Content Analysis of the Construction of Self and Others in Women with Bulimia Nervosa
Bibliographic record
Abstract
The purpose of this study is to explore the content of personal constructs in people diagnosed with bulimia nervosa (BN). We expect to find differences in the predominant content of the construct systems between women with and without BN. We analyzed the constructs elicited using the repertory grid technique from 120 women aged between 18 and 45 years, divided into two groups: a clinical group of women diagnosed with bulimia (n = 62) and a control group of university students without disorder (n = 58). The constructs were categorized using the Classification System for Personal Constructs (CSPC), composed of six thematic which are broken down into 45 categories. For this study, a new area called "Physical" is included, and it consists of three categories. The results indicated that women diagnosed with bulimia used significantly more constructs related to the body, while the control group used more constructs from the personal area. In addition, the congruent constructs from the clinical sample were predominantly moral, or related to values and interests, while discrepant constructs were personal and physical. The findings provide evidence for the clinical use of the CSPC as an instrument for exploring the content of personal meaning systems. Understanding the patient’s constructions about herself, others, in her own way of construing is useful for treatment. Moreover, it is important for clinicians to explore the content of constructs related to symptomatic areas, that could be hindering change, and focus on them to facilitate improvement.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".