Validity of trauma reporting in the agricultural community

Gerberich, Susan Goodwin; Gibson, R.W.; Gunderson, P.W.; Melton, L. Joseph; French, Richard H.; Renier, Colleen M.; Erdman, Art; True, Jack; Carr, Peter W.; Elkington, Jane

doi:10.1016/0376-6349(90)90102-2

Cited by 13 publications

(14 citation statements)

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“…The second method, which we call adj-1, adjusts for misclassiÿcation but using a constant sensitivity = 0:689 and (incorrectly) a constant speciÿcity = 0:983. The third method, called adj-2, adjusts for misclassiÿcation using a constant sensitivity = 0:689 and individualspeciÿc speciÿcity estimated from (2). Hence, only the adj-2 method is based on the correct modeling assumptions, whereas the other two are not (though all three methods use possibly misclassiÿed outcome Y i ).…”

Section: Methods To Be Comparedmentioning

confidence: 99%

“…The sensitivity and speciÿcity of the classiÿcation of farm-related injury status based on telephone interviews in RRIS-II were estimated from the OATS [2,3]. Table II shows the result if we treat both the sensitivity and speciÿcity as constant.…”

Section: Validation Study: Oatsmentioning

confidence: 99%

“…The validation study [2] was actually a sub-study of the OATS [3], which included all farms in Olmsted County, Minnesota identiÿed in the U.S.DA NASS master sampling frame. Data were collected using telephone interviews.…”

Section: Validation Study: Oatsmentioning

confidence: 99%

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Does it always help to adjust for misclassification of a binary outcome in logistic regression?

et al. 2005

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It is well known that in logistic regression, where the outcome is measured with error, a biased estimate of the association between the outcome and a risk factor may result if no proper adjustment is made. Hence, it seems tempting to always adjust for possible misclassification of the outcome. Here we show that it is not always beneficial to do so because, though the adjustment reduces the bias, it also inflates the variance, leading to a possibly larger mean squared error of the estimate. In the context of a data set on agricultural injuries, numerical evidence is provided through simulation studies.

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Section: Methods To Be Comparedmentioning

confidence: 99%

Section: Validation Study: Oatsmentioning

confidence: 99%

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Does it always help to adjust for misclassification of a binary outcome in logistic regression?

et al. 2005

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“…In this report, a farming operation-related intentional or unintentional injury was defined as an acute physiologic trauma that resulted in a loss of consciousness or restriction from regular activities for 4 or more hours and/or required health care. While it has been documented that within short time periods following an injury, the accuracy of reporting injuries is very high [Gerberich et al, 1990;Braun et al, 1994], there is a potential for serious underreporting of intentional injuries. Without comprehensive definitions and relevant examples of injuries being provided, there is a high probability of underreporting of other types of injuries as well, especially if long recall periods are used.…”

Section: Some Types Of Injuries May Be Severely Underreportedmentioning

confidence: 98%

Alternative approaches to analytical designs in occupational injury epidemiology

et al. 1997

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In this paper, we discuss the theoretical framework upon which observational studies of occupational injuries are based. Following a general description of how causal effects are estimated, the challenges faced by researchers working in this area are outlined, with an emphasis on case‐control studies. These challenges include defining the at‐risk period for workers whose tasks change over time and whose hazard period may be very brief, evaluating the underreporting of both exposures and injuries, and considering the effects of multiple injuries per individual on study design and data analysis. We review both the theoretical and practical considerations in the design and conduct of traditional case‐control studies, based on the collection of individual level data, as well as other approaches, such as using information culled from administrative and descriptive databases, and case‐control studies in which the plant or work site is the unit of analysis. The case‐crossover design is also reviewed and its utility for reducing confounding due to differences between individuals by self‐matching is highlighted. While this design has not yet been applied to the work setting, its potential for increasing our understanding of the causes of acute‐onset occupational injuries seems promising. Finally, a variety of hybrid designs are discussed, including combinations of case‐control, case‐crossover, and cohort designs. Am. J. Ind. Med. 32:129–141, 1997. © 1997 Wiley‐Liss Inc.

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“…To address this potential bias, along with further measurement and selection issues, multiple measures were taken. Based on prior validation efforts (Braun, Gerberich, & Sidney, 1994;Gerberich et al, 1990), injury data were collected for six-month windows to limit information bias. Additionally, behavior-related items were measured in reference to the months prior to the injury events for cases, or randomly selected months for controls.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Children's behavioral traits and risk of injury: Analyses from a case-control study of agricultural households

Carlson

Gerberich

Alexander

et al. 2009

Journal of Safety Research

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a b s t r a c t a r t i c l e i n f oProblem: Children on family agricultural operations have high risk of injury. The association between children's behavioral traits and their risk of injury is not well understood. Method: Data from the Regional Rural Injury Study-II were used to assess behavioral risk factors for injury to children ages six to b 20 years. A total of 379 injury events (cases) and 1,562 randomly selected controls were identified. Adjusted odds ratios (OR) and 95% confidence intervals (CI), calculated using logistic regression, were used to estimate injury risk in reference to behavioral traits. Results: Injury risks were greater for children with high levels of depressive symptoms (OR = 1.9, CI = 1.0-3.7) and aggression (OR = 1.6, CI = 0.9-2.7), and low levels of careful/cautious behavior (OR = 1.8, CI = 1.1-2.9). Children with low levels of self-regulation had reduced risks (OR = 0.4, CI = 0.2-0.8). Discussion: Results suggest that children's behaviors affect their risk of agricultural injury. Additional research could elucidate mechanisms and inform interventions. Impact on industry: The development of multifaceted, sustainable approaches for prevention is necessary for this unique population. These findings suggest a need for interventions that incorporate specific behavior-related risk factors in the context of family farms and ranches. National

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Validity of trauma reporting in the agricultural community

Cited by 13 publications

References 0 publications

Does it always help to adjust for misclassification of a binary outcome in logistic regression?

Does it always help to adjust for misclassification of a binary outcome in logistic regression?

Alternative approaches to analytical designs in occupational injury epidemiology

Children's behavioral traits and risk of injury: Analyses from a case-control study of agricultural households

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