Mental Health Service Use Among Young People From Families With Different Intergenerational Patterns of Child Protection Contact

Abstract

This study examined mental health service use among 75,784 Australian young people from families with different intergenerational patterns of child protection (CP) contact evident in longitudinal multi-agency administrative data, namely cycle maintainers (parental and offspring CP contact), cycle initiators (only offspring CP contact), cycle breakers (only parental CP contact), or no CP contact. Young people from cycle maintainer families had the highest prevalence of mental health service use (76%), followed by those from cycle initiator (70%), cycle breaker (53%), then no CP contact families (49%). Young people from cycle maintainer and cycle initiator families accessed mental health services earlier than those from cycle breaker and no CP contact families. While those from families with cumulative intergenerational CP involvement were the most likely to use mental health services, young people’s mental health service use appeared to be more closely linked to their own CP contact than to that of their parents.

Keywords

child protective services mental health services families youth cohort studies epidemiology

Introduction

Childhood experiences of maltreatment are associated with adverse mental health outcomes across the life course (Baldwin et al., 2023; Carr et al., 2020; Lang et al., 2020). Young people known to child protection (CP) services for suspected child maltreatment victimization have a nearly fourfold greater prevalence of mental disorders than the general population (Bronsard et al., 2016). There is concordance in the international literature that young people involved with the CP system are more likely to use mental health services compared to their peers. For example, studies have reported that 83% of young people in the CP system have a record of mental health service use in Canada (MacDonald et al., 2024), and children in the CP system use mental health services at higher rates than the general population in the United Kingdom (Ball et al., 2024) and Australia (Green et al., 2025; Judd et al., 2024; Leckning et al., 2023; Trott et al., 2024).

Young people are also at increased risk of mental health problems if their parents were involved with the CP system and/or maltreated as a child, suggesting that offspring mental health outcomes may be linked to CP contact and child maltreatment victimization across generations (Bosquet Enlow et al., 2018; Negriff et al., 2020; Warmingham et al., 2020). Four distinct patterns of (dis)continuity of CP contact and/or child maltreatment across parental and offspring generations have been distinguished in the literature, using self-report and/or administrative CP data sources, namely: cycle maintainers, where the parent(s) and their offspring were both known to CP services or both experienced child maltreatment; cycle initiators, where the parent(s) were not known to CP services or they did not experience child maltreatment but their offspring were or did; cycle breakers, where the parent(s) were known to CP services or experienced child maltreatment but their offspring were not or did not; and controls, where the parent(s) and offspring both were not known to CP services or did not experience child maltreatment (Dixon et al., 2009; Islam et al., 2023; McKenzie et al., 2021; St-Laurent et al., 2019). Several studies have examined these intergenerational patterns of CP contact in association with characteristics and outcomes for the parent generation (rather than the offspring generation), such as parenting styles (Dixon et al., 2009), parental mental disorders and mental health service use (McKenzie et al., 2025a, 2025b), and maternal psychological functioning (St-Laurent et al., 2019). One other recent study has reported higher rates of self-reported psychopathology among offspring from cycle initiator and cycle maintainer families, relative to those from families with no history of child maltreatment; in that study, offspring from cycle breaker families reported less psychopathology than those from cycle maintainer families, but had similar levels of psychopathology to offspring from control families (Islam et al., 2023). These findings are consistent with a ‘buffering risk’ hypothesis in which offspring from cycle breaker families are buffered from adverse consequences relative to those from cycle maintainer families, potentially owing to comparatively fewer cumulative adversities among families which break the cycle of child maltreatment (Islam et al., 2023).

The extent to which intergenerational contact with the CP system is associated with offspring mental health service use has been less studied. Understanding whether parental contact with the CP system is relevant to offspring mental health service use in addition to the offspring’s own CP contact, as well as which mental health services offspring interact with and when they first use these services can inform the allocation of resources to deliver timely, targeted mental health support for young people with different intergenerational patterns of CP contact. While administrative health records can be useful for these purposes, there are potential caveats in interpreting mental health service use as reflecting mental health burden, since there can be substantial differences between the need for mental health services (e.g., due to the presence of mental health problems) and the actual use of such services (Burns et al., 2004; Levitt, 2009). This may reflect inequity in access to mental health services (Hashmi et al., 2023) or system-driven pathways (e.g., screening protocols and mandated assessments) designed to improve the detection and surveillance of mental health problems among young people reported to the CP system, which can increase the use of mental health services among these young people (NSW Health, 2025). As such, the present study provides a descriptive overview of the utilization of mental health resources among young people from families with different intergenerational patterns of CP contact, with a view to inform capacity planning for and provision of mental health services in regions where CP contact is highly concentrated.

Specifically, this study examined young people’s use of mental health services across specific service types (including subsidized primary health care, ambulatory mental health care, emergency department presentations, and hospital admissions), and their age at the first contact with mental health services, according to different intergenerational patterns of contact with the CP system. We used data from a large, representative, population-based sample of young people (offspring) from families in New South Wales (NSW), Australia.

Methods

Data Source

Data were drawn from the NSW Child Development Study (NSW-CDS) (Green et al., 2024). The NSW-CDS is an Australian longitudinal cohort study that uses record linkage to combine routinely collected administrative records for a population-based sample of 91,597 young people (offspring). Linked parent data were available for 75,784 (82.7%) young people whose births were registered in NSW (enabling linkage to parental records), while the 15,813 young people who did not have linked parent records were excluded from the current analysis (Supplemental Figure 1). This subsample of 75,784 young people is representative of the general NSW and Australian populations (Green et al., 2018). Record linkages were conducted by the NSW Centre for Health Record Linkage (CHeReL) and the Australian Institute of Health and Welfare (AIHW) Data Integration Service Centre using probabilistic record linkage methods across a set of identifiers, with an estimated false positive linkage rate of 0.5%. Ethical approval was provided by the NSW Population Health Services and Australian Capital Territory (ACT) Health Human Research Ethics Committees (HREC/18/CIPHS/49), the AIHW Human Research Ethics Committee (EO2020/4/1026), and the Aboriginal Health & Medical Research Council of NSW Human Research Ethics Committee (2298/24) under the ‘waiver of consent’ provision of the National Statement of Ethical Conduct in Human Research (National Health and Medical Research Council, 2023).

Sample

Participants were 75,784 young people (born 2002–2005), as well as 74,519 mothers (born 1956–1989) and 74,042 fathers (born 1943–1988) of these young people. There were 2,625 (3.5%) young people who shared a mother and/or father (i.e., had a sibling) in the sample. At the time of linkage (3 June 2024), the mean age of the young people was 20.7 years (SD = 0.4); 97.9% (n = 74,199) were aged 20–22 years and 2.1% (n = 1,585) were aged 18–19 years. Detailed sociodemographic and CP contact characteristics for this sample are reported elsewhere (Green et al., 2026).

Measures

Intergenerational Patterns of CP Contact

Information on CP contact for alleged child maltreatment victimization was identified from the NSW Department of Communities and Justice ChildStory dataset (1971–2020), available from birth to age 16–18 years for the young people (offspring) and for the same period for the parents (individually dependent on their year of birth). CP contact was defined as any type of CP report (whether substantiated or unsubstantiated, and regardless of meeting the threshold for risk of significant harm or not) or placement in out-of-home care (OOHC). CP records were available dating back to 1971 for OOHC placement records, and 1987 for other types of CP reports; notably, OOHC placements prior to 1987 were limited to those with a placement recorded during or after 1987.

Family triads (i.e., offspring, mother and father) or dyads (where data for the father were not available) were categorised into family units representing one of four intergenerational patterns of CP contact and/or child maltreatment: (1) cycle maintainer families, where at least one parent and their offspring were both known to CP services; (2) cycle initiator families, where the parents were not known to CP services but their offspring were; (3) cycle breaker families, where at least one parent was known to CP services but their offspring were not; or (4) no CP contact families, where the parents and offspring were both unknown to CP services. This terminology has been used to maintain consistency with existing international literature (Dixon et al., 2009; St-Laurent et al., 2019), however we acknowledge that these terms minimize the complexity surrounding legal and practical applications of the CP system. Contact with the CP system is a proxy, and not a direct measure, for child maltreatment victimization. These terms do not imply that the parent(s) were responsible for perpetrating maltreatment against their offspring.

Mental Health Service Use

Young people’s use of mental health services between birth and age ∼21 years were identified in the AIHW Medicare Benefits Schedule (MBS, 2002–2024) and Pharmaceutical Benefits Scheme Data Collections (PBS, 2001–2024), the NSW Ministry of Health Mental Health Ambulatory Data Collection (MH-AMB, 2001–2020), and the NSW Ministry of Health and ACT Health Emergency Department (EDDC, 2005–2021) and Admitted Patient Data Collections (APDC, 2001–2020). The MBS dataset records the delivery of primary and specialist health care services subsidized by the Australian Government; mental health service use was determined using item numbers reflective of mental health services (including Better Access mental health initiative services) delivered by general practitioners (GPs), psychologists, psychiatrists, and other health professionals (Supplemental Table 1). Better Access mental health initiative services were examined as a separate subcategory as they represent a specific Australian Government initiative aimed at improving the treatment of mental disorders in the community (Australian Government, 2025). The PBS dataset records the supply of prescription medications which are subsidized by the Australian Government. In the PBS dataset, mental health service use was defined as any instance of the following World Health Organization Anatomical Therapeutic Chemical Classification categories: antipsychotics (N05A), anxiolytics (N05B), hypnotics and sedatives (N05C), antidepressants (N06A), and/or psychostimulants, agents used for attention deficit hyperactivity disorder and nootropics (N06B). A composite index of ‘subsidized primary health services' included both MBS-subsidized health service use and PBS-subsidized prescriptions for mental health reasons. The MH-AMB dataset records details of non-admitted patient services, including mental health day programs, psychiatric outpatient, and community outreach services (e.g., home visits). The EDDC dataset records details of presentations to the emergency department of public hospitals. The APDC dataset records details of admitted patient services provided by public and private hospitals. In the MH-AMB, EDDC and APDC datasets, mental health service use was defined as any instance of the following International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes recorded in primary and/or secondary diagnoses: F00–F99, O99.3, R45, T14.91, U79, X60–X84, Y87.0, Z00.4, Z03.2, Z04.6, Z09.3, Z13.3, Z50.2, Z50.3, Z54.3, Z71.4, Z71.5, Z86.4, Z86.5, and/or Z91.5 (Supplemental Table 2).

Covariates

The young person’s month and year of birth (used to determine their age at the most recent data linkage and at their first use of mental health services), sex assigned at birth, and Aboriginal and/or Torres Strait Islander background were determined via consensus across all available records in the NSW-CDS. Individuals who identify as Aboriginal and/or Torres Strait Islander (i.e., the First Peoples of Australia) have a higher rate of contact with the CP system and mental health services than non-Indigenous Australians (Australian Institute of Health and Welfare, 2024; O’Donnell et al., 2019). The Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) Index of Relative Socio-economic Disadvantage (IRSD) (Australian Bureau of Statistics, 2021b) and Australian Statistical Geography Standard (ASGS) Accessibility/Remoteness Index of Australia (ARIA) (Australian Bureau of Statistics, 2021a) were determined from residential postcode data in the NSW Registry of Births, Deaths and Marriages Birth Registration Data Collection (2000–2006) and the NSW Ministry of Health and ACT Health Perinatal Data Collections (2000–2006), and used as indicators of area-based socioeconomic status and geographical remoteness at birth. Five ordinal categories were derived using the SEIFA IRSD quintiles (1 = most socioeconomically disadvantaged to 5 = least socioeconomically disadvantaged). The ARIA categories were collapsed into three categories (1 = major cities, 2 = inner regional, and 3 = outer regional, remote, and very remote). Maternal and paternal diagnosis of mental health problems were identified from the MH-AMB (2001–2020), EDDC (2005–2021) and APDC datasets (2001–2020), and defined as any instance of the following International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes in primary and/or secondary recorded diagnoses: mental and behavioral disorders (F00–F99), suicidal ideation (R45.81, R45.851), and/or intentional self-harm (X60–X84, T14.91, Y87.0).

Analyses

Univariate (unadjusted) and multivariable (adjusting for all covariates) multinomial logistic regression analyses were used to estimate associations between the intergenerational patterns of CP contact and the young people’s use of different types of mental health services, reported as odds ratios and 95% confidence intervals. The multinomial logistic regression analyses used different reference groups comprised of young people from no CP contact, cycle breaker or cycle maintainer families. Unadjusted analyses included all 75,784 young people and adjusted analyses included 75,648 young people as 136 young people did not have information on area-based socioeconomic status and/or geographical remoteness at birth (Supplemental Figure 1). Results were considered statistically significant if the value of 1.00 was not included in the 95% confidence interval. Differences in the first type of mental health service accessed according to intergenerational pattern were examined using the Chi-squared test. Relationships between the median age at the first use of mental health services for each intergenerational pattern were assessed using the Kruskal-Wallis rank sum test, with pairwise comparisons evaluated using the Wilcoxon rank sum test, applying a Benjamini-Hochberg correction. Statistical significance was set at p < 0.05. Ethical restrictions prevented the reporting of cell sizes with less than 15 individuals. Statistical analyses were performed in RStudio version 2023.12.1 using R version 4.3.2 (R Core Team, 2023). The figures were generated using the ggplot2 package (Wickham, 2016).

Results

Descriptive Statistics

Descriptives for the young people’s mental health service use and sociodemographic characteristics are presented in Table 1, stratified by intergenerational pattern of CP contact. Figure 1 shows the cumulative proportion of the young people’s use of mental health services by age, according to the intergenerational patterns. Overall, 55.5% (n = 42,067) of the total sample had a record of any mental health service use between birth and age ∼21 years. A higher proportion of young people from cycle breaker, cycle initiator and cycle maintainer families were Aboriginal and/or Torres Strait Islander, living in more socioeconomically disadvantaged, regional or remote areas at birth, and/or had a parent with a diagnosis of mental health problems, compared to the young people from no CP contact families.

Table 1.

Descriptive Statistics for Young People’s Mental Health Service Use and Sociodemographic Characteristics Stratified by Intergenerational Pattern of Child Protection Contact

	Total sample (n = 75,784)	No CP contact (n = 51,352)	Cycle breakers (n = 965)	Cycle initiators (n = 19,846)	Cycle maintainers (n = 3,621)
	n (Column %)
Mental health service use
Any mental health service	42,067 (55.5)	24,966 (48.6)	514 (53.3)	13,815 (69.6)	2,742 (75.7)
Subsidized primary health services	40,625 (53.6)	24,189 (47.1)	494 (51.2)	13,306 (67.0)	2,636 (72.8)
MBS-subsidized health services	38,172 (50.4)	22,676 (44.2)	460 (47.7)	12,602 (63.5)	2,434 (67.2)
Better access mental health initiative services	25,465 (33.6)	15,564 (30.3)	246 (25.5)	8,287 (41.8)	1,368 (37.8)
GP mental health treatment plan services	36,512 (48.2)	21,554 (42.0)	451 (46.7)	12,155 (61.2)	2,352 (65.0)
Psychologist services	24,597 (32.5)	15,110 (29.4)	234 (24.2)	7,961 (40.1)	1,292 (35.7)
Psychiatrist services	8,163 (10.8)	4,851 (9.4)	75 (7.8)	2,769 (14.0)	468 (12.9)
PBS-subsidized medication	22,568 (29.8)	12,505 (24.4)	276 (28.6)	7,949 (40.1)	1,838 (50.8)
Ambulatory mental health or hospital services	11,065 (14.6)	4,434 (8.6)	118 (12.2)	5,186 (26.1)	1,327 (36.6)
Ambulatory mental health services	8,218 (10.8)	2,867 (5.6)	75 (7.8)	4,145 (20.9)	1,131 (31.2)
Emergency department presentation	4,826 (6.4)	1,619 (3.2)	50 (5.2)	2,474 (12.5)	683 (18.9)
Hospital admission	3,659 (4.8)	1,432 (2.8)	39 (4.0)	1,751 (8.8)	437 (12.1)
Sociodemographic characteristics
Sex assigned at birth (male)	39,161 (51.7)	26,680 (52.0)	506 (52.4)	10,126 (51.0)	1,849 (51.1)
Mean age ± standard deviation in years^a	20.7 ± 0.4	20.7 ± 0.4	20.6 ± 0.4	20.7 ± 0.4	20.6 ± 0.4
Aboriginal and/or Torres strait islander	7,161 (9.4)	1,938 (3.8)	231 (23.9)	3,258 (16.4)	1,734 (47.9)
Area-based socioeconomic status at birth (SEIFA IRSD quintile)^b
1 (most disadvantaged)	14,770 (19.5)	8,607 (16.8)	304 (31.5)	4,705 (23.8)	1,154 (31.9)
2	15,198 (20.1)	9,308 (18.1)	268 (27.8)	4,576 (23.2)	1,046 (29.0)
3	16,774 (22.2)	11,065 (21.6)	239 (24.8)	4,591 (23.2)	879 (24.3)
4	9,075 (12.0)	6,470 (12.6)	85 (8.8)	2,213 (11.2)	307 (8.5)
5 (least disadvantaged)	19,832 (26.2)	15,858 (30.9)	69 (7.2)	3,679 (18.6)	226 (6.3)
Geographical remoteness at birth (ARIA category)^c
Major cities	58,517 (77.4)	41,116 (80.1)	640 (66.3)	14,603 (73.9)	2,158 (59.7)
Inner regional	12,611 (16.7)	7,583 (14.8)	226 (23.4)	3,816 (19.3)	986 (27.3)
Outer regional, remote, and very remote	4,520 (6.0)	2,608 (5.1)	99 (10.3)	1,345 (6.8)	468 (13.0)
Maternal diagnosis of mental health problems	15,095 (19.9)	5,840 (11.4)	243 (25.2)	6,808 (34.3)	2,204 (60.9)
Paternal diagnosis of mental health problems	11,353 (15.0)	4,358 (8.5)	229 (23.7)	5,214 (26.3)	1,552 (42.9)

CP: child protection, MBS: Medicare Benefits Schedule, GP: General Practitioner, PBS: Pharmaceutical Benefits Scheme, SEIFA: Socio-Economic Indexes for Areas, IRSD: Index of Relative Socio-economic Disadvantage, ARIA: Accessibility/Remoteness Index of Australia.

^aAt most recent data linkage (3 June 2024, MBS Data Collection).

^bMissing data for n = 135 in total sample for area-based socioeconomic status at birth in the total sample.

^cMissing data for n = 136 in total sample for geographical remoteness at birth in the total sample.

Figure 1.

Cumulative proportion of young people’s mental health service use by age and intergenerational pattern of CP contact. ‘Subsidized primary health services’ included Medicare benefits schedule (MBS)-subsidized health services and pharmaceutical benefits scheme (PBS)-subsidized medication. ‘Ambulatory mental health or hospital services’ included ambulatory mental health services, emergency department presentation, and hospital admission; these three services were combined to suppress small cell sizes where frequencies were less than 15

Young People’s Mental Health Service Use

Unadjusted and adjusted associations between the intergenerational patterns of CP contact and young people’s mental health service use are presented in Table 2 (reference group: young people from no CP contact families) and Table 3 (reference group: young people from cycle breaker or cycle maintainer families) and illustrated in Figure 2; unadjusted covariate associations are provided in Supplemental Table 3. Young people from cycle breaker, cycle initiator and cycle maintainer families were more likely to access any mental health service compared to young people from no CP contact families (Table 2, Figure 2). While young people from cycle breaker families were more likely to use any mental health service, MBS-subsidized GP mental health treatment plan services, ambulatory mental health services, and present to the emergency department with a mental health problem compared to those from no CP contact families, they were not more likely to use MBS-subsidized Better Access mental health initiative, psychologist and psychiatrist services, receive PBS-subsidized medication, or be admitted to hospital with a mental health problem. Ambulatory mental health services, emergency department presentations, and hospital admissions had the largest magnitudes of association with all intergenerational patterns of contact with the CP system. Young people from the cycle maintainer and cycle initiator families had a higher likelihood of accessing any mental health service compared to those from cycle breaker families (Table 3, Figure 2). Young people from cycle initiator families were less likely to use mental health services compared to those from cycle maintainer families (significant adjusted odds ratios ranging from 0.74 to 0.89), with the exceptions of MBS-subsidized Better Access mental health initiative and psychiatrist services where there was no evidence of a difference, and MBS-subsidized psychologist services where those from cycle initiator families had slightly higher likelihood (Table 3, Figure 2).

Table 2.

Unadjusted and Adjusted Associations Between Young People’s Mental Health Service Use and Intergenerational Patterns of Child Protection (CP) Contact (Reference Group: Young People From no CP Contact Families)

	Cycle breakers ^a		Cycle initiators ^a		Cycle maintainers ^a
	uOR (95% CI)	aOR^b (95% CI)	uOR (95% CI)	aOR^b (95% CI)	uOR (95% CI)	aOR^b (95% CI)
Any mental health service	1.20 (1.06–1.37)	1.19 (1.04–1.36)	2.42 (2.33–2.50)	2.18 (2.10–2.26)	3.29 (3.04–3.56)	2.59 (2.38–2.82)
MBS-subsidized health services	1.15 (1.01–1.31)	1.19 (1.05–1.36)	2.20 (2.13–2.28)	2.05 (1.97–2.13)	2.59 (2.41–2.79)	2.30 (2.12–2.49)
Better access mental health initiative services	0.79 (0.68–0.91)	0.91 (0.78–1.05)	1.65 (1.59–1.71)	1.66 (1.60–1.73)	1.40 (1.30–1.50)	1.53 (1.42–1.66)
GP mental health treatment plan services	1.21 (1.07–1.38)	1.25 (1.10–1.43)	2.19 (2.11–2.26)	2.03 (1.96–2.11)	2.56 (2.39–2.75)	2.27 (2.10–2.46)
Psychologist services	0.77 (0.66–0.89)	0.89 (0.77–1.04)	1.61 (1.55–1.66)	1.63 (1.57–1.69)	1.33 (1.24–1.43)	1.48 (1.36–1.60)
Psychiatrist services	0.81 (0.64–1.02)	0.94 (0.74–1.20)	1.55 (1.48–1.63)	1.57 (1.48–1.65)	1.42 (1.29–1.58)	1.47 (1.31–1.64)
PBS-subsidized medication	1.24 (1.08-1.43)	1.16 (1.00-1.33)	2.08 (2.01-2.15)	1.83 (1.76-1.90)	3.20 (2.99-3.43)	2.33 (2.16-2.52)
Ambulatory mental health services	1.43 (1.12–1.81)	1.28 (1.01–1.63)	4.47 (4.24–4.70)	3.76 (3.56–3.98)	7.68 (7.09–8.32)	5.08 (4.63–5.58)
Emergency department presentation	1.68 (1.26–2.24)	1.43 (1.07–1.92)	4.38 (4.10–4.67)	3.63 (3.38–3.89)	7.14 (6.48–7.87)	4.53 (4.05–5.08)
Hospital admission	1.47 (1.06–2.03)	1.31 (0.94–1.81)	3.37 (3.14–3.63)	2.78 (2.57–3.00)	4.79 (4.27–5.36)	3.30 (2.90–3.76)

uOR: unadjusted odds ratio, aOR: adjusted odds ratio, 95% CI: 95% confidence interval, MBS: Medicare Benefits Schedule, GP: General Practitioner, PBS: Pharmaceutical Benefits Scheme.

^aUnadjusted analyses included n = 75,784 and adjusted analyses included n = 75,648 (owing to missing data for n = 136 for area-based socioeconomic status and/or geographical remoteness at birth in the total sample).

^bAdjusted for young people’s sex assigned at birth, Aboriginal and/or Torres Strait Islander background, area-based socioeconomic status at birth, geographical remoteness at birth, and maternal and paternal diagnosis of mental health problems.

Table 3.

Unadjusted and Adjusted Associations Between Young People’s Mental Health Service Use and Intergenerational Patterns of Child Protection Contact (Reference Group: Young People From Cycle Breaker or Cycle Maintainer Families)

	Cycle initiators^a (Reference: cycle breakers)		Cycle maintainers^a (Reference: cycle breakers)		Cycle initiators^a (Reference: cycle maintainers)
	uOR (95% CI)	aOR^b (95% CI)	uOR (95% CI)	aOR^b (95% CI)	uOR (95% CI)	aOR^b (95% CI)
Any mental health service	2.01 (1.77–2.29)	1.83 (1.60–2.09)	2.74 (2.36–3.17)	2.18 (1.87–2.54)	0.73 (0.68–0.80)	0.84 (0.77–0.92)
MBS-subsidized health services	1.91 (1.68–2.17)	1.72 (1.50–1.96)	2.25 (1.95–2.60)	1.93 (1.66–2.23)	0.85 (0.79–0.92)	0.89 (0.82–0.97)
Better access mental health initiative services	2.10 (1.81–2.43)	1.83 (1.58–2.13)	1.78 (1.51–2.08)	1.69 (1.44–1.99)	1.18 (1.10–1.27)	1.08 (1.00–1.17)
GP mental health treatment plan services	1.80 (1.58–2.05)	1.62 (1.42–1.85)	2.11 (1.83–2.44)	1.81 (1.56–2.10)	0.85 (0.79–0.92)	0.89 (0.83–0.97)
Psychologist services	2.09 (1.80–2.43)	1.83 (1.57–2.13)	1.73 (1.47–2.04)	1.66 (1.40–1.95)	1.21 (1.12–1.30)	1.10 (1.02–1.19)
Psychiatrist services	1.92 (1.52–2.44)	1.66 (1.31–2.11)	1.76 (1.37–2.27)	1.56 (1.20–2.02)	1.09 (0.98–1.21)	1.07 (0.96–1.19)
PBS-subsidized medication	1.67 (1.45–1.92)	1.58 (1.37–1.83)	2.57 (2.21–3.00)	2.02 (1.73–2.37)	0.65 (0.60–0.70)	0.78 (0.73–0.85)
Ambulatory mental health services	3.13 (2.47–3.98)	2.93 (2.31–3.73)	5.39 (4.22–6.89)	3.96 (3.09–5.08)	0.58 (0.54–0.63)	0.74 (0.68–0.81)
Emergency department presentation	2.61 (1.95–3.48)	2.53 (1.90–3.38)	4.25 (3.16–5.72)	3.16 (2.35–4.27)	0.61 (0.56–0.67)	0.80 (0.72–0.88)
Hospital admission	2.30 (1.66–3.18)	2.13 (1.54–2.94)	3.26 (2.33–4.56)	2.52 (1.80–3.55)	0.71 (0.63–0.79)	0.84 (0.75–0.95)

uOR: unadjusted odds ratio, aOR: adjusted odds ratio, 95% CI: 95% confidence interval, MBS: Medicare Benefits Schedule, GP: General Practitioner, PBS: Pharmaceutical Benefits Scheme.

^bAdjusted for young person’s sex assigned at birth, Aboriginal and/or Torres Strait Islander background, area-based socioeconomic status at birth, geographical remoteness at birth, and maternal and paternal diagnosis of mental health problems.

Figure 2.

Adjusted associations between young people’s mental health service use and intergenerational patterns of CP contact

Age at and Type of First Mental Health Service Use

Across the intergenerational patterns of CP contact, the most common service type to be first used was MBS-subsidized health services, while the least common were emergency department presentation and hospital admission (Table 4). Young people from cycle maintainer families had the highest degree of poly-service use at their first mental health service use, followed by young people from cycle initiator and cycle breaker families, and then those from no CP contact families (χ² = 3,202.68, df = 6, p < 0.001).

Table 4.

Young People’s First Use of Mental Health Services Stratified by Intergenerational Pattern of Child Protection Contact

	Total sample (n = 75,784)	No CP contact (n = 51,352)	Cycle breakers (n = 965)	Cycle initiators (n = 19,846)	Cycle maintainers (n = 3,621)
	n (Column %)
First mental health service use^a
Subsidized primary health services	36,880 (48.7)	22,656 (44.1)	460 (47.7)	11,613 (58.5)	2,151 (59.4)
MBS-subsidized health services	31,646 (41.8)	19,752 (38.5)	390 (40.4)	9,862 (49.7)	1,642 (45.3)
Better access mental health initiative services	1,896 (2.5)	n < 1,220	n < 15	596 (3.0)	77 (2.1)
GP mental health treatment plan services	28,451 (37.5)	17,701 (34.5)	364 (37.7)	8,888 (44.8)	1,498 (41.4)
Psychologist services	1,927 (2.5)	n < 1,230	n < 15	612 (3.1)	80 (2.2)
Psychiatrist services	772 (1.0)	n < 530	n < 15	208 (1.0)	39 (1.1)
PBS-subsidized medication	6,785 (9.0)	3,848 (7.5)	98 (10.2)	2,221 (11.2)	618 (17.1)
Ambulatory mental health or hospital services	5,294 (7.0)	2,386 (4.6)	56 (5.8)	2,253 (11.4)	599 (16.5)
Ambulatory mental health services	3,035 (4.0)	1,241 (2.4)	24 (2.5)	1,363 (6.9)	407 (11.2)
Emergency department presentation	1,283 (1.7)	576 (1.1)	24 (2.5)	545 (2.7)	138 (3.8)
Hospital admission	1,346 (1.8)	n < 700	n < 15	528 (2.7)	118 (3.3)
Number of service types accessed at first mental health service use^b
One	40,094 (52.9)	23,907 (46.6)	481 (49.8)	13,137 (66.2)	2,569 (70.9)
Two or more	1,973 (2.6)	1,089 (2.1)	33 (3.4)	678 (3.4)	173 (4.8)
Median number of service types (interquartile range)	1 (1–1)	0 (0–1)	1 (0–1)	1 (0–1)	1 (1–1)

CP: child protection, MBS: Medicare Benefits Schedule, GP: General Practitioner, PBS: Pharmaceutical Benefits Scheme.

^aCategories of first mental health service use were not mutually exclusive.

^bAmong MBS-subsidized health services, PBS-subsidized medication, ambulatory mental health services, emergency department presentation, and hospital admission.

The median age at the first use of any mental health service was earlier among young people from cycle maintainer (11.8 years, interquartile range [IQR] = 7.9–15.2) and cycle initiator families (12.5 years, IQR = 8.1–15.7) compared to those from cycle breaker (14.4 years, IQR = 10.2–17.1) and no CP contact families (14.6 years, IQR = 9.7–17.3) (Kruskal-Wallis chi-squared = 1,249.2, df = 3, p < 0.001), and pairwise comparisons identified a significant difference between those from cycle maintainer and cycle initiator families (p < 0.001) but not those from cycle breaker and no CP contact families (p = 0.67). The median age at the first use of subsidized primary mental health services was earlier among young people from cycle maintainer (12.4 years, IQR = 8.3–15.7) and cycle initiator families (12.9 years, IQR = 8.7–16.0) compared to those from the cycle breaker (14.7 years, IQR = 10.5–17.3) and no CP contact families (14.9 years, IQR = 10.4–17.4) (Kruskal-Wallis chi-squared = 1,190, df = 3, p < 0.001), and similarly, there was a significant difference between young people from cycle maintainer and cycle initiator families (p < 0.001) but not those from cycle breaker and the no CP contact families (p = 0.50). The median age at the first use of ambulatory mental health and/or hospital services was earlier for young people from cycle maintainer (13.2 years, IQR = 9.4–15.2), cycle initiator (13.7 years, IQR = 9.7–15.4) and no CP contact families (13.6 years, IQR = 7.0–16.0) compared to those from cycle breaker families (14.4 years, IQR = 11.6–16.2) (Kruskal-Wallis chi-squared = 13.02, df = 3, p = 0.005), and pairwise comparisons identified a significant difference between those from cycle maintainer and cycle initiator families (p = 0.02) as well as between those from cycle breaker and no CP contact families (p = 0.01).

Discussion

In a representative population sample of 75,784 young people and their parents, 76% of young people from cycle maintainer families, 70% of those from cycle initiator families, 53% of those from cycle breaker families and 49% of young people from families without CP contact had at least one record of mental health service use between birth and age ∼21 years. Young people who had been the subject of a report to CP services (i.e., those from cycle maintainer and cycle initiator families) were more likely to access all types of mental health services and were younger at their first use of mental health services relative to young people without CP contact (i.e., from cycle breaker and no CP contact families). These findings accord with previous evidence showing that young people known to CP services access mental health services more than their peers (Ball et al., 2024; MacDonald et al., 2024; Neil et al., 2020; Nilsen et al., 2021), and this may be interpreted to reflect, at least in part, current system-driven responses to protect the health and wellbeing of young people exposed to childhood maltreatment. Our study builds on this body of work by identifying that there were marginal increases in the rate of mental health service use among young people from families in which both the parents and offspring had been in contact with CP services, compared to those from families where only the offspring had CP contact. While this observation is consistent with an ‘additive risk’ hypothesis (in which maltreatment in each generation has additive effects on adverse consequences for offspring) (Islam et al., 2023), it also suggests that young people’s use of mental health services may be more strongly linked with their own CP involvement relative to their parents’ CP contact.

While the overall use of mental health services among young people whose parents had a history of CP contact in the absence of the offspring’s own CP involvement (i.e., those from cycle breaker families) was relatively similar to young people from families without CP contact, there were differences in the use of specific mental health services by young people from cycle breaker families. For example, young people from cycle breaker families were more likely to use MBS-subsidized GP mental health treatment plan services compared to those from no CP contact families but they were not more likely to use MBS-subsidized psychologist and psychiatrist services. This was an unexpected finding, since a GP mental health treatment plan enables individuals to access free or subsidized referred sessions with mental health professionals (e.g., psychologists and psychiatrists) through the MBS-subsidized Better Access initiative (Australian Government, 2025). It is possible that socioeconomic disparities make these health services unaffordable for parents with their own history of CP contact, even with government subsidies. That young people from cycle breaker families were substantially less likely to use mental health services compared to young people from cycle maintainer or cycle initiator families is consistent with the ‘buffering risk’ hypothesis proposed by Islam et al. (2023), as well as reports of enhanced protective factors (e.g., positive, safe, stable and nurturing relationships) which distinguish parents from cycle breaker families from parents from cycle maintainer or cycle initiator families (Dixon et al., 2009; Jaffee et al., 2013; St-Laurent et al., 2019). Our findings thus provide valuable insights into the use of mental health services among young people from families with intergenerational discontinuity of CP contact, in a field which has been largely dominated by studies of continuity across generations (McKenzie et al., 2024).

Turning to families in which the young people had contact with CP services, the rates of mental health service use among young people from cycle maintainer families were slightly higher than that among those from cycle initiator families; also, young people from cycle maintainer families accessed mental health services earlier than those from cycle initiator families. A companion paper reports that a higher proportion of young people from cycle maintainer families in this sample had an OOHC placement (23.5%) or substantiated risk of significant harm CP report (25.7%) as their highest level of CP response compared to those from cycle initiator families (6.2% with an OOHC placement and 14.3% with a substantiated risk of significant harm CP report) (Green et al., 2026). Young people entering OOHC in NSW are provided with coordinated health assessments (NSW Health, 2025), which likely contribute to the higher rates and earlier use of mental health service use among the young people from cycle maintainer families. Also, the larger proportion of young people from cycle maintainer families with substantiated risk of significant harm CP reports suggests that these young people may be exposed to more severe and/or frequent child maltreatment that is, in turn, associated with a greater degree of mental health problems (Green et al., 2025).

Notably, our study included Aboriginal and/or Torres Strait Islander background as a covariate in focal analyses, with significant associations found between this variable and young people’s mental health service use. In Australia, Aboriginal and/or Torres Strait Islander people (i.e., the First Peoples of Australia) are over-represented in both the mental health and CP systems (Higgins et al., 2024; O’Donnell et al., 2019). The history of colonization, systemic racism, individual and intergenerational trauma, and government interventions have contributed to this over-representation (Australian Institute of Health and Welfare, 2024; Harnett & Featherstone, 2020). Our observations highlight the capacity, resilience and resources of Aboriginal and Torres Strait Islander families in navigating complex health care systems. It is essential that future research in this area adopts a strength-based approach and acknowledges the principles of Indigenous data sovereignty and governance to improve our understanding of the unique cultural needs and range of factors influencing mental health service use among Aboriginal and/or Torres Strait Islander young people with different intergenerational patterns of CP contact (Australian Institute of Aboriginal and Torres Strait Islander Studies, 2020).

Our findings should be interpreted with consideration of several limitations. First, we used contact with the CP system is a proxy for child maltreatment victimization, without limiting our measure to substantiated CP reports because reports that meet the threshold for further investigation may remain unsubstantiated owing to resource constraints which influence prioritization for follow up by case workers, or because the risk of harm or actual maltreatment cannot be sufficiently determined even if it did occur. Furthermore, there is evidence to suggest that there are no significant differences in developmental and mental health outcomes of children with substantiated vs. unsubstantiated CP reports (Kohl et al., 2009; Mehta et al., 2023). Second, the parents’ CP records did not span the entire childhood period as they covered 1971–2020, where OOHC records began in 1971 (for those with a record of OOHC during or after 1987) and other types of CP reports after 1987. The young people may have misclassified intergenerational patterns of CP contact if their parent(s) had CP records outside of these calendar years. Third, while our study incorporated records from five government health agency datasets spanning subsidized primary health, ambulatory mental health, and hospital services, these datasets did not capture all mental health services (e.g., non-subsidized services and psychological services managed internally by the NSW Department of Communities and Justice). Fourth, we were unable to account for migration out of NSW; as such, young people who used mental health services in another state or country would be misclassified as having less or no use of mental health services. Therefore, the rates of mental health service use in this sample are likely to be underestimated. Fifth, our analysis did not account for potential clustering within families (e.g., offspring with siblings). Sixth, this epidemiological study provides an initial descriptive overview of the use of mental health services among young people from families with different intergenerational patterns of CP contact. Exploring other factors that may impact offspring’s mental health service use, such as the severity, chronicity and timing of CP contact and/or child maltreatment among offspring and parent generations (Dunn et al., 2018; Russotti et al., 2026; Wong & Anderson, 2025), was beyond the scope of our study. Finally, we recognize that the relationship between intergenerational patterns of CP contact and mental health service use may be bidirectional. Mental health screening and assessments initiated by the CP system may contribute to the young people’s use of mental health services, while the young people already using mental health services may be more exposed to the CP system through cross-sector referrals and mandatory reporting of suspected child maltreatment by health care professionals.

Conclusion

This study provides important insights to inform resourcing of mental health care for young people from families with different intergenerational patterns of contact with the CP system (Font et al., 2020; McKenzie et al., 2024). Drawing on a representative population sample of ∼75,000 Australian young people with linked parent records, we identified a higher rate of and earlier mental health service use among young people with their own CP contact and those from families with cumulative intergenerational CP involvement. Therefore, policy makers and practitioners should consider the CP contact of young people and their parents (among other factors) when allocating resources for, and delivering, mental health services. For example, systems need to ensure adequate workforce capacity to provide trauma-informed and family-focused mental health services in regions with high rates of cumulative intergenerational CP contact. Future research should examine whether the profiles of mental health service use identified in this study are reflective of mental health needs, difficulties accessing mental health services, or other relevant circumstances. Furthermore, families known to CP services have multifaceted needs and are often in contact with sectors other than the health system, including the criminal justice (Berger et al., 2016; Whitten et al., 2021), civil justice (Gilbert et al., 2022; Tsantefski et al., 2021), and public housing systems (Malvaso et al., 2022). Continued work in this area is crucial to improving cross-sector supports for families with different intergenerational patterns of CP involvement.

Supplemental Material

Supplemental Material - Mental Health Service Use Among Young People From Families With Different Intergenerational Patterns of Child Protection Contact

Supplemental Material for Mental Health Service Use Among Young People From Families With Different Intergenerational Patterns of Child Protection Contact by Melissa Mei Yin Cheung, Stacy Tzoumakis, Emma F. McKenzie, Kimberlie Dean, Oliver J. Watkeys, Ken Zulumovski, Vaughan, J. Carr and Melissa J. Green in Child Maltreatment

Footnotes

Acknowledgements

This research used population data owned by the NSW Department of Communities and Justice; NSW Ministry of Health; ACT Health; NSW Registry of Births, Deaths and Marriages; Australian Institute of Health and Welfare; and NSW Department of Education. This research used data from the Australian Early Development Census (AEDC). The AEDC is funded by the Australian Government Department of Education. The findings and views reported are those of the authors and should not be attributed to these Departments and Agencies, or the NSW, ACT and Australian Governments. Record linkages were conducted by the NSW Centre for Health Record Linkage (CHeReL) and the Australian Institute of Health and Welfare Data Integration Service Centre.

ORCID iDs

Melissa Mei Yin Cheung

Emma F. McKenzie

Melissa J. Green

Ethical Considerations

Ethical approval was provided by the NSW Population and Health Services and ACT Health Human Research Ethics Committees (HREC/18/CIPHS/49), the Australian Institute of Health and Welfare Human Research Ethics Committee (EO2020/4/1026), and the Aboriginal Health & Medical Research Council of NSW Human Research Ethics Committee (2298/24) under the ‘waiver of consent’ provision of the National Statement of Ethical Conduct in Human Research.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was conducted with financial support from the National Health and Medical Research Council (NHMRC) Project Grant (APP1148055); Australian Research Council (ARC) Discovery Project (DP230101990); Department of Health, Disability and Ageing Medical Research Future Fund Million Minds Mental Health Grant (APP2006436); and Australian Government Department of Health, Disability and Ageing National Suicide Prevention Research Fund, managed by Suicide Prevention Australia (Postdoctoral Fellowship awarded to OW). The funders had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data used in this project have been provided by government custodians for research purposes of the NSW Child Development Study and are unable to be shared with third parties or deposited into data repositories. Collaborative research activities may be possible depending on scope and resources; alternatively, researchers wishing to access these datasets can apply directly to the relevant data custodians.*

Supplemental Material

Supplemental material for this article is available online.

References

Australian

Government.

(2025). Better Access Initiative. Department of Health, Disability and Ageing. Retrieved 13 Feb 2025 from https://www.health.gov.au/our-work/better-access-initiative

Australian Bureau of Statistics . (2021a). Remoteness areas: Australian Statistical Geography Standard (ASGS) Edition 3. Retrieved 22 Nov 2024 from https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/remoteness-structure/remoteness-areas

Australian Bureau of Statistics . (2021b). Socio-Economic Indexes for Areas (SEIFA), Australia. Retrieved 22 Nov 2024 from https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/latest-release

Australian Institute of Aboriginal and Torres Strait Islander Studies . (2020). AIATSIS Code of Ethics for Aboriginal and Torres Strait Islander Research. Retrieved 22 Nov 2024 from https://aiatsis.gov.au/sites/default/files/2022-02/aiatsis-code-ethics-jan22.pdf

Australian Institute of Health and Welfare . (2024). Aboriginal and Torres Strait Islander Health Performance Framework: 3.10 Access to Mental Health Services. Retrieved 22 Nov 2024 from https://www.indigenoushpf.gov.au/measures/3-10-access-to-mental-health-services

Baldwin

J. R.

Wang

Karwatowska

Schoeler

Tsaligopoulou

Munafò

M. R.

Pingault

J. B.

(2023). Childhood maltreatment and mental health problems: A systematic review and meta-analysis of quasi-experimental studies. American Journal of Psychiatry, 180(2), 117–126. https://doi.org/10.1176/appi.ajp.20220174

Ball

W. P.

Anderson

Black

Gordon

Lackenby

Murchie

Ostrovska

O’Sullivan

Rowlands

Rzewuska Díaz

Butler

J. E.

(2024). Mental health service use in children at risk of significant harm: A record linkage study of a child protection register. Social Science & Medicine, 353, 117057. https://doi.org/10.1016/j.socscimed.2024.117057

Berger

L. M.

Cancian

Cuesta

Noyes

J. L.

(2016). Families at the intersection of the criminal justice and child protective services systems. The Annals of the American Academy of Political and Social Science, 665(1), 171–194. https://doi.org/10.1177/0002716216633058

Bosquet Enlow

Englund

M. M.

Egeland

(2018). Maternal childhood maltreatment history and child mental health: Mechanisms in intergenerational effects. Journal of Clinical Child and Adolescent Psychology, 47(sup1), S47–S62. https://doi.org/10.1080/15374416.2016.1144189

10.

Bronsard

Alessandrini

Fond

Loundou

Auquier

Tordjman

Boyer

(2016). The prevalence of mental disorders among children and adolescents in the child welfare system: A systematic review and meta-analysis. Medicine, 95(7), e2622. https://doi.org/10.1097/md.0000000000002622

11.

Burns

B. J.

Phillips

S. D.

Wagner

H. R.

Barth

R. P.

Kolko

D. J.

Campbell

Landsverk

(2004). Mental health need and access to mental health services by youths involved with child welfare: A national survey. Journal of the American Academy of Child & Adolescent Psychiatry, 43(8), 960–970. https://doi.org/10.1097/01.chi.0000127590.95585.65

12.

Carr

Duff

Craddock

(2020). A systematic review of reviews of the outcome of noninstitutional child maltreatment. Trauma, Violence, & Abuse, 21(4), 828–843. https://doi.org/10.1177/1524838018801334

13.

Dixon

Browne

Hamilton-Giachritsis

(2009). Patterns of risk and protective factors in the intergenerational cycle of maltreatment. Journal of Family Violence, 24(2), 111–122. https://doi.org/10.1007/s10896-008-9215-2

14.

Dunn

E. C.

Soare

T. W.

Raffeld

M. R.

Busso

D. S.

Crawford

K. M.

Davis

K. A.

Fisher

V. A.

Slopen

Smith

A. D. A. C.

Tiemeier

Susser

E. S.

(2018). What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: Recency, accumulation, or sensitive periods? Psychological Medicine, 48(15), 2562–2572. https://doi.org/10.1017/S0033291718000181

15.

Font

Cancian

Berger

L. M.

DiGiovanni

(2020). Patterns of intergenerational child protective services involvement. Child Abuse & Neglect, 99, 104247. https://doi.org/10.1016/j.chiabu.2019.104247

16.

Gilbert

Stewart

Hurren

Little

Allard

(2022). Dual-system involvement: Exploring the overlap between domestic and family violence and child maltreatment perpetration. Journal of Interpersonal Violence, 37(9-10), NP6733–NP6759. https://doi.org/10.1177/0886260520967138

17.

Green

M. J.

Harris

Laurens

K. R.

Kariuki

Tzoumakis

Dean

Islam

Rossen

Whitten

Smith

Holbrook

Bore

Brinkman

Chilvers

Sprague

Stevens

Carr

V. J.

(2018). Cohort profile: The New South Wales Child Development Study (NSW-CDS)—Wave 2 (child age 13 years). International Journal of Epidemiology, 47(5), 1396–1397k. https://doi.org/10.1093/ije/dyy115

18.

Green

M. J.

McKenzie

E. F.

Watkeys

O. J.

Cheung

M. M. Y.

Dean

O’Hare

Zulumovski

Butler

Carr

V. J.

Tzoumakis

(2026). Intergenerational patterns of child protection system involvement in an Australian population cohort. Child Abuse & Neglect, 172, 107844. https://doi.org/10.1016/j.chiabu.2025.107844

19.

Green

M. J.

Watkeys

O. J.

Harris

O’Hare

Whitten

Tzoumakis

Laurens

K. R.

Carpendale

E. J.

Dean

Carr

V. J.

(2024). Cohort profile update: The New South Wales Child Development Study (NSW-CDS) – Wave 3 (child age ∼18 years). International Journal of Epidemiology, 53(3), dyae069. https://doi.org/10.1093/ije/dyae069

20.

Green

M. J.

Watkeys

O. J.

O’Hare

Tzoumakis

Laurens

K. R.

Dean

Harris

Carr

V. J.

(2025). Cumulative incidence of adolescent mental disorders following childhood maltreatment: An Australian longitudinal population cohort study. Australian and New Zealand Journal of Psychiatry, 59(3), 197–201. https://doi.org/10.1177/00048674241307150

21.

Harnett

P. H.

Featherstone

(2020). The role of decision making in the over-representation of Aboriginal and Torres Strait Islander children in the Australian child protection system. Children and Youth Services Review, 113, 105019. https://doi.org/10.1016/j.childyouth.2020.105019

22.

Hashmi

Alam

Gow

Alam

March

(2023). Inequity in psychiatric healthcare use in Australia. Social Psychiatry and Psychiatric Epidemiology, 58(4), 605–616. https://doi.org/10.1007/s00127-022-02310-1

23.

Higgins

Sheather-Reid

R. B.

Chalup

S. K.

Wilson

R. L.

(2024). Disproportionate mental health presentations to emergency departments in a coastal regional community in Australia of first nation people. International Journal of Mental Health Nursing, 33(6), 2063–2070. https://doi.org/10.1111/inm.13362

24.

Islam

Jaffee

S. R.

Widom

C. S.

(2023). Breaking the cycle of intergenerational childhood maltreatment: Effects on offspring mental health. Child Maltreatment, 28(1), 119–129. https://doi.org/10.1177/10775595211067205

25.

Jaffee

S. R.

Bowes

Ouellet-Morin

Fisher

H. L.

Moffitt

T. E.

Merrick

M. T.

Arseneault

(2013). Safe, stable, nurturing relationships break the intergenerational cycle of abuse: A prospective nationally representative cohort of children in the United Kingdom. Journal of Adolescent Health, 53(4, Supplement), S4–S10. https://doi.org/10.1016/j.jadohealth.2013.04.007

26.

Judd

Pilkington

R. M.

Malvaso

Procter

A. M.

Montgomerie

Anderson

J. J. A.

Jureidini

J. N.

Petersen

Lynch

Chittleborough

C. R.

(2024). Mental health-related hospitalisations of adolescents and their contact with child protection services to age 11 years, South Australia: A whole-of-population descriptive study. Medical Journal of Australia, 221(10), 540–545. https://doi.org/10.5694/mja2.52489

27.

Kohl

P. L.

Jonson-Reid

Drake

(2009). Time to leave substantiation behind: Findings from a national probability study. Child Maltreatment, 14(1), 17–26. https://doi.org/10.1177/1077559508326030

28.

Lang

Kerr

D. M.

Petri-Romão

McKee

Smith

Wilson

Zavrou

Shiels

Minnis

(2020). The hallmarks of childhood abuse and neglect: A systematic review. PLoS One, 15(12), e0243639. https://doi.org/10.1371/journal.pone.0243639

29.

Leckning

Condon

J. R.

Das

S. K.

Hirvonen

Guthridge

(2023). Mental health-related hospitalisations associated with patterns of child protection and youth justice involvement during adolescence: A retrospective cohort study using linked administrative data from the Northern Territory of Australia. Children and Youth Services Review, 145, 106771. https://doi.org/10.1016/j.childyouth.2022.106771

30.

Levitt

J. M.

(2009). Identification of mental health service need among youth in child welfare. Child Welfare, 88(1), 27–48. http://www.jstor.org/stable/45390157.

31.

MacDonald

Desrosiers

Laporte

Iyer

S. N.

(2024). Mental health service use of young people in child welfare services in Quebec, Canada. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 33(2), 77–90. https://pmc.ncbi.nlm.nih.gov/articles/PMC11201724/.

32.

Malvaso

Montgomerie

Pilkington

R. M.

Baker

Lynch

J. W.

(2022). Examining the intersection of child protection and public housing: Development, health and justice outcomes using linked administrative data. BMJ Open, 12(6), e057284. https://doi.org/10.1136/bmjopen-2021-057284

33.

McKenzie

E. F.

Hurren

Tzoumakis

Thompson

C. M.

Stewart

(2024). New directions in intergenerational child maltreatment research and responses: Knowledge gaps and recommendations. Australian Journal of Social Issues, 59(2), 316–327. https://doi.org/10.1002/ajs4.281

34.

McKenzie

E. F.

Thompson

C. M.

Hurren

Tzoumakis

Stewart

(2021). Who maltreats? Distinct pathways of intergenerational (dis)continuity of child maltreatment. Child Abuse & Neglect, 118, 105105. https://doi.org/10.1016/j.chiabu.2021.105105

35.

McKenzie

E. F.

Thompson

C. M.

Ogilvie

J. M.

Tzoumakis

Hurren

(2025). Examining mental health service use across intergenerational patterns of child protection system contact: A case for cross-sector supports. Child Abuse & Neglect, 163, 107426. https://doi.org/10.1016/j.chiabu.2025.107426

36.

McKenzie

E. F.

Thompson

C. M.

Tzoumakis

Ogilvie

Hurren

Stewart

(2025). The overlaps between intergenerational (dis)continuity of child protection services involvement and mental illness diagnoses from hospital admissions. Journal of Family Violence, 40(3), 489–501. https://doi.org/10.1007/s10896-023-00610-x

37.

Mehta

Kelly

A. B.

Laurens

K. R.

Haslam

Williams

K. E.

Walsh

Baker

P. R. A.

Carter

H. E.

Khawaja

N. G.

Zelenko

Mathews

(2023). Child maltreatment and long-term physical and mental health outcomes: An exploration of biopsychosocial determinants and implications for prevention. Child Psychiatry and Human Development, 54(2), 421–435. https://doi.org/10.1007/s10578-021-01258-8

38.

National Health and Medical Research Council . (2023). National Statement on Ethical Conduct in Human Research. Retrieved 22 July 2024 from https://www.nhmrc.gov.au/about-us/publications/national-statement-ethical-conduct-human-research-2023

39.

Negriff

Palmer Molina

Hackman

D. A.

(2020). Parental exposure to childhood maltreatment and offspring’s mental health: Investigating pathways through parental adversity and offspring exposure to maltreatment. Child Maltreatment, 25(4), 422–432. https://doi.org/10.1177/1077559520912342

40.

Neil

A. L.

Islam

Kariuki

Laurens

K. R.

Katz

Harris

Carr

V. J.

Green

M. J.

(2020). Costs for physical and mental health hospitalizations in the first 13 years of life among children engaged with child protection services. Child Abuse & Neglect, 99, 104280. https://doi.org/10.1016/j.chiabu.2019.104280

41.

Nilsen

S. A.

Askeland

K. G.

Loro

D. P. J.

Iversen

A. C.

Havnen

K. J. S.

Bøe

Heradstveit

(2021). Mental health, adverse life events and health service use among Norwegian youth in the child welfare system: Results from a population-based study. Child & Family Social Work, 26(4), 601–616. https://doi.org/10.1111/cfs.12842

42.

NSW Health . (2025). Out-of-Home Care Health Pathway Program Retrieved 23 Mar 2026 from https://www.health.nsw.gov.au/kidsfamilies/MCFhealth/programs/Pages/out-of-home-care.aspx

43.

O’Donnell

Taplin

Marriott

Lima

Stanley

F. J.

(2019). Infant removals: The need to address the over-representation of Aboriginal infants and community concerns of another “stolen generation”. Child Abuse & Neglect, 90, 88–98. https://doi.org/10.1016/j.chiabu.2019.01.017

44.

R Core Team . (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/

45.

Russotti

Warmingham

Swerbenski

Handley

E. D.

Cicchetti

(2026). Intergenerational continuity of multidimensional patterns of child maltreatment exposure: A person-centered approach. Development and Psychopathology, 38(1), 405–417. https://doi.org/10.1017/s0954579425100217

46.

St-Laurent

Dubois-Comtois

Milot

Cantinotti

(2019). Intergenerational continuity/discontinuity of child maltreatment among low-income mother–child dyads: The roles of childhood maltreatment characteristics, maternal psychological functioning, and family ecology. Development and Psychopathology, 31(1), 189–202. https://doi.org/10.1017/S095457941800161X

47.

Trott

Bull

Najman

J. M.

Arnautovska

Siskind

Warren

Kisely

(2024). Hospital admissions and community health service contacts for mental illness following self-reported child maltreatment: Results from the Childhood Adversity and Lifetime Morbidity (CALM) study. Child Abuse & Neglect, 154, 106912. https://doi.org/10.1016/j.chiabu.2024.106912

48.

Tsantefski

Young

Wilde

O’Leary

(2021). High-risk cases at the intersection of domestic/family violence and child protection: Learning from practice. Journal of Family Violence, 36(8), 941–952. https://doi.org/10.1007/s10896-021-00255-8

49.

Warmingham

J. M.

Rogosch

F. A.

Cicchetti

(2020). Intergenerational maltreatment and child emotion dysregulation. Child Abuse & Neglect, 102, 104377. https://doi.org/10.1016/j.chiabu.2020.104377

50.

Whitten

Dean

Laurens

K. R.

Harris

Carr

V. J.

Green

M. J.

(2021). Earlier contact with child protection services among children of parents with criminal convictions and mental disorders. Child Maltreatment, 26(1), 63–73. https://doi.org/10.1177/1077559520935204

51.

Wickham

(2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag. https://ggplot2.tidyverse.org.

52.

Wong

D. R.

Anderson

K. G.

(2025). Life course models of child maltreatment: Effects on general psychopathology outcomes in a longitudinal sample. Child Maltreatment, 30(2), 318–330. https://doi.org/10.1177/10775595241270076

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.40 MB