Adverse childhood experiences, resilience and mental health in Australian men

Key findings and implication

Implications for policy and practice

These findings highlight the urgent need for population-based approaches to preventing adverse childhood experiences to be a core component of the primary prevention of mental ill-health in adulthood.

For those who have experienced ACEs, these findings support strengthening trauma-aware, ACE-informed approaches across adult health, mental health and social services.

Considering the combination and severity of adversity could enable more proportionate identification of ongoing mental health risk in adult services, without increasing burden on clients or providers.

Variation in risk across population groups of Australian men points to the value of tiered, context-sensitive approaches, including culturally safe, gender-responsive and place-based service models.

The evidence suggests that efforts to strengthen social connection and support are likely to be most effective when embedded within broader trauma-aware and structurally informed responses, rather than delivered as stand-alone initiatives.

These findings also indicate scope to improve low-cost and no-cost mental health pathways, service navigation and continuity of care, particularly for men with high adversity exposure and financial stress.

This report largely draws on data collected using validated survey instruments. In some instances, the wording of individual survey questions may not fully align with contemporary trauma-informed language or the preferences of people with lived experience of the issue. Where possible, we have used language that centres the dignity and rights of those affected. Where original item wording is reproduced (e.g. for methodological transparency), we note that this reflects the survey instrument and not the position of the authors or of the Australian Institute of Family Studies.

Overview

What do we know?

Adverse childhood experiences (ACEs), traumatic or stressful events before the age of 18, can shape health and wellbeing long after childhood. These include abuse, neglect and household dysfunction (Centers for Disease Control and Prevention [CDC], 2023; Felitti et al., 1998). These experiences are linked to poorer mental health in adulthood. Higher ACE counts are associated with earlier onset of mental-health conditions, higher risks of depression and anxiety (Daníelsdóttir et al., 2024; Hughes et al., 2017) and greater health care costs (Hughes et al., 2017; Senaratne et al., 2024).

ACEs are common (Herberholz et al., 2025; Lian et al., 2022; McLaughlin et al., 2010; Wang et al., 2024), though estimates vary according to how ACEs are defined and measured. The Australian Child Maltreatment Study (ACMS) found that 62% of adults experienced at least one form of child maltreatment (Higgins et al., 2023). By contrast, a national survey using a different framework to measure potentially traumatic events during childhood reported a lower prevalence of 42% (Barrett et al., 2025). A longitudinal study - using another measurement approach - found that 69% of children had 2 or more ACEs before age 18 (Sahle et al., 2024).

Despite differences in how adversity is captured across studies, these figures highlight substantial and widespread exposure at a population level. Understanding the long-term consequences of these experiences is essential for informing effective public policy.

Although ACEs are common and linked to poorer adult mental health, outcomes vary. Not all individuals with high ACE exposure experience poor health outcomes (Fritz et al., 2018). Some thrive, supported by factors such as strong social ties and access to trauma-informed services (Bethell et al., 2019; Fritz et al., 2018; Steen et al., 2022). Psychosocial and behavioural factors, such as social connection and substance use, may help explain variations in mental health outcomes (Templeton et al., 2025).

Many studies summarise adversity using cumulative ACE scores, which assume that all adversities contribute equally and independently to adult outcomes. While this approach captures overall burden, it can obscure how different types of adversity accumulate and interact to shape risk, as specific combinations of harms may matter for specific outcomes (Briggs et al., 2021; Merrick et al., 2017; Sahle et al., 2024). In practice, adversities often co-occur and are shaped by family, social and contextual environments (Higgins & Hunt, 2023; Joshi & Truong, 2024). These overlapping influences create patterns or clusters that can be more informative than raw counts (Barboza, 2018; Herberholz et al., 2025; Lacey et al., 2020; Lian et al., 2022; Tynan et al., 2022).

Contextual factors, the same social and economic factors that can increase the likelihood of experiencing ACEs such as financial stress, poverty, parental mental illness and substance use, can also increase the likelihood of poor adult mental health outcomes (Briggs et al., 2021; Herberholz et al., 2025; Hughes et al., 2017; Merrick et al., 2017; Woldegiorgis et al., 2025). These overlapping influences can confound associations, making it harder to interpret cumulative ACE scores in causal terms (Briggs et al., 2021; Hughes et al., 2017; Merrick et al., 2017). Using cumulative ACE scores can also overlook important differences in the types and combinations of adverse experiences and what effect these might have.

Several gaps make it hard for policy makers and practitioners to identify who is most at risk and what supports are needed. First, most ACE-mental health studies are cross-sectional, so they cannot clarify how childhood adversity leads to adult outcomes over time. Second, very little research focuses on adult men, despite gendered differences in symptoms and help seeking (Hughes et al., 2017; Merrick et al., 2017). Third, evidence on which protective factors buffer risk within different ACE patterns is limited, making it difficult to target prevention or support to adults (Wang et al., 2024). Fourth, although some studies have identified ACE patterns, most have not been nationally representative, and few have examined how these patterns relate to resilience. Finally, evidence is also limited on how the impact of ACEs differs for priority population groups such as men with disability, men living in regional or remote areas and culturally and linguistically diverse men.

Current Australian strategies highlight adversity and mental health but their focus is largely on early childhood. These include the National Preventive Health Strategy 2021-2030 (Department of Health [DoH], 2021), the National Children's Mental Health and Wellbeing Strategy (National Mental Health Commission, 2021), the National Framework for Protecting Australia's Children (Department of Social Services [DSS], 2021) and the Early Years Strategy 2024-2034 (DSS, 2024).

As a result, there is limited guidance on how to support adults who continue to experience the long-term effects of childhood adversity. Furthermore, although research demonstrating that gender can shape the experiences, reporting and impacts of ACEs, there remains little evidence specifically focused on men (Hughes et al., 2017; Merrick et al., 2017). It is also likely that many adults affected by ACEs did not receive early intervention or support as children. Policy makers therefore need clear information on which ACE patterns carry the highest risk for men, which protective factors have the strongest buffering effects, and which population groups are most in need of tailored, trauma-aware responses.

How will this research address policy relevant evidence gaps?

Together, these evidence gaps limit governments' abilities to design proportionate, effective responses for adults affected by childhood adversity, and to discern the relative importance of preventing boys' exposure to ACEs as part of the primary prevention of mental ill-health in men. Current policy settings provide little guidance on which men face the greatest ongoing risk, which patterns of adversity matter most, or where targeted investment is likely to deliver the greatest mental health gains.

By applying pattern-based analysis to a large, nationally representative cohort of Australian men, this study addresses these constraints directly. It identifies distinct patterns of childhood adversity, examines how they relate to different mental health outcomes, and tests how risk and protective factors vary across priority and intersecting population groups. In doing so, the study moves beyond broad prevalence estimates to generate policy-relevant evidence that can inform targeted prevention, trauma-aware service design and adult-focused mental health strategies - supporting more efficient use of resources and more equitable outcomes for men across the life course.

Research objectives

Research questions for this Ten to Men snapshot

1. Prevalence of individual ACEs and distinct patterns:
   1. What is the prevalence of individual ACEs in adult men?
   2. What distinct patterns of ACEs can be identified based on responses to 10 ACE items?
2. The association of ACEs with mental health:
   1. Which distinct patterns/clusters of the 10 ACEs are most strongly associated with adult mental health outcomes?
   2. What proportion of the association between ACE patterns and mental health can be explained by resilience-enhancing/enabling factors?¹
3. Moderation effects of priority population groups:²
   1. Do the effects of ACEs on mental health vary by priority population group?
4. Barriers and facilitators to mental health service access:
   1. What are the barriers and facilitators to mental health service access for men with high ACE exposure, and how do these relate to mental health resilience?

The relationships between childhood adversity and mental health conditions

Figure 1 presents the conceptual framework guiding this analysis. Childhood adversity is represented by ACE patterns (dark orange box), which are hypothesised to influence adult mental health outcomes (yellow box) both directly (orange arrow) and indirectly (blue arrow). Resilience-enhancing factors (blue box) are positioned as mediators, as they may partially explain how ACE exposure translates to mental health outcomes. Priority population groups,2 defined in line with the National Men's Health Strategy (Department of Health, 2019), are treated as effect modifiers (grey box), reflecting the possibility that the strength or direction of ACE-mental health associations differ across population groups. Demographic and socio-economic factors are included as confounders, as they may influence both ACE exposure and adult mental health outcomes.

Figure 1: Conceptual framework

Note: This framework models a mediating pathway whereby higher ACE exposure is associated with reduced resilience-enhancing factors, which subsequently influence mental health outcomes.

Glossary

Key exposure: The variable represents the primary exposure of interest in relation to adult mental health outcomes. In this study, ACEs are the exposures.

Mediator: The variable explains the mechanism through which ACEs affect mental health. The mediator is expected to be shaped by ACEs and, in turn, to shape mental health. Mediators in this study include resilience-enhancing factors.

Effect modifier/moderator: The association between the exposure and the outcome differs across levels of another variable (the effect modifier). In this study, priority population groups (see footnote 2) are examined as effect modifiers.

Confounder/covariate: The variable is associated with both ACEs and mental health but does not lie on the causal pathway between them. Confounders are included to reduce bias in the estimated association between ACEs and mental health.

Outcome: The variable of interest that is hypothesised to be influenced by ACEs, either directly or indirectly. In this study, outcomes include adult mental health indicators.

Latent class analysis (LCA): A statistical approach that identifies distinct groups within a population based on shared patterns across multiple observed variables. In this study, LCA was used to identify common patterns of ACEs and assign individuals to the most likely pattern, based on their responses.

Prevalence/risk: Prevalence refers to the proportion of individuals in the population with a given outcome at a specific point in time. Risk refers to the probability of developing an outcome over a specified period.

Adjusted risk ratio (aRR): A measure that compares the risk of an outcome between groups while accounting for differences in other factors (confounders). An aRR greater than 1 indicates higher risk, while an aRR less than 1 indicates lower risk, compared with the reference group.

Adjusted hazard ratio (aHR): A measure used in time-to-event (survival) analyses that compares the rate at which an outcome occurs over time between groups. An aHR greater than 1 indicates a higher rate of the outcome occurring, while an aHR less than 1 indicates a lower rate, compared with the reference group.

Findings

ACEs are common among Australian men and are often co-occurring

Childhood adversity is widespread among Australian men. In 2024-25, around 3 in 5 men (62%) reported at least one adverse childhood experience, and 44% reported exposure to 2 or more types of childhood adversity (multi-type exposure) (Table 1 and supplementary materials, Table S5).

The most common individual experiences were emotional abuse (38%), physical abuse (34%), household mental illness (25%) and parental loss (25%) (Table 1 and supplementary materials, Figure S2).

Note: ^a This item is drawn from a standardised measure which uses the phrase 'unwanted sexual contact'. The authors acknowledge that this phrasing is a limitation of the original survey questions. Use of the phrase in this report should not be interpreted as implying that any form of sexual contact with a child could be consensual.
Source: Ten to Men Wave 5

Importantly, adversities rarely occurred in just one domain: for men with multi-type exposure (defined as exposure to 2 or more ACEs), the most common co-occurrence was emotional and physical abuse (around 9%), reinforcing that many men experience combinations of adversity rather than single categories of exposure (see Figure 2). This pattern of high overall prevalence and frequent co-occurrence is consistent with Australian and international evidence (Higgins et al., 2023; Merrick et al., 2017; Wang et al., 2024).

Figure 2: Commonly reported combinations of ACE (≥1% prevalence)

Note: IPV = Intimate partner violence
Source: Ten to Men Wave 5

Childhood adversity takes multiple forms, with varying exposure

Looking beyond overall prevalence, the analysis identified 3 distinct profiles of childhood adversity (Figure 3) that were remarkably consistent across birth cohorts (see Figure 4). Most men fell into a low-exposure group (around 60%, Class 1), around 30% experienced a profile centred on emotional/physical abuse with moderate probabilities of household dysfunction (Class 2), and around 8%-12% experienced high exposure across multiple types of adversity (Class 3). Different patterns of low to high adversity exposure have been identified in international studies and in an early Australian study, although the size and composition of classes varied depending on the ACE items included and the populations studied (Barboza, 2018; Higgins, 2004; Lacey et al., 2020; Wang et al., 2024).

The 3 profiles differed meaningfully in the likelihood of having specific adversity items (Figure 3). For example, the 'moderate' group (Class 2) showed very high probabilities of emotional abuse (82%) and physical abuse (69%), while the high exposure group showed consistently higher probabilities across many domains, including emotional abuse (96%), physical abuse (87%) and sexual abuse (35%) (see Figure 3 and supplementary materials, Table S6).

These patterns matter because they indicate that risk is shaped not only by how many adversities occurred but by which adversities co-occurred, and whether exposure reflects abuse alone versus broader multi-domain adversity.

Figure 3: Distinct patterns of ACEs and conditional probabilities of endorsing each ACE item within each latent class (unweighted)

Source: Ten to Men Wave 5

Figure 4: ACE exposure patterns across birth cohorts (weighted)

Source: Ten to Men Wave 5

High childhood adversity is unevenly distributed across priority population groups

Exposure to ACEs was unevenly distributed across priority population groups,³ with higher levels of high and multiple adversity observed in some groups. High and multiple ACE exposure (Class 3) was more prevalent among men living in outer regional and remote areas than in major cities (15% vs 9%). A clear socio-economic gradient was also evident, with men in high-disadvantage areas twice as likely to be in Class 3 as those in low-disadvantage areas (14% vs 7%).

Class 3 prevalence was higher among Australian-born men than among immigrants from non-main English-speaking countries (11% vs 6%), and substantially higher among men with disability compared to those without disability (16% vs 5%). Aboriginal and/or Torres Strait Islander men showed the highest prevalence of Class 3 exposure (32% vs 10% among non-Indigenous men), and men who had ever served in the Australian Defence Force also had higher Class 3 prevalence than those who had not (14% vs 10%) (see Figure 5 and supplementary materials, Table S7).

Figure 5: Distinct patterns of ACEs by priority population groups (weighted)

Notes: MESC = main English-speaking countries. SEIFA = Socio-Economic Indexes for Areas. IRSD = Index of Relative Socio-Economic Disadvantage. Error bars show 95% confidence intervals.
Source: Ten to Men Wave 5

Mental health outcomes worsen as adversity exposure increases and becomes more complex

Mental health outcomes showed a clear gradient across adversity patterns. Moderate to severe mental health symptoms were reported by 78% of men in the high exposure group (Class 3), compared with 59% in Class 2 and 35% in Class 1. A similar stepwise pattern was observed for other indicators, including diagnosed mental health conditions and symptom-based outcomes (see Figure 6 and supplementary materials, Table S8).

This demonstrates that it is not simply exposure versus non-exposure that matters; rather, the increasing severity and complexity of adversity is associated with progressively worse adult mental health. This stepwise pattern is also consistent with international evidence and Australian data (Higgins, 2004; Hughes et al., 2017; Thurston et al., 2025).

Figure 6: Proportions of Australians with mental disorders by ACE Class (weighted)

Notes: Error bars show 95% confidence intervals.
Source: Ten to Men Wave 5

Childhood adversity remains strongly associated with mental health even after accounting for other factors

The association between childhood adversity and adult mental health remained strong after adjusting for a range of socio-economic and demographic factors (Figures 7 and 8 and supplementary materials, Table S9). For example, experiencing at least one ACE was associated with double the risk of depression (aRR = 2.04; 95% CI [1.83, 2.28]).

When adversity was modelled as classes (profiles), men in Class 2 had 80% higher risk of moderate to severe depression symptoms (aRR = 1.80; 95% CI [1.65, 1.96]) compared to those in Class 1. Men in Class 3 had more than double the risk (aRR = 2.40; 95% CI [2.16, 2.65]). A similar gradient was observed for other mental health outcomes.

This graded pattern was also similar for men diagnosed with mental health conditions. Men in Class 3 showed a roughly 3-fold higher risk (reported as aHR = 2.67 to 2.85) relative to Class 1 (see Figure 8). Graded associations between ACE exposure and adult mental health outcomes have been consistently reported in previous studies such as systematic reviews and meta-analyses (Hughes et al., 2017) and a recent large population-based cohort study (Daníelsdóttir et al., 2024).

Figure 7: Associations between individual ACEs and (a) recent mental health symptoms and (b) diagnosed mental health conditions from age 18+ years

Figure 8: Associations between clustered ACEs and (a) recent mental health symptoms and (b) diagnosed mental health conditions from age 18+ years

Notes: The model is adjusted for age, employment status, educational status, occupation, income, financial stress and living arrangements. 'Any mental health symptoms' refers to having at least one of the individual symptoms. Any mental health diagnosis refers to having been diagnosed with depression, anxiety or any other mental health condition. PHQ9 = Patient Health Questionnaire-9
Source: Ten to Men Wave 4 and Wave 5

Resilience helps but its effects are partial and cumulative

Men with higher exposure to childhood adversity were less likely to report resilience-enhancing factors. For example, the probability of having strong social support was 18% lower in Class 2 and 36% lower in Class 3, compared with Class 1. Mediation analyses indicated that individual resilience-enhancing factors explained a modest share of the overall ACE-mental health association. Social connectedness or social support explained around 20%-30% of the total association for depression symptoms (see Table 2 and supplementary materials, Tables S10-S17). These results show that resilience-enhancing factors clearly matter but they do not account for all of the elevated risk linked to higher exposure to childhood adversity, a pattern also observed in other population-based studies (Bethell et al., 2019; Fritz et al., 2018).

When resilience-enhancing factors were examined together, their influence was stronger. In particular, the combination of social connectedness and social support explained close to one-quarter to one-third of the ACE-mental health association across several symptom outcomes. Similarly, combining social support with no substance use explained around one-fifth to one-third of the total ACE-mental health association (see Table 2 and supplementary materials, Tables S18-S20). This is consistent with evidence that multiple protective factors can have additive or synergistic buffering effects (Bethell et al., 2019; Fritz et al., 2018).

These results suggest that resilience is not 'one thing', rather it reflects multiple reinforcing supports and behaviours. For policy and service design, this suggests the use of integrated approaches that strengthen social connection and support alongside addressing behavioural (such as substance use) and structural (such as financial stress) risks.

Note: The model is adjusted for age, employment status, educational status, occupation, income, financial stress and living arrangements. AUDIT = Alcohol Use Disorders Identification Test.
Source: Ten to Men Wave 5

The impact of childhood adversity differs across population groups

The effects of adversity varied across priority population groups (see Figure 9 and supplementary materials, Tables S21-S28). Some groups (including men with disability and men identifying as LGBTQA+) showed higher baseline prevalence of mental health symptoms and diagnosed conditions, with smaller incremental increases at higher adversity exposure - consistent with a ceiling effect, where high baseline symptoms limited the additional observable impact of ACEs, a phenomenon hypothesised in other intersectional analyses (Havers et al., 2023). By contrast, men born in non-English speaking countries showed lower baseline risk consistent with the well-documented healthy migrant effect (Elshahat et al., 2022; Lee, 2019) but experienced elevated risk when adversity exposure was high, indicating that severe adversity can erode initial health advantages.

These patterns underscore that adversity does not operate in a vacuum: baseline risk differs by group, and the additional impact of high adversity can vary depending on context. This is consistent with Australian evidence showing elevated exposure to child maltreatment and related mental health risks among diverse population subgroups, including people of diverse genders and sexualities (Higgins et al., 2025).

Figure 9: Interaction between ACE classes and priority population groups for: (a) recent mental health symptoms and (b) diagnosed mental health conditions from age 18+ years

Note: The model adjusted for age, employment status, educational status, occupation, income, financial stress and living arrangements. ACE = Adverse childhood experiences. MESC = main English-speaking countries.
Source: Ten to Men Wave 5

Intersecting factors can amplify or blunt adversity-related risk

To better understand how structural factors combine to shape risk for priority population groups under the Men's Health Strategy, the analyses examined men with childhood adversity in 3 combinations of population groups (see Table 3 and supplementary materials, Tables S29-S36):⁴

1. having disability and living in regional/remote areas
2. having disability and being born in a non-English speaking country
3. being born in a non-English speaking country and living in regional/remote areas.

Across the first 2 combinations involving disability, the additional mental health risk associated with high childhood adversity was smaller than expected, consistent with a ceiling effect. Men with disability already showed elevated baseline levels of mental health symptoms and diagnosed mental health conditions, and the incremental impact of high adversity exposure was therefore attenuated. For example, among men with disability living in regional/remote areas, the association between high adversity exposure and mental health symptoms was substantially weaker than among men without these intersecting characteristics.

In contrast, a different pattern emerged for men born in non-English-speaking countries and living in regional/remote areas. While this group showed relatively lower baseline mental health risk, exposure to high levels of childhood adversity was associated with markedly elevated risks of depression and broader mental health symptoms. This suggests that, in some contexts, intersecting structural factors can compound vulnerability, rather than blunt it.

Together, these findings show that the mental health impact of childhood adversity is not uniform across intersecting social and structural contexts. Some combinations are associated with reduced observable gradients due to high baseline risk, while others show amplified effects when severe adversity occurs, underscoring the importance of context-specific, targeted responses.

Note: Each interaction analysis was adjusted for age, employment status, financial stress, educational status, income and living arrangements. ACE = Adverse childhood experiences. MESC = main English-speaking countries.
Source: Ten to Men Wave 5

Mental health service use increases with adversity exposure but gaps remain

Nearly half of men (47%) consented to linkage with MBS and PBS records. Among those, service contact increased with adversity exposure but gaps persisted. Overall, 44% of men had received a Medicare-recorded mental health service or filled a mental health prescription at some point since age 18.

Service contact was lowest in Class 1 (39%, 95% CI [36%, 41%]) and highest in Class 3 (65%, 95% CI [60%, 71%]). However, despite this gradient, a notable proportion of men with an identified mental health need, across all ACE profiles, had never accessed Medicare-recorded care. Among men who reported having ever been diagnosed with a mental health condition since age 18, over one in five (22%) had never accessed a Medicare-recorded mental health service in adulthood, including 18% of men in Class 3 (95% CI [13%, 24%]).

Financial stress appeared to be a key barrier to service use: among men with high exposure to adversity and a self-reported mental health diagnosis, financial stress was associated with a 14% lower likelihood of service use compared to those not in financial stress (aRR = 0.86; 95% CI [0.78, 0.96]). See supplementary materials, Table S37.

Implications for policy and practice

Preventing adverse childhood experiences as a primary prevention strategy for men's mental ill-health

Given the high prevalence of ACEs among Australian men and the clear gradient between increasing adversity and poorer adult mental health, these findings highlight the importance of preventing ACEs as part of primary prevention efforts to reduce mental ill-health across the life course for men.

Extending ACE-informed, trauma-aware approaches to adult services

This study shows that childhood adversity remains common among Australian men and continues to be strongly associated with poor mental health well into adulthood. Many men affected by ACEs are already interacting with adult services, including primary care, community mental health and social services, but these settings may not always be designed to recognise or respond to childhood adversity.

These results suggest value in complementary early-intervention strategies with clearer guidance for adult services, including safe and proportionate ACE-aware enquiry, trauma-responsive practice and referral pathways that extend beyond child-focused systems.

Considering patterns of adversity, not only simple ACE counts

Distinct profiles of childhood adversity were more strongly associated with adult mental health outcomes than cumulative thresholds alone. Severe, multi-domain adversity was linked to substantially worse outcomes, whereas simple counts added limited additional insight.

This suggests potential benefits in exploring profile-based, proportionate assessment approaches within adult services, particularly where the aim is to identify individuals who may benefit from more targeted, trauma-aware supports without increasing the burden on clients or providers.

Supporting targeted and differentiated responses for men experiencing high and compounded ACE-related risk

Mental health risks associated with childhood adversity varied across priority population groups. Some groups showed high baseline prevalence of mental health symptoms or diagnosed mental health conditions, with smaller incremental effects of adversity. For other groups, they experienced amplified risk with higher levels of ACE exposure. Our analysis of men who were in multiple priority population groups highlighted that risk is shaped by social and structural contexts, not adversity exposure alone.

Taken together, these findings support tiered, context-sensitive approaches - including culturally safe, gender-responsive and place-based models - and a prevention approach that prioritises more intensive, trauma-aware and culturally responsive approaches for men experiencing both high adversity and compounding risk. Such targeting can help ensure prevention intensity is proportionate to need and aligned with lived contexts shaping risk, consistent with broader government commitments in the Early Years Strategy (DSS, 2024) and National Framework for Protecting Australia's Children (DSS, 2021).

Strengthening resilience-enhancing supports while recognising their limits

Resilience-enhancing factors such as social support, social connection and reduced substance use accounted for a meaningful - but still small - proportion of the ACE-mental health association. This is consistent with wider research showing that resilience buffers but does not eliminate adversity-related risk (Bethell et al., 2019; Fritz et al., 2018).

This suggests that resilience-building initiatives are most effective when integrated within broader, trauma-aware and structurally informed responses, rather than positioned as stand-alone solutions.

Reducing structural and financial barriers to mental health service access, particularly for men with high ACE exposure

Although service use increased with ACE exposure, a substantial proportion of men with diagnosed mental health conditions, across all ACE profiles, had never accessed a Medicare-recorded mental health service or prescription since age 18. Financial stress was associated with lower service use even among men with clear clinical need.

These findings suggest scope to strengthen low-cost and no-cost pathways to improve continuity and navigation across services and align service design more closely with men's help-seeking preferences, particularly for those experiencing financial stress.

Next steps with Ten to Men data

Building on these findings, Ten to Men offers a strong platform to further strengthen the evidence base for ACE-informed, adult-focused mental health policy in Australia.

1. Future analyses could track mental health trajectories across adulthood to examine how distinct ACE patterns shape the onset, persistence and recurrence of mental health conditions over time, helping identify critical periods where intervention may prevent escalation.
2. Further work could also identify who benefits most from resilience-enhancing supports. Examining whether these factors are more protective for specific groups - such as men experiencing financial stress, men with disability or culturally and linguistically diverse men - would support more targeted and cost-effective investment.
3. Linkage between Ten to Men survey data and Medicare administrative data provides opportunities to strengthen evidence on pathways into and through mental health care, including delays to first contact, continuity of care and reliance on medication versus psychological services. This would help identify where service systems are misaligned with the needs of men with high ACE exposure, particularly those facing financial barriers.
4. Future analyses could also clarify unmet need, such as the proportion of men with moderate to severe symptoms who have never accessed Medicare-recorded mental health care, and how this varies by ACE pattern and socio-economic circumstances. This would inform proactive outreach and low-barrier service models.
5. Further research is needed to translate the 3 ACE profiles into clinically usable indicators - such as specific combinations of adversities that reliably signal higher-risk profiles - to support trauma-informed screening and risk stratification in routine adult health care.

References

Barboza, G. E. (2018). Latent classes and cumulative impacts of adverse childhood experiences. Child Maltreatment, 23(2), 111-125.

Barrett, E. L., Grummitt, L., Jones, S., Rowlinson, K., Vasilopoulos, F., Teesson, M., & Sunderland, M. (2025). The prevalence of potentially traumatic events in childhood and associations with mental disorders, suicide and physical health in adulthood: An Australian nationally representative cross-sectional study. Australian & New Zealand Journal of Psychiatry, 60(1), 80-90. 
doi.org/10.1177/00048674251381004

Bethell, C. D., Jones, J., Gombojav, N., Linkenbach, J., & Sege, R. (2019). Positive childhood experiences and adult mental and relational health in a statewide sample: Associations across adverse childhood experiences levels. JAMA Pediatrics, 173(11), e193007. 
doi.org/10.1001/jamapediatrics.2019.3007

Briggs, E. C., Amaya-Jackson, L., Putnam, K. T., & Putnam, F. W. (2021). All adverse childhood experiences are not equal: The contribution of synergy to adverse childhood experience scores. American Psychologist, 76(2), 243-252. 
doi.org/10.1037/amp0000768

Centers for Disease Control and Prevention (CDC). (2023). Guidance for analysing 2021 ACEs and PCEs data. CDC. 
stacks.cdc.gov/view/cdc/183358.

Daníelsdóttir, H. B., Aspelund, T., Shen, Q., Halldorsdottir, T., Jakobsdóttir, J., Song, H. et al. (2024). Adverse childhood experiences and adult mental health outcomes. JAMA Psychiatry, 81(6), 586-594. doi.org/10.1001/jamapsychiatry.2024.0321

Department of Health (DoH). (2019). National men's health strategy 2020-2030. Australian Government, DoH. 
www.health.gov.au/sites/default/files/documents/2021/05/national-men-s-health-strategy-2020-2030_0.pdf

Department of Health. (2021). National preventive health strategy 2021-2030. Australian Government, DoH. www
.health.gov.au/sites/default/files/documents/2021/12/national-preventive-health-strategy-2021-2030_1.pdf

Department of Social Services (DSS). (2021). The national framework for protecting Australia's children 2021-2031. Australian Government, DSS. www.dss.gov.au/system/files/documents/2024-10/dess5016-national-framework-protecting-childrenaccessible.pdf

Department of Social Services. (2024). The early years strategy 2024-2034. Australian Government, DSS. 
www.dss.gov.au/system/files/resources/early-years-strategy-2024-2034.pdf

Elshahat, S., Moffat, T., Newbury, J., & MacDougall, C. (2022). Understanding the healthy immigrant effect in the context of mental health challenges: A systematic critical review. Journal of Immigrant and Minority Health, 24(6), 1564-1579.

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V. et al. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. American Journal of Preventive Medicine, 14(4), 245-258. doi.org/10.1016/S07493797(98)000178

Fritz, J., de Graaff, A. M., Caisley, H., van Harmelen, A.L., & Wilkinson, P. O. (2018). A systematic review of amenable resilience factors that moderate and/or mediate the relationship between childhood adversity and mental health. Frontiers in Psychiatry, 9, 230. doi.org/10.3389/fpsyt.2018.00230

Havers, L., McLaughlin, K. A., & Sheridan, M. A. (2023). The role of intersectionality on the impact of adverse childhood experiences on adolescent depressive and anxiety symptoms. Journal of the American Academy of Child & Adolescent Psychiatry, 62(10), S234-S235.

Herberholz, E. S., Wolchok, R. E., Rogers, J. M., Selenou-Yemgang, S., Beckwith, B. D., Smith, K. E. et al. (2025). Latent classes of adverse childhood experiences (ACEs) and adult substance-use problems and psychosocial outcomes: complex and heterogeneous associations. International Journal of Mental Health and Addiction, 1-20.

Higgins, D. J. (2004). The importance of degree versus type of maltreatment: A cluster analysis of child abuse types. The Journal of Psychology, 138(4), 303-324.

Higgins, D. J., & Hunt, G. R. (2024). Child, parent and contextual factors associated with child protection system involvement and child maltreatment in the family: A rapid evidence review. Australian Journal of Social Issues, 59(2), 358-400.

Higgins, D. J., Lawrence, D., Haslam, D. M., Mathews, B., Malacova, E., Erskine, H. E. et al. (2025). Prevalence of diverse genders and sexualities in Australia and associations with child maltreatment. Child Maltreatment, 30(1), 21-41.

Higgins, D. J., Mathews, B., Pacella, R., Scott, J. G., Finkelhor, D., Meinck, F. et al. (2023). The prevalence and nature of multitype child maltreatment in Australia. Medical Journal of Australia, 218(Suppl 6), S19-S25. doi.org/10.5694/mja2.51868

Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D., Mikton, C., Jones, L. et al. (2017). The effect of multiple adverse childhood experiences on health. The Lancet Public Health, 2(8), e356-e366.

Joshi, A., & Truong, M. (2024). The role of adverse childhood experiences (ACEs) in adolescent use of violence. Australian Institute of Family Studies.

Lacey, R. E., Minnis, H., & Pinder, R. (2020). Adverse childhood experiences and adult inflammation. Brain, Behavior, and Immunity, 87, 820-830.

Lee, R. (2019). Does the healthy immigrant effect apply to mental health? SSM - Population Health, 7, 100311.

Lian, J., Kiely, K. M., & Anstey, K. J. (2022). Cumulative risk and latent class analysis of childhood adversity. Child Abuse & Neglect, 125, 105486.

McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2010). Childhood adversities and adult psychopathology. Psychological Medicine, 40(5), 847-859.

Merrick, M. T., Ports, K. A., Ford, D. C., Afifi, T. O., Gershoff, E. T., & GroganKaylor, A. (2017). Unpacking the impact of adverse childhood experiences on adult mental health. Child Abuse & Neglect, 69, 10-19.

National Mental Health Commission (NMHC). (2021). National children's mental health and wellbeing strategy. Australian Government, NMHC. www.mentalhealthcommission.gov.au/sites/default/files/2024-04/the-national-children-s-mental-health-and-wellbeing-strategy.pdf

Sahle, B. W., Reavley, N. J., Morgan, A. J., Yap, M. B. H., Reupert, A., & Jorm, A. F. (2024). Adverse childhood experiences and adolescent anxiety and depression. BMC Psychiatry, 24(1), 289.

Senaratne, D. N., Thakkar, B., Smith, B. H., Hales, T. G., Marryat, L., & Colvin, L. A. (2024). Adverse childhood experiences and multimorbidity. BMC Medicine, 22(1), 315.

Steen, M., Raynor, J., Baldwin, C. D., & Jee, S. H. (2022). Child adversity and trauma-informed care teaching interventions. Pediatrics, 149(3), e2021051174.

Templeton, J. M., Dixon, W. E., Jr., Williams, S., Morelen, D., DriggersJones, L., & Robertson, C. (2025). Social support as a mediator between ACEs and adult mental health. Journal of Experimental Child Psychology, 252, 106148.

Thurston, C., Murray, A. L., Franchino-Olsen, H., Silima, M., Hemady, C. L., & Meinck, F. (2025). Prospective longitudinal associations between adverse childhood experiences and adult mental health outcomes: Systematic review and meta-analysis. Trauma, Violence, & Abuse, 15248380251358223.

Tynan, M., Wooldridge, J. S., Rossi, F., McLean, C. L., Gasperi, M., Bosch, J. et al. (2022). Latent class patterns of adverse childhood experiences and their relationship to veteran status and sex in the national epidemiologic survey of alcohol and related conditions Wave III. Military Medicine, 187(3-4), 304-312.

Wang, X., Jiang, L., Barry, L., Zhang, X., Vasilenko, S. A., & Heath, R. D. (2024). A scoping review on adverse childhood experiences studies using latent class analysis: Strengths and challenges. Trauma, Violence, & Abuse, 25(2), 1695-1708.

Woldegiorgis, M., Corrigan, A., Gasser, C., & Martin, S. (2025). The two-way relationship between socio-economic status and health conditions for Australian men. Australian Institute of Family Studies. aifs.gov.au/tentomen/insights-report/two-way-relationship-between-socio-economic-status-and-health-conditions.

Further details

See supplementary materials [PDF, 741 KB] for technical details of this research, including descriptions of the measures and detailed results.