Sintomas musculoesqueléticos em eletricistas de rede de distribuição de energia Musculoskeletal symptoms among energy distribution network linemen
Bibliographic record
Abstract
CONTEXTUALIZAÇÃO: A presença de sintomas musculoesqueléticos em eletricistas deve ser caracterizada para auxiliar na identificação de fatores de riscos para os distúrbios osteomusculares relacionados ao trabalho (DORT) e para possibilitar implementação de medidas preventivas. OBJETIVO: Avaliar a ocorrência de sintomas de DORT em eletricistas de uma regional de uma empresa de distribuição de energia elétrica, verificar se existiam diferenças entre as funções exercidas quanto à proporção de trabalhadores sintomáticos, e realizar um levantamento preliminar dos principais fatores de riscos presentes. MÉTODOS: Foram avaliados 30 eletricistas do sexo masculino (38,1±5,5 anos), divididos em três equipes conforme a função exercida (ELV=Eletricistas Linha Viva; EEM=Eletricistas Emergência/Manutenção; EC=Eletricistas Comerciais). Sintomas musculoesqueléticos foram identificados em mapa corporal, qualificados pelo Questionário McGill e quantificados por escala numérica. O questionário DASH também foi aplicado para avaliar impacto dos sintomas nos ombros na performance dos trabalhadores. RESULTADOS: 70% dos eletricistas apresentaram ao menos um sintoma musculoesquelético nos ombros, coluna ou joelhos. A equipe ELV apresentou sintomas musculoesqueléticos em 100% dos trabalhadores e maior pontuação no questionário DASH (28±15). A equipe EEM apresentou sintomas em 67% dos trabalhadores e pontuação DASH de 8±11, e a equipe EC apresentou sintomas em 50%, mas sem sintomas nos ombros. A proporção de trabalhadores sintomáticos nos ombros estava associada à função exercida (p=0.02). CONCLUSÕES: Eletricistas avaliados apresentaram alta proporção de trabalhadores sintomáticos, que variou conforme a atividade ocupacional. Intervenções são necessárias para reduzir os riscos de DORT dentre os eletricistas avaliados. BACKGROUND: Linemen should be evaluated regarding the presence of musculoskeletal symptoms to guide the identification of risk factors for development of work-related musculoskeletal disorders (WMSD) and to allow the implementation of preventive measures. OBJECTIVE: To assess the occurrence of WMSD symptoms among linemen working at a regional branch of an electricity distribution company, to investigate whether there were differences in the proportions of symptomatic workers among the functions performed, and to perform a preliminary survey of the main risk factors present. METHODS: Thirty male linemen (mean age 38.1±5.5 years) were evaluated, divided into three teams according to their job function (Live Line Linemen, LLL; Maintenance/Emergency Linemen, MEL; Commercial Linemen, CL). Musculoskeletal symptoms were identified on a body map, qualified using the McGill questionnaire and quantified using a numerical scale. The DASH questionnaire was also applied to evaluate the impact of the shoulder symptoms on the workers' performance. RESULTS: Seventy percent of the linemen presented at least one musculoskeletal symptom in the shoulders, back or knees. All of the LLL team presented musculoskeletal symptoms and these workers had the highest scores in the DASH questionnaire (28±15). Sixty-seven percent of the MEL team presented symptoms, and their DASH score was 8±11. Fifty percent of the CL team presented symptoms, but none of them had shoulder symptoms. The proportion of workers with shoulder symptoms was related to their job function (p=0.02). CONCLUSIONS: A high proportion of the linemen presented symptoms which varied according to the occupational activity. Interventions are needed to reduce the risk of WMSD among the linemen evaluated.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".