Adverse Childhood Life Events and Postpartum Psychosis in Bipolar Disorder

Background Women with bipolar disorder are at increased risk of postpartum psychosis. Adverse childhood life events have been associated with depression in the postpartum period, but have been little studied in relation to postpartum psychosis. In this study we investigated whether adverse childhood life events are associated with postpartum psychosis in a large sample of women with bipolar I disorder. Methods Participants were 432 parous women with DSM-IV bipolar I disorder recruited into the Bipolar Disorder Research Network (www.BDRN.org). Diagnoses and lifetime psychopathology, including perinatal episodes, were obtained via a semi-structured interview (Schedules for Clinical Assessment in Neuropsychiatry; Wing et al., 1990) and case-notes. Adverse childhood life events were assessed via self-report and case-notes, and compared between women with postpartum psychosis (n=208) and those without a lifetime history of perinatal mood episodes (n=224). Results There was no significant difference in the rate of any adverse childhood life event, including childhood sexual abuse, or in the total number of adverse childhood life events between women who experienced postpartum psychosis and those without a lifetime history of perinatal mood episodes, even after controlling for demographic and clinical differences between the groups. Limitations Adverse childhood life events were assessed in adulthood and therefore may be subject to recall errors. Conclusions We found no evidence for an association between adverse childhood life events and the occurrence of postpartum psychosis. Our data suggest that, unlike postpartum depression, childhood adversity does not play a significant role in the triggering of postpartum psychosis in women with bipolar disorder

Women's Preferences for Treatment of Perinatal Depression and Anxiety : A Discrete Choice Experiment

Perinatal depression and anxiety (PNDA) are an international healthcare priority, associated with significant short- and long-term problems for women, their children and families. Effective treatment is available but uptake is suboptimal: some women go untreated whilst others choose treatments without strong evidence of efficacy. Better understanding of women's preferences for treatment is needed to facilitate uptake of effective treatment. To address this issue, a discrete choice experiment (DCE) was administered to 217 pregnant or postnatal women in Australia, who were recruited through an online research company and had similar sociodemographic characteristics to Australian data for perinatal women. The DCE investigated preferences regarding cost, treatment type, availability of childcare, modality and efficacy. Data were analysed using logit-based models accounting for preference and scale heterogeneity. Predicted probability analysis was used to explore relative attribute importance and policy change scenarios, including how these differed by women's sociodemographic characteristics. Cost and treatment type had the greatest impact on choice, such that a policy of subsidising effective treatments was predicted to double their uptake compared with the base case. There were differences in predicted uptake associated with certain sociodemographic characteristics: for example, women with higher educational attainment were more likely to choose effective treatment. The findings suggest policy directions for decision makers whose goal is to reduce the burden of PNDA on women, their children and families

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Introduction to Addictive Behaviors

This widely adopted text, now in a revised and expanded 3rd edition, offers a balanced review of major contemporary perspectives on substance abuse and addiction, including disease models; psychoanalytic, conditioning, cognitive, and family systems formulations; and social and cultural foundations. Written in a lucid, accessible style, the volume emphasizes applications to the helping process and facilitates learning with case examples, review questions, and end-of-chapter summaries.https://digitalcommons.brockport.edu/bookshelf/1072/thumbnail.jp