Diagnosis of depressive disorder using interviewer-administered instruments is expensive and frequently impractical in large epidemiological surveys. The aim of this study was to assess the validity of three self-completion measures of depressive disorder and other psychiatric disorders in older people against an interviewer-administered instrument.

A random sample stratified by sex, age and social position was selected from the Whitehall II study participants. This sample was supplemented by inclusion of depressed Whitehall II participants. Depressive disorder and other mental disorders were assessed by the interviewer-administered structured revised Clinical Interview Schedule (CIS-R) in 277 participants aged 58–80 years. Participants also completed a computerized self-completion version of the CIS-R in addition to the General Health Questionnaire (GHQ) and the Center for Epidemiologic Studies Depression Scale (CES-D).

The mean total score was similar for the interviewer-administered (4.43) and self-completion (4.35) versions of the CIS-R [95% confidence interval (CI) for difference −0.31 to 0.16]. Differences were not related to sex, age, social position or presence of chronic physical illness. Sensitivity/specificity of self-completion CIS-R was 74%/98% for any mental disorder and 75%/98% for depressive episode. The corresponding figures were 86%/87% and 78%/83% for GHQ and 77%/89% and 89%/86% for CES-D.

The self-completion computerized version of the CIS-R is feasible and has good validity as a measure of any mental disorder and depression in people aged ⩾ 60 years. GHQ and CES-D also have good criterion validity as measures of any mental disorder and depressive disorder respectively.

To develop latent classes of exposure to traumatic experiences before the age of 13 years in an urban community sample and to use these latent classes to predict the development of negative behavioral outcomes in adolescence and young adulthood.

A total of 1815 participants in an epidemiologically based, randomized field trial as children completed comprehensive psychiatric assessments as young adults. Reported experiences of nine traumatic experiences before age 13 years were used in a latent class analysis to create latent profiles of traumatic experiences. Latent classes were used to predict psychiatric outcomes at age ⩾13 years, criminal convictions, physical health problems and traumatic experiences reported in young adulthood.

Three latent classes of childhood traumatic experiences were supported by the data. One class (8% of sample), primarily female, was characterized by experiences of sexual assault and reported significantly higher rates of a range of psychiatric outcomes by young adulthood. Another class (8%), primarily male, was characterized by experiences of violence exposure and reported higher levels of antisocial personality disorder and post-traumatic stress. The final class (84%) reported low levels of childhood traumatic experiences. Parental psychopathology was related to membership in the sexual assault group.

Classes of childhood traumatic experiences predict specific psychiatric and behavioral outcomes in adolescence and young adulthood. The long-term adverse effects of childhood traumas are primarily concentrated in victims of sexual and non-sexual violence. Gender emerged as a key covariate in the classes of trauma exposure and outcomes.

Depressive symptoms above screening thresholds have been shown to predict functional decline in older adults. Less is known about the impact of subthreshold depression, and whether more symptoms confer significantly greater risk compared to fewer symptoms.

Using data from the Duke Established Populations for Epidemiologic Studies of the Elderly (EPESE) collected over 10 years, we used repeated-measures mixed models to predict functional change by depression status at the prior (index) in-person interview. Depressive symptoms were measured using a modified version of the Center for Epidemiologic Studies Depression Scale (CES-D). Subthreshold depression was operationalized as 6–8 symptoms and CES-D-defined depression as 9–20 symptoms in the previous week. Three domains of functional status were assessed at the subsequent in-person interview: limitations in basic activities of daily living (ADL), instrumental ADL (IADL) and mobility.

Controlling for race, sex, age, education, marital status, cognitive status, health status, self-perceived health, perceived social support and functional status at the index interview, having ⩾6 depressive symptoms predicted an increase of 0.12 IADL limitations 3–4 years later (p=0.03). The incremental effect of CES-D-defined depression (⩾9 symptoms compared to 6–8 symptoms) was not significant, suggesting that the effect of more symptomatic depression did not add to that of subthreshold depression. CES-D score modeled as a continuous variable predicted functional change for all domains, but the relationship was not linear, supporting a possible threshold effect.

The relationship between depressive symptoms and functional change is complex, not necessarily linear, and may vary by tasks assessed.

Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a given person. We aim to examine the performance of machine learning methods in delivering replicable predictions of treatment outcomes.

Of 7732 non-duplicate records identified through literature search, we retained 59 eligible reports and extracted data on sample, treatment, predictors, machine learning method, and treatment outcome prediction. A minimum sample size of 100 and an adequate validation method were used to identify adequate-quality studies. The effects of study features on prediction accuracy were tested with mixed-effects models. Fifty-four of the studies provided accuracy estimates or other estimates that allowed calculation of balanced accuracy of predicting outcomes of treatment.

Eight adequate-quality studies reported a mean accuracy of 0.63 [95% confidence interval (CI) 0.56–0.71], which was significantly lower than a mean accuracy of 0.75 (95% CI 0.72–0.78) in the other 46 studies. Among the adequate-quality studies, accuracies were higher when predicting treatment resistance (0.69) and lower when predicting remission (0.60) or response (0.56). The choice of machine learning method, feature selection, and the ratio of features to individuals were not associated with reported accuracy.

The negative relationship between study quality and prediction accuracy, combined with a lack of independent replication, invites caution when evaluating the potential of machine learning applications for personalizing the treatment of depression.

The late positive potential (LPP) is an event-related potential component that is sensitive to the motivational salience of stimuli. Children with a parental history of depression, an indicator of risk, have been found to exhibit an attenuated LPP to emotional stimuli. Research on depressive and anxiety disorders has organized these conditions into two empirical classes: distress and fear disorders. The present study examined whether parental history of distress and fear disorders was associated with the LPP to emotional stimuli in a large sample of adolescent girls.

The sample of 550 girls (ages 13.5–15.5 years) with no lifetime history of depression completed an emotional picture-viewing task and the LPP was measured in response to neutral, pleasant and unpleasant pictures. Parental lifetime history of psychopathology was determined via a semi-structured diagnostic interview with a biological parent, and confirmatory factor analysis was used to model distress and fear dimensions.

Parental distress risk was associated with an attenuated LPP to all stimuli. In contrast, parental fear risk was associated with an enhanced LPP to unpleasant pictures but was unrelated to the LPP to neutral and pleasant pictures. Furthermore, these results were independent of the adolescent girls’ current depression and anxiety symptoms and pubertal status.

The present study demonstrates that familial risk for distress and fear disorders may have unique profiles in terms of electrocortical measures of emotional information processing. This study is also one of the first to investigate emotional/motivational processes underlying the distress and fear disorder dimensions.

Current psychological models of psychotic symptoms suggest that metacognitive beliefs impact on an individual's appraisal of anomalous experiences, and thereby influence whether these lead to distress and become clinical symptoms. This study examined the relationship between maladaptive metacognitive beliefs, anomalous experiences, anomaly-related distress, anxiety and depression and diagnostic status.

The Metacognitions Questionnaire (MCQ), Symptom Checklist 90 – Revised, and Appraisals of Anomalous Experiences interview were administered to 27 people diagnosed with a psychotic disorder, 32 people meeting At Risk Mental State (ARMS) criteria, 24 people with psychotic-like experiences but no need for care, and 32 healthy volunteers.

The two clinical groups scored higher than non-patient controls and individuals experiencing psychotic-like anomalies with no need for care on most subscales of the MCQ, particularly the ‘general negative beliefs about thoughts’ (NEG) subscale. However, most group differences became non-significant when anxiety and depression were controlled for. Few relationships were found between the MCQ subscales and psychotic-like anomalies and anomaly-related distress. Cognitive/attentional difficulty was the only type of anomaly to be significantly associated with maladaptive metacognitive beliefs. Anomaly-related distress was associated with only the NEG subscale of the MCQ.

Maladaptive metacognitive beliefs, as measured by the MCQ, appear to be related more to elevated levels of general psychopathology in psychotic and at-risk groups than to the presence of, and distress associated with, psychotic experiences. Processes by which metacognitions may impact upon the need for care are discussed.

The nosological status of olfactory reference syndrome (ORS) is a matter of debate and there is uncertainty as to what treatments are effective.

The world literature was searched for reports of cases of ORS. Clinical, nosological and therapeutic information from cases meeting proposed diagnostic criteria for the disorder was summarized and tabulated.

A total of 84 case reports (52 male/32 female) were found. Age of onset was <20 years in almost 60% of cases. Smell-related precipitating events were recorded in 42%. Most patients could not smell the smell or only did so intermittently. Authors of the reports expressed reservations about the delusional nature of the belief in slightly under half of the cases. Over two-thirds were improved or recovered at follow-up, with the disorder responding to antidepressants and psychotherapy more frequently than to neuroleptics.

ORS is a primary psychiatric syndrome that does not fit well into its current classification as a subtype of delusional disorder, both in terms of its nosology and its response to treatment.

Diagnostic errors can have tremendous consequences because they can result in a fatal chain of wrong decisions. Experts assume that physicians' desire to confirm a preliminary diagnosis while failing to seek contradictory evidence is an important reason for wrong diagnoses. This tendency is called ‘confirmation bias’.

To study whether psychiatrists and medical students are prone to confirmation bias and whether confirmation bias leads to poor diagnostic accuracy in psychiatry, we presented an experimental decision task to 75 psychiatrists and 75 medical students.

A total of 13% of psychiatrists and 25% of students showed confirmation bias when searching for new information after having made a preliminary diagnosis. Participants conducting a confirmatory information search were significantly less likely to make the correct diagnosis compared to participants searching in a disconfirmatory or balanced way [multiple logistic regression: odds ratio (OR) 7.3, 95% confidence interval (CI) 2.53–21.22, p<0.001; OR 3.2, 95% CI 1.23–8.56, p=0.02]. Psychiatrists conducting a confirmatory search made a wrong diagnosis in 70% of the cases compared to 27% or 47% for a disconfirmatory or balanced information search (students: 63, 26 and 27%). Participants choosing the wrong diagnosis also prescribed different treatment options compared with participants choosing the correct diagnosis.

Confirmatory information search harbors the risk of wrong diagnostic decisions. Psychiatrists should be aware of confirmation bias and instructed in techniques to reduce bias.

Several studies suggest that patients with late-onset major depression (MD) have an increased load of cerebral white-matter lesions (WMLs) compared with age-matched controls. Vascular risk factors such as hypertension and smoking may confound such findings. Our aim was to investigate the association between the localization and load of WMLs in late-onset MD with respect to vascular risk factors.

We examined 22 consecutive patients with late-onset first-episode MD and 22 age- and gender-matched controls using whole-brain magnetic resonance imaging (MRI). The localization, number and volume of WMLs were compared between patients and controls, while testing the effect of vascular risk factors.

Among subjects with one or more WMLs, patients displayed a significantly higher WML density in two white-matter tracts: the left superior longitudinal fasciculus and the right frontal projections of the corpus callosum. These tracts are part of circuitries essential for cognitive and emotional functions. Analyses revealed no significant difference in the total number and volume of WMLs between groups. Patients and controls showed no difference in vascular risk factors, except for smoking. Lesion load was highly correlated with smoking.

Our results indicate that lesion localization rather than lesion load differs between patients with late-onset MD and controls. Increased lesion density in regions associated with cognitive and emotional functions may be crucial in late-onset MD, and vascular risk factors such as smoking may play an important role in the pathophysiology of late-onset MD, consistent with the vascular depression hypothesis.

Telomere length is considered an emerging marker of biological aging. Depression and anxiety are associated with excess mortality risk but the mechanisms remain obscure. Telomere length might be involved because it is associated with psychological distress and mortality. The aim of this study was to test whether anxiety and depressive disorders predict telomere length over time in a large population-based sample.

All analyses were performed in a longitudinal study in a general population cohort of 974 participants. The Composite International Diagnostic Interview (CIDI) was used to measure the presence of anxiety and depressive disorders. Telomere length was measured using monochrome multiplex polymerase chain reaction (PCR) at approximately 2 years of follow-up. We used linear multivariable regression models to evaluate the association between anxiety and depressive disorders and telomere length, adjusting for adverse life events, lifestyle factors, educational level and antidepressant use.

The presence of anxiety disorders predicted shorter telomeres at follow-up (β = –0.073, t = –2.302, p = 0.022). This association was similar after controlling for adverse life events, lifestyle factors, educational level and antidepressant use (β = –0.077, t = –2.144, p = 0.032). No association was found between depressive disorders and shorter telomeres at follow-up (β = 0.010, t = 0.315, p = 0.753).

This study found that anxiety disorders predicted shorter telomere length at follow-up in a general population cohort. The association was not explained by adverse life events, lifestyle factors, educational level and antidepressant use. How anxiety disorders might lead to accelerated telomere shortening and whether this might be a mediator explaining the excess mortality risk associated with anxiety deserve further investigation.