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Children and Youth Services Review
journal homepage: www.elsevier.com/locate/childyouth
Why do people become a foster parent? Insights from a national study
Eunice Magalh˜aes a,* , Helena Carvalho b , Mariana Matoso c , Vˆania S. Pinto d , Patrício Costa e, Sofia Ferreira a, Joana Baptista a, Catarina Anjos c, Jo˜ao Graça f
a Instituto Universita´rio de Lisboa (ISCTE), CIS-Iscte, Lisbon, Portugal
b Instituto Universit´ario de Lisboa (ISCTE), CIES-Iscte, Lisboa, Portugal
c Instituto Universita´rio de Lisboa (ISCTE), Lisbon, Portugal
d School of Social Work, University of East Anglia

ABSTRACT

e Center for Psychology at the University of Porto, Faculty of Psychology and Education Sciences, University of Porto, Rua Alfredo Allen s/n, 4200 - 135 Porto, Portugal f University of Groningen, Groningen, the Netherlands
ARTICLE INFO

Keywords: Foster Care Enablers Barriers Clusters Recruitment

Objective: Many countries face a shortfall in the number of foster families needed to support maltreated children. This study aims to explore the drivers and barriers to becoming a foster family and to identify clusters derived from these drivers/barriers and their association with sociodemographic factors.
Method: A representative sample of 1,066 Portuguese adults (Mage = 52.76, SD = 14.92) responded to a survey assessing sociodemographic characteristics, awareness, willingness, and intention to foster and two open-ended questions related with enablers and barriers to becoming foster carers.
Results: Three profiles emerged: Material Resources (9.2% of participants), linked to material factors such as housing and economic resources; Personal Traits and Characteristics (23.0% of participants), associating the decision to become a foster family with various individual attributes and capabilities; and Child-centered Motivations (67.8% of participants), where the drivers to become a foster family focused on children and altruistic motivations, and barriers centered on personal and familial fears and threats, and child protection constraints. Differences regarding awareness, willingness and intention to foster, gender, marital status, education, family income, and having children significantly distinguished clusters.
Conclusions: The identification of these profiles, based on enablers and barriers to becoming a foster parent, can inform tailoring recruitment strategies that align with the specific needs and characteristics of prospective foster families.

* Corresponding author at: Centre for Social Research and Intervention, ISCTE-IUL, Av. das Forças Armadas, 1649-026 Lisbon, Portugal.
E-mail address: eunice_magalhaes@iscte-iul.pt (E. Magalh˜aes).
https://doi.org/10.1016/j.childyouth.2025.108686
Received 10 May 2025; Received in revised form 19 November 2025; Accepted 20 November 2025
Available online 21 November 2025
0190-7409/© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/).

1.		Introduction
Children may not always be safe when parenting proves harmful or abusive. In such circumstances, the removal of a child from the birth family and their placement in alternative care might be needed. In this sense, nearly half a million children in Europe and Central Asia reside in residential care facilities (UNICEF, 2023), even though the persistent institutionalization of children has been well-documented to have negative impacts on their health, development and well-being (Bick & Nelson, 2016; Nsabimana et al., 2019; Quick, 2024; van IJzendoorn et al., 2020). Most children and young people who are victims of maltreatment and require out-of-home care should be placed in family foster care instead of residential care (Carvalho et al., 2021; Delgado et al., 2020; Diogo & Branco, 2020; Li et al., 2019; Vanderfaeillie et al., 2013).
Foster care has become increasingly critical due to the EU’s initiative towards deinstitutionalization (European Commission, 2021). Despite the growing importance of foster families, there is a noticeable shortfall in the number of available families to meet the expanding needs of the foster care system; this issue is evident in various countries, including Greece, Cyprus, Luxembourg, and Portugal (Eurochild & UNICEF, 2021). Portugal faces significant challenges in providing family-based alternative care. As of 2023, only 4 % of children in out-of-home care were placed in foster families (ISS, 2024), a stark contrast to countries with the highest rates in the EU, like Latvia at 74 %, Estonia at 83 %, and Ireland at 91 %, but also when comparing with EU countries with the lowest rates (Greece at 16 %, Cyprus at 35 %, and Luxembourg at 43 %) (Eurochild & UNICEF, 2021). This disparity is largely due to the insufficient number of foster families, a problem that is not unique to Portugal (Diogo & Branco, 2017; Rodger et al., 2006), and the national disinvestment in foster care (Diogo, 2018). By 2030, the Portuguese government aims to significantly decrease the number of children in residential care to no more than 1200, through efforts to improve the foster care system, such as the development and implementation of a network of approved, trained, and closely supported foster families embedded in a national foster care program. Therefore, to enhance the state’s capacity for advancing sustainable reforms, there is a need for a profound understanding of why (and why not) people would become a foster family (Magalh˜aes et al., 2025).
1.1.		Enablers and barriers of fostering – What is known
Extensive research in foster care has primarily focused on foster families already engaged in the system. These studies typically examine the reasons for fostering, exploring what initially motivated individuals to become foster parents and what continues to retain them in this role (Gouveia et al., 2021). Based on existing knowledge, we present a summary of what is known about drivers and barriers to fostering. Foster parents identify many motives for fostering, and three main types of motivations emerge: child-oriented, society-oriented, and self-oriented (Migliorini et al., 2018; Sebba, 2012); among these, child-oriented motivations are the most frequently reported in the literature as drivers for fostering (Anjos et al., 2023; De Maeyer et al., 2014; Ferreira, Magalh˜aes, Pinto et al., 2025; Ferreira, Magalh˜aes & Graça, 2025). Child-oriented motivations are centered on the protective role of care, which is achieved by giving children and young people a safe and nurturing environment and avoiding their placement in residential care (Contreras & Mun˜oz, 2016; Diogo & Branco, 2020). Society-oriented motivations are typically ranked as the second or third most cited reasons. These often involve positive perceptions of foster care as fulfilling a broader societal need, such as contributing to the community (Sebba, 2012) or aligning with religious beliefs (e.g., Diogo & Branco, 2019; Keys et al., 2017). Self-oriented motivations also frequently emerge as centered on the needs and interests of the foster family or serve to fulfill personal aspirations (e.g., filling an empty nest, a lack of interest or inability to have biological children, the desire to expand the family, experiencing loneliness, having free time, or providing an educational experience for biological children) (e.g., Lo´pez & del Valle, 2016; Migliorini et al., 2018; Randle et al., 2014). Moreover, greater individual (e.g., available time, sufficient space, financial stability; Migliorini et al., 2018) and social resources (such as social support – which encompasses relationships with friends, family, religious and systemic support, e.g., Diogo & Branco, 2020; Dowdy-Hazlett & Clark, 2024; Ferreira, Mag- alha˜es, Pinto et al., 2025) might be associated with greater willingness to foster.
When analyzing barriers to becoming a foster family, a topic where studies have been conducted with the general population, one of the most prominent is the lack of awareness and understanding about foster care (Goodman et al., 2017). Some people may not consider it an option simply because they have never been exposed to the possibility (Anjos et al., 2023; Davi et al., 2021). Others may be unfamiliar with the concept of foster care (Negr˜ao et al., 2019), including the requirements and processes involved in becoming a foster family, often confusing foster care with adoption (Contreras & Mun˜oz, 2016). For those who understand what foster care involves, there are also recognized constraints, including perceived challenges with bureaucracy and a general lack of trust in the system (Blackburn, 2016), or insufficient information about the children’s background (e.g., Baer & Diehl, 2019; Cooley et al., 2015; Goodman et al., 2017). Concerns regarding challenges in managing relationships with the child’s birth family (e.g., Contreras & Mun˜oz, 2016; L´opez & del Valle, 2016), fears of not coping with the role, emotional challenges associated with reunification (Davi et al., 2021; Randle et al., 2014), fears of being falsely accused of seeking financial gain through fostering or being wrongly accused of maltreatment (Plumridge & Sebba, 2016), and overall concerns about societal stigma (Sebba, 2012) are also highlighted in the literature. Here, we propose adopting a bottom-up approach, capturing the views of a representative sample of people not involved in the foster care system. This will allow us to examine whether the motivations identified by foster parents in the literature are also observed in the general community and contribute to a better understanding of the enablers and barriers to fostering.
1.2.		Demographics related to fostering
Past research has obtained mixed findings regarding the relationship between the age of foster parents and their engagement in foster care. Some studies indicate that older individuals are more predisposed to become foster parents (Contreras & Mun˜oz, 2016; Gibbs, 2005) and are more likely to continue fostering (Gibbs & Wildfire, 2007). Conversely, other studies suggest that younger individuals may have a higher intention (Magalh˜aes et al., 2022; Raudkivi, 2020), greater interest (Ciarrochi et al., 2012), and a greater predisposition to become foster parents (Randle et al., 2014). Gender may also play a role in the likelihood of becoming a foster parent. Research suggests that women may be more willing to foster than men, and men are more likely to consider fostering when biological parenthood is not an option (Contreras & Mun˜oz, 2016). Apart from these findings, the role of gender on the predisposition to foster has not been extensively studied.
Research on the educational levels of foster families has revealed that individuals with higher education often demonstrate less willingness and intention to foster (e.g., Ahn et al., 2017; Raudkivi, 2020). Regarding employment status, findings are varied. Retired individuals tend to show less interest in fostering compared to those engaged in parttime or full-time work (Ciarrochi et al., 2012). However, higher levels of employment and income have been linked to a greater likelihood of discontinuing foster parenting (Gibbs, 2005), while another study found that higher income, combined with lower education, is associated with a greater intention to foster (Magalh˜aes et al., 2022). Finally, parental experience is another factor that appears to influence decisions about fostering, though the evidence is mixed. Some studies indicate that having parental experience is linked with a higher intention to foster (Magalh˜aes et al., 2022), with one study reporting that eighty-four percent of foster parents had their own children (Peak & Townsend, 2012). However, there is also evidence that existing parental responsibilities can deter individuals from becoming foster parents due to the demands of their own children (Randle et al., 2014). These conflicting findings highlight the need for further research, ideally with representative samples of the general population.
1.3.		Current study
Most evidence on why people would become a foster family comes from studies with foster families who are already performing the role (Anjos et al., 2023; Ciarrochi et al., 2012; Davi et al., 2021, Magalh˜aes et al., 2022). Therefore, gaining a deeper understanding of drivers and barriers to becoming a foster family – based on a representative sample from the general population – could provide meaningful contributions to the field (Magalh˜aes et al., 2022). Previous research has also focused primarily on profiling individuals who are already foster parents (Cooley et al., 2019; Dowdy-Hazlett & Clark, 2024). Here, we propose to use a bottom-up approach (cluster analysis) to examine patterns of association within the data and identify profiles that connect drivers, barriers, and demographic factors.
The current study takes place in the Portuguese context, considering the extremely low proportion of children placed in foster care (ISS, 2024). Recent changes in the legal framework posit family foster care as preferable to residential care and establishes a formal system for selecting and training foster families supported by social services institutions that are responsible for leading awareness campaigns and providing support (Decree-Law No. 139/2019; Law No. 37/2025). As such, this study aims: 1) to provide a deeper understanding of barriers and enablers to foster in a representative sample of the general population; and 2) to identify profiles of potential foster families, based on patterns of barriers and enablers and participants’ demographic characteristics.
2.		Method
2.1.		Participants
This study includes a representative Portuguese sample (in terms of gender, age, and geographical origin) of 1066 adults (Mage = 52.76, SD = 14.92; range 25–94). Most participants had children (72.0 %), were female (53.2 %), were married or in a civil partnership (63.6 %), had completed high school or a bachelor’s degree (67.5 %), and earned between € 1001 and € 2500 (57.8 %). Moreover, the majority (76.2 %) had no contact with the child protection system (see detailed sample in Table 1).
Table 1
Sample Characteristics.
Variable	% (n)	
Gender		
Female	53.2	
	(567)	
Male	45.7	
	(487)	
Non-binary	0.8 (9)	
Other	0.2 (2)	
Prefer not to respond	0.1 (1)	
Marital Status		
Single	18.5	
	(197)	
Married/Civil Partnership	63.6	
	(678)	
Divorced/Separated	12.7	
	(135)	
Widowed	5.3 (56)	
Education		
Elementary School (1st-4thgrade)	4.1 (44)	
Elementary School (5th-6th grade)	1.7 (18)	
Middle School (7th-9th grade)	6.9 (74)	
High School (10th-12th grade)	36.2	
	(386)	
Bachelor	31.3	
	(334)	
Master	12.3	
	(131)	
PhD	7.0 (75)	
Household Monthly Income		
≤1000	20.2	
	(215)	
1001–1500	25.2	
	(269)	
1501–2500	32.6	
	(347)	
>2500	22.0	
	(235)	
Contact with the Child Protection System		
No contact	76.0	
	(810)	
I had and/or my children had a CPS case	3.1 (33)	
I know people who have had and/or whose children have had a CPS	8.6 (92)	
case		
I know people who were or are currently foster families	8.1 (91)	
I lived in a residential care home	0 (0)	
I know people who lived in a residential care home	3.8 (40)	
I fostered a child in the past	0.6 (6)	
Professional contact/voluntary work current/past with the CPS	5.1 (54)	
2.2.		Instruments
2.2.1.		Sociodemographic questionnaire
A set of sociodemographic variables was used to assess participants’ characteristics, including age, parental experience (i.e., having children), gender, marital status, education, income, and contact with the child protection system.
2.2.2.		Open-ended questions
Two open-ended questions were used to assess participants’ enablers for fostering (i.e., “Please, indicate the main reasons or events that can/ could lead you to become a foster family”) and barriers for fostering (“Please, indicate the main reasons or events that can/could prevent you from becoming a foster family”).
2.2.3.		Awareness
A single item taken from Rienks and Oliva (2013) was adapted to evaluate awareness in the foster care context (i.e., “Have you heard about foster care?”). This item was responded to on a 5-point Likert-type scale, ranging from 1 (Never) to 5 (Very often).
2.2.4.		Willingness
To explore the participants’ willingness to foster, a single item (“I would like to become a foster family”) was used (Magalh˜aes et al., 2022). This item was responded to on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree).
2.2.5.		Intention
Three items taken from (Magalh˜aes et al., 2022) were applied to measure the intention to foster (e.g., “I will make an effort to become a foster family shortly”). Participants responded to these items using a 7- point Likert-type scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree) (α = 0.93) .
2.3.		Data collection and analysis
This study is part of a broader project focused on foster care that was approved by the University’s Ethics Committee (Reference number 117/ 2023). Data were collected from December 2023 to January 2024 by a polling company. The inclusion criteria were a) being 25 years old or over (since only adults aged 25 or over are eligible to be a foster family in Portugal); b) understanding the Portuguese language; and c) not being a foster family at data collection moment. A representative sample was targeted in terms of gender, age, and geographical region (i.e., North, Center, Lisbon Area, Alentejo, Algarve, Azores, and Madeira), and two complementary methodologies were used to achieve this representativeness [an online approach and the computer-assisted telephone interviewing system to address the difficulties of getting data online from the 65 + age group]. The participants were informed about the research aims and the conditions for participation, and after they gave consent, they responded to the questionnaire. A total of 1,082 participants were recruited for the broader project, but this study included only those who completed the open-ended questions (n = 1,066). As such, after 16 participants were excluded from this study, the representativeness was ensured (not only by the sampling and recruitment strategy) as non-significant chi-square tests were found for the three variables [gender (χ2(1, N = 1,054) < 0.001, p = 0.997), age (χ2(3, N = 1,066) = 3.96, p = 0.266), and region (χ2(6, N = 1,066) = 0.161, p > 0.999)]. Participants responded to a set of sociodemographic variables and the two open-ended questions, then the awareness question. This was followed by being presented with a definition of foster care and asked about their willingness and intention to foster.
Qualitative data analysis was performed using MAXQDA 2022, applying a bottom-up content analysis approach. Based on semantic criteria, the corpus was divided into units of analysis and arranged into categories and subcategories. Each category and subcategory were mutually exclusive, meaning that any unit of analysis could only be included in one (sub)category. Firstly, one researcher coded all material (CA), which was systematically discussed with a second researcher (EM). Once the coding was finalized, a third researcher (VSP) reviewed the codification and gave feedback. Finally, a fourth researcher (SF) cocoded 30 % of the material using the dictionary of categories and subcategories. The inter-coding agreement was computed to provide additional evidence of the validity and trustworthiness of the coding process, and an almost perfect agreement was found (kappa = 0.86) (Landis & Koch, 1977). The number and percentage of participants (n; %) who reported each subcategory and the number of units of analysis coded within each subcategory (f; %) are presented in Table S1 and S2.
Of the 1066 adults who participated in this study, around 7 % of the participants (n = 76, f = 77) reported being non-available to foster. In further detail, 54 participants revealed that they do not identify any enabler (e.g., “At this moment in my life, there is no reason or event that would lead me to become a foster family”, Female, 59y), and 22 participants revealed that they had never thought about it (e.g., “In fact, I’ve never thought about it”, Female, 50y). Moreover, 6.3 % of the participants (n = 67, f = 67) reported that they do not identify any barrier to becoming a foster family (e.g., “Nothing to mention”, Male, 31y). As such, the remaining units of analysis were organized into enablers (Table S1) and barriers (Table S2) to becoming a foster family, which will be detailed in the results section. Also, we describe the categories and the subcategories for enablers and barriers to becoming a foster family, illustrating these categories through participants’ examples of units of analysis.
After identifying the conceptual categories and subcategories, the aim was to identify profiles based on the common enablers and barriers mentioned by the participants (reported by at least 5 % of the participants). Considering that these were categorical variables, multiple correspondence analysis (MCA) was the most appropriate methodological choice to achieve the objective of defining profiles. Using an optimal algorithm, MCA submits categorical input variables to a quantification process, assigning quantifications to each category. Subsequently, by using these quantifications as coordinates, it becomes feasible to visually represent and interpret associations between all the multiple categories of input variables. The proximity between the categories, indicated by closely positioned points on the graph, makes it easier to identify potential profiles. Once the profiles had been identified and their definition theoretically supported, the participants were segmented into groups according to their profiles. Segmentation was carried out using cluster analysis. Initially, a hierarchical cluster analysis was chosen because no predefined number of clusters was required (Hair et al., 2019). The aim was to examine whether the quantitatively optimal number of clusters corresponded to that proposed by the MCA. To increase the robustness of these results, two clustering methods were used (Ward’s method and the Furthest method). After assessing the obtained solution, the final composition of the clusters was determined using a K-means optimisation method (Hair et al., 2019).
Chi-square and non-parametric one-way ANOVA tests were used to compare the three profiles according to sociodemographic variables [i. e., gender, age, marital status, education, family income, parental experience (i.e., having children), and behavior-related variables (i.e., awareness, willingness, and intention to foster)]. A non-parametric ANOVA was chosen because two of the three outcome variables were ordinal. Nonparametric pairwise multiple comparisons for independent groups were conducted using Dunn’s test with a Bonferroni adjustment.
3.		Results
3.1.		Enablers to becoming a foster family
Regarding enablers to become a foster family, a total of 1020 units of analysis were coded and sorted into 12 categories and 40 subcategories (Table S1). The Child-centered reasons (n = 260, f = 308) was the most coded category, where participants considered they would become a foster family mostly to protect children in need, such as those who were maltreated (“Fostering a child at risk or who has been a victim of maltreatment”; Female, 41y) as well to provide them with a better life, support, love, and affection. This was followed by Society-oriented reasons, which was the second most reported enabler (n = 180, f = 199), where participants considered becoming a foster family as a way of helping others (“The possibility of helping someone who might need it”; Male, 52y). This also included issues of social responsibility and solidarity. The third most reported enabler was Perceived resources (n = 150, f = 197), which included having economic (“Financial resources”; Male, 46y) or housing resources, as well as having time or physical assets.
Participants also conveyed they would consider becoming a foster family in case of Humanitarian and emergency issues (n = 78, f = 81), such as catastrophe and/or war situations (“Helping children or young people from countries at war”; Male, 41y), or in the face of an urgent need. Individual attributes (n = 60, f = 65) of foster families, such as the individual predisposition to being available (“Having availability to foster”; Male, 66y) as well as to love children, were reported, along with being healthy and empathic. Moreover, participants also considered that Having a relationship with the person in need (n = 56, f = 62) might promote their intention to foster, which included knowing the person in need and their situation (“Knowing a child who needed to be fostered”; Female, 26y) or having a family member in need. Parenting-related reasons (n = 43, f = 43), mostly related to difficulties in having biological children (“The main reason would be in the event of not being able to have children in a natural way”; Male, 29y) or not having biological children and an empty nest were also identified.
Self-oriented reasons (n = 23, f = 23), in which the participants considered they would become a foster family as a way of dealing with being alone and having company (“I would love to be a foster family because I live alone”; Female, 65y) or to get financial and personal benefits were mentioned by a small number of participants. Moreover, participants reported Child-protection system variables (n = 22, f = 22), such as awareness of the foster care system’s policies and procedures (“Promotion and information sessions on how foster family works”; Female, 40y), as well as the institutional support. Family-related resources (n = 12, f = 13) involving family agreement about fostering (“If my wife was willing to do it”; Male, 70y), as well as having quality relationships, were also highlighted as drivers to foster.
Lastly, the least coded categories were Cultural reasons (n = 4, f = 4) (“Getting to know new cultures and people and making our culture known”; Female, 26y), and An alternative to child institutionalization (n = 3, f = 3) (“Helping someone in great need so that they don’t go to an institution”; Female, 27y), which means that these participants believed that becoming foster families would prevent the placement of children in residential care homes.
3.2.		Barriers to becoming a foster family
As for the barriers to becoming a foster family, 1304 units of analysis were coded into 10 categories and 37 subcategories (Table S2). The category with the highest number of units of analysis was Lack of resources (n = 491, f = 617), which mainly included the lack of financial resources (“No financial capacity”; Male, 32y), shortage of housing, or general conditions. Individual barriers (n = 310, f = 375) such as age (“I’m too old to be a foster family”; Male, 66y), lack of willingness, and health problems seem to prevent the participants from becoming a foster family. Furthermore, a set of Family-related barriers (n = 68, f = 71) to foster were reported, mostly related to the lack of co-parenting (“Not having a partner”; Female, 38y), but also family (dis)agreements or the potential disruption of their family environment by fostering a child in need. Perceived fears and threats (n = 58, f = 60) might prevent people from becoming a foster family as this role is perceived as a threat to the security and privacy of the foster family, which means anticipating fear related to fostering a child and sharing their personal space (“Because I
don’t want to bring strangers into my house”; Female, 57y). Also, fears related to subsequent separation/suffering or with the child’s birth family were identified as barriers to becoming a foster family.
Participants reported Child-protection system-related barriers (n = 54, f = 57) that impede their willingness to foster, namely the lack of system initiatives in terms of encouraging foster care as an alternative context for children in need (“I was never contacted for that purpose”; Female, 46y) but also the bureaucracy and complexity of the process, as well as people’s dissatisfaction with the system. Having Current responsibilities as a caregiver (n = 32, f = 38), including having biological children (“Unless I have my own children”; Male, 29y), adopted children, or being an informal caregiver, seemed to impede people from deciding about becoming a foster family.
Barriers related to the Child characteristics (n = 29, f = 30) involved mostly child difficulties such as their mental health (“Children with behavioral/mental problems”; Male, 61y), but also their background or age. Participants also considered that their Professional issues (n = 21, f = 21), that is, not having the time to foster due to their work (e.g., “Working full time”, Female, 46y), might prevent them from becoming a foster family. Finally, obstacles related to social issues were reported, such as Societal barriers (n = 19, f = 20), namely, socio-political difficulties in Portugal (“The current social situation”; Male, 36y) or cultural and religious barriers, but also Representations related to alternative care (n = 15, f = 15). Specifically, these representations included participants’ perceptions of a high level of responsibility associated with the role (“A lot of responsibility”; Female, 68y), as well as the belief that there are other alternatives to foster care.
3.3.		Multiple correspondence analysis and clustering
The results of the MCA enabled the identification of three profiles (Fig. 1), followed by an examination of how participants were distributed across these profiles using clusters analysis. The Material Resources profile (Cluster 1, 9.2 % of the participants) refers to conceiving the decision to become a foster family as linked to material factors such as having housing and economic resources, and the lack of these resources being identified as a key barrier. The Personal Traits and Characteristics profile (Cluster 2, 23.0 % of the participants) refers to associating the decision to become a foster family with several individual attributes and capabilities, such as being available, being empathic, and having a predisposition to foster and provide care. This profile also included several personal characteristics and difficulties that might undermine one’s capacity to become a foster family, such as health difficulties or age barriers. Finally, the Child-Centered Motivations profile (Cluster 3, 67.8 % of the participants) refers to conceiving drivers to become a foster family focused on the children (e.g., protecting these children and providing them with a better life, and familiarity with the children), as well as altruistic motivations such as helping others. In turn, fears and perceived threats (e.g., threats to family security and privacy, fears related to subsequent separation) and child protection barriers (e.g., the bureaucracy and complexity of the process) appeared in this cluster as obstacles to becoming a foster family.
3.4.		Profiles and sociodemographic and behavioral attributes

Fig. 1. Topological Configuration of Profiles.

A set of associations was tested between the three profiles (represented by clusters) and the sociodemographic variables (Table 2).
Table 2
Sociodemographic and behavioral characteristics of the profiles.
	Profiles Material Resources profile	Personal Traits and
Characteristics	ChildCentered Motivations profile	
		profile N	%		
	N	%			N	%	
Gender	Female	45	46.4	152	63.1	370	51.7	
	Male	52	53.6	89	36.9	346	48.3	
	Total	97	100.0	241	100.0	716	100.0	
Age	Early	27	27.6	24	9.8	199	27.5	
	adulthood							
	Middle	46	46.9	49	20.0	341	47.2	
	adulthood							
	Late adulthood	25	25.5	172	70.2	183	25.3	
	Total	98	100.0	245	100.0	723	100.0	
Marital	Single	25	25.5	25	10.2	147	20.3	
status	Married	58	59.2	162	66.1	458	63.3	
	Divorced/	13	13.3	32	13.1	90	12.4	
	separated							
	Widowed	2	2.0	26	10.6	28	3.9	
	Total	98	100.0	245	100.0	723	100.0	
Education	ISCED 1 and 2	6	6.1	62	25.4	68	9.4	
	ISCED 3 and 4	47	48.0	78	32.0	261	36.3	
	=> ISCED 5	45	45.9	104	42.6	391	54.3	
	Total	98	100.0	244	100.0	720	100.0	
Family	= 1000 €	22	22.4	54	22.0	139	19.2	
income	1001 – 1500 €	31	31.6	67	27.3	171	23.7	
	1501 – 2500 €	30	30.6	60	24.5	257	35.5	
	> 2500 €	15	15.3	64	26.1	156	21.6	
	Total	98	100.0	245	100.0	723	100.0	
Have	Yes	63	64.3	202	82.4	502	69.4	
children	No	35	35.7	43	17.6	221	30.6	
	Total	98	100.0	245	100.0	723	100.0	
Awareness	Never	30	30.6	54	22.0	204	28.2	
	Rarely	28	28.6	46	18.8	131	18.1	
	Occasionally	34	34.7	73	29.8	264	36.5	
	Frequently	4	4.1	43	17.6	88	12.2	
	Very	2	2.0	29	11.8	36	5.0	
	Frequently							
	Total	98	100.0	245	100.0	723	100.0	
Willingness	Minimum = 1	M =	3.85	M =	2.93	M =	3.79	
	Maximum = 7							
Intention	Minimum = 1	M =	2,28	M =	1.92	M =	2.66	
	Maximum = 7							

Gender (χ2 (2, N = 1054) = 11.8, p = 0.003), marital status (χ2 (6, N = 1066) = 31.6, p < 0.001), education (χ2 (4, N =1062) =50.4, p <0.001) family income (χ2 (6, N = 1066) = 14.7, p = 0.023) and having children (χ2 (2, N = 1066) = 18.5, p < 0.001) significantly differentiated the profiles. The results suggested that Material Resources profile (represented by Cluster 1) included more men, single adults, middle level of education, low/middle level of income, and no children. The Personal Traits and Characteristics profile (represented by Cluster 2) is comprised mainly of women, widowed adults reporting lower levels of education, those who have children, and those with contrasting low and high levels of income. The Child-Centered Motivations profile (represented by Cluster 3) is comprised mainly of men, divided between single adults, married, and divorced, with higher education and income levels, and without children. Moreover, a non-parametric one-way ANOVA showed a significant relationship between age and the profiles (χ2 (2, N = 1066) = 135.1p < 0.001). Post-hoc comparisons indicated that age in cluster 2 was significantly higher than in cluster 1 (p < 0.001) and in cluster 3 (p < 0.001). However, there was no significant difference between clusters 2 and 3 (p = 0.801).
Regarding the behavior-related variables, a non-parametric one-way ANOVA showed a significant relationship between the profiles (represented by clusters) and awareness (χ2 (2, N = 1066) = 18.3, p < 0.001), willingness (χ2 (2, N = 1066) = 44.4, p < 0.001) and intention (χ2 (2, N = 1066) = 64.4, p < 0.001). Post-hoc comparison tests indicated that awareness in cluster 2 was significantly higher than in cluster 1 (p < 0.001) and in cluster 3 (p = 0.005). In contrast, willingness and intention in cluster 2 were significantly lower than in cluster 1 (p < 0.001 and p = 0.008, respectively) and in cluster 3 (p < 0.001 and p < 0.001, respectively). There were no significant differences between clusters 1 and 3 (p > 0.05) for the behavior-related variables.
4.		Discussion
Previous research has primarily focused on identifying enablers and barriers to fostering, using mainly foster parents or prospective families as samples. Still, there is a lack of research identifying profiles that connect drivers, barriers, and demographic factors from a bottom-up approach and using representative samples. As such, this study aimed to 1) provide a deeper understanding of enablers and barriers to fostering in a representative sample of the general population, and 2) identify profiles of potential foster families, based on those barriers and enablers and participants’ demographic characteristics.
Child-centered reasons emerged as the primary enabler for fostering. This aligns with multiple studies highlighting that motivations are often rooted in altruistic values, driving individuals to support and protect children in need and to make a meaningful difference in their lives by offering better family environments (Baer & Diehl, 2019; Diogo & Branco, 2017; L´opez & del Valle, 2016). Altruism plays a crucial role in the discourse around care and caregiving, reinforced by a deep affection for children and an awareness of the inadequate care many experienced next to their birth families (Diogo & Branco, 2019; Doyle & Melville, 2013). This finding closely relates to the second most frequently cited motivation for fostering, which is Society-oriented reasons. In line with existing literature, these motivations are often associated with positive perceptions of foster care as fulfilling broader societal needs and with a desire to contribute to the community (Sebba, 2012). Particularly interesting is the finding related to addressing Humanitarian and emergency situations, such as disasters or war conflicts, suggesting that enablers for fostering might be better framed in specific sociocultural and political contexts. Conversely, Societal barriers such as socio-political difficulties in Portugal or cultural and religious barriers were considered potential barriers. Indeed, the most prevalent cluster identified in this study was characterized by Child-Centered Motivations, where individuals are primarily driven to become foster families out of concern for the well-being of children. However, this cluster also included specific obstacles such as fears, perceived threats, and barriers related to child protection systems. According to previous studies, insufficient information about the children’s backgrounds and developmental histories, fears of rejection by the child, challenges associated with separation, the potential loss of contact after fostering, and managing relationships with the child’s relatives are often perceived as stressors (Baer & Diehl, 2019; Blackburn, 2016; Lo´pez & del Valle, 2016).
Moreover, a frequently mentioned enabler in this study was Having a relationship with the person in need, which encompasses knowing the child in need and their circumstances or having a direct familial connection to them. This emphasizes the impact of such relationships on the decision to foster. Studies have demonstrated that participants are more likely to foster when they already have a bond with the child, especially if the child is a relative (Anjos et al., 2023). This finding is supported by data showing that a substantial proportion of foster parents — 58.5 % in a study by Rodger and colleagues (2006) — initiated fostering because they had personal connections with a foster child or knew another foster family. Therefore, personal relationships may increase the likelihood that individuals will become foster carers when there is an existing emotional bond, as it promotes empathic concern. It is possible that the presence of a pre-existing relationship can mitigate some of the initial uncertainties or fears associated with fostering, providing a clearer insight into the child’s and the birth family’s needs. This finding is critical, as the law in Portugal changed very recently. Until recently, there were no kinship foster families in our legal framework; however, since March 31, 2025, this has become a possibility. As such, this new legal context may provide an additional capacity for our out-of-home system to recruitment and strategic planning.
Another significant enabler identified in this study is the availability of Perceived resources, which in this study not only ranks as the third most cited motivation for fostering but also emerges as the most noted barrier (i.e., Lack of resources) when such resources are lacking. These findings align with resource theory, which posits that the greater the resources an individual possesses (i.e., assets that one person can offer to another to help meet needs or achieve goals), the more capable and willing they are to provide support to others (De Maeyer et al., 2014; Migliorini et al., 2018). This dual role of resources highlights their critical impact on both enabling and inhibiting foster care engagement. In fact, another cluster identified in this study was the availability (or lack thereof) of Material Resources. This cluster included individuals whose decision to foster is heavily influenced by material factors such as sufficient housing and economic resources. Notably, the absence of these resources stands out as a significant barrier. This is particularly relevant for engaging the broader community in foster care, as financial considerations are a decisive factor for 40 % of potential foster parents, according to an international study (Peak & Townsend, 2012). This profile highlights the critical role of material resources in fostering decisions and the need for targeted support strategies that address financial and housing stability, which possibly could enhance foster care engagement.
Another factor identified as a driver in our study was Family-related resources, such as consensus within the family about the decision to foster and maintenance of quality relationships within the household. These positive family dynamics facilitate the fostering process by ensuring a supportive home environment. Conversely, the third most prominent barrier reported was family-related challenges, including lack of co-parenting – often experienced by single individuals or those living alone – as well as family disagreements or concerns about the potential disruption of fostering a child might bring to the existing family environment. The importance of social support in navigating the complexities of fostering is well-documented in the literature. Previous studies have shown that individuals are more likely to pursue fostering when they perceive strong support from their family and close relatives (Raudkivi, 2020). Social support can also serve as a buffer during challenging times in foster care (Pinto & Luke, 2022). For instance, foster parents who encounter difficulties with their foster child’s disruptive behaviors often cited social support as a protective factor. However, this support was less significant for those who faced fewer behavioral issues (Cooley et al., 2015). This suggests that while social support can potentially aid in the retention of foster families, its effectiveness may vary depending on the circumstances, indicating a need for further research to better understand how social support mechanisms can be optimized to support foster families more effectively.
Regarding the fifth most cited enabler for fostering identified in this study, Individual attributes, it highlights essential personal qualities that not only influence the ability and readiness of individuals to engage in foster care but also align with previous findings emphasizing the significance of individual traits in determining the suitability and readiness of prospective foster parents. Individual barriers, which were the second most cited barriers, such as age, lack of personal predisposition or willingness, and health issues, further underline the personal challenges that can inhibit individuals from fostering. Past research indicates that traits like empathy, coping skills, flexibility, openness, tolerance, hope, a positive problem-solving orientation, a sense of life’s meaningfulness, feelings of belonging, and self-efficacy are crucial for fostering children at risk and maintaining long-term commitments in foster care (Davi et al., 2021; Goodman et al., 2017; Keys et al., 2017; Mihalo et al., 2016; Pinto & Luke, 2022). Therefore, potential foster families may benefit from preparation programs that include skill-building and mental health approaches.
Relatedly, another cluster identified in this study was Personal Traits and Characteristics, which encompassed a range of individual attributes and capabilities critical for fostering, such as availability, empathy, and predisposition to provide care. This cluster also included personal challenges that could hinder one’s capacity to become a foster family, such as health difficulties or age barriers. Predominantly composed of older women with lower levels of education and low and high levels of income, this profile presented higher awareness but lower intention and willingness to fostering. In fact, despite literature suggesting that women (Contreras & Mun˜oz, 2016) and older individuals are generally more willing to foster (Contreras & Mun˜oz, 2016; Gibbs, 2005; Gouveia et al., 2021), and associations found between a combination of lower education and higher income with greater fostering intentions (Magalh˜aes et al., 2022), willingness and intention were lower in this cluster than in the Material resources and Child-centered motivations clusters. Interestingly, the heightened awareness in this cluster could explain why, despite recognizing the needs and benefits of fostering, individuals in this profile might feel less inclined or able to take on such responsibilities. They are possibly more aware of the personal implications and challenges involved in fostering, together with the acknowledgement of personal barriers (age, health difficulties), which lead to a cautious approach towards commitment. Being older and widowed often means that their own children may no longer live at home, which could contribute to a sense of isolation. This circumstance might make the idea of fostering appealing to mitigate loneliness, yet there is an acute awareness that they may not have the full capacity or resources to meet the demands of fostering. This nuanced understanding of the Personal Traits and Characteristics cluster emphasizes the complex interplay between individual capabilities, personal circumstances, and reasons for fostering.
Finally, several other enablers and barriers identified in the study are rooted in personal or familial connections with child protection services. This study identified Child-Protection system variables as drivers for fostering, emphasizing the importance of being well-informed about the policies and procedures of the foster care system and having robust institutional support. A clear understanding of the foster carer role as a viable Alternative to child institutionalization further motivates individuals to engage in foster care. Conversely, in the current study, Child-protection system-related barriers, including the lack of proactive system initiatives to promote foster care, the bureaucratic complexity of the process, and general dissatisfaction with how the system operates, were noted. Additionally, Representations related to alternative care, such as the perceived great responsibility associated with fostering and the belief in other less demanding alternatives, also deter potential foster parents. The literature highlights that limited access to accurate and effective information is a major deterrent for potential foster caregivers (Goodman et al., 2017; Randle et al., 2014). Even when information is available, it is often not appropriate or effectively communicated, leading to negative attitudes and misconceptions about foster care (Diogo & Branco, 2017; Leber & LeCroy, 2012; Randle et al., 2014). Moreover, these barriers are in line with other studies demonstrating the insufficient support provided by the system, where foster parents encounter significant challenges due to the lack of institutional, emotional, and financial support from fostering teams (Blackburn, 2016; Geiger et al., 2013; L´opez & del Valle, 2016). Better support systems and positive relationships with case workers are shown to enhance satisfaction with the fostering process and aid in the retention of foster parents (Mihalo et al., 2016; Pinto & Luke, 2022; Randle et al., 2017). Addressing these barriers may require a dual approach: firstly, enhancing the availability and quality of information provided to potential foster families, ensuring it is both accessible and tailored to build a realistic understanding of what fostering entails. Secondly, simplifying bureaucratic procedures and increasing visibility and support for foster care initiatives can contribute to reducing the perceived complexity and increasing satisfaction with the system. By improving both the dissemination of information and the structural aspects of the child-protection system, it is possible to make foster care a more attractive and feasible option for more families.
4.1.		Limitations and Directions for future research
This study provides insightful findings on this topic from a bottom-up approach and based on a representative sample. Still, the qualitative data gathered in this study were based on brief open-ended questions and did not provide an in-depth understanding of the reasons for fostering. As such, further studies based on in-depth interviews with diverse and representative community samples could be combined with large-scale studies to provide additional insights. They could also employ mixed method designs to combine qualitative and quantitative input, enabling a more robust understanding of the relationships between motivations, barriers, and foster care engagement. Also, longitudinal studies could follow the participants to understand who decides to apply to become a foster carer. Future studies could benefit from including additional individual variables, such as traits of personality or self-efficacy, or relational variables, such as social support, as these factors might provide further insights into why people become foster parents. Finally, future research could compare the characteristics of the clusters identified in this study with those of current foster carers in Portugal, where available, to reveal potential gaps between prospective and actual foster families and to inform more targeted recruitment and support strategies.
4.2.		Policy and Practice implications
The findings of this study demonstrate that both intrinsic and extrinsic factors significantly influence individuals’ decisions to engage in fostering. The importance of gathering information from the general community cannot be overstated, especially when attempting to understand and cultivate the profiles of potential foster families. By extending research beyond those already engaged in foster care to include a representative sample, policymakers and child protection agencies can gain a richer, more comprehensive understanding of what influences people to foster. This study presents relevant findings on enablers and barriers to fostering. By addressing these in a targeted and thoughtful manner, we can create a more robust and supportive foster care system that effectively meets the needs of both children in need of care and those who open their homes to them. Also, understanding which factors motivate or hinder individuals from becoming foster carers can inform the design of targeted recruitment campaigns and strategies to reduce barriers related to resources or system procedures.
In the Portuguese context, this study identifies three profiles within the general population that offer valuable insights into how fostering campaigns can be more effectively targeted. The cluster of participants who emphasized Child-centered Motivations may be particularly receptive to campaigns that highlight how fostering positively impacts a child’s emotional and developmental well-being. Policies should therefore focus on strengthening the societal value and public recognition of foster care, portraying it as a valuable contribution to children’s lives and to the wider community. For the cluster focused on Material Resources, campaigns that provide clear information on support systems, financial assistance, and the practical benefits of fostering, while addressing the perceived material barriers with concrete solutions, could be expected to be effective. At a policy level, this also involves streamlining bureaucratic processes, improving transparency regarding allowances and eligibility criteria, and ensuring equitable access to financial support. Lastly, the cluster of participants that emphasized Personal Traits and Characteristics may benefit from campaigns focusing on emotional support and preparation programs, highlighting stories of successful foster experiences and providing robust post-placement support to alleviate concerns about emotional efficacy and readiness. From a policy perspective, structured capacity building, including peer mentoring and facilitated access to respite care, may be required to transform personal willingness into sustainable fostering.
Ethical approval
This study is part of a broader project focused on foster care that was approved by the University’s Ethics Committee (Reference number 117/ 2023).
AI Declaration
During the preparation of this work the author(s) used Chat GPT4 for rearranging sentences or English language editing and improvement. After using this tool, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
Funding statement
This research received funding from “la Caixa” Foundation Social Observatory, granted under the competitive Call for Research projects on Childhood and Vulnerability in Portugal (Project code: FP23-1B023).
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi. org/10.1016/j.childyouth.2025.108686.
Data availability
The datasets generated during and/or analyzed during the current study are not publicly available due to ethical and privacy reasons, as the participants of this study did not give consent for their data to be shared publicly.
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