Does perfectionism in bipolar disorder pedigrees mediate associations between anxiety/stress and mood symptoms?

BACKGROUND: Bipolar disorder (BD) and the anxiety disorders are highly comorbid. The present study sought to examine perfectionism and goal attainment values as potential mechanisms of known associations between anxiety, stress and BD symptomatology. Measures of perfectionism and goal attainment values were administered to 269 members of BD pedigrees, alongside measures of anxiety and stress, and BD mood symptoms. Regression analyses were used to determine whether perfectionism and goal attainment values were related to depressive and (hypo)manic symptoms; planned mediation models were then used to test the potential for perfectionism to mediate associations between anxiety/stress and BD symptoms. RESULTS: Self-oriented perfectionism was associated with chronic depressive symptoms; socially-prescribed perfectionism was associated with chronic (hypo)manic symptoms. Self-oriented perfectionism mediated relationships between anxiety/stress and chronic depressive symptoms even after controlling for chronic hypomanic symptoms. Similarly, socially-prescribed perfectionism mediated associations between anxiety/stress and chronic hypomanic symptoms after controlling for chronic depressive symptoms. Goal attainment beliefs were not uniquely associated with chronic depressive or (hypo)manic symptoms. CONCLUSIONS: Cognitive styles of perfectionism may explain the co-occurrence of anxiety and stress symptoms and BD symptoms. Psychological interventions for anxiety and stress symptoms in BD might therefore address perfectionism in attempt to reduce depression and (hypo)manic symptoms in addition to appropriate pharmacotherapy.

What clinical features precede the onset of bipolar disorder?

Despite a growing number of reports, there is still limited knowledge of the clinical features that precede the onset of bipolar disorder (BD). To explore this, we investigated baseline data from a prospectively evaluated longitudinal cohort of subjects aged 12-30 years to compare: first, lifetime rates of clinical features between a) subjects at increased genetic risk for developing BD ('AR'), b) participants from families without mental illness ('controls'), and c) those with established BD; and, second, prior clinical features that predict the later onset of affective disorders in these same three groups. This is the first study to report such comparisons between these three groups (though certainly not the first to compare AR and control samples). 118 AR participants with a parent or sibling with BD (including 102 with a BD parent), 110 controls, and 44 BD subjects were assessed using semi-structured interviews. AR subjects had significantly increased lifetime risks for depressive, anxiety and behavioural disorders compared to controls. Unlike prior reports, preceding anxiety and behavioural disorders were not found to increase risk for later onset of affective disorders in the AR sample, perhaps due to limited sample size. However, preceding behavioural disorders did predict later onset of affective disorders in the BD sample. The findings that i) AR subjects had higher rates of depressive, anxiety and behavioural disorders compared to controls, and ii) prior behavioural disorders increased the risk to later development of affective disorders in the BD group, suggest the possibility of therapeutic targeting for these disorders in those at high genetic risk for BD.

Cognitive styles and clinical correlates of childhood abuse in bipolar disorder.

OBJECTIVES: In a relatively small number of previous studies, childhood abuse has been found to be associated with more severe symptom course, earlier onset, greater comorbidity, and greater suicidality in those diagnosed with bipolar disorder. There have been no prior reports looking for any association between childhood abuse and cognitive style. This study aimed to examine the relationship between cognitive factors, such as response styles to depressed mood and dysfunctional attitudes, clinical features, and childhood physical and sexual abuse in this population. METHODS: A total of 157 adult participants diagnosed with DSM-IV bipolar disorder I or II were assessed on clinical features of this condition and measures of childhood sexual and physical abuse. Participants also completed self-report questionnaires covering areas such as symptom measures of depression, anxiety and stress, dysfunctional attitudes, and response styles to depressed mood. RESULTS: Seventy-four participants (37%) reported having experienced either sexual or physical abuse. Those who reported physical or sexual abuse were significantly more likely to report self-harm or suicidal behaviors and showed higher stress scores. Specifically, those who reported sexual abuse were more likely to have simple phobias, to have attempted suicide, and to have had more hospitalizations for depression. After controlling for current mood severity, there were no significant differences on the self-report cognitive style measures for those who reported childhood sexual or physical abuse compared to those who did not report abuse. CONCLUSIONS: Cognitive styles were not found to be associated with childhood sexual or physical abuse in participants with bipolar disorder. Stress may be important to target in psychological interventions, whilst special attention should also be paid to those with a history of sexual abuse given the greater likelihood of suicide attempt.

Anxiety, stress and perfectionism in bipolar disorder.

BACKGROUND: Previous reports have highlighted perfectionism and related cognitive styles as a psychological risk factor for stress and anxiety symptoms as well as for the development of bipolar disorder symptoms. The anxiety disorders are highly comorbid with bipolar disorder but the mechanisms that underpin this comorbidity are yet to be determined. METHOD: Measures of depressive, (hypo)manic, anxiety and stress symptoms and perfectionistic cognitive style were completed by a sample of 142 patients with bipolar disorder. Mediation models were used to explore the hypotheses that anxiety and stress symptoms would mediate relationships between perfectionistic cognitive styles, and bipolar disorder symptoms. RESULTS: Stress and anxiety both significantly mediated the relationship between both self-critical perfectionism and goal attainment values and bipolar depressive symptoms. Goal attainment values were not significantly related to hypomanic symptoms. Stress and anxiety symptoms did not significantly mediate the relationship between self-critical perfectionism and (hypo)manic symptoms. LIMITATIONS: 1. These data are cross-sectional; hence the causality implied in the mediation models can only be inferred. 2. The clinic patients were less likely to present with (hypo)manic symptoms and therefore the reduced variability in the data may have contributed to the null findings for the mediation models with (hypo) manic symptoms. 3. Those patients who were experiencing current (hypo)manic symptoms may have answered the cognitive styles questionnaires differently than when euthymic. CONCLUSION: These findings highlight a plausible mechanism to understand the relationship between bipolar disorder and the anxiety disorders. Targeting self-critical perfectionism in the psychological treatment of bipolar disorder when there is anxiety comorbidity may result in more parsimonious treatments.

Comparison of depressive episodes in bipolar disorder and in major depressive disorder within bipolar disorder pedigrees.

BACKGROUND: Although genetic epidemiological studies have confirmed increased rates of major depressive disorder among the relatives of people with bipolar affective disorder, no report has compared the clinical characteristics of depression between these two groups. AIMS: To compare clinical features of depressive episodes across participants with major depressive disorder and bipolar disorder from within bipolar disorder pedigrees, and assess the utility of a recently proposed probabilistic approach to distinguishing bipolar from unipolar depression. A secondary aim was to identify subgroups within the relatives with major depression potentially indicative of 'genetic' and 'sporadic' subgroups. METHOD: Patients with bipolar disorder types 1 and 2 (n = 246) and patients with major depressive disorder from bipolar pedigrees (n = 120) were assessed using the Diagnostic Interview for Genetic Studies. Logistic regression was used to identify distinguishing clinical features and assess the utility of the probabilistic approach. Hierarchical cluster analysis was used to identify subgroups within the major depressive disorder sample. RESULTS: Bipolar depression was characterised by significantly higher rates of psychomotor retardation, difficulty thinking, early morning awakening, morning worsening and psychotic features. Depending on the threshold employed, the probabilistic approach yielded a positive predictive value ranging from 74% to 82%. Two clusters within the major depressive disorder sample were found, one of which demonstrated features characteristic of bipolar depression, suggesting a possible 'genetic' subgroup. CONCLUSIONS: A number of previously identified clinical differences between unipolar and bipolar depression were confirmed among participants from within bipolar disorder pedigrees. Preliminary validation of the probabilistic approach in differentiating between unipolar and bipolar depression is consistent with dimensional distinctions between the two disorders and offers clinical utility in identifying patients who may warrant further assessment for bipolarity. The major depressive disorder clusters potentially reflect genetic and sporadic subgroups which, if replicated independently, might enable an improved phenotypic definition of underlying bipolarity in genetic analyses.

Pain and rejection sensitivity in bipolar depression.

OBJECTIVES: Little is known regarding the correlates of pain in bipolar disorder. Recent neuroimaging studies support the contention that depression, as well as pain distress and rejection distress, share the same neurobiological circuits. In a recently published study, we confirmed the hypothesis that perception of increased pain during treatment-refractory depression, predominantly unipolar, was related to increased rejection sensitivity. In the present study, we aimed to test this same hypothesis for bipolar depression. METHODS: The present study analysed data from 67 patients presenting to the Black Dog Institute Bipolar Disorders Clinic in Sydney, Australia. The patients all met DSM-IV criteria for bipolar disorder and had completed a self-report questionnaire regarding perceived pain and rejection sensitivity during depression. RESULTS: A significant increase in the experience of headaches (p=0.003) as well as chest pain (p=0.004) during bipolar depression was predicted by a major increase in rejection sensitivity when depressed, i.e., state rejection sensitivity. Being rejection sensitive in general, i.e., trait rejection sensitivity, did not predict pain during depression. CONCLUSIONS: The experience of increased headaches and chest pain during bipolar depression is related to increased rejection sensitivity during depression. Research to further elucidate this relationship is required.

Characteristics of bipolar disorder in an Australian specialist outpatient clinic: comparison across large datasets.

OBJECTIVES: There have been relatively few detailed reports on the sociodemographic and clinical characteristics of bipolar disorder in large outpatient clinical samples. This paper reports on findings from the Black Dog Institute Bipolar Disorders Clinic (BDI-BDC) and compares this dataset with the predominantly outpatient Stanley Foundation Bipolar Disorders Network (SFBN) and Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) samples. METHODS: A total of 217 patients with DSM-IV bipolar disorder were assessed in detail in the BDI-BDC using a series of standardized and non-standardized structured interviews. Ninety per cent had bipolar I disorder, and 10% bipolar II disorder. This sample was compared with the SFBN and STEP-BD datasets. RESULTS: The sociodemographic characteristics of the three samples were remarkably similar. Female gender and younger age were overrepresented compared to the general population. Functional impairment, indicated by marital status and labour force participation, was clearly more common among the study subjects than in the general population. In all three samples, prior educational attainment was higher than the general population. With respect to clinical features, approximately half of each sample was euthymic and approximately one-third was in a DSM-IV episode of depression at study entry. One-half reported depression as their first episode of mood disturbance. Similar proportions identified positive family histories of bipolar disorder (40%) and unipolar depression (55%). Other clinical characteristics demonstrated more variation between the samples. The STEP-BD population reported an earlier age of onset. The SFBN subjects reported higher numbers of overall episodes, but psychotic features and suicide attempts were less common than in the BDI-BDC sample. CONCLUSIONS: This report highlights the marked commonalities of the sociodemographic and clinical characteristics of patients with bipolar disorder recruited predominantly in the outpatient setting in three different continents, that is, Australia, North America and Europe. It also demonstrates some critical distinctions between such samples, emphasizing the need to be aware of these differences when interpreting findings, such as treatment outcome, from different bipolar disorder datasets.

A randomized controlled trial of cognitive therapy for bipolar disorder: focus on long-term change.

BACKGROUND: This study reports the outcome of a randomized controlled trial of cognitive therapy (CT) for bipolar disorder. The treatment protocol differed from other published forms of CT for bipolar disorder through the addition of emotive techniques. METHOD: Fifty-two patients with DSM-IV bipolar I or II disorder were randomly allocated to a 6-month trial of either CT or treatment as usual, with both treatment groups also receiving mood stabilizers. Outcome measures included relapse rates, dysfunctional attitudes, psychosocial functioning, hopelessness, self-control, and medication adherence. Patients were assessed during treatment by independent raters blind to the patients' group status. RESULTS: At posttreatment, patients allocated to CT had experienced less severe depression scores (Beck Depression Inventory and Montgomery-Asberg Depression Rating Scale) and less dysfunctional attitudes. After controlling for the presence of major depressive episode at baseline, there was a statistical trend toward a greater time to depressive relapse (p=.06) for the CT group. At 12-month follow-up, the CT group showed a trend toward lower Young Mania Rating Scale scores and improved behavioral self-control. The Clinical Global Impressions-Improvement scale, comparing the 18 months prior to treatment to the severity of illness status at follow-up, showed a substantial difference between groups in favor of CT. CONCLUSION: Our findings corroborate previous bipolar disorder research in demonstrating the value of CT, particularly immediately post-treatment, and indicate some continuation (albeit diminishing) of benefits in the succeeding 12 months. These findings suggest that psychological booster sessions may be crucial for maintaining the beneficial effects of cognitive therapy.

Cognitive behavioural therapy for depression, panic disorder and generalized anxiety disorder: a meta-regression of factors that may predict outcome.

OBJECTIVE: To determine which factors impact on the efficacy of cognitive behavioural therapy (CBT) for depression and anxiety. Factors considered include those related to clinical practice: disorder, treatment type, duration and intensity of treatment, mode of therapy, type and training of therapist and severity of patients. Factors related to the conduct of the trial were also considered, including: year of study, country of study, type of control group, language, number of patients and percentage of dropouts from the trial. METHOD: We used the technique of meta-analysis to determine an overall effect size (standardized mean difference calculated using Hedges' g) and meta-regression to determine the factors that impact on this effect size. We included randomized controlled trials with a wait list, pill placebo or attention/psychological placebo control group. Study participants had to be 18 years or older and all have diagnosed depression, panic disorder (with or without agoraphobia) or generalized anxiety disorder (GAD). Outcomes of interest included symptom, functioning and health-related quality of life measures, reported as continuous variables at post-treatment. RESULTS: Cognitive behavioural therapy for depression, panic disorder and GAD had an effect size of 0.68 (95% CI=0.51-0.84, n=33 studies, 52 comparisons). The heterogeneity in the effect sizes was fully explained by treatment, duration of therapy, inclusion of severe patients in the trial, year of study, country of study, control group, language and number of dropouts from the control group. Disorder was not a significant predictor of the effect size. CONCLUSIONS: Cognitive behavioural therapy is significantly less effective for severe patients and trials that compared CBT to a wait-list control group found significantly larger effect sizes than those comparing CBT to an attention placebo, but not to a pill placebo. Further research is needed to determine whether CBT is effective when provided by others than psychologists and whether it is effective for non-English-speaking patient groups.

Cost-effectiveness of cognitive-behavioural therapy and drug interventions for major depression.

OBJECTIVE: Antidepressant drugs and cognitive-behavioural therapy (CBT) are effective treatment options for depression and are recommended by clinical practice guidelines. As part of the Assessing Cost-effectiveness -- Mental Health project we evaluate the available evidence on costs and benefits of CBT and drugs in the episodic and maintenance treatment of major depression. METHOD: The cost-effectiveness is modelled from a health-care perspective as the cost per disability-adjusted life year. Interventions are targeted at people with major depression who currently seek care but receive non-evidence based treatment. Uncertainty in model inputs is tested using Monte Carlo simulation methods. RESULTS: All interventions for major depression examined have a favourable incremental cost-effectiveness ratio under Australian health service conditions. Bibliotherapy, group CBT, individual CBT by a psychologist on a public salary and tricyclic antidepressants (TCAs) are very cost-effective treatment options falling below 10,000 Australian dollars per disability-adjusted life year (DALY) even when taking the upper limit of the uncertainty interval into account. Maintenance treatment with selective serotonin re-uptake inhibitors (SSRIs) is the most expensive option (ranging from 17,000 Australian dollars to 20,000 Australian dollars per DALY) but still well below 50,000 Australian dollars, which is considered the affordable threshold. CONCLUSIONS: A range of cost-effective interventions for episodes of major depression exists and is currently underutilized. Maintenance treatment strategies are required to significantly reduce the burden of depression, but the cost of long-term drug treatment for the large number of depressed people is high if SSRIs are the drug of choice. Key policy issues with regard to expanded provision of CBT concern the availability of suitably trained providers and the funding mechanisms for therapy in primary care.

The burden of major depression avoidable by longer-term treatment strategies.

BACKGROUND: Major depression is the largest single cause of nonfatal disease burden in Australia. Effective drug and psychological treatments exist, yet are underused. OBJECTIVE: To quantify the burden of disease currently averted in people seeking care for major depression and the amount of disease burden that could be averted in these people under optimal episodic and maintenance treatment strategies. DESIGN: Modeling impact of current and optimal treatment strategies based on secondary analysis of mental health survey data, studies of the natural history of major depression, and meta-analyses of effectiveness data. Monte Carlo simulation of uncertainty in the model. SETTING: The cohort of Australian adults experiencing an episode of major depression in 2000 are modeled through "what if" scenarios of no treatment, current treatment, and optimal treatment strategies with cognitive behavioral therapy or antidepressant drug treatment. MAIN OUTCOME MEASURE: Disability-Adjusted Life Year. RESULTS: Current episodic treatment averts 9% (95% uncertainty interval, 6%-12%) of the disease burden of major depression in Australian adults. Optimal episodic treatment with cognitive behavioral therapy could avert 28% (95% uncertainty interval, 19%-39%) of this disease burden, and with drugs 24% (95% uncertainty interval, 19%-30%) could be averted. During the 5 years after an episode of major depression, current episodic treatment patterns would avert 13% (95% uncertainty interval, 10%-17%) of Disability-Adjusted Life Years, whereas maintenance drug treatment could avert 50% (95% uncertainty interval, 40%-60%) and maintenance cognitive behavioral therapy could avert 52% (95% uncertainty interval, 42%-64%), even if adherence of around 60% is taken into account. CONCLUSIONS: Longer-term maintenance drug or psychological treatment strategies are required to make significant inroads into the large disease burden associated with major depression in the Australian population.

Using the effect size to model change in preference values from descriptive health status.

OBJECTIVES: This pilot study describes a modelling approach to translate group-level changes in health status into changes in preference values, by using the effect size (ES) to summarize group-level improvement. METHODS: ESs are the standardized mean difference between treatment groups in standard deviation (SD) units. Vignettes depicting varying severity in SD decrements on the SF-12 mental health summary scale, with corresponding symptom severity profiles, were valued by a convenience sample of general practitioners (n = 42) using the rating scale (RS) and time trade-off methods. Translation factors between ES differences and change in preference value were developed for five mental disorders, such that ES from published meta-analyses could be transformed into predicted changes in preference values. RESULTS: An ES difference in health status was associated with an average 0.171-0.204 difference in preference value using the RS, and 0.104-0.158 using the time trade off. CONCLUSIONS: This observed relationship may be particular to the specific versions of the measures employed in the present study. With further development using different raters and preference measures, this approach may expand the evidence base available for modelling preference change for economic analyses from existing data.

Evidence-based care for alcohol use disorders is affordable.

OBJECTIVE: Despite efficacious treatment, alcohol use disorders contribute significantly to the disability burden. Although wider dissemination of evidence-based health care may impact on the population burden, the affordability of this strategy is unknown. This article compares the cost-effectiveness of current treatment for alcohol use disorders with the cost-effectiveness of optimal treatment, a hypothetical treatment scenario that has been informed by evidence-based practice to determine the affordability of such an approach. METHOD: This study calculated the cost-effectiveness in the Australian population of evidence-based health care for alcohol harmful use and alcohol dependence, as defined by the International Classification of Diseases, Injuries, and Causes of Death, 10th Revision. Outcome was calculated as years lived with disability (YLD) averted. Data from the Australian National Survey of Mental Health and Wellbeing, in conjunction with published meta-analyses and expert reviews, were used to estimate 1-year costs (1997-98 Australian dollars) and YLD averted by current health care services as well as costs and outcomes for an optimal strategy of evidence-based health care. RESULTS: Of those currently seeking treatment, approximately 45% of those with alcohol harmful use and 58% of those with alcohol dependence receive an evidence-based intervention. The cost of this care was estimated at 73 million dollars, resulting in a cost per YLD averted of 96,813 dollars for harmful use of alcohol and 98,095 dollars for alcohol dependence. Under optimal care for harmful use, costs declined and health gains doubled, substantially reducing the cost per YLD averted to 8861 dollars. For dependence, costs doubled, but optimal treatment resulted in increased health gains, reducing the cost per YLD to 57,542 dollars. CONCLUSIONS: Evidence-based care for alcohol use disorders would produce greater population health gain at an increased cost for alcohol dependence but at a reduced cost for harmful use of alcohol. For both disorders, there are substantial increases in cost-effectiveness.

Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment of ten mental disorders.

BACKGROUND: Mental health survey data are now being used proactively to decide how the burden of disease might best be reduced. AIMS: To study the cost-effectiveness of current and optimal treatments for mental disorders and the proportion of burden avertable by each. METHOD: Data for three affective, four anxiety and two alcohol use disorders and for schizophrenia were compared interms of cost, burden averted and efficiency of current and optimal treatment. We then calculated the burden unavertable given current knowledge. The unit of health gain was a reduction in the years lived with disability (YLDs). RESULTS: Summing across all disorders, current treatment averted 13% of the burden, at an average cost of 30,000 Australian dollars per YLD gained. Optimal treatment at current coverage could avert 20% of the burden, at an average cost of 18,000 Australian dollars per YLD gained. Optimal treatment at optimal coverage could avert 28% of the burden, at 16,000 Australian dollars per YLD gained. Sixty per cent of the burden of mental disorders was deemed to be unavertable. CONCLUSIONS: The efficiency of treatment varied more than tenfold across disorders. Although coverage of some of the more efficient treatments should be extended, other factors justify continued use of less-efficient treatments for some disorders.

Reducing the burden of affective disorders: is evidence-based health care affordable?

BACKGROUND: Affective disorders remain the leading cause of disability burden despite the availability of efficacious treatment. A wider dissemination of evidence-based health care is likely to impact this burden, however the affordability of such a strategy at the population level is unknown. This study calculated the cost-effectiveness of evidence-based health care for depression, dysthymia and bipolar disorder in the Australian population, and determined whether it was affordable, based on current mental health-related expenditure and outcomes for these disorders. METHODS: Cost-effectiveness was expressed in costs per years lived with disability (YLDs) averted, a population health summary measure of disability burden. Data from the Australian National Survey of Mental Health and Wellbeing, in conjunction with published randomized trials and direct cost estimates, were used to estimate the 1-year costs and YLDs averted by current health care services, and costs and outcomes for an optimal strategy of evidence-based health care. RESULTS: Current direct mental health-related health care costs for affective disorders in Australia were 615 million dollars (1997-98 Australian dollars). This treatment averted just under 30,000 YLDs giving a cost-effectiveness ratio of 20,633 dollars per YLD. Outcome could be increased by nearly 50% at similar cost with implementation of an evidence-based package of optimal treatment, halving the cost-effectiveness ratio to 10,737 dollars per YLD. LIMITATIONS: The method to estimate YLDs averted from the literature requires replication. The costs of implementing evidence-based health care have not been estimated. CONCLUSIONS: Evidence-based health care for affective disorders should be encouraged on both efficacy and efficiency grounds.

Cost-effectiveness of current and optimal treatment for schizophrenia.

BACKGROUND: This paper is part of a project to identify the proportion of the burden of each mental disorder averted by current and optimal interventions, and the cost-effectiveness of both. AIMS: To use epidemiological data on schizophrenia to model the cost-effectiveness of current and optimal treatment. METHOD: Calculate the burden of schizophrenia in the years lived with disability (YLD) component of disability-adjusted life-years lost, the proportion averted by current interventions, the proportion that could be averted by optimal treatment and the cost-effectiveness of both. RESULTS: Current interventions avert some 13% of the burden, whereas 22% could be averted by optimal treatment. Current interventions cost about AUS 200,000 dollars per YLD averted, whereas optimal treatment at a similar cost could increase the number of YLDs averted by two-thirds. Even so, the majority of the burden of schizophrenia remains unavertable. CONCLUSIONS: Optimal treatment is affordable within the present budget and should be implemented.

Child sexual abuse revisited.

Notification of abuse should trigger initiatives to prevent further abuse and ameliorate adverse consequences.

Using epidemiological data to model efficiency in reducing the burden of depression*

BACKGROUND: The Global Burden of Disease study has suggested that mental disorders are the leading cause of disability burden in the world. This study takes the leading cause of mental disorder burden, depression, and trials an approach for defining the present and optimal efficiency of treatment in an Australian setting. AIMS OF THE STUDY: To examine epidemiological and service use data for depression to trial an approach for modelling (i) the burden that is currently averted from current care, (ii) the burden that is potentially avertable from a hypothetical regime of optimal care, (iii) the efficiency or cost-effectiveness of both current and optimal services for depression and (iv) the potential of current knowledge for reducing burden due to depression, by applying the WHO five-step method for priorities for investment in health research and development. METHODS: Effectiveness and efficiency were calculated in disability adjusted life years (DALYs) averted by adjusting the disability weight for people who received efficacious treatment. Data on service use and treatment outcome were obtained from a variety of secondary sources, including the Australian National Survey of Mental Health and Wellbeing, and efficacy of individual treatments from published meta-analyses expressed in effect sizes. Direct costs were estimated from published sources. RESULTS: Fifty-five percent of people with depression had had some contact with either primary care or specialist services. Effective coverage of depression was low, with only 32% of cases receiving efficacious treatment that could have lessened their severity (averted disability). In contrast, a proposed model of optimal care for the population management of depression provided increased treatment contacts and a better outcome. In terms of efficiency, optimal care dominated current care, with more health gain for less expenditure (28 632 DALYs were averted at a cost of AUD295 million with optimal care, versus 19 297 DALYs averted at a cost of AUD720 million with current care). However, despite the existence of efficacious technologies for treating depression, only 13% of the burden was averted from present active treatment, primarily because of the low effective coverage. Potentially avertable burden is nearly three times this, if effective treatments can be delivered in appropriate amounts to all those who need it. DISCUSSION: This paper reports a method to calculate the burden currently averted from cross-sectional survey data, and to calculate the burden likely to be averted from an optimal programme estimated from randomized controlled trial data. The approach taken here makes a number of assumptions: that people are accurate in reporting their service use, that effect sizes are a suitable basis for modelling improvements in disability and that the method used to translate effect sizes to disability weight change is valid. The robustness of these assumptions is discussed. Nonetheless it would appear that while optimal care could do more than present services to reduce the burden of depression, current technologies for treating depression are insufficient. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: There is an urgent need to educate both clinicians (primary and specialist) and the general public in the effective treatments that are available for depression. IMPLICATIONS FOR HEALTH POLICIES: Over and above implementing treatments of known efficacy, more powerful technologies are needed for the prevention and treatment of depression. IMPLICATIONS FOR FURTHER RESEARCH: Modelling burden averted from a variety of secondary sources can introduce bias at many levels. Future research should examine the validity of approaches that model reductions in disability burden. A powerful treatment to relieve depression and prevent relapse is needed.