spanish (10 %), and Polish (6 %) among emerging adults (38 %), adults (32 %) and adolescents (25 %). Significant positive correlations were reported between shame and guilt (r = 0.38-0.96) and authentic and hubristic pride (r = 0.57-0.87). Shame and guilt were generally linked to maladaptive behaviours (e.g., dietary restraint), while authentic and hubristic pride were protective. Investigations of intervention strategies to reduce appearance-related shame and guilt while fostering pride are needed.
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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 | 0.019 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.037 | 0.032 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".