Frequency of Heel Pain and Its Association with Quality of Life Among Hair Dressers in Lahore
Bibliographic record
Abstract
Background: Heel pain is a common occupational musculoskeletal complaint among workers who spend prolonged periods standing, including hairdressers, and may negatively affect physical functioning, psychological wellbeing, work performance, and overall quality of life. Objective: To determine the frequency of heel pain and assess its association with quality of life among hairdressers in Lahore. Methods: This cross-sectional observational study included 279 male and female hairdressers aged 18–35 years who had been practicing professionally for at least two years and worked 7–8 hours per day. Participants were recruited from salons in Lahore using convenience sampling. Heel pain intensity was assessed using the Numeric Pain Rating Scale and categorized as no pain, mild pain, moderate pain, or severe pain. Quality of life was assessed using domain-based questionnaire responses covering general health, physical health, psychological health, social relationships, and environmental health. Data were analyzed using descriptive statistics and tests of association, with statistical significance set at p < 0.05. Results: Most participants were male (61.6%). Heel pain was reported by 65 participants (23.3%), while 214 participants (76.7%) reported no pain. Mild pain was present in 21 participants (7.5%), moderate pain in 33 participants (11.8%), and severe pain in 11 participants (3.9%). Heel pain intensity showed a statistically significant association with poorer quality-of-life outcomes across general, physical, psychological, social, and environmental domains (p < 0.001). Conclusion: Heel pain affected nearly one-fourth of hairdressers and was significantly associated with reduced quality of life, particularly in physical and psychological domains. Early screening, ergonomic education, supportive footwear, rest breaks, and preventive workplace strategies may help reduce heel pain burden and improve wellbeing among hairdressers
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".