31 Epidemiology of migration and serious mental illness: the example of migrants to Europe, 579 Monica Charalambides, Craig Morgan and Robin M. 32 Epidemiology of migration addiction among Latin American populations and migration to the United States, 595.
Faraone
Department of Mental Health, Bloomberg School of Public Health, John Hopkins School of Hygiene and Public Health, John Hopkins University, 615 N.
Hudson
- What is epidemiology?
- Psychiatric epidemiology
- Causation in medicine
- Alternative explanations
- Causal inference
- The future for psychiatric epidemiology
It was not until the second half of the twentieth century that epidemiological methods began to be consistently applied to the full range of health problems. However, bias is more likely to be introduced by differential dropout from the cohort than from the initial selection of the subjects into the cohort, at least in this kind of design.
Introduction
In this chapter we provide an overview of many of the statistical methods commonly used for the analysis of categorical 'outcome' data in psychiatric studies. Much of the statistical theory underlying the analysis of categorical data is more easily formulated for 2×2 contingency tables.
Inference for a single proportion
- Example
Finally, we present an overview of regression models for categorical data, with extensive attention to logistic regression models for binary outcomes. The logistic regression model is first introduced for the simple case where there is only a single predictor or covariate.
- The odds ratio as a measure of association
- Examples
- Analysis of R × C contingency tables
- Example
In table 2.4, njk is the number of persons with X=j and Y=k; njk is called the number of cells. Returning to the data from the first-episode study of major affective disorders with psychosis in Table 2.1, the association between Axis I comorbidity and 2-year functional recovery is of scientific interest.
- Example
- Matched pair study design
- Example
However, unlike the Cochran-Mantel-Haenszel test, the Breslow-Day test requires that the sample size in each sub-table be large, even if the number of tables is large. Although each 2×2 table has only two subjects, provided the number of matched pairs is large, the Cochran–Mantel–Haenszel test can be used.
Logistic regression
- Interpretation of logistic regression coefficients
- Hypothesis testing and confidence intervals for logistic regression parameters
- Example: Logistic regression with a single binary covariate
- Multiple logistic regression
- Example: Multiple logistic regression
- Categorical predictors with more than two levels in logistic regression
- Example: Logistic regression with a three-level predictor
- Interactions in logistic regression
- Example: Logistic regression with interaction
- Goodness-of-fit
Similarly, the logistic regression slope, β1, in Equation 2.10 is interpreted as the change in the logarithm of the probability of success for a single unit change in xi. Each of the logistic regression slopes, βk(fork=1,. .,K), is interpreted as a change in the logarithm of the probability of success for a.
Advanced topics
- Conditional logistic regression
- Exact logistic regression
- Multinomial regression models
- Clustered categorical data
That is, the standard application of logistic regression (or any method that assumes independent observations) in this setting is no longer appropriate. In the first stage, the correlation between binary responses within a group is simply ignored and standard logistic regression is used to obtain estimates of the logistic regression coefficients.
Concluding remarks
Further reading
Introduction
The chain of psychiatric genetic research
- Is the disorder familial?
- What are the relative contributions of genes and environment?
- What is the mode of transmission?
- Where is the gene (or genes) located?
- What are the risk-conferring variants of the genes and what is the mechanism
Fifth: 'What are the risk-bearing variants of the genes and what is the disease mechanism?'. However, the probability that the marker locus is located on this segment increases the closer the marker is to the disease locus.
Psychiatric genetics and psychiatric epidemiology
Family-based association tests (FBATs) have been developed as extensions of the TDT model, where patients' parents or siblings are used as controls. The identification of specific genetic risk factors for psychiatric disorders will then facilitate the identification and quantification of environmental risk factors that interact with these genes to produce disease.
Acknowledgements
Affected-ancestry-member method of linkage analysis. Am. 1993) Some developments on the affected-descent-member method of linkage analysis. Am. 1990). Inferring the mode of inheritance by comparing the results of lod.Am. 1987) Genetic linkage: sampling issues and multipoint mapping.
Further reading
- Introduction
- The process of genetic epidemiology
- Gene–environment interplay takes different forms
- Gene–environment correlation
- Gene–environment interaction
- Measurement of genotype, environmental exposure
Number of families needed to detect or rule out linkage heterogeneity.Am. 1987) Power and consistency of the linkage homogeneity test in the genetic analysis of common disorders.J. 1989). Box 4.1 Process for identifying common gene-environment interactions influencing risk for psychiatric disorders.
Measurement of genetic variants
Biological synergism/interaction is therefore defined when two risk factors are components of the same sufficient cause [35]. The disadvantage of omnibus models is non-differential information bias due to false negative misclassification of the genetic risk.
Measurement of environmental exposures
In addition, they suggest using multiple markers spanning the length of the candidate gene to ensure that all its regions are examined [ 36 ]. If a haplotype is identified, it is often possible to identify a single 'marker' marker, which will capture most of the variation across that region of the gene [37] so that the number of markers required for full coverage , be reduced.
Measurement of the pathological phenotype (disorder)
Models of GxE
Which scale should we use to measure GxE ?
Inherent in the use of the multiplicative scale is the idea that the causal factors are independent of each other. Another approach is to present the full multiplicative model, including the direct effects and product terms, allowing recalculation of the joint effect on an additive scale [58].
Study designs for the detection of GxE
- Cohort design
- Case–control design
- Case only design
- Family designs
- Gene–environment wide interaction studies (GEWIS)
According to this hypothesis, the combined effect of G and E will be equal to the product of the individual effects. In addition, this method only allows the assessment of the interaction and not the main effect of genotype and environment.
Threats to the validity of epidemiological GxE studies
- Confounding by gene–environment correlation
- Population stratification
- Power, sample size and issues of multiple comparisons
GxE strategies have been shown to be effective in evaluating pharmacological interventions (pharmacogenetics) [90]. Power and sample size calculations are critical in the design of GxE studies and will vary depending on the design used.
Epigenetic mechanisms
Epidemiological and genetic approaches in the study of gene-environment interaction: an overview of available methods. Epidemiol. 2003) Selection bias in the assessment of gene-environment interaction in case-control studies. Am. 2003) Interaction as deviation from additivity in case-control studies: a caution.
Introduction
The reliability coefficient
This can be thought of as the proportion of σX2 that represents genuine, repeatable differences in subjects. For example, it can be shown that the correlation between X and another variable Y will become smaller as the reliability coefficient of any variable becomes smaller [3, 4].
Designs for estimating reliability
- The effect of population variance on reliability
To the extent that the trained lay interviewers performed as well as the professionals, the results can be interpreted as the test-retest reliability of the DIS. If the level of training did in fact make a difference, then the results can be interpreted as validating the use of lay interviewers (assuming that professionals are the ideal interviewers for this structured measure).
Statistical remedies for low reliability
In all the reliability models discussed above, we assumed that the respondents were sampled from the population to be studied. When several items are available as repeated measures, it is usually the scale score reliability (item sum or mean) that is of interest.
Reliability theory and binary judgements
Another is the relation of the expected mean of a binary variable and the expected variance of that variable. This fact has implications in the interpretation of equation (5.1), the determination of the reliability coefficient.
Reliability statistics: General
- One-way ANOVA analyses
- Two-way ANOVA analyses
- The reliability of the average of k fixed measures: Cronbach’s alpha
Subject Crossed Assessor Design Fixed ICR(3,1)= TMS−EMS. B) Reliability of mean k scores. In this case, the mean measurement reliability can be calculated directly using ICR(3,k) from Table 5.3.
Other reliability statistics
- Cohen’s kappa
- Product moment correlation
- Item response theory statistics
The estimate of the reliability of the sum or average of the k fixed items can be calculated using ICR(3,k). Investigators who have a set of survey questions known to reflect an underlying dimension, such as the severity of distress or impairment, often report estimates of Cronbach's alpha as a summary of measurement quality.
Summary and conclusions
An alternative approach is to focus on the relationship of each item response pattern to the underlying dimension. When items are clearly formulated and related to the underlying (latent) dimension, the probability of endorsing an item category will be systematically related to the latent dimension (see for example [45]).
Introduction
In this discussion, the moderator/mediator approach specifically aimed at understanding the genetic influences on disorders will be discussed. If G and E were studied simultaneously, in the population of interest, the risk difference (RD) between those with both G.
Current methodological barriers
- Case–control studies
- Statistical significance necessary but not sufficient
- Odds ratio is not a clinically interpretable effect size
- Correlation versus interaction
The most common effect size used in epidemiological and genetic research is the odds ratio. In every 2×2 table there are four relative risks and the odds ratio is always greater than the largest one.
Moderation, mediation and other ways in which risk factors
A common source of confusion is that between two risk factors that are correlated and two risk factors that interact. On the other hand, G and E interact in their effect on a specific outcome D if the effect size relating E to D is different for those with G=1 than for those with G= 0, or equivalently if the effect size which is related. G to D is different for those with E=1 than for those with E=0, that is.
G moderates E in its effect on D
Limit values are measured in units of standard deviation from the point halfway between the centers of the two distributions. Indeed, "susceptibility" genes may often be the genes that moderate the effect of environmental stressors on later onset of disorders.
Independent risk factors
Proxies
However, when G and E are considered together here, in both boys and girls, ball throwing ability is unlikely to be correlated with D. If, considered together, only one of the two such variables appears to be related to D, the other is a proxy for the variable that matters.
Overlapping risk factors
If so, throwing ability (E) is proxy for gender (G) for onset of depression (D), that is, it is probably not worth teaching girls to throw a ball better to prevent depression. Proxies are often found when there is one strong risk factor, but correlates of that risk factor are also considered simultaneously.
Summary
If G were to be ignored here, E could turn out to be a risk factor for later onset of depression. A similar situation occurs with two G's or two E's, i.e. there is no time advantage between the risk factors.
Extensions
- One risk factor at each of two time points measured at any level
- Multiple risk factors at two time points
- Multiple risk factors at multiple time points
First, one would examine all pairs of risk factors in the set of risk factors measured at each time point, identifying and removing proxies, and combining or otherwise removing overlapping variables. This process reduces the set of variables measured at any time to a smaller set of independent risk factors for the outcome.
Beyond moderators and mediators
Then one would examine whether any variables in the earlier set moderate any of the variables in the later set. Since the pathways leading to the disorder may differ in the subgroups defined by a moderator of subsequent risk factors for the disorder, problems associated with Simpson's paradox may be quite widespread [40–43].
Introduction
1 Department of Psychiatry and Medicine at Brigham and Women's Hospital (BWH), Harvard Medical School, Boston, MA, USA. 2Connors Center for Women's Health and Gender Biology, Department of Medicine, Brigham & Women's Hospital, Boston, MA, USA.
Validity of a construct
- Content validity
- Examples of assessment of content validity
- Criterion validity
- Examples of criterion validity
- Construct validity
- Application of construct validity to psychiatric diagnosis
- The future of validating psychiatric disorders: Towards DSM-5 and beyond
Therefore, it involves a theoretical understanding of the concept of interest in order to measure it accurately. In fact, content and criterion validity are considered part of the construct validity assessment process.
Validity of the relationships between variables
Internal validity The validity of conclusions that apply to the subjects in a study. Mortality effects refer to different dropout or rejection rates between groups that may affect the post-treatment group mean.
Summary
For example, communication between patients in the treatment and control groups about the treatment in question can lead to rivalry between the groups. Insights from neuroscience for the concept of schizotaxia and the diagnosis of schizophrenia, in Advancing DSM: Dilemmas in Psychiatric Diagnosis (eds K.A. Phillips, M.B. First and H.A. Pincus), American Psychiatric Association, Washington, DC, pp. 1997) 6p24- 22 region and major psychosis among the population of Eastern Quebec.
Introduction
By connecting different registers, it is also possible to investigate risk factors for mental disorders. Where previous reviews of the use of Nordic health registries have focused on specific topics or on one country, the first and main purpose of the current work is to describe the registries used in psychiatric research and to discuss issues related to registry-based research.
Registers for use in psychiatric research
- Hospital discharge registers
- Medication data
- Cause of death registers
- Other registers
National Center for Registry-Based Research www.ncrr.au.dk Descriptions and addresses of various health registries. National Institute of Social Welfare and Health www.thl.fi Medical register of births, register of hospital discharges.
Register research in Denmark
Another study, in which the National Register was linked with the Danish Central Psychiatric Register, found no support for the hypothesis that depression independently increases the risk of cancer [60]. Frequent changes of residence in childhood were associated with an increased risk of suicide in a study that used the National Register combined with the Central Psychiatric Register [64].
Register research in Finland
Current drug use among the subjects who had ever used an antidepressant was associated with a significantly lower risk of suicide and mortality compared to no current drug use. 75] found that among second-generation antipsychotics, clozapine was associated with substantially lower mortality than any other antipsychotic.
Register research in Norway
85] linked genetic data used in the Nord-Trondelag Health Study with antipsychotic drug data from the Norwegian Prescription Database. The prescription database has also been used to study trends in the use of selective serotonin reuptake inhibitors [87].
Register research in Sweden
The work demonstrates the possibility of using data from registers to inform about the epidemiology of long-term sick leave. The first Norwegian twin study based on the Norwegian twin registries was by Kringlen [88], who investigated genetic factors in psychoses, an important finding was that problems with sampling techniques in previous studies of schizophrenia resulted in overestimation of the genetic factors.
Discussion
- Main findings
- Methodological and administrative challenges
- The Nordic countries: An epidemiologist’s paradise?
Aberrant intrauterine growth and risk of schizophrenia: A 34-year follow-up of the Northern Finland 1966 Birth Cohort. Schizophr. 2008) CNS infections during childhood and the risk of subsequent psychotic illness: a cohort study of more than one million Swedish subjects.Am. 2008) Scholastic achievement at age 16 and risk of schizophrenia and other psychoses: a national cohort study. Psychol.
Introduction
4 Head, Health Services Research Unit (IMIM-Hospital del Mar), CIBER Epidemiolog´ıa y Salud P´ublica (CIBERESP), Spain, Master Program in Public Health (UPF-UAB), Carrer del Doctor Aiguader, Barcelona, Spain. It was not until 1998 that Tansella and Thornicroft published their paper "A conceptual framework for mental health services: the matrix model", which aimed to review the main concepts and applications of HSR in mental health services [5].
What is mental health services research?
The context in which HSR and mental HSR have developed suffers from internal and external difficulties. On the other hand, both general and mental HSR must deal with specific internal characteristics of the health care arena.
A framework for mental health services research
The process phase: in this phase, the focus is on activities developed to deliver mental health services. The use of the matrix model can help researchers in psychiatry consider various factors that can help them answer complex questions.
Key concepts in mental health services research
- Need
- Want, demand and supply
- Efficacy, effectiveness and efficiency
- Appropriateness of care
- Small area variations (SAV)
- Factors associated with access to health care
- Equity
According to Shape and Faden [21], the concept of appropriateness should be considered from at least three different perspectives: i) from a clinical perspective, i.e. is there sufficient evidence of the intervention in terms of potential benefits and harms?; (ii) the perspective of the individual patient; that is, values and "non-clinical" benefits and harms to patients and their interests must be included when examining appropriateness. Demand-related (i.e., patient) variables such as socioeconomic level, education, ethnicity, health status, and beliefs are a major source of variability [26].
Examples of mental health services research studies
- Administrative data
- Studies using primary data collection
- Qualitative studies
One of the main studies in Mental HSR is the World Health Organization (WHO) Mental Health Atlas. On the other hand, the provision of mental health services in Talcahuano was reorganized during the 1990s.
Conclusion
Use of mental health services for anxiety, mood and substance disorders in 17 countries in the WHO global mental health surveys.Lancet. 47] ADEMM-Usuaris de Salut Mental de Catalunya (2007) The relationship between users and professionals in the scope of mental health.
Introduction
Spending on public programs such as Medicare and Medicaid in the United States has tripled over the past thirty years, from 1.3% of gross domestic product in 1975 to 4% in 2007 and is expected to continue to rise to 12% under current policies by 2050. 6]. In 2005, the US Food and Drug Administration (FDA) warned of increased mortality among older patients with dementia who were taking second-generation antipsychotics.
Overview of
Although the United States spends the largest percentage of gross domestic product on health care, recent data from the World Health Organization's World Mental Health Survey show that the United States lags behind other developed nations in the rate of receiving effective treatment [9] . Similarly, analyzes of temporal trends in the United States have shown that although the use of mental health treatments increased 65% in the last decade, the prevalence of mental disorders and suicidality did not decrease [10–12].
A brief history
Major advances in the data and study designs available to psychopharmacoepidemiologists have enabled an expansion of the field's role. Methodological advances in the analysis of pharmacoepidemiological data have enabled researchers to more effectively deal with, or at least quantify, threats to the validity of observational studies, such as the common problem of confounding by.
Sources of data
- Large governmental administrative databases
- Data from health maintenance organizations
- Large-scale surveys
- Practice-based networks
The establishment of government entitlement programs such as Medicaid in the mid-1960s created an important source of data for psychopharmacoepidemiologists [33]. Other office-based networks in the United States include the Ambulatory Sentinel Practice Network (ASPN) of family practice, Pediatric Research in Office Settings (PROS), and the Practice Research Network (PRN) of psychiatrists of the American Psychiatric Association.
Examples of recent
Advantages of data from such surveys include the ability to generate nationally representative estimates of psychiatric medication use. General advantages of data from practice-based networks include their more accurate clinical information and the potential to develop representative estimates; disadvantages include the high cost of maintaining the networks and the uncertainty of whether patients actually took the prescribed medication.
- Uncovering adverse effects and unanticipated benefits of psychiatric
- Descriptive analyses of the use and quality of psychiatric medication use
- Pharmacoeconomic analyses
- Studying interventions to optimise psychiatric medication use
- Conclusions
- Introduction
- Levels of causation
WHO World Mental Health Research Consortium (2007) Global use of mental health services for anxiety, mood and substance disorders: results from 17 countries in the World Health Organization World Mental Health (WMH) surveys. Lancet Changing profiles of service sectors used for mental health care in the United States. Am. Antidepressant treatment and risk of death and. non-fatal self-harm in the first episode of depression.
A historical overview
- Levels of causation
- Individual level
- Contextual level
- Combining individual and contextual levels
- Causation over (life) time
- Examples
- Parental age
- Neighbourhood and ethnic density
- Alcohol: Genes, culture and health
- Course and outcome of schizophrenia in developing
- BirthWeight and psychiatric outcomes
- Violence and mental illness
- Framing the future
- Introduction
- Onset
- Prodromes and precursors
This chapter provides a conceptual framework for research into the natural history of psychopathology and illustrates details of the framework with examples from research in psychiatric epidemiology. This chapter discusses concepts and methods for the study of the natural history of psychopathology.
