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The evaluation of performance in scientific research at any level - whether at the individual, institutional, research council or country level - is not easy. Traditionally, research evaluation at the individual and institutional levels has depended largely on peer opinion, but with the rapid growth of science over the last century and the availability of databases and scientometric techniques, quantitative indicators have gained importance. Both peer review and metrics are subject to flaws, more so in India because of the way they are used. Government agencies, funding bodies and academic and research institutions in India suffer from the impact factor and h-index syndrome. The uninformed use of indicators such as average and cumulative impact factors and the arbitrary criteria stipulated by agencies such as the University Grants Commission, Indian Council of Medical Research and the Medical Council of India for selection and promotion of faculty have made it difficult to distinguish good science from the bad and the indifferent. The exaggerated importance given by these agencies to the number of publications, irrespective of what they report, has led to an ethical crisis in scholarly communication and the reward system in science. These agencies seem to be unconcerned about the proliferation of predatory journals and conferences. After giving examples of the bizarre use of indicators and arbitrary recruitment and evaluation practices in India, we summarise the merits of peer review and quantitative indicators and the evaluation practices followed elsewhere.

Against the backdrop of comments on chemistry research in

Aim Knowledge, belief, attitude and values shape the health behaviour and all these can help in deciding whether to behave in one way or the other. Therefore, the underlying relationship between knowledge, attitude and practice (KAP) regarding causation, prevention and treatment of filarial disease is studied separately for affected and normal individuals. Methods KAP aspects of the disease were measured using a structured questionnaire and methods were designed to quantify all the variables for which data were collected. A salient feature of the method is the judicious assignment of scores to individual items and summing the scores across items for appropriate standardization. Results Multiple regression analyses indicate that the knowledge on disease treatment, mode of transmission, prevention and income explain about 29% of variation that occurs in knowledge on mosquito breeding and control. Standard of living, knowledge on disease transmission and knowledge on mosquito breeding and control explain 23% of variation in practice measures against mosquito biting. Knowledge gained on disease treatment, prevention, diagnosis and knowledge on mosquito breeding and control is greatly improving the prevention practices against mosquito breeding and control.Interpretation The results reveal that through imparting health education on disease prevention, diagnosis and treatment, awareness about mosquito breeding and control can be achieved.

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