Epidemiology Applied to Mental Health

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Table of Contents

Introduction
Summary I
Evaluation I
Summary II
Evaluation II
Conclusion – Synthesis of the two papers
References

Introduction

Chen et al (2005) in their paper titled “Prevalence and co-occurrence of psychiatric symptom clusters in the U.S, adolescent population using DISC predictive scales” have estimated the 12-month prevalence and co-occurrence of symptoms of specific mental problems among US adolescents (12–17 years) by age, sex and racial/ethnic subgroups and have concluded that mental health problems among U.S. youth may be far more common than previously believed, although these symptoms have not yet reached the point of clinical impairment. Heller et al (2006) in their study titled “Helping to prioritize interventions for depression and schizophrenia: use of Population Impact Measures” aim to demonstrate how population impact measures may be used to prioritize alternative treatments for psychiatry. Population impact measures refer to the estimation and prioritization of potential benefits of interventions in specific populations. Heller et al (2006) have studied the implementation of best practice recommendations for preventing depression and schizophrenic and conclude that population impact measures can be the key to deciding which intervention works best in a given population. The two studies taken together complement each other.

Summary I

Though adolescents are found to suffer from several kinds of mental disorders, there is very little information regarding the actual prevalence of various psychiatric disorders among adolescents in the general population. Many studies have been conducted in this context such as those of Turner and Gil (2002) and Costello et al. (2003) National surveys also provide some epidemiological information but they have a lot of limitations such as small samples, or samples from clinics or institutions; overly specific research foci; and screening questions either limited in number or not closely aligned with DSM diagnostic criteria. Hence there is no adequately reliable information regarding what are the mental problems that adolescents face and to what extent. Moreover, there is no information regarding ethnic group specificity of mental health needs that would be needed to design subpopulation specific mental health interventions. To overcome such limitations and estimate the prevalence of mental disorders in the general U.S. adolescent population, Chen et al (2005) have found that the best way will be to include in national surveys of the general population structured diagnostic interviews or selected screening items or scales of symptoms of psychiatric problems that have high predictive value for diagnosis. Though this may not lead to actual diagnosis of disorder, it can help to identify those people at high risk and also help in identifying differential patterns in important demographic groups, including age, gender and race/ethnicity. Chen et al (2005) have estimated the prevalence and co-occurrence of specific mental disorders among US adolescents (12-17) years of age, sex and racial/ethnic sub groups. For this estimation the researchers have used data from the 2000 National Household Survey of Drug Abuse (NHSDA) along with the DISC predictive scales. Multiple logistic regressions were applied to study and find the prevalence and co-occurrence of psychiatric problems in adolescents taking into consideration demographics and environmental factors. Chen et al (2005) conclude that mental health problems among U.S. adolescents may be far more common than it is believed to be though these symptoms may not have been serious enough to call for medical attention.

Evaluation I

Kevin W. Chen, Ley A. Killeya-Jones and William A. Vega are professors at the Department of Psychiatry, University of Medicine and Dentistry of New Jersey – Robert Wood Johnson Medical School in New Jersey USA. Ley A. Killeya- Jones is also associated with the Center for Child and Family Policy, Duke University, Durham, North Carolina. The article is very detailed and includes literature review on the subject. The references used are from peer reviewed journals, and publications from the National Institute of Drug Abuse. Hence they are all authentic sources. The artilce has been published in the journal, “Clinical Practice and Epidemiology in Mental Health” 2005. The authors have discussed national surveys such as the Epidemiological Catchment Area Study the National Comorbidity Survey and the National Comorbidity Survey-Replication. The DISC-2.3 is well explained as a highly structured diagnostic instrument used to screen six categories of the most common mental disorders among children and adolescents. The study makes use of the DISC Predictive Scale. The authors make use of tables to analyze the data in the NHSDA, make comparisons and portray visually the prevalence and co-occurrence of psychiatric symptom clusters based on DPS among U.S. adolescents by gender, race/ethnicity and age over a period of twelve months. The conclusions may be easily deduced from the table. The discussion of the results is conducted from various angles and different possible interpretations are discussed. The paper also includes discussion of its limitations and clinical implications making it very valuable for practitioners of psychiatry.

Summary II

There are many kinds of treatment options in psychiatry and the problem lies in deciding which one to prioritize for development and implementation. Number Needed to Treat (NNT) and Quality Adjusted Life Year (QALY) – are some of the measures used so far to make the decision on prioritizing. But the authors Heller et al have developed a new set of Population Impact Measures to describe the population impact of risks and benefits. PIMs are easy to computer and are relevant to the problem of prioritizing psychiatric interventions. For describing the population impact of an intervention, the Number of Events Prevented in a Population (NEPP) is used. It describes the impact of treatment or other interventions and is defined as “the number of events prevented by the intervention in your population over a defined time period”. The NEPP is an extension of the Number Needed to Treat (NNT), and takes into account the extent to which the condition occurs in the population and the proportion of those with the condition who are actually exposed to the intervention. The measure helps policy-makers to identify and prioritize the potential benefits of interventions on their own population. Heller et al derives NEPP for interventions used in two important psychiatric conditions – schizophrenia and depression. They have concluded that there is a great potential for NEPP to help prioritize psychiatric interventions to maximum benefit.

Evaluation II

The researchers, Richard F. Heller, Islay Gemmel and Lesley Patterson are all professors in the School of Epidemiology and Health Sciences, The Medical School, The University of Manchester, UK and this article has been published in the journal “Clinical Practice and Epidemiology in Mental Health”, 2006. Hence the article is peer-reviewed and authentic. The authors have structured this article well and have explained the concept of Population Impact Measures well. They clearly show the advantage of NEPP over other practice guidelines in the UK and UK and say that other practices do not give an idea of the benefit of different interventions to a particular population while NEPP does. They have used tables to illustrate their arguments in a visual manner. It is interesting that they have omitted the cost data that would be needed to make a final prioritization decision, but they have explained it saying that it was deliberately left out so that the outcomes were described in terms in which the data were collected. They recommend that cost calculations might be added in a subsequent step. They have made use of literature based estimates which vary among them considerably and that is the only limitation.

Conclusion – Synthesis of the two papers

The two papers together constitute a group of writing that tells about the application of epidemiology to the identification and implementation of psychiatric interventions. The paper by Heller et al (2006) suggests using NEPP as a measure to prioritize psychiatric interventions as it is a population impact measure and takes into consideration the impact of a particular intervention on the population. Moreover it demonstrates the use of NEPP in the case of schizophrenia and depression. Chen et al (2005) point to the fact that the adolescent population in the United States suffers from mental disorders to a large extent and that is indicated by applying DISC predictor scales (DPS) to existing data from national surveys. Both the papers acknowledge that there is data that can be processed to maximize the efficiency of the interventions, but eliciting them for relevance needs some mathematical processing. While NEPP is used by Heller et al (2006), Chen at al (2005) find application in DISC predictor scales. Chen et al focus on the adolescent age population. There is future scope for research when the two articles are taken together. The NEPP suggested by Heller et al may be used by Chen et al. As it is a population impact measure, the NEPP will show the extent and prevalence of mental disorders among the adolescents in the United States.

References

Chen, W. Kevin; Killeya-Jones, A. Ley and Vega, A. William (2005). Prevalence and co-occurrence of psychiatric symptom clusters in the U.S, adolescent population using DISC predictive scales. Clinical Practice and Epidemiology in Mental Health, 2005, 1 (22), p. 1-12

Heller, F. Richard; Gemmell, Islay and Peterson, Lesley (2006). Helping to prioritize interventions for depression and schizophrenia: Use of Population Impact Measures. Clinical Practice and Epidemiology in Mental Health, 2006, 2 (3), p. 1-7

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