Caring for a child with an eating disorder: Understanding differences among mothers and fathers of adolescent and adult children
Bibliographic record
Abstract
OBJECTIVE: This study investigated treatment-engagement fears, self-efficacy, and accommodating and enabling in mothers and fathers of adolescent and adult children with eating disorders. METHODS: This study involved a secondary analysis of pre-treatment data from a subsample of 143 parents (95 mothers; 48 fathers) from a Canada-wide multi-site study. Parents completed the Caregiver Traps Scale, Parents Versus Anorexia Scale, and the Accommodation and Enabling Scale for Eating Disorders. Data were analysed using factorial Multivariate Analysis of Variance and mediation via multiple regression. RESULTS: Mothers reported higher levels of treatment-engagement fears than fathers. Among mothers, higher fear predicted lower self-efficacy and more accommodating and enabling behaviours. Among fathers, neither fear nor self-efficacy predicted accommodating and enabling. No differences in treatment-engagement fear or self-efficacy between parents of adolescent child and adult children were found at pre-treatment. CONCLUSIONS: Mothers' and fathers' experience different levels of fear related to their involvement in their ill-child's treatment at pre-treatment, and that fear is uniquely related to variables that impact treatment outcomes. There is a need to support parents even when their child is an adult. This study can inform family-based treatments vis-a-vis tailoring interventions for mothers and fathers and providing support to parents of children with eating disorders across the lifespan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".