The impact of the COVID-19 pandemic on children and adolescents eating disorders: A systematic review
Bibliographic record
Abstract
• The COVID-19 pandemic had a negative impact on eating disorders. • Several factors were associated with children and adolescent’s eating disorders. • Factors included gender, age, sporting activities, and economic and social support. • Targeted measures need to be in place for future public health crisis. During the COVID-19 pandemic an increased prevalence of eating disorders was seen globally. For vulnerable groups, in particular children and adolescents, public health measures including lockdowns, limited in-person healthcare access, increased focus on handwashing and sanitization, and the increased fear related to the COVID-19 pandemic had a profound negative impact on this population. Despite the increased vulnerability of these children and adolescents to eating disorders during the pandemic and the trend observed, there has been limited research in this area. Hence, this systematic review aims to identify the impact of COVID-19 on eating disorders among children and adolescents globally. Using PRISMA guidelines, a systematic search of 8 databases was conducted. We identified 4428 results, of which 250 studies were selected for full-text review. Of these, 42 studies were synthesized for our final analysis. We found that the majority of studies (83%) reported that the COVID-19 pandemic and related public health measures had a negative impact on eating disorders among youth and adolescents. We also found several individual, household and socio-structural factors associated with the worsening of eating disorders. Specifically, 17% of studies found that pandemic-origin fears and stress increased eating disorder-related outcomes. Twelve percent of studies reported parental influence to be associated with eating disorders during the COVID-19 pandemic and 14% of studies linked the loss of health services to an increase in eating disorders. In addition, age, gender, social support, co-morbidities or pre-existing symptoms and media were significantly associated with children and adolescent’s eating disorders. Various factors stemming from the COVID-19 pandemic were found to have increased the prevalence of eating disorders in children and adolescents. Based on these findings, we suggest several policy implications and future areas of research.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".