Australia’s vulnerability to natural disasters is a recurring theme in Australian communities,Reference Leivesley¹ with these events occurring more frequently since the 1970s.Reference Keenan, Weston and Volkova^2, Reference Filkov, Ngo and Matthews³ Disasters are accompanied by destruction of property and infrastructure, the loss of wildlife, and often loss of human lives. These were familiar occurrences following the bushfires and floods that plagued Australian communities between 2019 and 2022.Reference Filkov, Ngo and Matthews^3–5 Although climate variables have a role in the genesis of disasters, poverty, previous trauma experiences, building codes, and community and individual resilience are risk factors that influence the outcome of disasters.Reference Chaudhary and Piracha⁶ These risks are not static. The severity of events, greater urbanization, and an aging and growing population intensify the disaster risks through increased vulnerability and a reduced response capacity in disaster-affected communities.Reference Kelman, Gaillard and Lewis^7–Reference Swerts, Pumain and Denis¹¹ The worldwide trend towards urban livingReference Leeson¹² is particularly evident in Australia where 89% reside in urban areasReference Maude¹³ with 92% of Australians predicted to live in urban communities by 2050.Reference Jiang and O’Neill¹⁴ The population drift towards major cities, established coastal centers, or regional centers exposes communities to an increased risk of disasters due to coastal or pluvial flooding or cyclonic activity.Reference Buckle and Osbaldiston¹⁵

The adverse economic, social, family, and mental health outcomes for disaster-affected Australian communities are well described.Reference Singh-Peterson and Lawrence^16–Reference Crompton and McAneney¹⁸ Jurisdictions recognize the need for structured, planned, and integrated frameworks for responding to disasters. The frameworks include addressing immediate safety and infrastructure recovery and the provision of psychosocial support, although the impact of disasters on the health and well-being of communities is likely to be underestimated and may be cumulative.Reference Morrissey and Reser^19–Reference Reifels, Pietrantoni and Prati²³ The Australian disaster management framework includes prevention and preparation strategies and mental health strategies to address identification of at-risk populations, service accessibility, and outreach programs.^24–26

However, there are gaps between the demand for services post-disaster and service availability: Post-Hurricane Katrina, those experiencing psychological problems described service access difficulties resulting in increased unmet mental health needs. The nature of the disaster and geographical factors influence service access. An Australian study demonstrated that exposure to bushfires increases the likelihood of seeking primary mental health care compared to those exposed to other disasters.Reference Reifels, Bassilios and Spittal²⁷ Ethnicity, income, job loss, and disability affect service access and help-seeking behavior.Reference Lowe, Norris and Galea^28–Reference Wang, Gruber and Powers³⁰

Like the flood events that affected New South Wales (NSW) and Victoria in 2022-2023, the Queensland floods and cyclones (2010-2011) were associated with significant infrastructure damage, human tragedy, and psychosocial distress. A third of Queensland’s population was affected, 10 500 people were evacuated from their homes, and towns became isolated. The flood affected the capital, provincial cities and rural communities.Reference Arklay³¹ An evaluation estimated 314 000 people were vulnerable to emotional distress, with a predicted 1% increase in severe mental disorders and a 5% increase in mild to moderate mental disorders.³²

The Queensland Mental Health Natural Disaster Recovery Plan 2011-13 (The Plan) was developed to address psychosocial recovery in the immediate and the medium to long-term.^{33, 34} The Plan addressed the mental health challenges associated with evacuation, damaged homes, and infrastructure and aimed to link primary health care, the non-government sector (NGOs), community-based supports, and health services. A critical feature of the strategy was addressing the needs of vulnerable populations, providing evidence-informed treatment programs, and enhancing resilience.^{35, 36} The Specialised Mental Health Program (SMHP) was a key element of the mental health response.²² Across Queensland, SMHP treatment teams were implemented in areas affected by floods and cyclones. The Centre for Trauma, Loss and Disaster Recovery undertook the implementation, oversight, and monitoring of the SMHP and established a database to support staff supervision and report on service activity.^{37, 38}

The SMHP multidisciplinary teams included mental health nurse, psychologists, social workers, occupational therapists, and psychiatrists. Clinical services were provided in community facilities, general practices, or homes. The Australian Government National Disaster Relief and Recovery Arrangements (NDRRA) funded the services. The clinicians were trained in Skills for Psychological Recovery (SPR) and Trauma-Focused Therapy.Reference Crompton, Young and Shakespeare-Finch³⁹ The program included pre-referral assessment, standardized pre-post assessments, and clinical evaluation. The treatment sessions included psychoeducation and Cognitive Behavioral Therapy (CBT) to address anxiety and depression and trauma-focused CBT (TF-CBT).

Despite the extensive mental health response plan to the Queensland floods and cyclones of 2010-11, there were concerns regarding the program’s capacity to meet the demands for specialist mental health care due to the size of the state and the number of people affected. These concerns reflect those of other studies. Following Hurricanes Katrina and Sandy, the demand for services and the delayed emergence of adverse psychological adversely exceeded the availability of trained clinicians.Reference Lowe, Norris and Galea^28, Reference Taioli, Tuminello and Lieberman-Cribbin^40–Reference Ruskin, Schneider and Bevilacqua⁴²

The mismatch between service demand and clinician availability is not unique to disasters. The development of a capacity to predict who may participate in treatment is, therefore, likely to assist in determining resource allocation and treatment planning.Reference Bone, Simmonds-Buckley and Thwaites^43, Reference Uckelstam, Philips and Holmqvist⁴⁴ Previous studies have highlighted witnessing injury or death as aspects of the disaster experience that increase the risk of adverse psychological outcomes, while noting indirect factors such as resilience potentially ameliorate the psychosocial effects.Reference Maguire and Hagan^45–Reference Brooks, Amlôt and Rubin⁴⁹ Similarly, studies have identified a relationship between optimismReference Hirsch, Wolford and LaLonde^50, Reference Benight, Swift and Sanger⁵¹, perception of well-beingReference Clemens, Berry and McDermott⁵², and coping styleReference Benight, Ironson and Durham^53–Reference Navarro, Krien and Rommel⁵⁵ and the psychosocial response to disasters. Other studies recognize that psychosocial outcomes are influenced by pre-and-post disaster experiences and pre-disaster physical and general health.Reference Seplaki, Goldman and Weinstein^56–Reference Lowe, McGrath and Young⁵⁸

This paper reports a retrospective evaluation of the relationship between perception of optimism and resilience, disaster-related factors, physical and mental health history, family history, pre-event trauma experiences, demographics, post-disaster health, social changes, and the likelihood of participation in a specialist post-disaster mental health program (Figure 1). This study aimed to identify factors that may predict participation in a specialist program in those exposed to a natural disaster and assessed as at risk for post-traumatic stress disorder. A Classification Tree Analysis (CTA)Reference Atieh, Pang and Lian⁵⁹ was utilized to identify which assessment measures predicted participation in the post-disaster SMHP.

Figure 1.

Triage, intake, and discharge assessment questions.

a) If the participant experienced bereavement due to the floods or cyclones, complete CBI, and if yes referred to bereavement service.

b) Clinicians should review if self-rated questions are not answered.

c) To be completed if a participant entered the treatment program.

**) If the answer was “yes” to this question, participants were referred to the Post-disaster Bereavement Service

Results

Descriptive Analyses

In 2012, 881 people were assessed by the SMHP. The mean PC-PTSD was 2.14 (SE 0.029, 95%, CI: 2.08;2.20). The treatment group (TG) (n = 215), in contrast to the non-treatment group (NTG) (n = 666), were more likely to describe their life was threatened by floods or cyclones (85.1% vs 8.1%), a fear of dying (78.6% vs 11%), and fear for the lives of others (81.9% vs 9.9%).

The TG response to the CATI question differed from the NTG; 15.3% of the TG reported “Life was good,” whereas 62.5% of the NTG described life as “good,” The TG recorded an altered level of optimism (TG 74.2% vs NTG 33%). The CR-2 scores differed; 66% of the TG and 2.7% of the NTG perceived an inability to adapt to change and bounce back after adversity. The TG considered themselves as “less optimistic in uncertain times and less likely to look on the bright side of life” compared to the NTG (70.2% and 6.9%, respectively). Thoughts of self-harm were uncommon (TG 9.77% and NTG nil) (Table 1).

Table 1.

Pre-treatment screening assessment: narrative history of disaster exposure, CATI question, optimism, resilience, and thoughts of self-harm

The majority of those assessed were aged 20-49 (76.6%). Queensland’s 2011 population data indicates 41.6% were aged 20-49.⁸⁵ Social security was the primary income source for the TG (63.3%). Almost 50% of the NTG had full-time employment. The marital status of those assessed differed from Queensland 2011 ABS: married/de-facto 19.5% vs 59.6%, divorced 23.7% vs 9.1%, and separated 31.6% vs 3.3%. Flooding affected the majority of those assessed (TG 83.3%, NTG 89.9%).

The TG, compared to the NTG, more often reported major property damage compared to none, minor, or moderate damage (43.3% vs 3.8%; P<0.05), relocation from home (32.6% vs 8.3%; P<0.05), personal loss (53.5% vs 24.3%; P<0.01), protracted insurance claims (25.6% vs 12.6%; P<0.01), or litigation 10.2% vs 0.5%; P<0.01) (Table 2). Changes to physical health, relationships, tobacco and alcohol use, gambling, and the type of stresses individuals experienced experiencing are detailed in Table 3. The impact on physical health was similar for the TG and NTG (47.4% vs 41.6%); relationship deterioration was more common in the TG (28.4% vs 0%; P<0.01,) while increased alcohol and drug use, tobacco consumption, and gambling were apparent in the TG (20% vs 8.1%, 16.7% vs 4.2%, and 3.3% vs 0%, respectively; all significant P<0.01). The TG reported more anxiety/depression (40.9% vs 16.2%; P<0.01). Interestingly, the NTG more often reported increased social stressors (TG 4.7% vs NTG 27.5%; P<0.01).

Table 2.

Property and financial intake (economic) variables

Table 3.

Stress impact variables

Personal and family history of physical and psychological health and previous disaster experience are detailed in Tables 4-5. The TG more frequently described a history of trauma. Family violence was reported in 16.7% of the TG compared to 11.9% in the NTG (P < 0.01). Childhood abuse occurred in 16.7% of the TG (NTG 5.7%, P<0.01), and sexual abuse in 11.6% of the TG and 6.5% of the NTG (P < 0.01). Prior exposure to disasters was more common in the TG (10.7% vs NTG 6.8%, P<0.01). The TG more often reported a family history of mental illness, a history of complex grief and suicidal thoughts, and personal history of mental illness and treatment (17.7% vs 11.3%, 14.4% vs 9.3%, 16.3% vs 2.4%, 27.9% vs 6.6%, and 31.6% vs 2.0%, respectively [all significant P<0.01]) (Table 4). The TG in comparison with the NTG more often experienced chronic illness (20% vs 6.4%) and was more likely to take prescribed medications (34% vs 9.6%; P<0.01) (Table 5).

Table 4.

Pre-disaster mental health variables

Table 5.

Chronic disease variables

The intake assessment was generally completed in full for demographic data and the impact of the disaster. In contrast, the family history, history of trauma, and personal history of mental and physical illness were often omitted, particularly for the NTG.

Classification Tree Analysis

The initial CTA (Tree 1) included all independent variables. The analysis identified the resilience measures as the initial (node 0) distinguishing feature (P < 0.001) between the TG and NTG, with property damage, financial losses, and threat to life (nodes 1, 2, and 3, respectively – all P<0.001) as the next factors that distinguished between the TG and NTG. Insurance claims (P < 0.001) linked to the perception that one’s life was threatened was the only other feature that distinctly predicted the decision to enter or not enter treatment (Figure 2 and Table 6). The CTA prediction accuracy for the TG was 90.3% and NTG 96.7%.

Figure 2.

Classification Tree Analysis (CTA); treatment group (TG) vs non-treatment group (NTG).

Table 6.

CHAID treatment group (TG) vs non-treatment group (NTG) model predicts 90.3% entering TG and 96.7% of NTG

CHAID was separately used to assess the relevance of (a) demographic factors (Tree 2), (b) narrative questions and psychological measures (Tree 3), (c) property damage and insurance claims (Tree 4), (d) physical health, behavior changes and stressors (Tree 5), (e) previous mental health history and family history (Tree 6), and (e) and (f) chronic disease variables (Tree 7). The CTA prediction accuracy for the NTG varied from 91.9%-100%. In contrast, prediction was less accurate for the TG (28.6%-84.7%) (Table 7).

Table 7.

CHAID treatment group (TG) vs non-treatment group (NTG) model prediction CTA

The CTA (Table 7) indicates that prior mental health factors, the post-disaster perception of stress, property damage and losses, whether someone believed their life was threatened, coping, and the presence of chronic disease predicted non-participation (>90%). In contrast, the factors in Tree 3 (84.7%) were the only variables that predicted participation in treatment with greater than 80% accuracy.

The CHAID methodology identifies 5 items that distinguish between the TG and NTG. The resilience questions (TG vs NTG P<0.001), severity of property damage (TG vs NTG P<0.001), financial losses (TG vs NTG P<0.001), the belief one’s life was threatened (TG vs NTG P<0.001), and ongoing insurance claims (TG vs NTG P<0.003) identified those who entered treatment (90.3%) and the NTG (96.7%) (Table 6).