Endorsement of Avoidant/Restrictive Eating Motivations Across Restrictive Eating Disorders: A Trait‐ and State‐Level Examination
Bibliographic record
Abstract
OBJECTIVE: Research on avoidant/restrictive food intake disorder (ARFID) and anorexia nervosa (AN) has emphasised differences between these disorders, but similarities maintaining dietary restriction may be overlooked. ARFID-related eating disturbances may also occur and facilitate egosyntonic restriction in AN. METHOD: Using the Nine Item ARFID Screen (NIAS; N = 141) and ecological momentary assessment (N = 76), we examined endorsement of ARFID-related and traditional eating disorder (ED) reasons for restrictive eating in women with ARFID, AN-restrictive subtype (AN-R), AN binge eating/purging subtype (AN-BP), and controls. RESULTS: Clinical groups scored higher on NIAS subscales than controls. ARFID participants scored higher on NIAS-Picky than AN groups, and higher on NIAS-Fears and NIAS-Appetite than AN-BP, while AN-R did not differ from either. For skipped meals, ARFID and AN-R did not differ on ratings of avoidant/restrictive motivations, while AN-BP did not differ from either on fears of aversive consequences. For restriction at meal/snack, ARFID did not differ from AN-R on endorsement of picky eating nor AN-BP on lack of interest but endorsed stronger fears of aversive consequences. CONCLUSIONS: While sensory sensitivity/picky eating appears unique to primarily-restrictive EDs, lack of interest was common across clinical groups. Results highlight differences and potential transdiagnostic treatment targets.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".