Examination of pathways by which parental attachment and secondary attachment strategies predict disordered eating attitudes and behaviours
Bibliographic record
Abstract
Research has established a connection between insecure attachment and disordered eating (O?Kearney, 1996; O?Shaughnessy & Dallos, 2009; Ward et al., 2000). Over three studies, the current research examined the relationship between attachment and disordered eating attitudes and behaviours (DEABs) in the context of control theory analysis (Kobak, Cole, Ferenz-Gillies, Fleming and Gamble, 1993). This theory was developed to help understand the relationship between internal working models and the development of attachment strategies to regulate emotion. The purpose of Study 1 was to investigate the processes by which parental attachment and the secondary attachment strategies proposed by Kobak et al. are associated with DEABs. Participants included 281 female high school and university students (M = 19.29 years). Multiple mediation models were tested using bootstrapping methods outlined by Preacher and Hayes (2008). Results suggested that the relationship between both anxious (hyperactivated) and avoidant (deactivated) attachment strategies and DEABs were significantly mediated by Negative Affect, self-esteem, and Perfectionistic Self-Promotion. As Avoidant and Anxious Attachment were highly correlated, a composite variable, Overall Insecure Attachment was created. The relationship between Overall Insecure Attachment and DEABs was similarly mediated. Multiple regression analyses revealed that feelings of alienation from both mothers and fathers significantly predicted Avoidant, Anxious, and Overall Insecure Attachment. Results suggested that the development of DEABs may not be associated with one type of secondary attachment strategy, but rather insecure attachment in general. Further, parental attachment relationships predicted insecure attachment strategies.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".