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Record W2918549767 · doi:10.1097/der.0000000000000450

Occupation-Related Symptoms in Hairdressers

2019· article· en· W2918549767 on OpenAlexvenueno aff
Linda Piapan, Jacopo Baldo, Francesca Larese Filon

Bibliographic record

VenueDermatitis · 2019
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIrritationDermatologyRespiratory systemSkin irritationDry skinPopulationBurning SensationSurgeryEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: During work, hairdressers are exposed to several hazardous agents that can cause skin and respiratory symptoms. Because few data are available for long-term follow-up, and none are from Italy, the aim of our study was to investigate occupational symptoms in hairdressers after a 10-year follow-up. METHODS: Work-related skin and respiratory symptoms were investigated in 2006 and 2016 by means of a standardized questionnaire and medical examination. RESULTS: Eighty-two workers completed the 10-year follow-up with a response rate of 86.3%. At follow-up, skin- and respiratory work-related symptoms had increased significantly, involving 40.7% of workers. Skin symptoms increased to 12.5%, throat irritation to 15.6%, and cough to 12.5%. The occurrence of the symptom of skin irritation was significantly related to dryness of the skin at the baseline. CONCLUSIONS: Our long-term follow-up on hairdressers demonstrated an increase in work-related irritant skin and upper respiratory symptoms that involved more than one-third of the population studied. More efforts are needed in prevention activities to promote better ventilation of workplaces, use of less irritating and less sensitizing hair products, and use of moisturizers to prevent dry skin.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.006
GPT teacher head0.247
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2019
Admission routes1
Has abstractyes

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