The impact, prevalence, and association of different forms of hair loss among individuals with anxiety disorder: Systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Hair loss is a serious health concern, with individuals having to bear the associated psychological impact of the condition. Alopecia has been linked to emotional and psychological anguish in relationships, career, and personal life. OBJECTIVE: This study aimed to elucidate the intricate association, prevalence, and impact of hair loss with anxiety disorders, distinguished from other psychological impacts of alopecia. METHODS: The current review and meta-analysis were performed in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework. A comprehensive search was performed using the Cochrane, PubMed, and Google Scholar electronic databases studies published in English and conducted between January 2014 and September 2024. Statistical analysis was performed using STATA version 16.0 (StataCorp LLC), and the Newcastle-Ottawa Scale and RoB 2 tools were used for critical quality appraisal. RESULTS: A total of 24 eligible articles were included in the current study, with a cumulative of 5553 patients presenting with 1 or more forms of hair loss. Anxiety disorder was significantly prevalent among patients with alopecia event rate (ER) 0.47 (95% CI: 0.39-0.54). Anxiety severity analysis also showed a significant relationship between anxiety and hair loss, with ERs of 0.35 (95% CI: 0.10-0.60), 0.15 (95% CI: 0.01-0.29), and 0.05 (95% CI: 0.03-0.29), respectively. Statistical significance was also demonstrated by a mean HADS-A score of 7.87 (95% CI: 6.85-8.88). However, considerable heterogeneity was observed in various statistical analyses. CONCLUSION: In summary, our study showed that among people with hair loss-related diseases, alopecia was substantially linked to anxiety disorders, with the frequency of anxiety among those affected being noticeably higher.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.039 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".