The relevance of attachment theory and research for practice has become increasingly clear. The authors describe a series of studies with 3 aims: (a) to validate measures of attachment for use by clinicians with adolescents and adults, (b) to examine the relation between attachment and personality pathology, and (c) to ascertain whether factor analysis can recover dimensions of attachment reflecting both interpersonal and narrative style. In 3 studies, experienced clinicians provided psychometric data using 1 of 4 attachment questionnaires (2 adolescent and 2 adult samples). Attachment dimensions predicted both personality pathology and developmental experiences in predictable ways. Factor analysis identified 4 dimensions that replicated across adolescent and adult samples on the basis of a combination of interpersonal and narrative indicators: secure, dismissing, preoccupied, and incoherent/disorganized.

Objective To study the comorbidity of common mental disorders (CMDs) and cancer, and the mental health treatment gap among community residents with active cancer, cancer survivors and cancer-free respondents in 13 high- and 11 low-middle income countries. Methods Data were derived from the World Mental Health Surveys (N=66,387; n=357 active cancer, n=1,373 cancer survivors, n=64,657 cancer free respondents). The WHO/Composite International Diagnostic Interview was used in all surveys to estimate CMDs prevalence rates. Respondents were also asked about mental health service utilization in the preceding 12 months. Cancer status was ascertained by self-report of physician’s diagnosis. Results Twelve month prevalence rates of CMDs were higher among active cancer (18.4% SE=2.1) than cancer free respondents (13.3%, SE=0.2) adjusted for socio-demographic confounders and other lifetime chronic conditions (Adjusted Odds Ratio (AOR)=1.44 95% CI 1.05–1.97). CMD rates among cancer survivors (14.6% SE=0.9) compared with cancer-free respondents did not differ significantly (AOR=0.95 95% CI 0.82–1.11). Similar patterns characterized high and low-middle income countries. Of respondents with active cancer who had CMD in the preceding 12 months 59% sought services for mental health problems (SE=5.3). The pattern of service utilization among people with CMDs by cancer status (highest among persons with active cancer, lower among survivors and lowest among cancer-free respondents) was similar in high- (64.0% SE=6.0, 41.2% SE=3.0, 35.6% SE=0.6) and low-middle income countries (46.4% SE=11.0, 22.5% SE=9.1, 17.4% SE=0.7). Conclusions Community respondents with active cancer have relatively higher CMD rates and relatively high treatment gap. Comprehensive cancer care should consider both factors.

Previous studies have documented diagnostic bias and noted that its reduction could eliminate misdiagnosis and improve mental health service delivery. Few studies have investigated clinicians' methods of obtaining and using information during the initial clinical encounter. We describe a study examining contributions to clinician bias during diagnostic assessment of ethnic/racial minority patients. A total of 129 mental health intakes were videotaped, involving 47 mental health clinicians from 8 primarily safety-net clinics. Videos were coded by another clinician using an information checklist, blind to the diagnoses provided by the original clinician. We found high levels of concordance between clinicians for substance-related disorders, low levels for depressive disorders, and anxiety disorders except panic. Most clinicians rely on patients' mention of depression, anxiety, or substance use to identify disorders, without assessing specific criteria. With limited diagnostic information, clinicians can optimize the clinical intake time to establish rapport with patients. We found Latino ethnicity to be a modifying factor of the association between symptom reports and likelihood of a depression diagnosis. Differential discussion of symptom areas, depending on patient ethnicity, may lead to differential diagnosis and increased likelihood of diagnostic bias. Diagnostic assessment bias occurs when clinicians make systematic errors in the collection or processing of clinical information that could lead to misdiagnosis, 6 false-positives, or falsenegatives. 7 Reducing diagnostic bias is one way to eliminate misdiagnosis 8 and improve service delivery. But identification of the patient's main problem, which is the foundation for the proper treatment of psychiatric disorders, is challenging given the level of unavoidable uncertainty in diagnostic decision making. 9 In fact, the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) was expected to make substantial improvements to diagnostic formulation by offering a checklist of symptoms, whereby clinicians would first determine which diagnostic criteria were present, whether enough criteria had been fulfilled to justify the diagnosis, and then rule out medical conditions or other psychiatric conditions that could account for these symptoms. 10 However, it is not only the information collected in diagnostic assessment, but also how the information is applied in decision making that is critical for an accurate diagnosis. Paul Meehl 11 showed that "actuarial" methods (eg, formal, algorithmic procedures whereby symptoms are collected in a checklist and statistically analyzed to reach a prediction) for combining diagnostic information were superior to clinical judgments (eg, those that rely on human judgment to merge information, discuss it with others, and reach a diagnostic impression). Yet clinicians resist actuarial or statistical methods in diagnostic formulation. 12 A structured interview may seem to constrain clinicians to prescribed questions and cli...

HCPs reports of their lack of training and awareness on identifying suicide risk is alarming given the higher risk of suicide among cancer patients. Training programs should incorporate the successful strategies used by HCPs and overcome barriers to identifying suicide risk.

The data demonstrate that clinicians' judgments about their patients' functioning and histories agree with patients' self-reports and that in areas of discrepancy, clinicians tend to make appropriately conservative judgments in the absence of clear data. These findings suggest that quantified clinical judgment provides a vast untapped potential for large-sample research on psychopathology and treatment.

This study examines the role of acculturation, perceived discrimination, and self-esteem in predicting the mental health symptoms and risk behaviors among 1.5 and second generation non-Jewish adolescents born to migrant families compared with native-born Jewish Israeli adolescents in Israel. Participants included n = 65 1.5 migrant adolescents, n = 60 second generation migrant adolescents, and n = 146 age, gender, and socioeconomic matched sample of native-born Jewish Israelis. Participants completed measures of acculturation pattern, perceived discrimination, and self-esteem as well as measures of mental health symptoms and risk behaviors. Results show that migrant adolescents across generations reported worse mental health symptoms compared with native-born Jewish Israelis. However, only the 1.5 generation migrants reported higher engagement in risk behaviors compared with second generation migrants and native-born Jewish Israelis. Our findings further showed that acculturation plays an important role in predicting the mental health status of migrant youth, with those characterized with integrated acculturative pattern reporting lower mental health symptoms compared with assimilated acculturation pattern. Importantly, contextual factors, such as higher perception of discrimination in the receiving culture as well as individual factors such as lower self-esteem and female gender were strongly associated with worse mental health symptoms. The findings manifest the complex relationship between contextual factors and individual level variables in the acculturative process of migrants as well as the importance of examining the effect of migration generation on mental health outcomes.

clinicaltrials.gov Identifier: NCT01947283.

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