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Retrospective reports of lifetime experience with mental disorders greatly underestimate the actual experiences of disorder because recall error biases reporting of earlier life symptoms downward. This fundamental obstacle to accurate reporting has many adverse consequences for the study and treatment of mental disorders. Better tools for accurate retrospective reporting of mental disorder symptoms have the potential for broad scientific benefits.
Methods
We designed a life history calendar (LHC) to support this task, and randomized more than 1000 individuals to each arm of a retrospective diagnostic interview with and without the LHC. We also conducted a careful validation with the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition.
Results
Results demonstrate that—just as with frequent measurement longitudinal studies—use of an LHC in retrospective measurement can more than double reports of lifetime experience of some mental disorders.
Conclusions
The LHC significantly improves retrospective reporting of mental disorders. This tool is practical for application in both large cross-sectional surveys of the general population and clinical intake of new patients.
Epidemiological research on post-stroke affective disorders has been mainly focusing on post-stroke depression (PSD). In contrast, research on post-stroke anxiety (PSA) is in its early stages. The present study proposes a broad picture on post-stroke affective disorders, including PSD and PSA in German stroke in-patients during rehabilitation. In addition, we investigated whether lifetime affective disorders predict the emergence of PSD and PSA.
Methods:
289 stroke patients were assessed in the early weeks following stroke for a range of mood and anxiety disorders by means of the Structured Clinical Interview relying on the Diagnostic and Statistical Manual of Mental Disorders IV. This assessment was conducted for two periods: for post-stroke and retroactively for the period preceding stroke (lifetime). The covariation between PSD and PSA was investigated using Spearman-ρ correlation. Predictors of PSD and PSA prevalence based on the respective lifetime prevalence were investigated using logistic regression analyses.
Results:
PSD prevalence was 31.1%, PSA prevalence was 20.4%. We also found significant correlations between depression and anxiety at post-stroke and for the lifetime period. Interestingly, lifetime depression could not predict the emergence of PSD. In contrast, lifetime anxiety was a good predictor of PSA.
Conclusions:
We were able to highlight the complexity of post-stroke affective disorders by strengthening the comorbidity of depression and anxiety. In addition, we contrasted the predictability of PSA based on its lifetime history compared to PSD which was not predictable based on lifetime depression.
Epidemiological research is believed to underestimate the lifetime prevalence of mental illness due to recall failure and a lack of rapport between researchers and participants.
Method
In this prospective study, we examined lifetime prevalence and co-morbidity rates of substance use disorders, antisocial personality disorder (ASPD) and major depressive disorder (MDD) in a representative, statewide Minnesota sample (n = 1252) assessed four times between the ages of 17 and 29 years with very low attrition.
Results
Lifetime prevalence rates of all disorders more than doubled between the ages of 17 and 29 years in both men and women, and our prospective rates at the age of 29 years were consistently higher than rates from leading epidemiological surveys. Although there was some variation, the general trend was for lifetime co-morbidity to increase between the ages of 17 and 29 years, and this trend was significant for MDD–alcohol dependence, MDD–nicotine dependence, and ASPD–nicotine dependence.
Conclusions
Overall, our results show that emerging adulthood is a high-risk period for the development of mental illness, with increases in the lifetime prevalence and co-morbidity of mental disorders during this time. More than a quarter of individuals had met criteria for MDD and over a fifth had experienced alcohol dependence by the age of 29 years, indicating that mental illness is more common than is estimated in cross-sectional mental health surveys. These findings have important implications for the measurement of economic burden, resource allocation toward mental health services and research, advocacy organizations for the mentally ill, and etiological theories of mental disorders.
Research on the structure of co-morbidity among common mental disorders has largely focused on current prevalence rather than on the development of co-morbidity. This report presents preliminary results of the latter type of analysis based on the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A).
Method
A national survey was carried out of adolescent mental disorders. DSM-IV diagnoses were based on the Composite International Diagnostic Interview (CIDI) administered to adolescents and questionnaires self-administered to parents. Factor analysis examined co-morbidity among 15 lifetime DSM-IV disorders. Discrete-time survival analysis was used to predict first onset of each disorder from information about prior history of the other 14 disorders.
Results
Factor analysis found four factors representing fear, distress, behavior and substance disorders. Associations of temporally primary disorders with the subsequent onset of other disorders, dated using retrospective age-of-onset (AOO) reports, were almost entirely positive. Within-class associations (e.g. distress disorders predicting subsequent onset of other distress disorders) were more consistently significant (63.2%) than between-class associations (33.0%). Strength of associations decreased as co-morbidity among disorders increased. The percentage of lifetime disorders explained (in a predictive rather than a causal sense) by temporally prior disorders was in the range 3.7–6.9% for earliest-onset disorders [specific phobia and attention deficit hyperactivity disorder (ADHD)] and much higher (23.1–64.3%) for later-onset disorders. Fear disorders were the strongest predictors of most other subsequent disorders.
Conclusions
Adolescent mental disorders are highly co-morbid. The strong associations of temporally primary fear disorders with many other later-onset disorders suggest that fear disorders might be promising targets for early interventions.
An important issue in assessing the societal burden of mental disorders is whether the evidence of increasing prevalence in recent cohorts is real or a methodological artifact. The chapter begins with a broad overview of results concerning the estimated lifetime prevalence, age-of-onset distributions, projected lifetime risk, cohort effects, and sociodemographic correlates of the Diagnostic and Statistical Manual DSM-IV disorders assessed in the National Comorbidity Survey Replication (NCS-R). It then turns to a discussion of the prevalence of these same disorders in the year before the NCS-R interview. This is followed by a brief review of data regarding trends in disorder prevalence and treatment in the NCS-R compared to a decade earlier in the baseline NCS. The chapter closes with a discussion of interpretations and implications of these results along with anticipated future directions in the investigation of the prevalence of mental disorders.