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1.
Ann Epidemiol ; 24(1): 72-4, 2014 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-24252715

RESUMO

PURPOSE: This study examined data equivalency and loss to follow-up rates from Internet and interactive voice response (IVR) system surveys in a prospective-cohort study. METHODS: 475 limited-service restaurant workers participating in the 12-week study were given a choice to report their weekly slipping experience by either IVR or Internet. Demographic differences, loss to follow-up, self-reported rates of slipping, and selection of first and last choices were compared. RESULTS: Loss to follow-up rates were slightly higher for those choosing the IVR mode. Rates of slipping and selection of first and last choices were not significantly different between survey modes. Propensity to choose an Internet survey decreased with increasing age, and was the lowest among Spanish speakers (5%) and those with less than a high school education (14%). CONCLUSIONS: Studies relying solely on Internet-based data collection may lead to selective exclusion of certain populations. Findings suggest that Internet and IVR may be combined as survey modalities within longitudinal studies.


Assuntos
Acidentes por Quedas/estatística & dados numéricos , Coleta de Dados/métodos , Internet , Perda de Seguimento , Restaurantes , Telefone , Acidentes de Trabalho/estatística & dados numéricos , Adulto , Fatores Etários , Comportamento de Escolha , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Fatores Socioeconômicos , Inquéritos e Questionários
2.
J Occup Environ Hyg ; 6(10): 612-23, 2009 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-19626529

RESUMO

The purpose of this study was to provide new insight into the etiology of primarily nonfatal, work-related electrical injuries. We developed a multistage, case-selection algorithm to identify electrical-related injuries from workers' compensation claims and a customized coding taxonomy to identify pre-injury circumstances. Workers' compensation claims routinely collected over a 1-year period from a large U.S. insurance provider were used to identify electrical-related injuries using an algorithm that evaluated: coded injury cause information, nature of injury, "accident" description, and injury description narratives. Concurrently, a customized coding taxonomy for these narratives was developed to abstract the activity, source, initiating process, mechanism, vector, and voltage. Among the 586,567 reported claims during 2002, electrical-related injuries accounted for 1283 (0.22%) of nonfatal claims and 15 fatalities (1.2% of electrical). Most (72.3%) were male, average age of 36, working in services (33.4%), manufacturing (24.7%), retail trade (17.3%), and construction (7.2%). Body part(s) injured most often were the hands, fingers, or wrist (34.9%); multiple body parts/systems (25.0%); lower/upper arm; elbow; shoulder, and upper extremities (19.2%). The leading activities were conducting manual tasks (55.1%); working with machinery, appliances, or equipment; working with electrical wire; and operating powered or nonpowered hand tools. Primary injury sources were appliances and office equipment (24.4%); wires, cables/cords (18.0%); machines and other equipment (11.8%); fixtures, bulbs, and switches (10.4%); and lightning (4.3%). No vector was identified in 85% of cases. and the work process was initiated by others in less than 1% of cases. Injury narratives provide valuable information to overcome some of the limitations of precoded data, more specially for identifying additional injury cases and in supplementing traditional epidemiologic data for further understanding the etiology of work-related electrical injuries that may lead to further prevention opportunities.


Assuntos
Acidentes de Trabalho , Traumatismos por Eletricidade/etiologia , Indenização aos Trabalhadores , Acidentes de Trabalho/classificação , Acidentes de Trabalho/economia , Acidentes de Trabalho/estatística & dados numéricos , Adolescente , Adulto , Idoso , Algoritmos , Demografia , Traumatismos por Eletricidade/classificação , Traumatismos por Eletricidade/economia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Ocupações/estatística & dados numéricos , Estados Unidos/epidemiologia , Indenização aos Trabalhadores/estatística & dados numéricos , Adulto Jovem
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