The power of feeling seen: perspectives of individuals with eating disorders on receiving validation
Bibliographic record
Abstract
BACKGROUND: A common complaint of individuals suffering from mental health conditions is feeling invalidated or misunderstood by care providers. This is notable, given that non-collaborative care has been linked to poor engagement, low motivation and treatment non-adherence. This study examined how receiving validation from care providers is experienced by individuals who have an eating disorder (ED) and the impact of receiving validation on the recovery journey. METHODS: Eighteen individuals who had an eating disorder for an average duration of 19.1 years (two identifying as male, 16 identifying as female), participated in semi-structured interviews on barriers and facilitators to self-compassion. Seven were fully recovered, and 11 were currently participating in recovery-focused residential treatment. Thematic analysis focused on the meaning and impact of receiving validation to participants. RESULTS: Five care provider actions were identified: (i) making time and space for me, (ii) offering a compassionate perspective, (iii) understanding and recognizing my treatment needs, (iv) showing me I can do this, and (v) walking the runway. These were associated with four key experiences (feeling trust, cared for, empowered, and inspired), that participants described as supportive of their recovery. CONCLUSIONS: This research provides insight into patient perspectives of validation and strategies care providers can use, such as compassionate reframing of difficult life experiences, matching interventions to patient readiness, and modeling vulnerability.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| 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".