Impact of eating disorders on paid or unpaid work participation and performance: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Eating disorders (EDs), including binge eating disorders (BEDs), bulimia nervosa (BN) and anorexia nervosa (AN), can inflict adverse effects on well-being, daily functioning, and workplace performance, presenting significant occupational, social, and economic challenges. This systematic review seeks to explore the relationship between ED symptomatologies and their impacts on work performance. METHODS: This systematic review adhered to The Preferred Reporting Items for Systematic Reviews and Meta-analyses. Formal methods of critical appraisal for both qualitative and quantitative studies were utilized. Six studies were included. RESULTS: Participants across all studies (n = 20,367) exhibited heightened levels of presenteeism, absenteeism, work productivity impairment, and higher annual burden costs compared to their non-ED counterparts. CONCLUSION: Impaired decision-making, cognitive inflexibility, and poor executive functioning significantly impact work participation and performance, underscoring the need for workplace policies that reduce stigma and stress, and calls for further research into how environmental factors and interventions affect ED recovery. LEVEL OF EVIDENCE: Level I, systematic review.
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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".