The DST and psychiatry : possible effects on decision making, diagnosis and treatment

The introduction of a technique that purports to increase our understanding of a particular disorder leads inevitably to a reassessment of the existing body of knowledge about that disorder. Sometimes a re-evaluation of the methods of the discipline may occur. When one such innovation, the dexamethasone suppression test (DST), was introduced into clinical psychiatry at the Royal Adelaide Hospital, a study was conducted into its effects on diagnosis and treatment of depression. The results of this study, which are detailed in chapter Three of this dissertation, indicate that considerable changes in management (and also perhaps in thinking about clinical problems) occurred concurrently with the introduction of the DST. Specifically, the study showed increases in the diagnosis of biological depression and treatment with antidepressants. There htas no association between DST results and particular management plans. There was, however, a very strong association between requesting the DST and subsequent management with antidepressants . These results Ied to a re-evaluation of the literature of the development of the DST as a specific laboratory test for melancholia. Chapter Two follows Rubin and Mandell's hypothesis that elevated cortisol levels were a specific concomitant of depression, through nearly 20 years of research. In particular, the rapid increase in the literature on the DST in the early '80s is reviewed. The chapter ends with a discussion of Some very recent cautionary articles about the application of the DST to psychiatry. The results of the DST study led also to a re-evaluation of one of the fundamental processes of psychiatry and of all medicine, the process of clinical judgment. chapter one is concerned with decision making in psychiatry and how the process in psychiatry differs from that in general medicine. Issues of diagnosis are considered, along with the relevance of diagnosis to treatment. The notion of a psychiatrist's "set" with respect to management is commented upon, along with the notion of maximising utility with respect to diagnosis and treatment. The dissertation concludes with only conjectures to explain the results. Studies to address these conjectures could lead to a greater understanding, not only of the DST, but also to the process of clinical judgment in psychiatry.Thesis (M. Clin. Sc.)--University of Adelaide, Dept. of Psychiatry, 198

An eHealth Intervention for Patients in Rural Areas: Preliminary Findings From a Pilot Feasibility Study

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.Background: eHealth facilitation of chronic disease management has potential to increase engagement and effectiveness and extend access to care in rural areas. Objective: The objective of this study was to demonstrate the feasibility and acceptability of an eHealth system for the management of chronic conditions in a rural setting. Methods: We developed an online management program which incorporated content from the Flinders Chronic Condition Management Program (Flinders Program) and used an existing software platform (goACT), which is accessible by patients and health care workers using either Web-enabled mobile phone or Internet, enabling communication between patients and clinicians. We analyzed the impact of this eHealth system using qualitative and simple quantitative methods. Results: The eHealth system was piloted with 8 recently hospitalized patients from rural areas, average age 63 (SD 9) years, each with an average of 5 chronic conditions and high level of psychological distress with an average K10 score of 32.20 (SD 5.81). Study participants interacted with the eHealth system. The average number of logins to the eHealth system by the study participants was 26.4 (SD 23.5) over 29 weeks. The login activity was higher early in the week. Conclusions: The pilot demonstrated the feasibility of implementing and delivering a chronic disease management program using a Web-based patient-clinician application. A qualitative analysis revealed burden of illness and low levels of information technology literacy as barriers to patient engagement

Development of an Online Well-Being Intervention for Young People: An Evaluation Protocol

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be includedBackground: Research has shown that improving well-being using positive mental health interventions can be useful for predicting and preventing mental illness. Implementing online interventions may be an effective way to reach young people, given their familiarity with technology. Objective: This study will assess the effectiveness of a website called the “Online Wellbeing Centre (OWC),” designed for the support and improvement of mental health and well-being in young Australians aged between 16 and 25 years. As the active component of the study, the OWC will introduce a self-guided app recommendation service called “The Toolbox: The best apps for your brain and body” developed by ReachOut.com. The Toolbox is a responsive website that serves as a personalized, ongoing recommendation service for technology-based tools and apps to improve well-being. It allows users to personalize their experience according to their individual needs. Methods: This study will be a two-arm, randomized controlled trial following a wait-list control design. The primary outcome will be changes in psychological well-being measured by the Mental Health Continuum Short Form. The secondary outcomes will be drawn from a subsample of participants and will include depression scores measured by the Center for Epidemiologic Studies Depression Scale, and quality of life measured by the Assessment of Quality of Life-four dimensions (AQOL-4D) index. Cost-effectiveness analysis will be conducted based on a primary outcome of cost per unique visit to the OWC. Utility-based outcomes will also be incorporated into the analysis allowing a secondary outcome to be cost per quality-adjusted life year gained (based on the AQOL-4D values). Resource use associated with both the intervention and control groups will be collected using a customized questionnaire. Online- and community-based recruitment strategies will be implemented, and the effectiveness of each approach will be analyzed. Participants will be recruited from the general Australian population and randomized online. The trial will last for 4 weeks. Results: Small but clinically significant increases in well-being symptoms are expected to be detected in the intervention group compared with the control group

There is no association between the omega-3 index and depressive symptoms in patients with heart disease who are low fish consumers

Background: Long chain Omega-3 polyunsaturated fatty acids (LCn3PUFAs) may improve cardiovascular health and depression. This study investigated the relationships between erythrocyte membrane LCn3PUFA status, depression and angina symptoms in patients with heart disease.  Methods: We recruited 91 patients (65 males and 26 females, mean age 59.2 ± 10.3 years) with heart disease and depressive symptoms (Center for Epidemiological Studies Depression Scale, CES-D ≥ 16) and low fish/fish oil intakes. The Omega-3 Index (EPA+DHA) of erythrocyte membranes (as a percentage of total fatty acids) was assessed by gas chromatography. Depression status was measured by both self-report and clinician-report scales; CES-D and the Hamilton depression scale (HAM-D). Angina symptoms were measured using the Seattle Angina Questionnaire and the Canadian Cardiovascular Society Classification for Angina Pectoris.  Results: The mean Omega-3 Index was 4.8 ± 1.0% (±SD). Depression scores measured by CES-D and HAM-D were 29.2 ± 8.8 (moderate to severe) and 11.0 ± 5.7 (mild) (arbitrary units) respectively reflecting a different perception of depressive symptoms between patients and clinicians. Angina status was inversely associated with depression scores (r > -0.26, P < 0.03). There were no significant relationships between individual LCn3PUFA or the Omega-3 Index and either the depression scores or the angina symptoms.  Conclusion: Worse angina status was associated with worse depression, but the Omega-3 Index was not associated with symptoms of depression or angina in patients with heart disease

The promise and the reality: a mental health workforce perspective on technology-enhanced youth mental health service delivery

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background: Digital technologies show promise for reversing poor engagement of youth (16–24 years) with mental health services. In particular, mobile and internet based applications with communication capabilities can augment face-to-face mental health service provision. The literature in this field, however, fails to adequately capture the perspectives of the youth mental health workforce regarding utility and acceptability of technology for this purpose. Methods: This paper describes results of in-depth qualitative data drawn from various stakeholders involved in provision of youth mental health services in one Australian rural region. Data were obtained using focus groups and semi-structured interviews with regional youth mental health clinicians, youth workers and support/management staff (n = 4 focus groups; n = 8 interviews) and analysed via inductive thematic analysis. Results: Results question the acceptability of technology to engage clients within youth mental health services. Six main themes were identified: young people in a digital age, personal connection, power and vulnerability, professional identity, individual factors and organisational legitimacy. Conclusions:These findings deepen the understanding of risks and challenges faced when adopting new technologies in mental healthcare. Recommendations for technology design and implementation in mental health services are made

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Chronic depression : clinical features, classification and natural history / Geoffrey Schrader.

Bibliography: leaves 339-361.xii, 361 leaves ; 30 cm.Thesis (Ph.D.)--University of Adelaide, Dept. of Psychiatry, 199

Predictors of depression 12 months after cardiac hospitalization: the identifying depression as a comorbid condition study

The definitive version is available at www.blackwell-synergy.comObjective: To determine characteristics which predict depression at 12 months after cardiac hospitalization, and track the natural history of depression. Method: Depressive symptoms were monitored at baseline, 3 and 12 months in a cohort of 785 patients, using the self-report Center for Epidemiological Studies Depression Scale. Multinomial regression analyses of baseline clinical and demographic variables identified characteristics associated with depression at 12 months. Results: Three baseline variables predicted moderate to severe depression at 12 months: depression during index admission, past history of emotional health problems and current smoking. For those who were depressed during cardiac hospitalization, 51% remained depressed at both 3 and 12 months. Persistence was more evident in patients who had moderate to severe depressive symptoms when hospitalized. Mild depression was as likely to persist as to remit. Conclusions: Three clinically accessible characteristics at the time of cardiac hospitalization can assist in predicting depression at 12 months and may aid treatment decisions. Depressive symptoms persist in a substantial proportion of cardiac patients up to 12 months after hospitalization. Key words: depression, heart disease, inpatient, natural history, predictor.Geoff Schrader, Frida Cheok, Ann-Louise Hordacre and Julie Marke