The Loss of Autonomy in Eating Disorder Treatment: A Patient Perspective
Bibliographic record
Abstract
INTRODUCTION: In this text, the author's lived experiences as a youth with anorexia nervosa, anxiety, and depression are explored. Experiences with accessing North American health services, both in specialized eating disorder (ED) and disordered eating (DE) settings, as well as in healthcare more broadly are shared. AIM: This work seeks to shed light on a patient perspective in mental health and to draw attention to some of the ways that the current framings of EDs and DE within the biomedical system might perpetuate harm. METHODS: In this piece, a collection of the author's lived-experiences and interactions with the healthcare system are explored. FINDINGS: The medical framing of EDs as a defect of both mind and body can jeopardize one's autonomy and contribute to a sense of hopelessness. As mental health treatment increasingly prioritizes evidence-based approaches and standardized practices, there is a growing concern that this shift risks undermining the autonomy of those it aims to support. The dualistic conceptualizations of mental and physical health in ED/DE treatment, at times, can cause harm, particularly for those who do not present with the physical manifestations of an ED/DE but remain largely affected in day-to-day life. DISCUSSION: The imposition of rigid treatment regimens can inadvertently diminish personal agency, overshadowing the nuanced, individualized needs and preferences of patients. Lived experience narratives encompass the personal, subjective insights of individuals navigating mental health challenges, in turn, providing invaluable insight that conventional methods may overlook.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".