Reviewing the revisions: what are the Australian Bureau of Statistics suicide figures really telling us?

To the Editor: For several years, the Australian Bureau of Statistics (ABS) has cautioned data users of likely underreporting of suicide statistics due to delays in coronial processes and (since 2006) exclusive reliance on the National Coronial Information System, which often contains incomplete information on cause of death.1 In 2009, the ABS introduced data revision processes that allowed additional information received to be added in two rounds of revisions at 12 and 24 months after the initial processing of coroner-certified deaths. This assisted coders in assigning more specific causes of death, thereby replacing the previous default “accident” category for ambiguous cases.

These changes have increased reported suicide rates, predominantly due to parallel reductions in deaths assigned to “Other ill-defined and unspecified causes of mortality” (International Classification of Diseases, 10th revision [ICD-10] code R99), which have more than halved, and “Event of undetermined intent” (ICD-10 codes Y10–Y34, Y87.2), which have reduced by around two-thirds.2,3 As these categories often represent “holding bays” for cases with insufficient information at initial processing, such decreases would be expected after the revisions. However, the figures remained inflated: in the 2006–2009 data (which have undergone two rounds of revision), ill defined causes of death remained more than double the levels recorded during the 1990s, and deaths of undetermined intent more than three times higher.3

Currently, the only reliable alternative source of suicide mortality data in Australia, albeit at the state level, is the Queensland Suicide Register (QSR). The differences between the two datasets have been detailed elsewhere.4 From 2003, the discrepancy between QSR data and ABS preliminary data on suicide grew exponentially, reaching 47.1% in 2007.4 Final revisions of ABS data from 2006 have reduced the gap to levels comparable to those seen during the 1990s and early 2000s (Box). However, the two datasets remain significantly different for 2003–2005, for which ABS data were not revised. It is reasonable to conclude that considerable numbers of suicides in these years remain misclassified.

Data users should be aware of these caveats when interpreting ABS statistics, particularly the recently announced 17% drop in suicide rate over the past decade.2 Continuous efforts to improve the reliability
and validity of suicide data are of paramount importance for developing and evaluating suicide prevention programs.

Differences in Queensland suicide rates reported by the
QSR and the ABS, 2001–2009

	Rate per 100 000
Year	QSR	ABS	Difference

2001	14.05	13.75	2.2%
2002	15.64	14.46	8.2%
2003	14.33	12.23	17.2%
2004	15.25	11.61	31.3%
2005	14.17	11.49	23.3%
2006	12.91	12.08 (F)	6.9%
2007	12.89	12.39 (F)	4.0%
2008	13.86	12.83 (F)	8.0%
2009	13.39	11.86 (F)	13.0%
QSR = Queensland Suicide Register. ABS = Australian Bureau of Statistics. F = final data after ABS revisions.

Philately and the Diagnostic and statistical manual of mental disorders

To the Editor: I was interested in the recent articles from the “Stamps of greatness” series, reprinted from past issues of the AMA Gazette, containing the memorialisation in stamps of famous historical leaders in medicine. Few readers would be likely to realise the association between the hobby of philately (the study and collection of postage stamps) itself and the development of the Diagnostic and statistical manual of mental disorders (DSM) classification of psychiatric illness.1

As an activity in itself, the hobby of philately is likely to have significant mental health benefits, such as enhancing organisational ability in a relaxed environment, as well as allowing the collector to enjoy the design and art of the stamps, and to engage intellectually with the value, geography and historical context of the stamp. However, the way in which philately applied to the development of the DSM is one of those chance moments that affect the subsequent course of history.

William Menninger, a member of a prominent United States family of psychiatrists from Kansas, was appointed to the 4th Service Command of the US Army during the Second World War after the sudden death of the head of the neuropsychiatric division. Menninger commented that on his appointment, his commanding general, Major General Henning, had little use for psychiatrists. However, when Menninger made his first formal call on Major General Henning, he found him working on his stamp collection and was able to develop immediate rapport with him because of a common interest in philately.

Menninger also displayed other talents, such as playing the piano and exhibiting an appropriate sense of humour in gatherings of senior military officers, which further enhanced his acceptance within the staff of the US Surgeon General and increased his influence, leading to his subsequent promotion to Brigadier General. Menninger used his position to add a substantial number of psychiatrists to the Surgeon General’s division.2

The acceptance that Menninger developed within the division also led him to chair a committee that produced the War department technical bulletin, medical 203 in 1946, a document that classified mental illness in a detailed fashion for the first time in the US. Menninger’s interest in psychological factors related to mental illness, rather than the more narrow categorisation of the mental illness of people in institutional care, appeared to strongly influence the document, which later had a significant effect on the development of the DSM by the American Psychiatric Association.2

Trends in pre-existing mental health disorders among parents of infants born in Western Australia from 1990 to 2005

It has long been established that parental mental health can affect children’s outcomes.1 These outcomes not only relate to children’s mental health but also language development, behaviour and physical health.2 An intergenerational pathway of how parental mental health can adversely affect children’s development has been suggested, which includes the direct effects of the illness and associated contextual stressors, such as poverty and disruptions to caregiving.3 Social welfare agencies have reported increasing numbers of families facing complex issues, including parental mental health problems and substance use, resulting in concerns about children’s wellbeing.4,5

While Australia has good data on the rates of mental health disorders in the Australian community, the prevalence of mental health disorders in parents is difficult to estimate. The National Survey of Mental Health and Wellbeing reported that 25% of individuals aged 16–44 years had a mental health disorder in the 12 months before completing the survey;6 this is an age group in which people are most likely to become parents. However data about adults with mental health disorders who are also parents are not routinely collected. To date, no studies have investigated the population prevalence of previous and current mental health disorders in parents, including trends over time. We aimed to fill this research gap by using mental health-related data on public and private hospital inpatient admissions and public outpatient contacts, to provide information on trends in parental mental health disorders in particular diagnostic groups.

Methods

Study population and data sources

To determine the population prevalence of parental mental health disorders, we conducted a retrospective cohort study of all parents of infants born in Western Australia between 1990 and 2005 using de-identified population level data, linked across health datasets. The health data collections used were WA’s Hospital Morbidity Data Collection, Mental Health Information System, Midwives Notification System and Birth Register. The Hospital Morbidity Data Collection contains information on all hospital admissions (public and private hospitals) with corresponding diagnostic information using the International Classification of Diseases (ICD)7 coding system recorded for each episode of care for parents from 1970 to 2005 (ICD-8 for 1970 to 1978, ICD-9 for 1979 to June 1999, ICD-10 for July 1999 to 2005). The Mental Health Information System contains information on all mental health-related public and private inpatient admissions and public outpatient contacts for the period 1980–2005. The Midwives Notification System contains birth information, including maternal characteristics and infant outcomes, for the period 1990–2005.

Each of the datasets are linked by the WA Data Linkage Branch using probabilistic matching that compares identifiers across datasets with extensive clerical review to resolve doubtful links.8 Only a unique project identifier and the individual’s clinical information is provided to the researcher; identifying information is removed.

Ethics

Ethics approval for this study was obtained from the University of Western Australia Human Research Ethics Committee, WA Department of Health Human Research Ethics Committee and Western Australian Aboriginal Health Ethics Committee.

Parental mental health and demographic variables

Mental health contact by parents was based on any reported diagnosis relating to mental health before the birth year of the child. Parents were identified as having had a mental health-related hospital admission or outpatient contact if they had mental health-related ICD diagnostic codes (ICD-9 codes 290–319) or external cause of self-harm (ICD-9 codes E950–E959).7 ICD-8 and ICD-10 codes were mapped to ICD-9 codes. Parents were defined as having a current mental health contact if there had been a contact in the 12 months before the year of birth. For each birth, parents with a prior mental health contact were counted once even if they had had more than one prior mental health contact; similarly, parents with a current mental health contact were counted once even if they had had more than one mental health contact in the 12 months before the birth year. Mental health diagnostic groups were determined by using the mental health diagnoses reported for the most recent contact before the birth year. If there was more than one diagnosis, the parent was grouped into each relevant diagnostic group. Diagnostic groups and codes for each group are listed in the Appendix.

Aboriginal and Torres Strait Islander children and parents (hereafter referred to as “Aboriginal”) were identified if the child or parent was listed in the birth or midwives data as being Aboriginal or Torres Strait Islander. Socioeconomic status was determined using the Index of Relative Social Disadvantage assigned to each collection district by the Australian Bureau of Statistics.9 Four levels of disadvantage were classified: 1 (low disadvantage) to 4 (high disadvantage).

Statistical analysis

Prevalence of prior mental health disorders in parents of children born during the period 1990–2005 (per 1000 births) was calculated for each birth year, using birth data as denominators. Separate analyses were conducted for mothers, fathers, all births, first births and mental health diagnostic groups. First births for mothers were defined as those for which the midwives data listed parity as zero and listed the sum of previous live births and still births as zero. For fathers, first births were identified by selecting the earliest birth. Age-specific rates were calculated for parental age.

Trends are presented as the percentage change in the odds for each increase in birth year and their 95% CI. Generalised estimating equations were used to calculate robust standard errors for odds ratios when analysing all births, owing to clustering of births to the same parent. Logistic regression was used to calculate odds ratios for Aboriginality, maternal age and socio-economic status where the outcome was a first-born child who had a mother with a prior mental health disorder, with estimated odds ratios stratified by birth-year group (1990–1993, 1994–1997, 1998–2001 and 2002–2005). R version 2.11.1 (R Foundation for Statistical Computing)10 was used for all analyses.

Results

Of 404 022 live births in the period 1990–2005, 43 700 children were born to mothers with a prior mental health disorder. Overall, prevalence of prior mental health disorders in mothers increased, from 76 per 1000 births in 1990 to 131 per 1000 births in 2005 (Box 1). There was an estimated 3.7% (95% CI, 3.5%–4.0%) increase per year in the odds of children being born to mothers with a prior mental health disorder. Prior mental health disorders in mothers of first-born children also increased, from 66 per 1000 births in 1990 to 88 per 1000 births in 2005 (a 2.0% [95% CI, 1.6%–2.4%] increase in odds per year), although there was a plateau from 2001 onwards (Box 1). When the analysis was restricted to mothers with a current mental health contact, there was an increase from 12 per 1000 births in 1990 to 27 per 1000 births in 2005 (4.7% [95% CI, 4.2%–5.2%] increase in odds per year) for all births, and an increase from 14 per 1000 births in 1990 to 17 per 1000 births in 2005 (2.4% [95% CI, 1.6%–3.3%] increase in odds per year) for first-born children (Box 1).

There were 31 201 children born to fathers with a prior mental health disorder. Overall, prevalence of prior mental health disorders in fathers increased, from 56 per 1000 births in 1990 to 88 per 1000 births in 2005 (Box 1). There was a 3.1% (95% CI, 2.8%–3.4%) increase per year in the odds of children being born to fathers with a prior mental health disorder. Prevalence of prior mental health disorders in fathers of first-born children increased at a similar rate, from 52 per 1000 births in 1990 to 71 per 1000 births in 2005 (a 2.4% [95% CI, 2.0%–2.8%] increase in odds per year). However, similar to mothers, the rate plateaued from 2000 onwards. When the analysis was restricted to fathers with a current mental health contact, the rates were 7.9 per 1000 births in 1990 and 8.2 per 1000 births in 2005 for all births, with fluctuations over that time (Box 1).

When we analysed the data by maternal diagnostic group, the most prevalent disorders among mothers, at any time before birth, were substance-related disorders — prevalence increased from 19 per 1000 births in 1990 to 32 per 1000 births in 2005 (4.6% increase per year; Box 2). Among mothers, there were also large increases in adjustment and stress-related disorders (5.5% per year) and non-organic psychotic disorders (16.7% per year). The most prevalent disorders among fathers at any time before birth were substance-related disorders, which increased from 32 per 1000 births to 40 per 1000 births (1.7% increase per year; Box 2). Among fathers, there were also large increases in organic disorders (6.7% per year) and adjustment and stress-related disorders (9.3% per year).

The proportion of Aboriginal children born to mothers with a prior mental health disorder (269 per 1000 births) was more than twice that for non-Aboriginal children (119 per 1000 births) in 2005. The rates were lower for fathers, but there was a similar difference between Aboriginal children (204 per 1000 births) and non-Aboriginal children (80 per 1000 births). The rates for Aboriginal and non-Aboriginal children had increased from 1990 to 2005, although the increases were greater for Aboriginal children (5.8% v 3.3% increase in odds per year for mothers; 6.5% v 2.6% increase in odds per year for fathers).

There was a higher prevalence of mental health disorders in mothers and fathers aged < 20 years in 2005 compared with the other age groups (158 per 1000 births and 147 per 1000 births, respectively), closely followed by those aged 20–29 years (148 per 1000 births and 114 per 1000 births, respectively).

The results of a multiple logistic regression analysis of factors associated with the odds of the first child being born to a mother with a prior mental health disorder are shown in Box 3. Young maternal age (< 30 years), low socioeconomic status and being Aboriginal significantly increased the odds. An increasing temporal trend in the odds of being born to a mother with a prior mental health disorder was seen in the youngest maternal age category (< 20 years).

Discussion

Our study is one of few that have used population-level linked data to determine the prevalence of a prior history of mental health disorders in parents and, to our knowledge, the only study to examine trends over time. It shows that prevalence of prior mental health disorders increased in parents of infants born from 1990 to 2005; there was a 3.7% increase per year for mothers and a 3.1% increase per year for fathers. The lower prevalence for fathers could be due to underascertainment of fathers on the Birth Register, which has been documented previously.11

There are a number of possible reasons for the increase. It could be due to broader service availability in WA for inpatients and outpatients, the increasing trend to deinstitutionalise people with mental health disorders (particularly during the mid 1980s),12 and better data collection by the Mental Health Information System. However, there could be a true increase in the prevalence of mental health disorders in parents. A previous study by our group showed that there had been an increase in the prevalence of babies born with neonatal withdrawal syndrome in WA,13 indicating increasing drug use by pregnant women. This is also indicated by our data, which show increasing trends in mental health disorders relating to substance use between 1990 and 2005. Another study that used linked prescription and birth data has shown high and increasing use of antidepressants during pregnancy.14 An Australian national survey of psychosis also showed an increase (from 1997 to 2010) in the number of dependent children living at home with parents who have psychosis, particularly mothers.15 These data highlight the increasing burden of parental mental health disorders on the mental health system and on families.

The diagnostic group for which prevalence was highest, in mothers and fathers, was substance-related disorders. For mothers, prevalence was also high for three other diagnostic groups: self-harm ever; depression not otherwise classified and neurotic disorders; and adjustment and stress-related disorders. Aboriginal children had a greater burden of parental mental health disorders compared with non-Aboriginal children for both mothers and fathers. This is consistent with findings from a national survey which found that Aboriginal Australians were twice as likely to report high or very high levels of psychological distress compared with non-Aboriginal Australians.16 In addition, our study shows that there were larger increases over time in the proportions of Aboriginal children born to mothers and fathers with a prior mental health disorder compared with increases for non-Aboriginal children. This indicates an increasing burden in Aboriginal families of parents with a mental disorder, and highlights the need for culturally appropriate mental health services such as healing and wellbeing centres, as called for in the Bringing them home report.17

Younger parental age is also associated with a higher burden of mental health disorders and this has risen over time. National mental health surveys have shown that young people aged 16–24 years have the highest prevalence of mental health disorders in the 12 months before completing the survey,6 which is consistent with our findings.

Although the strengths of our study included its population-based nature and the long period of data collection, our data on prevalence of mental health disorders are likely to be underestimates because we only captured inpatient hospital admissions and public outpatient contacts in the Mental Health Information System. We did not have access to primary care data or a prescription database that could have provided data on individuals who saw general practitioners or received prescriptions for mental health disorders; therefore, we may have potentially missed patients in the community with mental health disorders. By only using hospital admissions data and public outpatient contact data, our sample is biased towards patients with more severe mental disorders.

Despite these limitations, the use of population-level data overcomes many of the difficulties associated with traditional research designs, such as surveys or interviews. Parents may be reluctant to admit to a mental health disorder, particularly those related to substance use. It is important to obtain prevalence estimates of parental mental health disorders to inform practitioners, service providers and policymakers on the extent of the burden and the resources required. Most importantly, our study shows that there has been an increase in prevalence of children born to parents with previous mental health contacts. Moreover, although under-ascertained, our study includes fathers, an important group who are often not captured or not assessed in surveys and screening tools. Our study also highlights high-risk groups that have had increasing mental health admissions over time, including Aboriginal families, younger parents and low socioeconomic groups. These high-risk groups should be a focus for intervention and prevention.

In terms of practice and policy implications, parents with mental health disorders should be offered early intervention, referral and support. The National Perinatal Depression Initiative has highlighted the importance of early assessment and intervention in the perinatal period.18 GPs and mental health workers also play important roles in discussing the ongoing impact of mental health disorders on families and in working with families to plan for respite and support when required. The National Institute for Health and Clinical Excellence has provided guidelines for the clinical management of antenatal and postnatal mental health problems experienced by mothers and has stipulated the importance of the ongoing management of mental disorders.19 As the World Health Organization has stated, “effective solutions for mental disorders are available . . . Some mental disorders can be prevented, while most can be treated”.20 Mental health needs to be considered during treatment and health care planning for parents, to alleviate the symptoms experienced by individuals and to reduce the impact of symptoms on children and their families.

1 Prevalence of children having a parent with a prior mental health disorder or current mental health contact (all birth and first births, Western Australia, 1990–2005)

2 Prevalence of children having a parent with a prior mental health disorder, by mental health diagnostic group (all births, Western Australia, 1990–2005)

3 Factors associated with the first child being born to a mother with a prior mental health disorder

Odds ratio (95% CI)

1990–1993

1994–1997

1998–2001

2002–2005

Aboriginal or Torres Strait Islander

1.3 (1.1–1.5)

1.2 (1.0–1.4)

1.2 (1.1–1.4)

Maternal age

< 20 years

1.9 (1.6–2.2)

1.7 (1.5–2.0)

2.1 (1.9–2.4)

2.2 (1.9–2.5)

20–29 years

1.2 (1.1–1.4)

1.2 (1.1–1.3)

1.3 (1.2–1.5)

1.4 (1.3–1.6)

30–39 years

Reference

> 39 years

1.2 (0.7–1.9)

1.0 (0.6–1.4)

1.4 (1.0–1.8)

1.2 (0.9–1.6)

Socioeconomic status

1 — low disadvantage

Reference

1.1 (1.0–1.3)

1.3 (1.2–1.5)

1.2 (1.1–1.4)

1.1 (1.0–1.2)

1.2 (1.0–1.3)

1.4 (1.2–1.6)

1.4 (1.3–1.6)

1.3 (1.2–1.5)

4 — high disadvantage

1.5 (1.3–1.7)

1.7 (1.5–1.9)

1.6 (1.5–1.8)

Changes to the Healthy Kids Check: will we get it right?

Are we at risk of over-medicalising and under-researching?

In 2011, the Australian Government announced plans to change the voluntary Healthy Kids Check (HKCheck) during 2012–2013,1 by lowering the age of screening to children aged 3 years and incorporating elements of social and emotional wellbeing. The HKCheck will be conducted by general practitioners, practice nurses and Aboriginal health workers, and will cost about $11 million over 5 years.2

The Expert Working Group developing the HKCheck has not made public what the check comprises and what screening will be involved. While the first media release focused on 3-year-olds and “social and emotional development”, the most recent release (March 2013) announced that the expanded HKCheck will be phased in initially in eight Medicare Local areas in 2013, and the target group will be children aged from 3 to 5 years.3

It is not clear from the latest media release if social and emotional development will be included, and whether the HKCheck will identify “at-risk” families (ie, those with risk factors for children with psychological, conduct and behavioural problems) or whether it will identify risk factors for childhood psychiatric disorders. One aim of a population screening program, such as the HKCheck, is to ensure support for children by identifying and referring families to an appropriate health professional for an in-depth assessment and appropriate intervention (if initial primary health screening finds children who potentially would benefit from this).

Conducting population screening raises a number of complex issues. We will discuss the potential health benefits and risks of population social–emotional screening of children 3–4 years of age, and propose options based on currently available evidence. The first 3 years of life are crucial in terms of neurodevelopment — trauma, stress and/or attachment disruption may have adverse effects on brain and psychological development.4 Early adversity is associated with a range of later difficulties in multiple domains in life, including development and psychiatric disorders;4 however, this important topic is beyond the scope of our article.

Screening for mental health in early childhood

Social and emotional wellbeing in early childhood is defined as a “young child’s capacity to experience, regulate and express emotions, form close and secure relationships, and explore the environment and learn . . . these capacities [are] best accomplished within the context of the caregiving environment that includes family, community and cultural expectations . . .”.5 This definition implies that promoting children’s social and emotional wellbeing means alleviating current distress and suffering; enhancing social and emotional competence; establishing and sustaining positive developmental trajectories; and taking a holistic approach rather than concentrating just on the child.

Population screening aims to accurately and inexpensively identify children in need of a more comprehensive social–emotional assessment. Screening instruments used for widespread detection should be brief; easy to administer, score and interpret; of acceptable reliability and validity; and able to provide information that is both developmentally appropriate and clinically useful. Recommended levels for specificity and sensitivity are greater than 80%. There is a need for a balance between identifying a sufficient proportion of “cases” to effectively improve early detection, while minimising false positives.6 Risks of screening include over-medicalising (ie, inter-preting normal and individual variation or transient disturbances as psychopathological conditions); not identifying relationship disturbances; and labelling (with the associated stigma). Finally, screening is potentially very costly.

Currently, there are a number of clinical instruments that examine social and emotional development in 3-year-olds.

The one-page Pediatric Symptom Checklist, for use by paediatricians, is a brief assessment from parental reporting of dysfunction in major areas of a child’s daily life. A positive score suggests the need for further evaluation by a qualified mental health worker. This instrument has a specificity of 68% and a sensitivity of 95% when compared with clinicians’ ratings of children’s psychosocial dysfunction.7
The Child Behavior Checklist (CBCL/1.5-5) for ages
1–5 years has good reliability and validity, but is lengthy (99 items).8 It is not a screening instrument, but is used as part of a comprehensive assessment by experienced clinicians.
The 11-item Brief Infant–Toddler Social and Emotional Assessment (BITSEA) assesses social–emotional abilities, such as empathy, prosocial behaviours and compliance,
up to age 36 months and takes about 10 minutes to complete.9 Research has shown that its internal consistency and inter-rater reliability are marginal.10
The Ages and Stages Questionnaire – Social Emotional (ASQ-SE) is a comprehensive tool for screening possible delays in social–emotional and developmental functioning in children. It takes 15 minutes to complete and its sensitivity has been found to be 71%–85%.11
Parents’ Evaluation of Developmental Status (PEDS) is a brief screening tool for developmental and behavioural screening and ongoing surveillance of children from birth through to 8 years of age. Summary psychometric figures are sensitivity 86% and specificity 74%. However, only two specific questions concern mental health issues, and its validity testing (that it measures what it purports to measure) is mainly derived from overall development and not specifically social–emotional development.12

While the BITSEA and ASQ-SE were developed as clinical screening tools, they were not designed for large-scale population screening. These instruments may be used in a number of clinical settings, although they are most easily applied where time is not an issue and by those who have in-depth knowledge of child development (eg, staff of child health clinics). The CBCL/1.5-5, the BITSEA and the ASQ-SE need to be purchased and require training to score.

In summary, none of these tools meets all requirements for a brief population screen of children’s social–emotional development.

Is it possible to characterise psycho-pathological conditions in early childhood?

The same clustering of symptoms seen in 3-year-olds also occurs in older children and adolescents, and these symptom clusters are associated with socioemotional impairment, including social problems or a negative impact on the family. Studies using available validated instruments and clinical assessment have found the most prevalent clusters to be anxiety disorders, attention deficit hyperactivity disorder (ADHD), depressive disorder and behavioural difficulties.13 Kowalenko notes a range of prevalence figures of 7%–26%, reflecting the need for caution in interpreting these data and for further research.13 Another population study reported prevalence rates of impairment of 7%–11% (Diagnostic and statistical manual of mental disorders [DSM-IV]) in children entering school.14

Some problem behaviours and symptoms in early childhood are not transient. Typically, research in this area involves measuring internalising (eg, anxiety15) and/or externalising (eg, aggression15) symptoms, or specific symptoms, including attention problems15 and post-traumatic stress disorder.16 In general, studies suggest moderate continuity of symptoms (although most studies are not continued into adolescence), and there can be a change in symptom presentation over time.17 Children who frequently engage in externalising or internalising problem behaviours are at greater risk of a range of negative long-term outcomes, including dropping out of school and incarceration.18,19 A repeated finding is that elevated aggression persists from the age of 3 years to middle childhood. Currently, there is no research showing screening results at 3 years being predictive of specific psychopathological conditions in adulthood.20

Risk factors identified for symptom clusters in 3-year-olds are similar to those in older children.21 For example, there is evidence of long-term implications of early impairment, including that caused by parental mental health problems.4 Relatively few empirical studies have quantified the long-term predictive strength of these risk factors, when measured at, or near, the age of school entry. The moderating and mediating variables (eg, family factors, socioeconomic status) associated with the persistence of difficulties are typically not included in current screening measures.

Potential benefits of screening

Waiting to screen, identify and intervene may leave children “at risk” and miss opportunities for early intervention, prevention and improved trajectories, resulting in loss of both health and future economic benefits.22 Psychosocial problems are increasingly difficult to change or correct at an older age, but a meta-analysis has demonstrated the effectiveness of intervention in early childhood.23 However, similar to older children, younger children generally do not receive interventions because the problems remain undetected.24 From a broader perspective, identifying high-risk or symptomatic young children, and providing accurate prevalence estimates, would enable appropriate funding for the health and educational services necessary to support these children and their families.

Limitations and barriers associated with screening

As well as the previously noted risks, there are challenges in terms of both GPs using screening instruments and parents attending services offered.25 While there is research highlighting some of the short-term and longer-term problems in at-risk groups, developmental psychopathology is complex and it may not be possible to design a screening tool that can accurately identify young children who will develop disorders in the future.

Emotional and behavioural symptoms in young children are a final common pathway produced by multiple possible aetiologies requiring individual treatment planning. It is currently unclear which domains a screening instrument should include.

Evidence-based early intervention programs have often involved economically disadvantaged families. While there are well researched early intervention programs, some programs were shown not to be beneficial and, until further evidence is available, some scepticism remains about the universal application of early intervention programs.5 Is it better to have a population-based approach to treatment that does not need screening, or screening that leads to more targeted interventions? Further research is needed.

Children identified as being in need of more assessment may overwhelm currently available Australian health care resources. Jureidini and Raven note that interventions must be widely and equitably available to those who screen positive and, when targeted to those with “pre-disease”, should effectively reduce the likelihood of developing disorders.26

Future options

Given current knowledge, two fundamental steps are needed. First, we need to invest in methodologically robust, longitudinal population studies, starting before birth, which include risk factors and multiple outcome parameters. This information combined with that from the Australian Early Development Index (a population tool used in the first year of school, measuring five domains of children’s development)27 would provide much needed data on norms for Australian 3-year-olds to assist service planning.

Second, rather than spending money on screening that lacks an evidence base, a logical first step would be to develop a population-based screening instrument. One possible strategy would be to modify existing instruments to make them briefer. Alternatively, we could design a new instrument following best practice, after a comprehensive review of the existing literature, and obtain expert advice to ascertain which domains to include (infant, infant–parent interaction, family interaction). Then factor analysis and psychometric testing could be used to validate a brief population-screening version. Finally, its applicability in broader contexts could be assessed, including in different cultures.

Despite good intentions, further research and planning are needed before starting large-scale, population social–emotional screening of 3-year-old children in Australia.

Screening, referral and treatment for depression in patients with coronary heart disease

In 2003, an Expert Working Group of the National Heart Foundation of Australia (NHFA) issued a position statement on the relationship between “stress” and heart disease. They concluded that depression was an important independent risk factor for first and recurrent coronary heart disease (CHD) events.1 Here, we provide an update on evidence obtained since 2003 regarding depression in patients with CHD, and include guidance for health professionals on screening and treatment for depression in these patients. Our statement refers to depression in general (mild, moderate and severe), as all grades of depression have an impact on CHD prognosis. The process for developing this consensus statement is described in Box 1. Treatment decisions should take into account the individual clinical circumstances of each patient.

Epidemiology

The prevalence of depression is high in patients with CHD. Rates of major depressive disorder of around 15% have been reported in patients after myocardial infarction (MI) or coronary artery bypass grafts.3,4 If milder forms of depression are included, a prevalence of greater than 40% has been documented.3,4 Recently, the EUROASPIRE III study investigated 8580 patients after hospitalisation for CHD.5 The proportion of patients with depression, measured by the Hospital Anxiety and Depression Scale, varied from 8.2% to 35.7% in men and 10.3% to 62.5% in women. This is consistent with Australian and New Zealand data from a 6-year study, Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID).6,7 At the end of this trial, 27% of men and 35% of women were identified as depressed, using the Beck Depression Inventory II (BDI-II) questionnaire.

A large systematic review in 2006 suggested that individuals with depression, but no current CHD, have a moderately elevated risk of 1.6 for a later index CHD event.8 This elevated risk was confirmed in the Whitehall II study of 5936 healthy individuals over a 6-year period, in which depression was associated with a hazard ratio of 1.93 for cardiovascular events.9 In the Nurses Health Study, 78 282 healthy women were assessed for depression. In the 6-year follow-up period, 4654 deaths were reported, including 979 deaths from cardiovascular disease.10 Depression was associated with increased all-cause mortality, with an age-adjusted relative risk of 1.76 (95% CI, 1.64–1.89).10 The effect of depression on CHD incidence is thought to be strongest around the time of the depressive episode, with longer-term effects mediated via recurrence of depression.11 In young people the association between depression and CHD may be stronger.12

The case–control INTERHEART Study included 11 119 patients with MI from 52 countries.13 Perceived stress and depression were shown to be important risk factors, which together accounted for 32.5% of the population attributable risk (PAR) for CHD, suggesting that together they were as important as smoking and more important than diabetes (PAR, 9.9%) and hypertension (PAR, 17.9%) as risk factors for CHD.13

For people with CHD and comorbid depression, the relative risk (RR) of death is increased (RR, 1.80 [95% CI, 1.50–2.15]), independent of standard risk factors for secondary prevention.8 Comorbid depression also leads to a higher risk of other adverse outcomes in patients with CHD, such as a lower likelihood of return to work, poorer exercise tolerance, less adherence to therapy, greater disability, poorer quality of life, cognitive decline and earlier dependency.14–20 Individuals with CHD and comorbid depression often have less access to interventions for CHD, despite being in a higher-risk group.21–23

Definition of depression and types of depression

The diagnosis of depression can be difficult in people with cardiovascular disease, as depressive symptoms such as fatigue and low energy are common to both CHD and heart failure, and may also be a side effect of some drugs used to treat cardiovascular disease, such as β-blockers.24 The diagnosis may be further complicated in such patients by their responses to their disease (and the associated stigma), which may include denial, avoidance, withdrawal and anxiety.

According to the Diagnostic and statistical manual of mental disorders, fourth edition (DSM-IV),25 major depression is diagnosed when there is a minimum of 2 weeks of depressed mood and/or lack of pleasure (anhedonia), accompanied by four or more other (listed) symptoms such as sleep disturbance, appetite disturbance, poor energy, psychomotor impairment or agitation, poor concentration or poor decision making, and suicidal ideas or thoughts of death. The association with CHD appears to increase with greater severity of depressive symptoms across the spectrum, with no discrete cut-off point at “major depression”. Some studies have suggested links between particular subtypes of depression, such as somatic or anhedonic depression, but these are not consistent findings.26–28

Screening for depression in patients with coronary heart disease

Screening of a population group for a risk factor or disease is worthwhile when the risk factor or disease has a reasonably high prevalence, there is a robust screening test, and effective and cost-effective treatments are readily available.29,30 Depression is both a risk factor and a disease in its own right, and fulfils these criteria for population screening. Screening for depression in patients with CHD would be expected to produce a higher yield than screening for depression in the general population, owing to a much higher prevalence of depression in patients with CHD. It is important to recognise depression in patients with CHD in order to provide the best possible care. Asymptomatic patients with significant cardiovascular risk factors (eg, those with diabetes) may also be considered for screening, as they have a high risk of depression.31

Many self-reported screening tools exist with the aim of detecting possible depression. These include the Patient Health Questionnaire (PHQ-2, PHQ-9), the Cardiac Depression Scale (CDS), the BDI-I and -II, and the Hospital Anxiety and Depression Scale.32,33 The BDI appears to be the most commonly used tool in studies involving cardiac patients. The CDS was developed by a member of the Expert Working Group (D L H) specifically for patients with cardiac disease.33 The short version (short form) has only five items. There is limited but expanding information on the use of the PHQ-9 in patients with cardiac disease.34,35 It is used widely in primary care. Simple tools such as the Kessler Psychological Distress Scale (K10),36 a measure of general distress, will often overdiagnose depression. This tool is currently used in mental health plans in Australia; however, there is no evidence of its use specifically for patients with CHD.

Recognising the need for a simple screening tool for depression in cardiovascular patients, the 2008 American Heart Association (AHA) Science Advisory suggested the use of the PHQ-2.37 The PHQ-2 is an abbreviated form of the PHQ-9, with only the first two of the nine questions in the PHQ-9 (Box 2).38 There are also other versions of the PHQ-2, which may use shorter time frames. The AHA recommended the use of the PHQ-9 if depression was noted using the PHQ-2.37 The Royal Australian College of General Practitioners’ Guidelines for preventive activities in general practice (the red book) also uses a categorical (Yes/No) version of the PHQ-2.39

The PHQ-2 and the PHQ-9 screening tools are associated with reasonable sensitivity and specificity.34 Importantly, depression diagnosed with the PHQ-2 and the PHQ-9 has been shown to predict worse CHD outcomes. In the Heart and Soul Study, positive responses to either question in the PHQ-2 (Yes/No version) predicted a 55% greater risk of cardiovascular events.35 Furthermore, the validity of the PHQ-2 and the PHQ-9 has been assessed in a variety of patients with varying clinical problems, ages and ethnicities, including in Australian Aboriginal people from urban and rural areas and people from the Torres Strait Islands.40–42 Adapted versions exist for use with Indigenous people.

Access to each of the tools varies. No copyright is breached by use of the PHQ-2 and the PHQ-9, and the PHQs and the CDS are free.43 However, some questionnaires such as the BDI-I and -II are subject to copyright and a royalty must be paid each time they are used.44

Implicit in the AHA Science Advisory37 is that screening and identification of patients with depression leads to appropriate treatment, or referral for treatment, by the responsible attending medical practitioner. Unfortunately, research has shown that screening may have little or no impact on the treatment of depression or on outcomes.45,46 Screening by nurses, researchers, receptionists or social workers is not sufficient without appropriate referral or treatment.

It is recommended that a simple tool, such as the PHQ-2 or the short-form CDS, is incorporated into routine screening of patients with CHD. Routine screening for depression is indicated at first presentation, and again at the next follow-up appointment. A follow-up screen should occur 2–3 months after a CHD event. Screening should then be considered on a yearly basis, as for any other major risk factor for CHD. Consideration should also be given to screening the partner or spouse of these patients for depression, as studies show that they are at an increased risk of developing depression.47 If screening is followed by comprehensive care, depression outcomes are likely to be improved.

Treatment of depression in patients with CHD

Collaborative care

Although individual treatment approaches and strategies have been studied, in practice a collaborative-care or stepped-care approach is probably optimal for managing patients with CHD and comorbid depression. The concept of collaborative care involves a group of health professionals working together in a coordinated manner, and this approach has consistently been shown to be associated with greater improvement in depression for patients with CHD compared with standard care, and to be cost-effective.48–52 For example, collaborative care after coronary artery bypass grafting improved depression scores, but not physical function or re-hospitalisation rates.48 In patients with depression comorbid with poorly controlled diabetes and/or CHD, the collaborative approach resulted in improvement in depression scores, glycated haemoglobin levels, low-density lipoprotein cholesterol levels, and systolic blood pressure.50

The Coronary Psychosocial Evaluation Studies (COPES) trial52,53 used a stepped-care treatment approach in patients with acute coronary syndromes (ACS) and persistent depression. Depressive symptoms decreased substantially in the intervention (stepped-care) group. Only three (4%) of the intervention patients experienced major adverse cardiac events compared with 10 (13%) of the patients given usual care, suggesting improved cardiovascular outcomes. Moreover, this stepped-care approach was associated with a 43% lower total health cost over the 6-month trial period.54

Pharmacological therapy

The efficacies of fluoxetine,55 sertraline (Sertraline Antidepressant Heart Attack Randomized Trial [SADHART],56 Enhancing Recovery in Coronary Heart Disease Patients [ENRICHD] trial),57 citalopram (Cardiac Randomized Evaluation of Antidepressant and Psychotherapy Efficacy trial [CREATE])58 and mirtazapine (Myocardial Infarction and Depression Intervention Trial [MIND-IT])59 have been evaluated in clinical trials involving patients with CHD.

SADHART studied depression after ACS over 6 months. Depression scores in patients taking sertraline improved significantly more than in those receiving placebo. Most patients were also prescribed aspirin, statins and β-blockers. Life-threatening cardiovascular events occurred less frequently in the sertraline group; however, this result was not statistically significant.56

ENRICHD was a large trial that evaluated the effect of cognitive behaviour therapy (CBT) on depression or low social support in patients with a recent MI. Depression was diagnosed in 74% of participants. CBT improved depression but failed to reduce the number of CHD events. Patients whose depression did not respond to CBT were referred for treatment with antidepressant drugs. Selective serotonin reuptake inhibitors (SSRIs) (mainly sertraline) significantly improved depression in those patients. In the SSRI-treated group, there was a 43% (P < 0.005) reduction in deaths or recurrent MIs.57 However, this was a subset analysis, and therefore is hypothesis generating only.

In the Canadian CREATE trial58 and the MIND-IT trial,59 there were too few CHD events reported to enable analysis of cardiovascular outcomes.

Tricyclic antidepressants may worsen CHD outcomes and should be avoided in patients with CHD. Importantly, tricyclic antidepressants have been associated with increased mortality in patients with CHD.60–62 In contrast, a recent meta-analysis of trials involving SSRIs in patients with CHD concluded that this class of drugs was well tolerated, with the risk of adverse events being similar to that for placebo.63

Psychological therapy

Of the various psychological therapies, CBT and integrative therapies (eg, interpersonal psychotherapy) have the best documented efficacy for treatment of major depressive disorder.64,65 CBT was used in the ENRICHD trial,57 interpersonal psychotherapy in the CREATE trial,58 and problem-solving therapy in the COPES trial.52,53 These therapies were all beneficial for depression but did not affect CHD outcomes. The efficacy of psychological therapy as a treatment for major or minor depression was evaluated in patients who underwent coronary artery bypass surgery.66 Significantly more patients in the CBT group (71%) and the stress management group (57%) had low depressive symptom levels, compared with those having usual care (33%), and these results were maintained at 6 months.66

A Cochrane review of psychological interventions for patients with CHD found evidence of small-to-moderate improvements in depression and anxiety symptoms with such interventions, but no strong evidence that the interventions reduced total deaths, risk of revascularisation, or non-fatal infarction.67 The interventions that were less effective were those that aimed to educate patients about cardiac risk factors; those that included client-led discussion and emotional support; or those that included family members in the treatment process.67 Uncertainty remains regarding the subgroups of patients who would benefit most from psychological treatments and the characteristics of successful interventions.

Exercise

Many patients with mild depression respond well to regular exercise and cardiac rehabilitation (exercise-based). A recent Cochrane review of exercise as a treatment for depression concluded that exercise improves depression with a similar efficacy to CBT.68 The benefit of exercise appears to have a dose–response relationship, needing at least 30 minutes of moderate aerobic activity on 5 days per week.69,70 This is consistent with usual public health recommendations.

The benefit of exercise in patients with CHD and depression has been demonstrated in the recent UPBEAT (Understanding the Prognostic Benefits of Exercise and Antidepressant Therapy) trial.71 Patients with CHD with at least a mildly elevated score for depressive symptoms (BDI score > 7) were allocated at random to treatment with SSRIs, exercise or neither. Exercise was equivalent to SSRI treatment in improving depression scores, with patients in both groups showing greater improvement than the control group.71 In a large randomised controlled trial (RCT) of 2322 patients with heart failure (of whom 28% were depressed), exercise, in addition to reducing mortality and hospitalisation (P = 0.03), significantly reduced depression (P = 0.002).72

Complementary and alternative therapies

Up to 50% of patients with depression have been shown to use complementary and alternative medicines without disclosing this to their treating clinician.73 Therapies that may be effective in depression are supplemental marine n-3 fatty acids (eicosapentaenoic acid [EPA] and docosahexaenoic acid [DHA]), S-adenosylmethionine (SAMe) and St John’s wort.74 Specific trials in patients with CHD and depression have not been performed with the latter two therapies.

Marine n-3 fatty acids (at a dose of 1 g per day of combined EPA–DHA) are recommended by the NHFA and the AHA for all patients with CHD.75 This dose also may improve mild depression. However, the addition of 2 g/day of combined EPA and DHA to sertraline 50 mg daily for depressive symptoms appears to provide no added benefit over sertraline alone.76 Some trials comparing St John’s wort and SAMe to antidepressant medications suggest a similar effectiveness in improving depression to antidepressant medications.77–79 However, most commercial brands of St John’s wort have not undergone randomised trials.78,79

Adherence

Depression is a major predictor of poor adherence in patients with CHD, be it to drug therapy or lifestyle measures.80,81 Patients with depression are three times more likely to be non-compliant with medical treatment than patients without depression.82 Greater severity and chronicity of depression have been associated with poorer adherence to aspirin therapy after MI.83 Adherence to aspirin therapy after ACS has been shown to be significantly lower in persistently depressed patients (76.1%) than in those whose depression improved (87.4%), or who were not depressed (89.5%).83 Patients who are persistently depressed are also less likely to undertake behaviours that reduce risk; for example, quitting smoking, taking medications, exercising and attending cardiac rehabilitation.81 The SADHART trial showed adherence to medication increased after remission of depression in 68.4% of participants taking the trial medication.84

A recent RCT of a collaborative-care depression treatment program in 134 patients with depression after ACS demonstrated improved adherence to medications and secondary prevention behaviours and was independently associated with improvement in depression.85 However, in another RCT of 157 patients undergoing treatment for depression after ACS, there were no improvements in adherence to risk-reducing behaviours in spite of a significant reduction in depression.86

Referral

Once depression is identified through screening, treatment may be initiated immediately, or referral to psychological or psychiatric services may also be considered appropriate. Most patients with depression in Australia are managed by general practitioners.87

Members of the Cardiac Society of Australia and New Zealand, the majority of whom are clinical cardiologists, were surveyed regarding assessment of depression. Most respondents screened for depression occasionally, with only 3% using a formal tool. Lack of confidence in identifying depression was the strongest predictor of a low screening frequency. Cardiologists rarely initiated treatment for depression, and 43% did not feel they were responsible for treating depression.88

There can be a reluctance to treat depression in patients with CHD because of a belief that depression is normal after an acute cardiovascular event. Mild depression may resolve spontaneously; however, for most individuals with CHD, depression remains long term.89

Conclusion

A summary of the key evidence-based points is provided in Box 3 and Box 4, and the Appendix gives the National Health and Medical Research Council grades of recommendations and evidence hierarchy.

High-quality care for treatment of depression is achievable and affordable. The benefits of treating depression in people with CHD include improved quality of life, improved adherence to other therapies and potentially improved CHD outcomes.90 Effective treatment of depression may decrease CHD events but this is not proven, as no adequately powered trials have been completed, nor are there any ongoing.

1 Process used to develop this National Heart Foundation of Australia consensus statement

The Expert Working Group members performed relevant literature searches using key search phrases including, but not limited to, “stress”, ”depression”, “anxiety”, “treatment of depression”, “acute coronary syndromes”, “adherence and depression” and “screening for depression”. This was complemented by reference lists compiled from reviews and personal collections of the Expert Writing Group members.

Searches were limited to evidence available for human subjects with coronary heart disease published in English up to December 2012. The recommendations made in this consensus statement have been graded according to the National Health and Medical Research Council guidelines (see Appendix).2 The Cardiac Society of Australia and New Zealand, beyondblue: the national depression initiative and the Royal Australian and New Zealand College of Psychiatrists were consulted during the development of this document and have endorsed its content.

2 Patient Health Questionnaire (PHQ-2) Yes/No version35

During the past month, have you often been bothered by feeling down, depressed or hopeless?
During the past month, have you often been bothered by little interest or pleasure in doing things?

3 National Heart Foundation of Australia grades of recommendation and levels of evidence for screening, referral and treatment for depression in patients with coronary heart disease (CHD)2

Recommendation

Grade2

Level2

For patients with CHD, it is reasonable to screen for depression

Treatment of depression in patients with CHD is effective in decreasing depression

Treatment of depression in patients with CHD improves CHD outcomes

Treatment of depression in patients with CHD changes behavioural risk factors/adherence

III-2

Exercise is an effective treatment of depression in patients with CHD

Exercise improves CHD outcomes in patients with CHD

Psychological interventions improve depression in patients with CHD

Psychological interventions improve CHD outcomes in patients with CHD and depression

SSRIs improve depression in patients with CHD

SSRIs improve CHD outcomes in patients with CHD and depression

III-1

Collaborative-care approach improves depression in patients with CHD

Collaborative-care approach improves CHD outcomes in patients with CHD and depression

SSRIs = selective serotonin reuptake inhibitors.

4 Treatment of depression in patients with coronary heart disease (CHD) — summary of treatment subgroup effects showing grade of recommendation and level of evidence

Treatment

Depression

CHD outcome

Grade2

Level2

Grade2

Level2

Non-drug

Exercise

Psychological, including CBT

St John’s wort*

—*

n-3 fatty acids

D†

SAMe*

—*

Collaborative

Drug

SSRIs

III-1

CBT = cognitive behaviour therapy. SAMe = S-adenosylmethionine. SSRIs = selective serotonin reuptake inhibitors. * Insufficient evidence to rate or no trials have been performed. † Data not available in patients with CHD.

Appendix: Definition of National Health and Medical Research Council (NHMRC) grades of recommendations and evidence hierarchy*

Definition of NHMRC grades of recommendations

Grade

Description

Body of evidence can be trusted to guide practice

Body of evidence can be trusted to guide practice in most situations

Body of evidence provides some support for recommendation(s) but care should be taken in its application

Body of evidence is weak and recommendation must be applied with caution

NHMRC evidence hierarchy: designation of levels of evidence

Level

Intervention

A systematic review of level II studies

A randomised controlled trial

III-1

A pseudorandomised controlled trial (ie, alternate allocation or some other method)

III-2

A comparative study with concurrent controls:

Non-randomised, experimental trial
Cohort study
Case—control study
Interrupted time series with a control group

III-3

A comparative study without concurrent controls:

Historical control study
Two or more single arm study
Interrupted time series without a parallel control group

Case series with either post-test or pre-test/post-test outcomes

* From NHMRC additional levels of evidence and grades for recommendations for developers of guidelines.2

The boy who didn’t cry wolf

Someone once told me that during his life, Winston Churchill would often refer to his depression as a “black dog” — a vile, loathsome creature that would shadow every decision and thought in his mind. But to me,
it was not just a dog, but something more sinister and predatory.

The beast followed me in the same way that a lapdog would follow its master, though there was no doubt of who was in charge. Behind every thought, decision and doubt in my mind, the black dog would be not too far away, waiting for a moment of weakness. Feeding off my shame, regret and self-loathing, its hunger knew no bounds and it could smell the fear that seeped from my skin.

For most of my adolescent years, that’s what it was like living with my depression. Every day was a new trial for me to fail and a new reason to undermine my existence. No matter what I did, no matter how hard I worked, I would always come home beaten and shamed. I was constantly making mistakes and no matter how trivial they were, I always punished myself. Every transgression I made was
a constant reminder of how worthless I was.

I never felt more alone than I did during those years. While my peers enjoyed themselves by going out, playing sports or singing in musicals, I spent my breaks eating my lunch alone. I always compared myself to them, asking myself why I couldn’t be like them. Each time, the conclusion was the same; it was because they were normal and I wasn’t. I felt there was something wrong with me, something I couldn’t fix. It was a period of time in which I felt my life was spinning out of control and my sanity was slowly unravelling.

The only thing keeping me alive was my desire to do medicine. Even before I met the black dog, becoming a doctor was all I ever wanted. To work in a craft that was centred around people and their ability to care. It was my calling in life and it was something that I needed to do. But most importantly, it allowed me to push past my depression and survive. No matter how hard things got, I had the strength to continue. I wanted desperately to speak to the school counsellor and confide in her all the pain and misery I was feeling. Maybe there was a cure. I owed it to myself to try. But what would happen if people found out that I was seeing her? What if my peers thought I was insane? The disgrace and humiliation I would feel if everyone knew would be too hard for me to handle. No, I decided. It was
my burden to bear and no one else needed to find out.

It wasn’t long before I tumbled. Months passed, the days became harder for me to bear and my depression deepened. As life continued and my peers moved forward, I was left behind, forgotten. It was as if everyone was in on a big secret that I was not privy to. The cruel isolation wreaked havoc on my self-esteem, pushing me further towards the brink of insanity. As my mind unravelled, my body ached with constant agony.

And then everything became too much. I felt numb and sick at the same time. Waves of nausea, spite and humiliation washed over me as all my mistakes flashed before my eyes. My breathing became laboured and what little tenacity I had left crumbled. I had finally convinced myself that I was a complete and utter failure. I wept. While I sobbed, I wondered what it was like to feel normal and why I lived a cursed life. I pleaded with the Almighty for sweet relief, one way or another. I didn’t care anymore, I just wanted out. As the depression took hold, I reached the chasm’s edge. One step and I would be committed forever. I asked a God I didn’t believe in to give me a break.

To this day, I am thankful for what happened next. After I confessed everything to the counsellor, she helped me realise that no matter how alone I felt, I had my family, my friends and the school to stand by me. That this unbearable agony
I was feeling was common. That people do care. It was something I needed to hear. I was quickly referred to a psychologist for further treatment and I began acceptance and commitment therapy, where I learnt how to acknowledge my faults and move on with my life. Just sharing my problems with someone else and feeling as if they cared was enough to relieve my grief. The pain and doubt that used to hound my every move had less of an impact now. With each session, I could feel the dog — my dog — being pushed further away until it was out of sight.

During the course of the next few months, I was able to complete my final year and secure an interview for medicine. As the date of my interview approached, I became nervous and anxious but I strengthened my resolve. It was my only chance to rectify what had happened to me and I wasn’t going to throw it away. When the day came, I gave it my all.
I talked about why I loved medicine and how I couldn’t see myself doing anything else. I showed them the passion I
had for the profession and the drive necessary to succeed. Afterwards, I was able to rest knowing that I did everything I could. My biggest fight was over.

One month later, I received a call that I had started to believe would never come. I was offered a place to study medicine. It was as if a burden was lifted off my chest. I finally had what I so dearly coveted. It made me realise that anything was possible. That I could live again. Despite being harder than anything I had ever done, studying medicine was the best thing that ever happened to me. I was no longer held back by the expectations that others had of me and was able to become whoever I wanted to be.

That said, I still needed to control my depression. At times, I could feel it edging back into my life and I fought to keep it in check. It was the little things, like new experiences and social pressure, that I struggled with. However, the hardest part was learning about depression at university. Learning about its causes and symptoms made me relive the trauma
I went through. But I always remembered what my life was like before medicine, and how grateful I am for my life now.

Despite my terrible ordeals, I feel that my depression has made me more empathetic. As I remember my clinical experience as a patient, I find it easier to understand what the patient is going through. This recognition allows me to identify with the patient and develop rapport. I know that the dog is not gone forever and I still have bad days. But for the first time in my life, I think I can handle it. I am ready for the next step and this time I’m not alone.

The case for CBT over antidepressants

THIS BOOK is by a doctor with an abiding interest in the philosophy of medicine. Paul Biegler is an Australian Research Council Postdoctoral Fellow at the Centre for Human Bioethics, Monash University, and a recipient of the 2011 Australian Museum Eureka Prize for Research in Ethics.

The book describes the therapeutic use of antidepressant medication (ADM) versus cognitive behaviour therapy (CBT), and concludes that it is unethical to provide the former as a first option to all patients suffering from depression. This is based on the author’s view that ADMs do not promote autonomy nor change vulnerability, whereas CBT enhances resilience and changes cognitive vulnerability to depression.

However, Biegler does not sufficiently discriminate between different types of depression. He acknowledges that some types may require ADMs to allow patients to process information, but underplays this point. In these cases — such as melancholic and psychotic depression, some medical illnesses and, arguably, depression related to serious personality disorders — ADMs can improve cognition and judgement to enable sufferers to make informed choices, while ongoing ADMs and psychotherapy may be necessary to decrease vulnerability and promote autonomy. And although Biegler talks about precipitating stressors, he doesn’t acknowledge the place that environmental stressors can play in melancholic depression, often a point of confusion.

The case is meticulously built up through progressive chapters. It is a thought-provoking book, but not one to skim through or dip into. It is recommended for people with a serious interest in the area. It addresses important issues and is timely as the costs of providing CBT have become less of an issue with the advent of excellent self-help books and internet programs, and greater access to clinicians providing CBT. It will be of interest to general practitioners, psychiatrists, psychologists and people involved in health economics and health planning, albeit with the aforementioned caveats in mind.

The role of depression in the primary prevention of cardiovascular disease

To the Editor: We would like to add a cautionary note to O’Neil’s support for the inclusion of “depression and other psychosocial factors” in the updated National Vascular Disease Prevention
Alliance guidelines for assessing cardiovascular disease (CVD) risk. Her statement “it is now clear that depression is also an important risk factor for CVD” is premature.1 Different authors have challenged the suggested relationship and, given divergent findings and opinions, it is misleading to claim that the matter is now “clear”.2–5 We do not deny a possible link between depression and coronary heart disease (CHD) but suggest that the extent and nature of the relationship has yet to be clarified. Premature acceptance and promotion of the idea that depression is a risk factor for CHD might contribute to overdiagnosis and overtreatment of depression as well as undue worry about the risk of CHD by individuals diagnosed with depression.

The role of depression in the primary prevention of cardiovascular disease

In reply: I thank Stampfer, Hince and Dimmitt for their response.
While I acknowledge that there are aspects of the relationship between cardiovascular disease (CVD)
and depression that remain undetermined, recent evidence clearly supports the role of depression as an independent risk factor for CVD and is indeed convincing.1–3 This is especially true in studies that assess depression using diagnostic criteria.4 We know that the risk of developing coronary heart disease (CHD) for individuals with depression is twofold, and these individuals have a similar risk of CVD-related death.2 We also know that the independent contribution of depression to CVD is at least comparable to that of more traditional risk factors including diabetes, hypercholesterolaemia, smoking or obesity.5 A decade has now passed since the National Heart Foundation’s seminal position paper concluded that: “there is strong
and consistent evidence of an independent causal association between depression, social isolation and lack of quality social support and the causes and prognosis of CHD”.5 Despite this, depression remains underestimated as a meaningful contributor to CVD.

Long-term health and wellbeing of people affected by the 2002 Bali bombing

The 2002 Bali bombing resulted in the deaths of over 200 people, including 88 Australians and 35 Indonesians, making it the single worst act of terrorism to have affected either country.1 A further 209 people were injured, including 66 Australians who suffered severe burns and complex shrapnel wounds.2,3

Terrorism exposure may have significant long-term effects on the mental health and wellbeing of survivors. Post-traumatic stress disorder (PTSD) is the most common psychological condition observed in the aftermath of such events, but it often coexists with depression, functional impairment or substance misuse.4,5 Few studies have examined the long-term effects on terrorism survivors, although one large study found increases in PTSD between 3 and 5 years after the September 11 attacks.6,7 Risk factors included direct exposure (proximity, injury, witnessing horror), incident-related bereavement and low social support.

Bereavement that occurs in traumatic circumstances may have a considerable long-term impact on psychological distress and appears to slow the rate of recovery.8 Deaths involving deliberate violence are associated with higher prevalence of trauma conditions, depression and prolonged or “complicated” grief.8,9 Complicated grief is characterised by continuing separation distress and bereavement-related traumatic distress. While frequently comorbid with depression or PTSD, it is increasingly recognised as a distinct condition that is associated with persistent functional impairments and negative health outcomes, particularly among those bereaved through terrorism.9,10

The health and psychosocial effects of terrorism exposure have rarely been investigated beyond 3–4 years after such incidents.4,11 No studies have examined these effects among Australian survivors. Our aim was to examine the physical and mental health status of individuals directly affected by the 2002 Bali bombing, 8 years after the incident, and to determine demographic, exposure and loss-related correlates of these health outcomes.

Methods

Participants constituted a cross-sectional convenience sample of individuals who had experienced personal exposure and/or loss related to the 2002 Bali bombing and had current contact details listed with a New South Wales Ministry of Health therapeutic support program (Bali Recovery Program), where they had attended at least one consultation. Those who registered interest in response to a written invitation were contacted, given a description of the study, and asked for verbal consent. Professional interviewers from the NSW Health Survey Program completed computer-assisted telephone interviews between 9 July and 22 November 2010, excluding a period around the bombing anniversary (1–23 October). The validity of telephone-based interviews to assess stress and anxiety conditions has been demonstrated.12

Measures

We examined demographic and exposure factors to determine their relationship with physical and mental health outcomes. Exposure variables were: lifetime traumatic incident exposure,13 presence in Bali during/after the bombing, involvement in the search for missing friends/relatives (first 48 hours), and bereavement circumstance (eg, multiple loss, family). Perceived social support from family and friends was assessed with two items from the Perceived Social Support Scale,14 as well as single items regarding neighbourhood social connectedness15 and overall support since the bombing.

Current bereavement experience (“experiential” grief) was measured using six items from the Inventory of Complicated Grief-Revised (ICG-R): separation distress (longing/yearning) and cognitive, affective or behavioural items (anger, acceptance, detachment, emptiness/meaninglessness, difficulty moving on). High factor loadings related to the single underlying complicated grief factor and elapsed time since bereavement guided item selection.16

Self-rated physical health in the previous month was measured with a single validated item from the NSW Population Health Survey.15 We used the short form of the Connor-Davidson Resilience Scale (CD-RISC2) to measure current perceived personal adaptability and ability to continue to function effectively in stressful circumstances.17 A score of 7–8 indicates high personal resilience.

Anxiety, depression, agitation, psychological fatigue and associated functional impairment (ie, full days unable to manage day-to-day activities due to symptom effects) in the past month were measured using the Kessler Psychological Distress Scale (K10+). Individual scores range from 10 to 50, indicating low (10–15), moderate (16–21), high (22–29) and very high (30–50) psychological distress. The latter is indicative of a significant mental health condition.18

We used the Primary Care PTSD Screen (PC-PTSD) to measure past-month traumatic stress-related symptoms (TSRS) specific to Bali-related experiences. Single items relate to one underlying characteristic specific to PTSD: re-experiencing, numbing, avoidance and hyper-arousal. The endorsement of 3–4 symptoms indicates “probable” PTSD and the need for specialist assessment.19

Statistical analysis

The dataset was weighted by age and sex to reflect registered participants in the Bali Recovery Program (n = 115). Current physical and mental health were analysed as outcome measures, with demographic, traumatic incident exposure, perceived support and bereavement factors used as independent variables.

Responses to the support and bereavement questions were expressed as dichotomous variables, with a value of 1 assigned to responses “agree” or “strongly agree”, and 0 to “disagree”, “strongly disagree” and “don’t know”. The outcome variables of physical health, personal resilience and functional loss were dichotomised into high and low (or good and poor) outcomes. Three outcome categories based on established clinical cut-offs were adopted for psychological distress (low–moderate, high and very high) and TSRS (low, moderate and high).18,19

Analyses were performed using Stata statistical software, version 12.0 (StataCorp), with “Svy” commands to allow for adjustments for sampling weight. We used the Taylor series linearisation method to determine prevalence estimates, and χ2 tests to test for significant differences in the prevalence of physical and mental health outcomes. Due to the relatively small sample size, an α significance level (P < 0.15) was adopted, as it is a commonly used threshold for entry into multiple logistic regression analyses,20 and could provide indicative findings in the context of this exploratory study. Multiple testing using the Bonferroni correction was also carried out by dividing the target α level by the number of tests being performed. The significant adjusted P values are reported.

Ethics approval

All study protocols were approved by the ethics committees of the Northern Sydney Local Health District and the University of Western Sydney (H7143).

Results

Of 81 individuals contacted, 55 agreed to participate (68% of eligible respondents). The mean interval between the 2002 bombing and the interview was 7 years and 11 months (range, 7 y 9 m – 8 y 1 m). There were no significant differences between the respondents and the total Bali Recovery Program population in terms of mean age (P = 0.38) or male sex (P = 0.39).

Respondent characteristics

Demographic, exposure and bereavement characteristics of the respondents are shown in Box 1. Of the 55 respondents, 21 were present in Bali during or shortly after the bombing. Almost three-quarters (39/54) experienced at least one family bereavement due to the bombing. The loss of children (of adult age) was predominant (21/54). Fifteen respondents experienced multiple losses of exclusively non-family members (average of seven friends and acquaintances killed).

Physical health and personal resilience

Physical and mental health prevalence estimates for the weighted sample are presented in Box 2 and Box 3. Good physical health in the past month and high personal resilience were reported by 45 and 30 of the 55 respondents, respectively. Respondents had an aggregate resilience score on the CD-RISC2 of 6.45. Poor self-rated health showed a significant relationship with current yearning for the deceased (P = 0.04) and perceived current difficulties moving on with life after the loss (P = 0.02). Experiential bereavement factors were the only variables associated with low personal resilience: current yearning (P = 0.02); perceived detachment from others (P = 0.04); life feeling empty without the deceased (P = 0.02); and perceived difficulty moving on (P = 0.003).

Psychological distress and daily functioning

Current high and very high psychological distress was reported by seven and five respondents, respectively. High distress was significantly associated with difficulty accepting the loss (P = 0.03); feeling detached (P = 0.001); and anger (P = 0.04). Very high distress was associated with bombing-related injury (P = 0.005); current yearning (P = 0.004); difficulty moving on (P = 0.003); and life feeling empty (P < 0.001). Very high distress also showed significant inverse relationships with current marital or de facto relationship (P = 0.02); perceived family support (P = 0.03); and better neighbourhood connectedness (P = 0.02). Loss of at least one full day of functioning in the past month was reported by nine respondents (range, 0–16 days; mean, 0.74). Significantly greater functional loss was associated with bombing-related injury (P = 0.04) and not being in a current marital or de facto relationship (P = 0.04).

Traumatic stress-related symptoms

Moderate TSRS (two symptoms) and high TSRS (three or more symptoms) in the past month were reported by 11 and 15 respondents, respectively. High TSRS was positively associated with all assessed features of bereavement but no other outcome variables: current yearning (P = 0.007); difficulty accepting the loss (P = 0.005); feeling detached (P = 0.01); anger (P = 0.002); life feeling empty (P = 0.02); and difficulty moving on (P < 0.001).

Comparisons with the NSW
general population

Compared with NSW population estimates, the respondents reported greater rates of high (12.7% v 8.2%) and very high (9.1% v 2.9%) psychological distress (Box 4) and functional impairment (mean, 0.74 v 0.60 days lost in the past month).15 Respondents were significantly less likely to report low levels of psychological distress (P < 0.05). Good self-reported health was slightly higher among respondents than the population mean (81.8% v 80.4%).

Discussion

Eight years after the first Bali bombing, a substantial proportion of this directly affected group were experiencing high levels of psychological distress and TSRS. These individuals, who had sought help, were also experiencing near-normal physical health, and their aggregate resilience score fell within a “high resilience” range observed in United States population estimates.17 Although a specific comparison group is not available, access to modern treatment methods and support may have promoted these positive long-term outcomes. Notably, experiential features of grief (eg, emptiness, difficulty moving on) were the only factors associated with reduced resilience, suggesting that early intervention with a specific focus on these factors may be indicated for such groups.10

Direct exposure to disasters is considered to have a dose–response effect. Factors such as proximity, injury and perceived threat to life are consistently associated with adverse mental health effects, but they are rarely examined beyond 3–4 years after terrorism incidents because of difficulty accessing affected cohorts.11 Eight years after the Bali bombing, a significant association was observed between incident-related physical injury and both psychological distress and functional impairment. These findings extend the current literature, showing that some of the most direct forms of exposure (proximity and injury) remain substantial risk factors at this extended time point.

Social support has a positive role in mental health and may foster recovery from trauma over time.21 We found that being in a marital or de facto relationship was the only demographic factor associated with distress in the respondent group, showing an inverse relationship with high psychological distress. Inverse relationships were also observed with the broader social support factors of high perceived family support and neighbourhood social connectedness.

The strength of our findings in relation to complicated grief variables appears to highlight important aspects of grief, as it relates to terrorism violence and loss. The ability to “make sense” of a loved one’s death is considered a central process of grieving.8 However, the irrational or meaningless nature of violent death, particularly through terrorism, has been found to interfere with this cognitive process for many survivors.22 Moreover, it is associated with more severe complicated grief, higher psychological distress and poorer physical health.23 While such mediating variables cannot be inferred in relation to our data, it is notable that complicated grief symptoms in this study were also associated with distress and poor physical health, as well as TSRS. Similarly, grief symptoms were also the only factors associated with significantly lower personal resilience. This suggests that among bereaved survivors of terrorism, grief maladaptation may represent a more significant long-term risk factor for health outcomes than incident exposure or post-event variables.

Our findings have implications for the support of people directly affected by terrorism. Complicated grief factors emerged as the strongest correlates of adverse physical and mental health status. Longer-term monitoring of survivor groups is indicated, including screening programs that incorporate grief-specific items. Previous short-term screening has effectively linked survivors with evidence-based care.10,24 However, case-finding from primary care pathways was poor, suggesting that outreach is required for longer-term initiatives.24 Significantly, 7 years after the September 11 attacks, registered individuals who had escaped the World Trade Center reported difficulty accessing physical and mental health care and often failed to connect long-term symptoms with their September 11 exposures.25

Our study has some notable strengths and several limitations. The sample ostensibly constitutes a traumatically bereaved population, with varying levels of direct incident exposure and use of clinical services. Respondents may represent a more seriously affected, but possibly better supported cohort than those who did not seek services from the program. This may limit generalisability of these findings to other survivor groups. This cross-sectional study can only determine significant associations at a single time point. No conclusions can be drawn regarding longitudinal health effects or their causes.

The response rate had the potential to introduce responder bias, although no significant differences in sex or age were found between the respondent sample and the total program population. Items from the complicated grief measure (ICG-R) examined a subset of symptoms only and cannot be considered to indicate syndrome-level complicated grief.

Importantly, this analysis presents the largest study sample to date of Australians directly affected by a single terrorist incident. In completing a quantitative analysis of their health status 8 years after a major bombing, it also represents, to our knowledge, the longest follow-up period of a terrorism-affected population reported in the literature.

1 Demographic, exposure and bereavement-related variables of the respondents

Variable	Unweighted (n = 55)	Weighted (n = 115)

Mean age (range)	50 (20–73)	50 (42–53)
Male	23 (41.8%)	48 (41.8%)
Education
University degree	15 (27.2%)	31 (27.3%)
TAFE certificate or diploma	17 (30.9%)	36 (30.9%)
Higher school certificate	11 (20.0%)	23 (20.0%)
School certificate	9 (16.4%)	19 (16.4%)
Other	3 (5.5%)	6 (5.5%)
Marital status
Married or de facto	40 (72.7%)	84 (72.7%)
Widowed	3 (5.5%)	6 (5.5%)
Separated or divorced	4 (7.3%)	8 (7.3%)
Never married	8 (14.5%)	17 (14.5%)
Location during/after bombing
Bali, in club*	6 (10.9%)	13 (10.9%)
Bali, near club*	3 (5.5%)	6 (5.5%)
Bali, not nearby	3 (5.5%)	6 (5.5%)
Bali, arrived after bombing	9 (16.4%)	19 (16.4%)
Not in Bali	34 (61.8%)	71 (61.8%)
Injured during bombing
No	48 (87.3%)	100 (87.3%)
Yes	7 (12.7%)	15 (12.7%)
Involved in search (first 48 hours)
No	39 (70.9%)	84 (72.7%)
Yes	16 (29.1%)	31 (27.3%)
Primary bereavement type†
Child	21 (38.2%)	44 (38.9%)
Sibling	11 (20.0%)	23 (20.4%)
Spouse	3 (5.5%)	7 (5.6%)
Other family member	4 (7.3%)	9 (7.4%)
Non-family member(s)	15 (27.3%)	32 (27.8%)
Loss†
Single family member	29 (52.7%)	61 (53.7%)
Multiple family members	4 (7.3%)	9 (7.4%)
Multiple family and non-family	6 (10.9%)	13 (11.1%)
Multiple non-family	15 (27.3%)	32 (27.8%)

TAFE = technical and further education. * Bomb site. † Bereaved respondents (n = 54).

2 Prevalence estimates of individual health and wellbeing indicators in the weighted sample, by sociodemographic and perceived support factors

Covariate	Good self-rated health	High resilience*	Functional loss†	High distress‡	Very high distress‡	Moderate TSRS§	High TSRS§

Sex
Male	78.3%	60.9%	17.4%	8.7%	4.3%	13.0%	21.7%
Female	84.4%	53.1%	15.6%	15.6%	12.5%	25.0%	34.4%
Age
18–40 years	73.3%	57.9%	26.3%	10.5%	10.5%	26.3%	26.3%
> 40 years	86.1%	55.6%	11.1%	13.9%	8.3%	16.7%	30.6%
Education
University	86.7%	66.7%	20.0%	13.3%	6.7%	20.0%	26.7%
High school/other	80.0%	52.5%	15.0%	12.5%	10.0%	20.0%	30.0%
Employed
No	75.0%	41.7%	25.0%	16.7%	8.3%	8.3%	50.0%
Yes	83.7%	60.5%	14.0%	11.6%	9.3%	23.3%	23.3%
Household income
≤ $60 000	77.8%	44.4%	27.8%	22.2%	11.1%	16.7%	22.2%
> $60 000	82.9%	62.9%	11.4%¶	8.6%	5.7%	20.0%	31.4%
Marital status
Married or partnered	85.0%	52.5%	10.0%	12.5%	2.5%	17.5%	30.0%
Not married or partnered	73.3%	66.7%	33.0%**	13.3%	26.7%**	26.7%	26.7%
Have children
No	75.0%	58.3%	16.7%	8.3%	16.7%	33.3%	33.3%
Yes	83.7%	55.8%	16.3%	14.0%	7.0%	16.3%	27.9%
Perceived support, family
Low	80.0%	60.0%	20.0%	20.0%	40.0%	40.0%	20.0%
High	82.0%	56.0%	16.0%	12.0%	6.0%**	18.0%	30.4%
Perceived support, friends
Low	85.7%	42.9%	14.3%	14.3%	14.3%	0.0%	42.9%
High	81.3%	58.3%	16.7%	12.5%	8.3%	22.9%	27.1%
Social connections, neighbourhood
Low	88.9%	66.7%	33.3%	11.1%	33.3%	33.3%	22.2%
High	80.4%	54.3%	13.0%¶	13.0%	4.3%**	17.4%	30.0%
Long-term support, all sources
Low	75.0%	75.0%	0.0%	25.0%	12.5%	0.0%	37.5%
High	83.0%	53.2%	19.1%	10.6%	8.5%	23.4%	27.7%
Total respondent group (95% CI)	81.8% (68.9%– 90.1%)	56.4% (42.7%–69.1%)	16.4% (8.6%–29.0%)	12.7% (6.0%–24.8%)	9.1% (3.7%–20.5%)	20.0% (11.2%–33.1%)	29.1% (18.4%–42.8%)

TSRS = traumatic stress-related symptoms. * Score of 7–8 on the short form of the Connor-Davidson Resilience Scale. † Unable to complete usual activities on 1 or more days in previous month. ‡ Score of 22–29 on the Kessler Psychological Distress Scale indicates high psychological distress; 30–50 indicates very high distress. § Two symptoms on Primary Care PTSD Screen indicates moderate TSRS; 3–4 symptoms indicates high TSRS. ¶ P < 0.15. ** P < 0.05.

3 Prevalence estimates of individual health and wellbeing indicators in the weighted sample, by incident exposure and bereavement factors

Covariate	Good self-rated health	High resilience*	Functional loss†	High distress‡	Very high distress‡	Moderate TSRS§	High TSRS§

Lifetime exposure¶
Low	84.0%	60.0%	16.0%	16.0%	4.0%	32.0%	32.0%
High	80.0%	53.3%	16.7%	10.0%	13.3%	10.0%	26.7%‡‡
In Bali during or after bombing
No	88.2%	55.9%	11.8%	11.8%	2.9%	20.6%	20.6%
Yes	71.4%‡‡	57.1%	23.8%	14.3%	19.0%‡‡	19.0%	42.9%
Injured during bombing
No	83.3%	58.3%	12.5%	12.5%	4.2%	18.8%	27.1%
Yes	71.4%	42.9%	42.9%§§	14.3%	42.9%§§	28.6%	42.9%
Involved in search (first 48 hours)
No	87.5%	60.0%	12.5%	12.5%	5.0%	22.5%	22.5%
Yes	66.7%‡‡	46.7%	26.7%	13.3%	20.0%	13.3%	46.7%
Bereavement**
Non-family member(s)	80.0%	46.7%	20.0%	13.3%	13.3%	20.0%	40.0%
Family member(s)	84.6%	61.5%	12.8%	10.3%	7.7%	20.5%	23.1%
Bereavement involved child**††
No	81.8%	57.6%	15.2%	9.1%	9.1%	21.2%	30.3%
Yes	85.7%	57.1%	14.3%	14.3%	9.5%	19.0%	23.8%
Current yearning for loved one(s)**
No	93.1%	72.4%	10.3%	3.4%	0.0%	20.7%	10.3%
Yes	72.0%§§	40.0%§§	20.0%	20.0%	20.0%§§	20.0%	48.0%§§
Difficulty accepting loss**
No	90.6%	62.5%	15.6%	3.1%	6.3%	18.8%	12.5%
Yes	71.4%‡‡	47.6%	14.3%	23.8%§§	14.3%	19.0%	52.4%§§
Feel detached from others**
No	84.3%	60.8%	15.7%	7.8%	7.8%	21.6%	23.5%
Yes	66.7%	0.0%§§	0.0%	66.7%§§	33.3%	0.0%	100.0%§§
Feel angry about loss**
No	92.0%	60.0%	16.0%	0.0%	8.0%	24.0%	4.0%
Yes	75.9%‡‡	55.2%	13.8%	20.7%§§	10.3%	17.2%	48.3%§§
Life feels empty without loved one(s)**
No	86.4%	65.9%	11.4%	6.8%	2.3%	22.7%	20.5%
Yes	66.7%	22.2%§§	22.2%	33.3%	33.3%¶¶	11.1%	66.7%§§
Moving on remains difficult**
No	87.5%	64.6%	12.5%	8.3%	6.2%	22.9%	18.8%
Yes	50.0%§§	0.0%§§	21.4%	33.3%	33.3%§§	0.0%	100.0%¶¶
Total respondent group (95% CI)	81.8% (68.9%–90.1%)	56.4% (42.7%–69.1%)	16.4% (8.6%–29.0%)	12.7% (6.0%–24.8%)	9.1% (3.7%–20.5%)	20.0% (11.2%–33.1%)	29.1% (18.4%–42.8%)

TSRS = traumatic stress-related symptoms. * Score of 7–8 on the short form of the Connor-Davidson Resilience Scale. † Unable to complete usual activities on 1 or more days in previous month. ‡ Score of 22–29 on the Kessler Psychological Distress Scale indicates high psychological distress; 30–50 indicates very high distress. § Two symptoms on Primary Care PTSD Screen indicates moderate TSRS; 3–4 symptoms indicates high TSRS. ¶ Lifetime exposure to potentially traumatising events: low = 1–2 events; high ≥ 3 events (excluding Bali exposure). ** Bereaved respondents (n = 54). †† Non-dependent child. ‡‡ P < 0.15. §§ P < 0.05. ¶¶ P < 0.001 (Bonferroni adjusted).

4 Population comparison of prevalence estimates* of psychological distress† in the past month

* Bali Recovery Program 2010 weighted sample and New South Wales population weighted prevalence estimates (2010).15 † Measured using the Kessler Psychological Distress Scale. ‡ P < 0.05.