Search

Purpose: The early postnatal period is a time of increased risk for psychiatric admission. However, there is scope to further examine if this increase in risk extends to the entire perinatal period (pregnancy and first postnatal year), and how it compares to admission outside of the perinatal period. Methods: Data were linked across birth and hospital admission registers from July 2000 to December 2009. The study cohort, consisting of all pregnant and childbearing women with a psychiatric history, was divided into two groups: case women (at least one perinatal principal psychiatric admission in the study period) (38%) and comparison women (no perinatal principal psychiatric admissions) (62%). Outcomes were admission rate and length of stay adjusted for diagnosis, socio-demographic factors and timing of admission. Results: Antenatal and postnatal admissions rates were both higher than non-perinatal admission rates for case women for all diagnoses. There was little evidence that women with perinatal admissions were at an increased risk of admissions at other times. Socially disadvantaged women had significantly fewer and shorter admissions than their respective counterparts. Conclusions: The entire perinatal period is a time of increased risk for admission across the range of psychiatric disorders, compared to other times in a woman's childbearing years. Reduced admission rate and length of stay for socially disadvantaged women suggest lack of equity of access highlighting the importance of national perinatal mental health policy initiatives inclusive of disadvantaged groups. [ABSTRACT FROM AUTHOR]

Purpose: To examine the impact of substance use and other risk factors on conviction rates in people with a psychotic illness (PI) and other mental disorders (OMD) compared to those with no mental illness (NMI).Methods: This research is part of a longitudinal record-linked whole-population study of 467,945 children born in Western Australia (WA) between 1980 and 2001. This cohort was identified through linkages between the WA psychiatric case register, WA corrective services data and other state-wide registers. We assessed 184,147 individuals born during 1983-1991 to explore the impact of exposure to a variety of risk factors on conviction rates.Results: People with PI and OMD had higher conviction rates than those with NMI, with unadjusted incidence rate ratios (IRR) of 3.98 (95% CI 3.67-4.32) for PI and 3.18 (95% CI 3.03-3.34) for OMD. Adjusting for substance use reduced the rates by 60% in PI and 30% in OMD: IRRs 1.59 (95% CI 1.45-1.74) and 2.24 (2.12-2.37), respectively. Minimal change was seen when adjusting for other potential risk factors (including socio-demographics, victimisation and parental offending), with adjusted IRRs 1.58 (95% CI 1.43-1.74) for PI and 1.90 (95% CI 1.80-2.02) for OMD.Conclusions: Our analysis shows people with a mental illness have higher rates of conviction than those with NMI. Substance use has a major impact on this rate. Results suggest the need for a greater investment in programs addressing the issue of comorbid substance use with a view to reduce the rate of convictions in this population. [ABSTRACT FROM AUTHOR]

Purpose: Our aim was to establish the 12-month prevalence of violent victimisation in a large sample of adults with psychotic disorders (N = 1825), compare this to population estimates, and examine correlates of violent victimisation.Methods: The Australian national psychosis survey used a two-phase design to draw a representative sample of adults aged 18-64 years with psychotic disorders. Interview questions included psychopathology, cognition, sociodemographics, substance use, criminality, and childhood and adult victimisation. Multivariable logistic regression models were used to examine the independent contributions of known risk factors, clinical profile and childhood abuse, on risk of violent victimisation. Differences between men and women were examined.Results: Among adults with psychotic disorders, 12-month prevalence of any victimisation was 38.6% (males 37.4%, females 40.5%), and of violent victimisation was 16.4% (males 15.2%; females 18.3%). Violent victimisation was 4.8 times higher than the population rate of 3.4% (6.5 times higher for women; 3.7 times higher for men). Significant correlates of violent victimisation were established sociodemographic and behavioural risk factors predicting victimisation in the general community: younger age, residence in the most disadvantaged neighbourhoods, homelessness, lifetime alcohol abuse/dependence, and prior criminal offending. Among clinical variables, only mania and self-harm remained significant in the multivariable model. Childhood abuse was independently associated with violent victimisation.Conclusions: Rates of violent victimisation are high for people with psychotic disorders, especially women, compared to population rates. Greater exposure to sociodemographic and behavioural risks may render them particularly vulnerable to victimisation. Social cognition as a valuable treatment target is discussed. [ABSTRACT FROM AUTHOR]

Purpose: Information on older offenders' mental health service (MHS) used before and after sentence is sparse. We therefore aimed to determine the 1-year prevalence of MHS use before sentence, and the likelihood and predictors of MHS use in the 5-year post-sentence period by first-time older adult offenders (≥45 years).Methods: Pre- and post-sentence MHS use by a cohort of 1,853 first-time offenders over 45 years in Western Australia was determined through whole-population linked administrative data. Logistic regression models compared the 1-year pre-sentence MHS contacts between offenders and matched non-offenders. Cox proportional hazards regression models identified the socio-demographic, offending and pre-sentence health service variables that determined post-sentence MHS use.Results: Older offenders were six times more likely to have used MHSs than non-offenders before sentence. Substance use was the most commonly treated disorder. Non-custodial offenders were twice more likely than prisoners to have been treated for any mental disorder and substance use disorders, and violent offenders were four times more likely to have attempted self-harm than non-violent offenders before being sentenced. The strongest predictors of post-sentence MHS contact were past psychiatric diagnosis in offenders with a pre-sentence MHS contact, and pre-sentence hospitalisation for attempted self-harm or physical illness, or being a male in those without. Discontinuity in MHS use after sentence by over half of the offenders with a prior contact was prominent.Conclusion: Better detection and treatment of mental disorders in older offenders to ensure continuity of care at all transition points through age-sensitive correctional and community-based MHSs is needed. [ABSTRACT FROM AUTHOR]

Purpose: With the high risk of death associated with mental disorders and their increased prevalence in offenders, it is judicious to investigate the risk of post-sentence mortality with respect to offenders' psychiatric treatment history. Methods: Using linked administrative data for a whole-population retrospective cohort of first-time adult offenders ( n = 25,537) sentenced to either prison or non-custodial orders in Western Australia, we determined the risk and baseline predictors of post-sentence mortality. Results: Of 192 deaths within 2 years of sentence completion, deaths from injury/poisoning (55.6 %), cancer (13.3 %) and cardiovascular disorders (9.7 %) were the most common. Pre-sentence history of mental health service (MHS) contact doubled the risk of post-sentence all-cause and injury/poisoning-related mortality. Physical comorbidity was the strongest predictor of mortality irrespective of pre-sentence MHS contact. Baseline history of attempted self-harm and being an Indigenous male were associated with an elevated risk of death in offenders with a pre-sentence MHS contact. In offenders without a pre-sentence MHS contact, socio-economic disadvantage and incarceration almost doubled the risk of dying from any cause and injury/poisoning. Conclusions: Mortality risk in the 2 years following sentence completion is associated with pre-sentence health service use and a range of socio-demographic factors for both incarcerated and non-custodial offenders. The opportunity afforded by imprisonment could be exploited by provision of funding to identify and treat mental illness, impart preventive health education addressing modifiable risk factors and provide transitional care to community-based services, all of which may help reduce preventable post-sentence deaths. Diversion to non-custodial sentences is also a plausible option. [ABSTRACT FROM AUTHOR]

Purpose: Registers derived from administrative datasets are valuable tools in psychosis research, but diagnostic accuracy can be problematic. We sought to compare the relative performance of four methods for assigning a single diagnosis from longitudinal administrative clinical records when compared with reference diagnoses. Methods: Diagnoses recorded in inpatient and community mental health records were compared to research diagnoses of psychotic disorders obtained from semi-structured clinical interviews for 289 persons. Diagnoses were derived from administrative datasets using four algorithms; 'At least one' diagnosis, 'Last' or most recent diagnosis, 'Modal' or most frequently occurring diagnosis, and 'Hierarchy' in which a diagnostic hierarchy was applied. Agreements between algorithm-based and reference diagnoses for overall presence/absence of psychosis and for specific diagnoses of schizophrenia, schizoaffective disorder, and affective psychosis were examined using estimated prevalence rates, overall agreement, ROC analysis, and kappa statistics. Results: For the presence/absence of psychosis, the most sensitive and least specific algorithm ('At least one' diagnosis) performed best. For schizophrenia, 'Modal' and 'Last' diagnoses had greatest agreement with reference diagnosis. For affective psychosis, 'Hierarchy' diagnosis performed best. Agreement between clinical and reference diagnoses was no better than chance for diagnoses of schizoaffective disorder. Overall agreement between administrative and reference diagnoses was modest, but may have been limited by the use of participants who had been screened for likely psychosis prior to assessment. Conclusion: The choice of algorithm for extracting a psychosis diagnosis from administrative datasets may have a substantial impact on the accuracy of the diagnoses derived. An 'Any diagnosis' algorithm provides a sensitive measure for the presence of any psychosis, while 'Last diagnosis' is more accurate for specific diagnosis of schizophrenia and a hierarchical diagnosis is more accurate for affective psychosis. [ABSTRACT FROM AUTHOR]