Characteristics of affected family members seeking treatment in their own right: a secondary analysis of existing Irish health data for 2010–2020

Abstract

Background

Affected family members (AFMs) are impacted by a significant other’s drug, alcohol, or behavioural addictions, and deserve support in their own right. The aim of this study was to describe AFMs seeking treatment and the support received.

Methods

Referral data (2010–2020) for AFMs seeking treatment because of being affected by another’s drug, alcohol, or behavioural addictions were analysed descriptively in this cross-sectional study (n = 13,744). The data are from an existing Irish health surveillance system.

Results

Referrals were mostly females (77.5%) aged 35–54 years (38.9%). Children and young adults each accounted for 6.5% of referrals. Adults mostly lived with children (61.7%) and self-referred (63.1%). Children mostly lived with family (93.2%) and were referred through social/community services (42.0%) and family/friends (40.7%). Individual counselling and brief intervention were the main treatments for adults and children. Among adults, the highest median treatment duration was for group counselling (120 days); among children, it was individual education/awareness programmes (165 days).

Conclusions

Findings demonstrate the demand for services for AFMs, and highlight the need for services for women, children, and young adults. Routine surveillance is a valuable source of data and could include further items on AFMs seeking personal support and supporting others through addiction treatment.

Keywords:

• Affected family members
• treatment
• problem substance use
• addiction
• health surveillance

Introduction

Drug, alcohol, and other addictions are a major contributor to adult ill-health globally, impacting not only on those with addictions but also on the health and well-being of the individuals, families and communities around them. Policy makers, practitioners, and health service planners face significant challenges in responding to the issue and in ensuring services address the needs of those impacted. Sometimes forgotten are the partners, wives, husbands, parents, siblings, children, extended family, friends, work colleagues, and others who are significantly close to, or involved in, the lives of persons experiencing substance use and other addictions (Orford, 2022). Conservative estimates place the number of adult family members that are affected by a loved one’s substance addiction at over 100 million worldwide (Orford et al., 2013). While this figure includes non-related persons, it does not include persons concerned about others’ non-substance (behavioural) addictions such as gambling, nor does it include the children whose lives are disrupted due to addiction within their families. Sometimes people use drugs or alcohol, or engage in behaviours like gambling or gaming, in a way that negatively impacts on their lives, as well negatively affecting the lives of those around them. For some, problem substance use and other non-substance problem behaviours become addictions, where a person has an inability to control their problem behaviour despite severe negative consequences for them and for their loved ones. In this study, family members, friends, and colleagues who are affected by, or concerned about, a significant other’s problem substance use, non-substance problems such as gambling, or addictions, are referred to as affected family members (AFMs).

Traditionally, AFMs have rarely been the primary focus of policy, research, and practice in the field of addiction (Orford, 2022). As such, they have been largely ‘unknown and uncounted’ and the level of harm experienced has been poorly understood (Orford et al., 2013, p. 71). In the past decade, some national policies in Ireland and elsewhere have begun to acknowledge both the needs of family members and their role in prevention, treatment and recovery for persons experiencing addictions (Devaney, 2017). Once viewed as part of the problem, AFMs are increasingly being considered a source of recovery capital and as deserving of assistance in their own right (Devaney, 2017). However, despite the enhancing attention, AFMs remain a specialised subject, largely ignored by policy makers, marginalised in health services, and neglected by academic research (Orford, 2022).

Existing research documents the considerable stress and strain experienced by AFMs in association with problem substance use, non-substance behavioural problems, and addictions among their significant others (Bischof et al., 2022; Dowling et al., 2014; McDonagh et al., 2019; Orford, Copello et al., 2010; Orford et al., 2010, 2017, 2019). AFMs experience multiple stressors and face many coping dilemmas (Benishek et al., 2011; Orford, 2017; Orford et al., 2010, 2017). Often, family members support and care for their significant others without recognition or reward, and sometimes at great social, financial, emotional, and physical cost (Bischof et al., 2022; Copello et al., 2010; Copello & Templeton, 2012; Di Sarno et al., 2021). AFMs tend to face such difficulties alone and in isolation, often for long periods of time, and without receiving support in their own right (Copello et al., 2010; McDonagh et al., 2019).

Much of the literature on the experiences of AFMs has focused on those impacted by problem substance use (drugs and/or alcohol) or gambling. Family members affected by a significant other’s problem substance use experience multiple biopsychosocial stressors that impact on health and quality of life. Emotional distress, family and relationship issues, financial problems, and health consequences are common (Benishek et al., 2011). Many report feelings of worry, anxiety, helplessness, anger, guilt, and despair (Orford et al., 2010). AFMs report poorer general health, as well as psychological symptoms, clinically significant mental health issues, and sometimes substance use (Di Sarno et al., 2021; Orford et al., 2010; Ray et al., 2007). The stress experienced may be intensified where there are concurrent mental health disorders among significant others (Denomme & Benhanoh, 2017). Similarly, those affected by another’s problem gambling report negative impacts on their psychological and physical health, relationships, social lives, work, and finances (Dowling et al., 2014; Svensson et al., 2013). Indeed, the issues faced by family members affected by a significant other’s problem gambling are akin to those experienced by family members impacted by problem substance use (Orford et al., 2017). With gambling, however, additional issues arise from the hidden, secretive nature of the problem, the sudden traumatic way in which it is often discovered, and the associated impacts on family finances (Orford, 2015; Orford et al., 2017). There is also some evidence to suggest that children’s experiences are similar whether the problem of the parent/caregiver is gambling or substance use, and these include a risk of neglect and of experiencing emotional and educational difficulties (Orford et al., 2017).

A review by Orford et al. (2010), spanning two decades of qualitative research, identified a universal core experience for family members affected by a significant other’s drug, alcohol, or other addiction. This includes a deterioration in the relationship with the significant other, which involves poorer communication and sometimes aggression, as well as physical violence, emotional abuse, and conflict over material possessions. Family members may experience uncertainty and worry about the significant other and harmful effects on home and family life. Though universal, this core experience is modified by factors such as the relationship of the family member and significant other, their ages and genders, the substance(s) used and where use takes place (inside or outside the home), and the sociocultural group to which they belong. Additionally, the burden on AFMs is intensified where there are multiple co-occurring problems, where the affected family member is in a position of dependence and subordination (especially women and children), and when quality social support is lacking (Orford, 2022).

According to the Stress-Strain-Coping-Support (SSCS) Model, being an affected family member is inherently stressful and can result in strain manifesting in physical and psychological health problems (Orford, Copello et al., 2010). The strain experienced depends on how the affected individual responds to, or copes with, the adverse circumstances. High quality social support, which includes emotional supports, information, and practical help, received formally or informally, enhances coping, and reduces negative impacts on health and functioning (Orford, Copello et al., 2010). However, good social support, though highly valued by AFMs, is often not available (Orford et al., 2010). Interventions tailored to the needs of AFMs in their own right have been lacking (Kitt-Lewis et al., 2022; Merkouris et al., 2020; Orford et al., 2013; Shorter et al., 2022). Furthermore, barriers exist for family members seeking and accessing help. These include a lack of awareness of own needs or services available and how to access them (Adfam, 2010; McDonagh et al., 2019), as well as logistical issues (e.g. transport, childcare), and reluctance or fear to engage due to loyalty to the family and significant other and/or concerns about confidentiality (McDonagh et al., 2019). Additionally, stigma, shame, threats, and coercive control can be significant deterrents to support seeking among AFMs (Adfam, 2012; Hing et al., 2013; McDonagh et al., 2019; Orford et al., 2010).

In international research in the area, involving various sampling strategies, participants tend to be mostly females (typically mothers and female partners), though males (usually fathers and partners) and other relatives (siblings and adult children) are also represented (Orford et al., 2010, 2013, 2017, 2019, Sakiyama et al., 2015; Shorter et al., 2022). In one of the largest studies of AFMs to date (n = 3,158), Orford et al. (2019) convenience sampled family members from treatment settings across Brazil, and reported 80.6% of participants were females, and 46.6% were female parents; the modal age group of participants was 45–54 years; and 0.6% of participants were children (aged under 18 years).

Among those affected by others’ problem substance use or addiction, children (aged under 18 years) are recognised as a special subgroup (Comiskey, 2019; Health Service Executive (HSE), & Tusla Child and Family Agency (TUSLA), 2019; Velleman & Templeton, 2016). Having a parent experiencing problem substance use is associated with negative outcomes in all life domains, both short and longer term (Velleman & Templeton, 2016). The risk is intensified with the presence of co-occurring problems (especially domestic abuse), having more than one parent with problem substance use, and the extent of other addiction-associated issues within and outside the family (Velleman & Templeton, 2016). Factors such as a child’s gender, age, and developmental stage will affect how they are impacted by a parent’s problem substance use, with those youngest and those experiencing key transitions likely to be most vulnerable (Templeton, 2013, as cited in Velleman & Templeton, 2016). While it is difficult to estimate the extent of such hidden harm (Galligan & Comiskey, 2019), treatment data give some indication. In Ireland, for example, 15.8% of cases entering treatment for drugs in 2021, and 21.2% of cases entering treatment for alcohol the same year, were residing with children aged under 18 years (Kelleher et al., 2022; Lynch et al., 2022).

As a hidden population, prevalence data in relation to AFMs are lacking, and where they exist, are likely to underestimate the extent of the issue (Copello & Templeton, 2012). Other than applying a multiplier to every individual dealing with a personal addiction, it is very difficult to estimate how many concerned others might be affected (Copello et al., 2010; Orford et al., 2013). While data on AFMs are not yet captured in population surveys in Ireland, these have been a source of information on this group internationally. A study in Germany, using a nationally representative sample of residents aged 15+, reported 9.5% of respondents had a relative with a current substance use problem and a further 4.5% were affected in the past 12 months (Bischof et al., 2022). Data on AFMs are not routinely included in surveillance data from addiction services, although routine monitoring is a potentially valuable source of evidence on the characteristics of this group and numbers affected (Copello et al., 2010). In Ireland, the National Drug Treatment Reporting System (NDTRS) has collected data on AFMs since 2010.

The aim of the current study was to maximise the use of an existing surveillance dataset (the NDTRS) to generate evidence to inform policy, planning and the delivery of services for AFMs, both in Ireland and internationally. The data were analysed to describe characteristics of AFMs seeking support in their own right, and the services they received, including treatment settings and referral pathways. To the authors’ knowledge, this is the first study of its kind in Ireland or beyond. The evidence generated contributes to the growing international body of evidence on AFMs and their support needs.

Methodology

A secondary analysis of data from an Irish national health surveillance system, the NDTRS, was undertaken to describe the characteristics of AFMs accessing specialised addiction and family support services in Ireland over an 11-year period (2010–2020) and the services they received. This was a primarily descriptive study, conducted within a cross-sectional research design. The approach was data-driven, with the analysis determined by the variables in the existing dataset (Cheng & Phillips, 2014).

Established in 1990, the NDTRS is the national public health surveillance database that records and reports on treated problem drug and alcohol use in Ireland. The NDTRS is managed by the Health Research Board (HRB) on behalf of the Department of Health. For the purposes of the NDTRS, treatment is broadly defined as any activity which aims to ameliorate the psychological, medical, or social state of individuals seeking help. Information from the NDTRS is required to meet mandatory reporting requirements at national, European and international levels. Data are routinely collected from statutory, community and voluntary drug and alcohol treatment providers nationally. NDTRS data collection complies with the European Treatment Demand Indicator (TDI) protocol (European Monitoring System for Drugs and Drug Addiction (EMCDDA), 2012) and is a comprehensive measure of treatment demand (Bruton et al., 2021). NDTRS data are episodic, and there is a possibility that individuals appear more than once in the database if accessing different treatment services or if they return to the same service. It is not possible to track individuals across services, as a unique health identifier has not yet been implemented in Ireland. Further information on the NDTRS methodology is presented in Bellerose et al. (2011).

In 2010, in response to service providers’ data needs, the NDTRS began facilitating the recording of data on AFMs accessing addiction and family support services for personal support in coping with their significant other’s problem drug or alcohol use or addiction, or behavioural addictions such as gambling, gaming, sex, porn, and spending. Such AFMs, may self-refer to services, or may be referred through other social, community, or medical sources. Though not mandated by national policy, NDTRS-participating service providers can optionally record data on referrals for, and supports provided to, AFMs (with client consent). During the study period, 255 individual services returned data on AFMs to the NDTRS. Due to the voluntary recording of the data, it is possible the figures reported in this study underestimate referrals for AFMs nationally. However, recording of the data has been driven by service providers’ desire to evidence the breadth and scope of their work. Additionally, NDTRS data coverage (numbers of admissions and treatment services reporting data) is high (Health Research Board. Irish National Focal Point to the European Monitoring Centre for Drugs and Drug Addiction, 2017), particularly in inpatient, outpatient and low threshold settings (Bruton et al., 2021). The NDTRS is the only source of data on AFMs seeking support nationally and the data can provide a valuable insight into the characteristics of those accessing treatment and the services they received.

To maximise the use of the existing data, all available records for AFMs in the NDTRS database (2010–2020) were included in this study (n = 13,744). A limited set of variables (mainly demographics) was available for data capture initially (2010–2015). Following requests from service providers, data capture was extended in 2016 to include assessment and treatment information, where possible to record. Analysed for the current study were:

• basic demographic variables (gender, age, education, employment, living circumstances) and types of treatment setting for all referrals for 2010–2020 (n = 13,744);

• additional demographic variables (country of birth, language spoken at home) for a subset of referrals from 2016 to 2020 (n = 6,546);

• the source of referral for a subset of referrals from 2016 to 2020 (n = 4,542); and

• the main treatment interventions received and duration of treatment for cases that exited treatment from 2016 to 2020, where treatment data were available (n = 3,084).

The NDTRS does not collect information on the relationship between the AFM seeking support and their significant other, nor the living status, or problems of the significant other, nor does it collect data on associated issues within the relationship such as domestic violence.

NDTRS data are validated and cleaned according to agreed coding rules. Additional logic checks were completed on the data subset included in this study prior to analysis. The data were analysed descriptively using SPSS Statistics (Version 26) (IBM Corp, 2019). Variables were analysed without cases where the response was ‘unknown.’ For each variable, the total number of cases and percentage of valid responses were calculated and then compared descriptively across response items. Descriptive statistics (number of cases and percentages) are presented for all variables for all referrals and separately for adult referrals and child referrals. For age, the mean, standard deviation, median and range at 5th and 95th percentiles were calculated. To examine the age and gender of referrals in more detail, grouped age and gender variables were cross tabulated, and results are described for all referrals. Findings are reported in accordance with RECORD guidelines for reporting observational health data that are routinely collected (Benchimol et al., 2015).

This study involved the analysis of a pseudonymised dataset extracted from an existing health surveillance database. This secondary use of the data is compatible with the original purposes of the data, and therefore, study-specific ethical approval and consent were not required.

Results

Demographic characteristics of referrals 2010–2020

From 2010 to 2020, 13,744 referrals for AFMs were recorded (Table 1). Females were in the majority, accounting for more than three quarters (77.5%) of all referrals. The median age of referrals was 45 years. Where age was known, 93.5% of referrals were for adults (aged 18 years and over). Females accounted for 79.0% of the adult referrals and half of the adult referrals were aged 46 years or under. Where age was known, 6.5% (815) of referrals were for children (aged under 18 years). Females accounted for 54.8% of the child referrals and half of the child referrals were aged 15 years or under.

Table 1. Gender and age of referrals 2010–2020, all referrals, adult referrals, and child referrals^a.

	All referrals		Adult referrals		Child referrals
Total	n = 13,744		n = 11,754		n = 815
Gender	n = 13,698	%	n = 11,714		n = 814	%
Male	3,087	22.5	2,460	21.0	368	45.2
Female	10,611	77.5	9,254	79.0	446	54.8
Age	n = 12,569		n = 11,754		n = 815
Mean age (years)	43.4		45.4		14.2
Std deviation	15.1		13.5		2.6
Median age (years)	45		46		15
Range (5th–95th percentiles)	16–67		22–68		9–17

^aVariables were analysed without cases where the response was ‘unknown.’

To further examine the age and gender of referrals, gender and grouped age (where known) were cross tabulated (Table 2). Over a quarter of all referrals (26.2%) were aged 45–54 years, making this the modal age group. The second largest age group was 35–44 years, accounting for 22.1% of referrals. Young adults (aged 18–24 years) accounted for 6.5% of referrals, the same proportion as children (aged under 18 years). Among all referrals, females aged 45–54 years (20.7%) comprised the largest age/gender subgroup.

Table 2. Gender and grouped age cross tabulation for all referrals 2010–2020.

		Grouped age
		All referrals
		<18	18–24	25–34	35–44	45–54	55–64	65+	Total
Male	n	368	202	302	490	688	524	254	2,828
	% within gender	13.0	7.1	10.7	17.3	24.3	18.5	9.0	100.0
	% within age	45.2	24.7	16.3	17.7	21.0	25.5	27.1	22.6
	% of total	2.9	1.6	2.4	3.9	5.5	4.2	2.0	22.6
Female	n	446	615	1,554	2,278	2,589	1,534	684	9,700
	% within gender	4.6	6.3	16.0	23.5	26.7	15.8	7.1	100.0
	% within age	54.8	75.3	83.7	82.3	79.0	74.5	72.9	77.4
	% of total	3.6	4.9	12.4	18.2	20.7	12.2	5.5	77.4
Total	n	814	817	1,856	2,768	3,277	2,058	938	12,528
	% within gender	6.5	6.5	14.8	22.1	26.2	16.4	7.5	100.0
	% within age	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
	% of total	6.5	6.5	14.8	22.1	26.2	16.4	7.5	100.0

Number where age and gender known = 12,528.

For all age groups, females were in the majority among referrals (Table 2). Among the 25–34 years and 35–44 years age groups, females accounted for more than eight-in-ten referrals. Among young adult referrals, 75.1% were females and 24.7% were males.

Among the female referrals, the 45–54 years age group was the largest, accounting for over a quarter (26.7%) of these referrals (Table 2). Half of the female referrals (50.2%) were aged 35–54 years. Males aged 45–54 years accounted for almost a quarter (24.3%) of male referrals, making this the modal age group for males. Males in this age group accounted for just 5.5% of all referrals.

Of the adult referrals, 65.1% had completed some post-primary education (24.1% Junior Certificate and 41.0% Leaving Certificate) and 22.9% had completed third level education (Table 3). Around one-in-ten adult referrals (11.9%) had not completed education beyond primary level. A small proportion of referrals (0.1%) had never been to school. Almost all (94.2%) of the child referrals were students and most (95.8%) had not yet completed upper post-primary level education (Leaving Certificate).

Table 3. Education and employment of referrals 2010–2020, all referrals, adult referrals, and child referrals^a.

	All referrals		Adult referrals		Child referrals
Total	n = 13,744		n = 11,754		n = 815
Education	n = 8,811	%	n = 8,192	%	n = 425	%
Primary level incomplete	150	1.7	105	1.3	42	9.9
Primary level	1,072	12.2	870	10.6	194	45.5
Junior Certificate	2,180	24.7	1,977	24.1	172	40.4
Leaving Certificate	3,460	39.3	3,355	41.0	17	4.0
Third level	1,936	22.0	1,873	22.9	0	0.0
Never went to school	13	0.1	12	0.1	0	0.0
Employment	n = 12,582	%	n = 10,767	%	n = 796	%
In paid employment	6,010	47.8	5,482	50.9	7	0.9
Student	1,060	8.4	286	2.7	750	94.2
Training course	219	1.7	190	1.8	11	1.4
Housewife/husband	1,597	12.7	1,378	12.8	0	0.0
Unemployed	2,361	18.8	2,192	20.4	25	3.1
Other	18	0.1	15	0.1	<5	<1.0

^aVariables were analysed without cases where the response was ‘unknown.’

Almost half (47.8%) of all referrals were in paid employment, while 18.8% were unemployed (Table 3). Around one-in-ten (10.1%) referrals were in education or training and 12.7% were home makers.

Most referrals (98.4%) were living in stable accommodation (Table 4). Adults mostly lived with others; many were living with children, either alone with child(ren) (19.0%) or with a partner and child(ren) (42.7%). Around one-in-ten (9.5%) adult referrals were living alone. Children mostly lived with parents and family (93.2%). A small proportion of children (2.6%) and young adults (<0.1%) were living in foster care.

Table 4. Living circumstances of referrals 2010–2020, all referrals, adult referrals, and child referrals^a.

	All referrals		Adult referrals		Child referrals
Total	n = 13,744		n = 11,754			n = 815
Living where	n = 13,409	%	n = 11,500	%		n = 803	%
Stable accommodation	13,198	98.4	11,321	98.4		782	97.4
Homeless	52	0.4	47	0.4		<5	<1.0
Other unstable accommodation	102	0.8	86	0.7		10	1.2
Prison	<5	<1.0	<5	<1.0		0	0.0
Institution (residential care/halfway house)	54	0.4	43	0.4		7	0.9
Living arrangements	n = 13,268	%	n = 11,371	%		n = 807	%
Alone	1,140	8.6	1,078	9.5		0	0.0
Parents or family	2,202	16.6	1,338	11.8		752	93.2
Friends	138	1.0	128	1.1		7	0.9
Partner (alone)	1,701	12.8	1,615	14.2		<5	<1.0
Partner and child(ren)	5,428	40.9	4,860	42.7		6	0.7
Alone with child(ren)	2,417	18.2	2,161	19.0		<5	<1.0
Other	212	1.6	183	1.6		18	2.2
Foster care	32	0.2	8	<0.1		21	2.6

^aVariables were analysed without cases where the response was ‘unknown.’

Additional demographic variables were available for a subset of referrals for 2016–2020. Of the 6,546 referrals, 5,715 were for adults and 532 were for children (Table 5). Over ten percent of the referrals (12.5%) spoke a language other than the country’s official languages (English or Irish) at home, with 13.3% of adult referrals and 6.9% of child referrals speaking another language at home (Table 5). The main languages reported were Polish, Russian, Latvian, and Romanian. Over ten percent of referrals (12.1%) were born outside of Ireland, with 13.1% of adult referrals and 5.6% of child referrals born in another country.

Table 5. Additional demographic variables for referrals 2016–2020, all referrals, adult referrals, and child referrals^a.

	All referrals		Adult referrals		Child referrals
Total	n = 6,546		n = 5,715		n = 532
Language at home	n = 4,357	%	n = 3,818	%	n = 378	%
English or Irish	3,814	87.5	3,310	86.7	352	93.1
Other language	543	12.5	508	13.3	26	6.9
Country of birth	n = 5,384	%	n = 4,681	%	n = 485	%
Ireland	4,735	87.9	4,069	86.9	458	94.4
Outside Ireland	649	12.1	612	13.1	27	5.6

^aVariables were analysed without cases where the response was ‘unknown.’

Treatment and supports received

Treatment variables were analysed for 3,084 AFM cases that exited treatment, where treatment data were available. Where age was known, 93.0% of cases were adults and 7.0% (212) were children (Table 6). Individual counselling (37.3%) was the most common intervention, received by 38.3% of adult cases and 30.2% of child cases. This was followed by brief intervention (20.8%), received by 37.3% of adult cases and 20.8% of child cases (20.8%), and by individual education awareness programme (11.5%), received by 11.1% of adult cases and 16.5% of child cases. Multi-component model, which for the NDTRS includes the 5-Step Model developed for use with AFMs (Copello et al., 2010), was recorded for 5.5% of all cases. Additional support activities reported included key working, received by 33.5% of cases and care plan, received by 32.9% of cases (n = 3,084).

Table 6. Main treatment interventions received for treated cases, where known, 2016–2020, all cases, adult cases, and child cases.

	All cases		Adult cases		Child cases
Total	n = 3,084		n = 2,818		n = 212
Treatment interventions	n	%	n	%	n	%
Individual counselling	1150	37.3	1078	38.3	64	30.2
Brief intervention	1118	36.3	1051	37.3	44	20.8
Individual education awareness	354	11.5	313	11.1	35	16.5
Group education awareness	318	10.3	302	10.7	8	3.8
Family therapy	272	8.8	250	8.9	10	4.7
Group counselling	170	5.5	169	6.0	<5	<1.0
Multi-component model^*	137	4.4	107	3.8	30	14.2

^*Includes the 5-Step Model.

Where known, more than three-in-five child AFM cases (63.9%) had another person (family member, friend, or other significant individual) involved in their treatment who was not being treated for a personal issue (n = 191). Over a third of adult AFM cases (36.7%) had another person involved in their treatment (n = 2,514).

Duration of treatment

Among adult cases, group counselling had the highest median treatment duration, with half of cases receiving this intervention for 120 days or more (Table 7). Among child cases, the highest median duration in treatment was observed for individual education awareness programme, with half of child cases receiving this intervention for 165 days or more.

Table 7. Main interventions - length of treatment in days for treated cases, where known, 2016-2020, all cases, adult cases, child cases.

	All cases			Adult cases			Child cases
	n	Median	Range^a	n	Median	Range^a	n	Median	Range^a
Individual counselling	1,150	85	(1–460)	1,078	85	(1–458)	64	96	(8–438)
Individual education awareness	354	60	(1–324)	313	57	(1–332)	35	165	(7–291)
Group education awareness	318	22	(1–357)	302	22	(1–364)	8	33	(N/A)
Family therapy	272	43	(1–302)	250	43	(1–286)	10	86.5	(1-N/A)
Group counselling	170	120	(8–367)	169	120	(8–367)	<5	36	(36–36)
Multi-component model	137	37	(4–297)	107	64	(1–303)	30	37	(17–277)

^aDay range presented is the 5th percentile to 95th percentile. N/A: median cannot be calculated.

Treatment duration was not calculated for brief intervention as it is by definition a treatment of short duration (1–4 sessions), often implemented opportunistically (Mattoo et al., 2018). However, some 2,715, instances of brief intervention were recorded among 1,039 cases for which the number of sessions was available, making an average of 2.6 sessions per case.

Treatment settings and referral pathways

The majority of referrals were made to outpatient settings (76.1%) (Table 8). Low threshold settings received 23.7% of adult referrals and 34.1% of child referrals.

Table 8. Treatment setting for referrals 2010–2020, all referrals, adult referrals, and child referrals^a.

	All referrals		Adult referrals		Child referrals
Setting	n = 13,744	%	n = 11,754	%	n = 815	%
Outpatient	10,466	76.1	9,496	80.6	537	65.9
Inpatient	24	0.2	24	0.2	0	0
Low threshold	3,254	23.7	2,261	19.2	278	34.1

^aVariables were analysed without cases where the response was ‘unknown.’

Adults were most likely to self-refer to treatment (63.1%), with smaller proportions referred by social services (12.7%) and family and friends (13.1%) (Table 9). General practitioners (3.8%), hospitals and other medical sources (3.5%) accounted for small proportions of adult referrals. A small proportion of child referrals were self-referred (5.9%), with the majority being made by social/community services (42.0%) and family and friends (40.7%).

Table 9. Source of referral 2016–2020, for all cases, adult cases, and child cases^a.

	All referrals		Adult referrals		Child referrals
	n = 4,542		n = 4,080		n = 324
Source of referral	n	%	n	%	n	%
Self	2,670	58.8	2,576	63.1	19	5.9
Social services/community services	679	14.9	520	12.7	136	42.0
Family and friends	595	13.1	443	10.9	132	40.7
Another drug treatment centre	182	4.0	168	4.1	11	3.4
Hospital or other medical source	169	3.7	142	3.5	19	5.9
General practitioner	168	3.7	157	3.8	6	1.9
Court/probation/police	70	1.5	65	1.6	<5	<1.0
Other	9	0.2	9	0.2	0	0.0

^aVariables were analysed without cases where the response was ‘unknown.’

Discussion

In this study, 13,744 records for AFMs referred to specialised addiction and family support services were analysed in, to the authors’ knowledge, the first study to use routine surveillance data to describe AFMs referred for treatment in their own right, and the services they received. Over an 11-year period, the NDTRS recorded an average of 1,249 referrals annually for AFMs seeking treatment, revealing a substantial demand on addiction and family support services. A main finding was that the majority of referrals were for females and many were females aged 35–54 years. Also noteworthy, is that a large number of referrals were for children, half of whom were aged 15 years or under, and that young adults were also represented. For both adult and child cases, the most common treatments reported were individual counselling and brief intervention. Adults mostly self-referred, while children were mostly referred through social/community services and family and friends. The majority of referrals were made to outpatient treatment settings.

The gender profile of referrals observed in the current study is consistent with findings from other studies of AFMs internationally, demonstrating that participants tend to be women (Orford, Copello et al., 2010; Orford et al., 2010, 2013, 2017, 2019; Sakiyama et al., 2015; Shorter et al., 2022). The increasing number of such studies, using various sampling methods and involving different sociocultural groups, suggests that women are more likely to experience the burdens of being an affected family member. Also consistent with previous research (Orford et al., 2019), women aged 35–54 years were over-represented among referrals in this study, accounting for 38.9% overall. Although it was not possible to tell from the NDTRS data, these family members are likely to be mothers, wives, and female partners, consistent with other studies (Orford et al., 2019). It should be noted that men, accounting for 22.6% of referrals in the current study overall, may also experience the burdens associated with being an AFM and can face various barriers in seeking and accessing help (Orford et al., 2010). As might be expected, the gender disparity in adult referrals was not observed among the child referrals, with girls and boys almost equally represented. While it is possible that gender differences in coping and help seeking behaviours (Orford et al., 2010) may mean more female than male adult AFMs come into contact with services, given the greater representation of men in substance use treatment statistics in Ireland (Kelleher et al., 2022; Lynch et al., 2022) and elsewhere (EMCDDA, 2022), it is reasonable to expect the gender differences among affected others reflect a disproportionate burden on women.

The current study has also provided evidence of the need for services tailored for children as AFMs, as a substantial number of referrals were for children, and many of the adult referrals (61.7%) were living with children. Due to the voluntary recording of AFMs in the NDTRS, these figures do not reflect the full extent of demand for services for affected children, nor indeed the extent of hidden harm, given the level of treated substance use in the population and the expected numbers of associated children (Galligan & Comiskey, 2019). It is likely that many affected children are not accessing support or treatment, are obtaining it elsewhere, or are coping without. Clearly, children do not have the same coping resources as adults, and due to their developmental stages, they are especially vulnerable to the negative impacts of problem substance use and addictions in their families (Velleman & Templeton, 2016). It is also known that multiple and complex issues may exist within families, given the frequent co-occurrence of problem substance use with mental health issues, domestic violence, and other associated problems (Health Service Executive (HSE), and Tusla Child and Family Agency (TUSLA), 2019). However, it is difficult to assess the extent of such hidden harm as many children experiencing adverse effects of familial problem substance use are not known to services (Galligan & Comiskey, 2019). Other potential sources of evidence in this regard include data on the family and living circumstances of people entering treatment, such as that collected by the NDTRS for the EMCDDA. Such routine treatment monitoring is a potentially valuable source of information and evidence on the hidden harm associated with problem substance use (Comiskey, 2019; Galligan & Comiskey, 2019; Health Service Executive (HSE) & Tusla Child and Family Agency (TUSLA), 2019). It must be recognised, however, that some addiction service users may not disclose dependent children for reasons such as stigma and fear of losing access to their children (Stringer & Baker, 2018). Others in need, notably females, may not access treatment services for reasons including trauma, stigma, and fear associated with traditional mixed-gender services (Merchants Quay Ireland, 2022).

It is worth noting that a similar number of young adults as children were represented among the referrals studied. Young adulthood, the period from 18 to 24 years of age, is recognised as a distinct developmental life stage during which the young person transitions to full adult maturity (Arnett, 2000). Social relationships with family, friends, and peers during this time play an important role in determining later outcomes in adulthood (Arnett, 2000; Jorgensen & Nelson, 2018). Three-quarters (75.3%) of the young adult referrals in this study were for females, suggesting the requirement for services that are sensitive to the unique needs of this group of AFMs.

In this study, most of the referrals were living in stable accommodation, and the majority were living with others. From the data, it was not possible to determine how many were living with a significant other who was experiencing problem substance use or addiction, or other behaviourial issues like gambling, nor how many had additional risks from associated issues such as mental health problems, intimidation, domestic violence, and coercive control, as these data are not collected by the NDTRS. One-in-ten adult referrals were living alone, suggesting that they were not experiencing the problem behaviours of their significant other in their home.

Adults were most likely to self-refer for treatment, suggesting the importance of raising awareness of services in community settings and the potential benefit of multiple access points to supports within communities. Children were mostly referred through family/friends or through school and other social/community services. Most of the child referrals were still in formal education, indicating educational settings as important sites for raising awareness, identifying need, and providing information and support. Findings also highlight the importance of services sensitive to the needs of new communities and tailored to those whose first language is other than the country’s national languages, and for information to be made available in other languages.

In this study, individual counselling was the main treatment received by AFMs, among both adult and child cases. Based on the data recorded, it is unclear the extent to which the 5-Step Model (based on the SSCP Model) is utilised, but it may be that fewer than five percent of treated family members received it. Among the various models of support developed for family members, the 5-Step Model is among the most prominent. However, according to Orford (2022), the other existing models share common features with the 5-Step Model, including a focus on validation, normalisation, education, and helping the affected family member to cope and manage effectively. Whichever approach is used, the quality of the relationship between therapist/care giver and affected family member is of paramount importance (Orford, 2022). Previous research has emphasised the significance of quality social support for affected family members, both formal and informal (Orford, 2017; Orford et al., 2010). In the current study, it is notable that one third of adult cases and almost two thirds of child cases reported having non-professional others, likely family or friends, involved in their treatment.

In line with previous research, findings of the current study highlight a greater demand for services for affected women than for men and emphasise that tailored supports are required for AFMs from birth through to young adulthood. For AFMs, the EMCDDA (2022) recommends the provision of dedicated family support services, supports for kinship carers of children whose relatives use drugs, appropriate health care and evidence-based interventions in primary care (including the 5-Step Model), specialised intensive treatment such as couples therapy, and bereavement support. The EMCDDA also recommends assessing the family relationships of persons entering treatment and targeting support toward their families. This might include interventions specifically for their children, as well as interventions provided to support persons in treatment in parenting and guardianship of their children. The provision of gender-specific services for women with addiction issues would mean more women can access treatment when needed and that interventions can be provided for their children, who may otherwise remain invisible (Merchants Quay Ireland, 2022). Children affected by others’ addictions need support in coping and can achieve positive outcomes with support systems among their families and communities as they mature into adulthood (Comiskey, 2019). Various intervention programmes exist for children whose parents use drugs and some have demonstrated positive outcomes (Bröning et al., 2012, as cited in Comiskey, 2019).

Historically, there has been a lack of interventions for family members in their own right that do not include the significant other who is experiencing the addiction (Denomme & Benhanoh, 2017; Kitt-Lewis et al., 2022; Merkouris et al., 2020; Orford et al., 2013; Shorter et al., 2022). However, a number of reviews of the evidence on psychological treatments for AFMs have been conducted (McGovern et al., 2021; Merkouris et al., 2020; Shorter et al., 2022). Merkouris et al. (2020) identified some evidence for the effectiveness of interventions to help the family member cope with the personal impacts of addiction (Community Reinforcement Approach and Family Training (CRAFT), the 5-Step Model, and coping skills training (CST)), as well as interventions that help the AFM support their significant other (CRAFT and Pressures to Change), and those that may improve relationship functioning (CRAFT). While the literature reviewed was mainly concerned with substance addictions, the findings may inform the development of evidence-based interventions for those impacted by gambling and other addictions (Merkouris et al., 2020). Shorter et al. (2022) found that AFMs impacted by significant others’ alcohol addictions specifically can benefit in their own right from brief intervention and there is some evidence for the effectiveness of other various interventions (e.g. based on motivational interviewing, anxiety management, or cognitive-behaviour therapy) on diverse physical, psychological, and social outcomes for AFMs. McGovern et al. (2021) identified positive social and psychological outcomes for AFMs both from behavioural interventions addressing AFMs in their own right and those including their significant others who are experiencing substance addictions. They concluded, however, that existing interventions do not adequately address the complex and multifaceted issues faced by families impacted by addiction and that further research is needed to develop and evaluate suitable interventions.

This research study has maximised the use of existing data to obtain useful insights into a hidden population that is poorly understood. Secondary analysis of routinely collected health data presents opportunities for innovative, efficient, and cost-effective observational research that can inform health policy, planning, and research (Benchimol et al., 2015). However, with a retrospective study of this kind, limitations of the existing data must be considered, notably the incomplete pre-2016 dataset (fewer variables were available), and possible selection bias resulting from the optional recording of relevant cases. Moreover, potentially important additional variables, such as the relationship of the AFM and significant other, or problem substances/behaviours of the significant other, were not available for inclusion in the analysis, as these data are not collected. While the study has shown a large demand on services, the true extent of service utilisation by AFMs is likely much greater, as not all services provided this data to the NDTRS during the study period. Furthermore, the study relates only to family members accessing support via treatment providers participating in the NDTRS; others will have accessed support through services (including family supports services) not yet participating and through mainstream support services currently outside of its remit. It is also possible that many AFMs are not accessing formal support and are coping alone or relying on informal support systems such as friends. Without nationally representative data from the general population, it is not possible to know the full extent of those affected, and without full coverage of services in monitoring systems such as the NDTRS, it is not possible to know the full extent of treatment needs for AFMs and demands on services.

Quality data and evidence are essential for ensuring appropriate services are provided for those who need them. Currently, there are no comparable data at an EU level on the availability of supports for AFMs or the uptake of these supports (EMCDDA, 2022). There is scope to expand routine monitoring to include further data on family members seeking support and supporting others through addiction treatment; for example, by including data on the relationship of the AFM to the significant other; the substance use, non-substance problem, or addiction issue(s) of the significant other; whether the significant other is in treatment; and the family relationships of those entering treatment for substance use or other addictions. To ensure adequate and tailored supports, it would also be useful to capture information on the co-occurrence of mental health problems, intimidation, domestic violence, and coercive control with problem substance use and other addictions as issues facing AFMs. Additionally, data collection around hidden harm is necessary to ensure services and interventions are provided for children affected by substance use and other addictions in their families. The implementation of a unique health identifier would greatly improve understanding of treatment needs both for persons with addiction issues and their families.

In conclusion, this study has provided valuable insights into the demand for services and the characteristics of those seeking treatment and has highlighted the potential of routine monitoring systems for collecting data on persons affected by others’ substance use and other addictions. These insights can inform the design and delivery of services and referral pathways for AFMs and will complement findings from future studies using routine surveillance data or employing primary research methods, including population health surveys.

Acknowledgements

The authors would like to thank the Health Research Board, the NDTRS team, and all the service providers who provide NDTRS data.

Disclosure statement

The authors report no potential conflicts of interest.

Additional information

Funding

The author(s) reported there is no specific funding associated with the work featured in this article.