Application Of Measurement Methods In Public Health Contexts (E.G. Surveillance And Screening In Health Settings)

Application Of Measurement Methods In Public Health Contexts (E.G. Surveillance And Screening In Health Settings)

 

Government policy documents are beginning to suggest the use of surveillance methods such as repeat surveys over time in order to evaluate policies and success in implementing health objectives (e.g., England; Department of Health, 1999). National mental health strategies should set realistic targets for improvements in the mental health of the population ( Jenkins et al., 2002). The example of a common mental disorder for which there is a range of effective treatments deserves mention. Despite the high prevalence rates of common mental disorders, they have traditionally been underdetected and undertreated. In recent years changes in services should have improved this situation in Great Britain. A campaign by the Royal Colleges of General Practitioners and of Psychiatrists to increase awareness and the effective treatment of depression led to over half of general practitioners (GPs) taking part in teaching sessions on depression. The pharmaceutical industry successfully encouraged increased prescription of newer antidepressants. The effectiveness of such innovations may be evaluated by monitoring the mental health and treatment of representative samples of the whole population surveyed in 1993 and 2000. However, a recent examination of rates of such disorders in 1993 and 2000, during which rates of treatment increased dramatically, concluded that treatment with psychotropic medication alone is unlikely to improve the overall mental health of the population nationally (Brugha et al., 2005). Similar conclusions have emerged since from the USA (Kessler et al., 2005). Such evidence can be interpreted as pointing to the need to develop effective prevention policies for which surveillance methods would also be essential.

Policy Information And Decision Making

Little is known or understood about how policymakers use information from mental health surveys. Expectations are likely to be shaped by the nature and value of information used in physical health and evidence-based treatments and services, including prevention policies. This may be why information on the prevalence of mental disorders is often sought and provided, although the concept may have little meaning. A surprisingly large number of systematic reviews, often including the use of synthetic methods such as meta-analysis, have appeared in the psychiatric epidemiology literature in the past decade. Policymakers require guidance on the value of such reviews, given the technical difficulties faced in carrying out good-quality studies in this field.

Conclusions

Methods for measuring psychiatric and related psychological disorders and outcomes in populations have advanced considerably, particularly in the past two decades. Some long-standing assumptions have been tested, sometimes with surprising conclusions. Contemporary researchers pay particular attention to consistency and reproducibility of findings, in contrast to an earlier era in which clinical applicability often dominated the choice of the method used. Studies have become much larger and require the input of many more and different disciplines than in the past; this is probably to the good, as it may help render the topic of mental disorder more acceptable and less stigmatizing. Although the field seems new and technologically exciting, old principles are still important: simplicity and clarity of purpose, an appropriate design, the use of well-tested measures, and the interpretation of findings with a clear understanding of the limitations of the methods used. The measurement of mental disorder now stands equal in importance, in methodological rigor and usefulness, to other major public health topics. Bibliography:
  1. American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC: American Psychiatric Association.
  2. Biemer P, Groves RM, Lyberg LE, Mathiowetz NA, and Sudman S (1991) Measurement Errors in Surveys. New York: John Wiley & Sons.

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