PubMed · 11646389
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1984-05-26. Experimenting with workers.. https://pubmed.ncbi.nlm.nih.gov/11646389/
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It is necessary to subject published research to critical scrutiny, in order to evaluate the robustness of the findings. The criteria used in evaluation require to be appropriate for the research paradigm, i.e. quantitative or qualitative. Quantitative conceptualizations of reliability and validity are unsuitable for evaluation of qualitative research as they were not devised for this purpose. The use of quantitative criteria to evaluate qualitative research may create the impression that the latter is not academically rigorous. Evaluation criteria which are specific to qualitative research require identification and application, in order to provide a formalized and rigorous approach to critical appraisal. A formalized framework for evaluation will help to ensure that the contribution of qualitative studies, with specific reference to health services research, receives optimum recognition. The work of a number of writers is used in this paper to examine the features which distinguish qualitative research and the following are discussed: the need for researcher reflexivity; the use of the 'first person' in academic work; the context in which research takes place; the selection of research participants; the interpretation of participants' accounts; the active acknowledgement of 'lay' knowledge; researcher flexibility within the research process; the generalizability of findings. It is concluded that academically rigorous criteria, which are appropriate for evaluation of qualitative research, exist and are available for use by practitioners and researchers.
The sensitivity of a neural network's output to its input perturbation is an important issue with both theoretical and practical values. In this article, we propose an approach to quantify the sensitivity of the most popular and general feedforward network: multilayer perceptron (MLP). The sensitivity measure is defined as the mathematical expectation of output deviation due to expected input deviation with respect to overall input patterns in a continuous interval. Based on the structural characteristics of the MLP, a bottom-up approach is adopted. A single neuron is considered first, and algorithms with approximately derived analytical expressions that are functions of expected input deviation are given for the computation of its sensitivity. Then another algorithm is given to compute the sensitivity of the entire MLP network. Computer simulations are used to verify the derived theoretical formulas. The agreement between theoretical and experimental results is quite good. The sensitivity measure can be used to evaluate the MLP's performance.
OBJECTIVE: To determine the sensitivity, specificity, predictive value, and accuracy of a program of pulse oximetry screening of asymptomatic newborns for critical congenital cardiovascular malformation (CCVM). METHODS: Pulse oximetry was performed on asymptomatic newborns in the well-infant nurseries of 2 hospitals. Cardiac ultrasound was performed on infants with positive screens (saturation 24 hours). Data regarding true and false positives as well as negatives were collected and analyzed. RESULTS: Oximetry was performed on 11 281 asymptomatic newborns, and 3 cases of CCVM were detected (total anomalous pulmonary venous return x2, truncus arteriosus). During the study interval, there were 9 live births of infants with CCVM from a group of 15 fetuses with CCVM detected by fetal echocardiography. Six infants with CCVM were symptomatic before screening. There was 1 false-positive screen. Two infants with negative screens were readmitted (coarctation, hypoplastic left pulmonary artery with aorto-pulmonary collaterals). Other cardiac diagnoses in the database search were nonurgent, including cases of patent foramen ovale, peripheral pulmonic stenosis, and ventricular septal defect. The prevalence of critical CCVM among all live births was 1 in 564 and among the screened population was 1 in 2256 (sensitivity: 60%; specificity: 99.95%; positive predictive value: 75%; negative predictive value: 99.98%; accuracy: 99.97%). CONCLUSIONS: This screening test is simple, noninvasive, and inexpensive and can be administered in conjunction with state-mandated screening. The false-negative screen patients had lesions not amenable to detection by oximetry. The sensitivity, specificity, and predictive value in this population are satisfactory, indicating that screening should be applied to larger populations, particularly where lower rates of fetal detection result in increased CCVM prevalence in asymptomatic newborns.