The Role of Dosage and Family Profiles in a Child Welfare Home Visiting Program

Vol.:(0123456789) https://doi.org/10.1007/s10566-024-09826-4 ORIGINAL PAPER The Role ofDosage andFamily Profiles inaChild Welfare Home Visiting Program Victoria Hidalgo García1 · Javier Pérez‑Padilla2,3 · Carlos Camacho Martínez‑Vara de Rey4 · Lucía Jiménez García1 Accepted: 6 September 2024 © The Author(s) 2024 Abstract Background Among the different modalities of family support, home visiting programs have proved to be one of the most effective secondary prevention models for families involved in child welfare services. Despite the promising outcomes and the extensive available literature, further research is needed to investigate target population characteristics and implementation factors that may explain the heterogeneity in the outcomes of these programs for families receiving child welfare services. Objective This longitudinal study explored the role of dosage and family characteristics related to the effectiveness of the Family Intervention Program (FIP), which is a homebased Spanish child welfare service for supporting families at psychosocial risk. Method To this end, a quasi-experimental design was followed, including a time-series evaluation of the 289 families receiving the FIP. In order to examine the impact of the FIP, the evolution of child well-being (CWB) was evaluated with Child Well-Being Scales every 6 months. Results The results showed that the highest average CWB score was observed after 39months of intervention, observing no improvements in CWB from that point. Similarly, the results showed that the FIP was more effective for single parent families at higher socioeconomic levels. Conclusions This article provides new knowledge for the understanding of home visiting programs success, concluding that the programs are not equally effective for all family profiles, and that it is necessary to adjust each program to the specific characteristics of the target population. Keywords Home visiting program· Program evaluation· Dosage· Child welfare· Child wellbeing Introduction There is a widespread consensus among researchers and policymakers on the need for effective interventions for promoting child well-being in families at psychosocial risk, since these families are unable to adequately meet the needs of their children (Jiménez etal., Extended author information available on the last page of the article / Published online: 19 September 2024 Child & Youth Care Forum (2025) 54:435–452 2019). To understand the functioning of families at psychological risk, the most suitable theoretical framework is the ecological-transactional perspective (Bronfenbrenner, 1979; Bronfenbrenner & Ceci, 1994; Cicchetti & Lynch, 1993). From this approach, it has been highlighted that parenting depends on factors related to the characteristics of the parents (e.g., developmental trajectory, personality, parenting skills, etcetera), the characteristics of the children (e.g., age, temperament, developmental needs, etcetera) and the psychosocial environment that surrounds the family (e.g., social support, community resources, etcetera) (Belsky, 1984). In accordance with this explanatory model of parenting, it is possible to identify both risk and protective factors at each of the different domains and ecological levels. The balance between the risk and protective factors present in the ecology of each family would explain whether parents are capable of adequately meeting the needs of children (Cicchetti & Valentino, 2006). To serve families that do not adequately cover children’s needs, family preservation services are currently a social and political priority for most countries supported by international agreements (Council of Europe, 2011 and 2016; United Nations, 1989). According to these regulations, care for at-risk families has evolved from a traditional deficit-based model to a positive family support approach with the promotion of parenting skills and community strengthening as the main purposes of interventions (e.g., Daly etal., 2015; Davies etal., 2019; Gentles-Gibbs, 2016). In the research arena, this approach has led to the identification of core components and main quality standards of evidence-based practices and programs (Axford, 2012; Barlow & Coren, 2018; Barret, 2010). In the scope of practices, this approach has involved the diversification of intervention modalities to address diverse family needs (Walsh etal., 2015). Among the different modalities of family support, home visiting programs have proved to be one of the most effective secondary prevention models for families involved in child welfare services (e.g., Acquah & Thévenon, 2020; Lee etal., 2018; Paulsell etal., 2011). Since the late twentieth century, home-based parenting support has gained increasing recognition as a useful strategy to prevent child abuse and neglect, to improve parenting skills and to promote child development (Council of Community Pediatrics, 2009). In fact, home visiting is currently the most widely used child maltreatment prevention strategy in the United States (Casillas etal., 2016; Supple etal., 2012), and it is a type of intervention used as a family support tool in most European countries (e.g., Jungmann etal., 2015; Veerman & De Meyer, 2015). Home visiting programs are defined as family preventive and preservation interventions that use home visiting as the primary service delivery strategy. These services involve assessing family needs, providing education and supports to parents and connecting families to community support resources. Home visiting programs vary widely in their approach, mainly, in terms of target population (risk profile, cultural group, timing of parenthood), home visitor qualifications (professional or trained paraprofessional), dosage and intensity of the interventions (from a few months to several years), and the curriculum and visit content (Casillas etal., 2016; Segal etal., 2012). Positive effects of home visiting programs on parenting beliefs and practices, child health and development in at-risk families, as well as their effectiveness in preventing child maltreatment, have been demonstrated in both empirical studies and meta-analyses (Avellar & Supplee, 2013; Duggan etal., 2018; Paulsell etal., 2010, 2014; Sama-Miller etal., 2017, 2019; Van Assen etal., 2020). There is also some evidence of the long-term effects of home visiting programs (Michalopoulos etal., 2017). Despite these promising outcomes and the extensive available literature, the evidence supporting the effectiveness of home visiting programs is still inconclusive, with reviews reporting mixed results, particularly for families involved in the child welfare system (Chaffin etal., 2012; Chaiyachati etal., 2018; Lee etal., 2018). Among the reasons offered to explain the variability in the obtained Child & Youth Care Forum (2025) 54:435–452 436 results, the considerable diversity in the program components and implementation factors has been the most frequent explanation (Kaye etal., 2018; Segal etal., 2012). In relation to program components associated with home visiting effectiveness, the review conducted by Gubbel etal. (2021) revealed that programs that focused on improving the parental expectations and responsiveness to a child’s needs yielded relatively larger effects. In the review by Kaye etal. (2018), problem-solving strategies were a key ingredient of evidence-based programs. Programs with high levels of participant involvement, a strengths-based approach, and a component of social support have also been linked to effectiveness (MacLeod & Nelson, 2000). The consistency between the theory of change, the needs of the target population and the program objectives and activities has also been demonstrated (Booth & Leavitt, 2011; Segal etal., 2012). Several recent reviews have analyzed the impact of implementation factors on the determination of home visiting programs’ success (Casillas etal., 2016; Paulsell etal., 2014; Segal etal., 2012). Implementation fidelity appears to be a crucial effectiveness moderator of home visiting programs, as noted by implementation scientists (Durlak & DuPre, 2008; Fixsen etal., 2005). The meta-analytic review of Casillas etal. (2016) revealed that several implementation factors, such as training, supervision, and fidelity monitoring, had a significant effect on program outcomes. Despite these advances, there are no conclusive data on other aspects of program delivery that may be important for program success, such as dosage and duration of interventions. In relation to dosage, some studies have found no effect of service duration or intensity (Littell & Schuerman, 2002). However, the evidence also shows that interventions of longer duration and greater intensity are more effective (Bilukha etal., 2005; Howard & Brooks-Gunn, 2009; Lagerberg, 2000). In most cases, dosage is reported as raw data, without analyzing the dosing thresholds required to achieve the expected results according to the program model (Paulsell etal., 2014). To improve the understanding of dosage, studies with pretest–posttest designs may not be sufficient, since it is necessary to have successive measurements throughout the intervention process to know when the outcomes are achieved (Singer & Willett, 2003). In addition to the observed difference in the effectiveness of home visiting programs in terms of the implementation conditions, another element that adds variability is the one related to the family profile, since the existing data show that those interventions are not equally effective for all families. In relation to target population profile, although most studies have used ethnically and socioeconomically diverse samples, the results are reported for the total study sample, without providing data differentiated by subgroups based on particular characteristics (Sama-Miller etal., 2019). The scarce data available on this aspect are not consistent. Some studies indicate greater effectiveness with low-income, single and first-time mothers without mental health, violence or addiction problems (Guterman etal., 2014; Segal etal., 2012). Other studies have reported that parents of a lower socioeconomic status have poorer outcomes (MacLeod & Nelson, 2000). In most cases, data come mainly from programs developed in the United States. Analyzing the differences between the families that obtain better results and those who obtain lower benefits from the intervention, as well as generating information from the results of these interventions in other cultural contexts, is essential for better understanding the effectiveness of home visiting programs (Sweet & Appelbaum, 2004). In the case of Spain, the social and cultural context related to family and child welfare presents important differences with respect to that of the United States. A universalist model of social services is well established since the last decade of the last century, while increasingly ambitious policies regarding children’s rights and family support have been progressively introduced. Currently, there are modern policies and laws regarding Child & Youth Care Forum (2025) 54:435–452 437 childhood and family (rights to same-sex marriage, adoption reforms and protection of children from situations of violence) that have placed Spain among the best-ranked European countries in terms of recognition of family diversity (Pérez-Caramés, 2014) and promotion of positive parenting (Jiménez etal., 2019). However, familism, which is deeply rooted in Spain, has meant that public spending allocated to family policies, as well as financial support for families, remains partially below the European Union averages in terms of benefits in cash, services and tax breaks (Churchill etal., 2020). Among other intervention actions with families at risk, home visit programs have also begun to spread in Spain in recent years (Hidalgo etal., 2018), making it necessary to obtain evidence for their effectiveness in this social context. As has been widely highlighted, effectiveness evaluations require not only knowing the general impact of the interventions but also analyzing the target users and the conditions under which the best results are obtained (Flay etal., 2005; Gottfredson etal., 2015). Thus, additional empirical studies are necessary to identify both dosage thresholds to produce outcomes and family characteristics associated with greater effectiveness. To analyze the moderating influence of these aspects in the effectiveness of home visiting programs, it is also important to have evaluation designs and measurement tools that allow verifying how changes take place progressively in the target dimensions of the intervention. Since the ultimate aim of these interventions is to promote child development while preventing child abuse and neglect, the evaluation cannot be limited to checking the decrease of the out-of-home placement rates; it is also necessary to assess the improvements in the development of children who stay in their homes (Berry & McLean, 2014). In this sense, the improvement in child well-being can be taken as an appropriate measure of the effectiveness of home visiting programs. Among the most commonly used tools for measuring child well-being in at-risk families is The Child Well-Being Scales (CWBS) (Magura & Moses, 1986). The CWBS is a useful tool for measuring the child well-being and has been used in different European countries with satisfactory indicators of validity and reliability (e.g., Grimaldi-Puyana etal., 2019; Nunes etal., 2022; Serbati etal., 2015a and b). Specifically, many studies have shown the capacity of these scales to evaluate programs’ effectiveness and the follow-up of families involved in child welfare services (e.g., Cash & Berry, 2003; Serbati etal., 2015a and b). Aims ofthePresent Study Recent evidence shows home visiting programs as a useful strategy for improving parenting skills, family functioning and child well-being. However, effectiveness evaluations require not only knowing the general impact of the interventions, but also analyzing the target users and the conditions under which the best results are obtained. Thus, further research is needed to investigate target population characteristics and implementation factors that may explain the heterogeneity in the outcomes of these programs for families involved in child welfare services. Likewise, most of the available data correspond to the evaluation of programs developed in the United States; therefore, it is necessary to produce further evidence in other cultural contexts. In this framework, this study aims to contribute with new knowledge to the understanding of home visiting programs’ success, exploring dosage and family characteristics related to the effectiveness of the Family Intervention Program (FIP), a home visiting program developed in Spain for families at psychosocial risk. Specifically, the aims of this study Child & Youth Care Forum (2025) 54:435–452 438 were: (1) to analyze the improvement in child well-being throughout the intervention process, and (2) to explore the variability in the effectiveness of the intervention as a function of certain individual and family characteristics. In relation to the first objective and according to the existing evidence in the literature, we expect that the longer the intervention, the greater the effectiveness. In relation to the second objective, we expect differences according to socio-economic level, family structure and children’s age. Specifically, and according to the available evidence, our hypothesis is that greater effectiveness will be observed in single and low-income families with younger children. Method Intervention The Family Intervention Program (FIP) is an evidence-based home visiting program that is part of the local resources of family attention carried out in a town in Northern Spain (Pamplona Cityhall, 2008), within the services provided by the Child Protection System (CPS) in Spain (OSB, 2015; Spanish Ministry of Health, Social Services and Equality, 2013). The FIP is designed for at-risk families attended by family preservation services. The FIP is supported by different theoretical models, mainly the systemic model, the cognitive-behavioral model, and the humanistic theories. The contents tackled in the FIP are aimed at the promotion of parental competencies (conflict solving, communication, attention to children’s needs, household management) and other personal skills (professional integration, health and quality of life), which are worked on both in the entire family as a whole and in the different members of the family to promote the development and wellbeing of the children. The implementation of the FIP includes 2–5 weekly visits of 2h for 2years, although the duration can be extended if the family difficulties persist. The professionals who carry out the intervention are psychologists, social educators and social workers with specialized training in the program and previous experience in family intervention. Intervention methods include cognitive-behavior techniques (e.g., modeling), psycho-educational guidelines and orientation, emotional support and playing-based activities. Case monitoring with child welfare service practitioners was carried out on a monthly basis. Participants All the families who were under the intervention of the FIP participated in the study. Thus, 289 families took part in this FIP trial, which lasted 27months on average, with an intensity of three weekly sessions (M = 2.95, SD = 0.78, Min. = 2, Max. = 5), which lasted 2 h per session. The professionals in charge of the implementation classified the families as being at medium–high psychosocial risk in a 11-point scale rating from 0 (very low risk) to 10 (extremely high risk). According to this assessment, 93.03% of the sample obtained a score of 5 or more with a mean of 7.15 points (SD = 1.69, Min. = 1, Max. = 10). The most frequent family structure was the single parent family (61.24%), although most of them were defined by the stability of their composition (86.85%). The families were constituted by approximately 4 members (M = 3.70, SD = 1.36) with around 2 children (M = 1.96, SD = 0.95). The results regarding the economic level indicate that 10.03% were extremely poor, 24.22% were precarious and 36.33% presented low income. Child & Youth Care Forum (2025) 54:435–452 439 Among the parents of the participating families, 43.59% presented a basic education level and 31.49% had no education. Only 6.57% of the parents had university studies and 18.35% completed high school. Moreover, there was a high percentage of migrant parents (39.58%), who had lived in Spain for an average of 9.71years (SD = 4.64, Min = 1, Max = 30). The children of these families were equitably distributed in terms of sex, since 59.17% were boys and 40.83% were girls. The mean age of the children was 10.76years (SD = 4.40, Min = 0, Max = 18). Measures Socio‑Demographic Profile We used an ad hoc questionnaire to collect sociodemographic information at both the family and individual levels, reporting family composition (number of family members and children at home), family structure (single-parent/two-parent structure), family stability (in terms of composition), and family socio-economic level (extreme: the family does not have an income other than that coming from financial support from public or private organizations; precarious: unstable and scarce family income, where some of the adults work, even sporadically, and sometimes depend on financial support to cover basic needs; low: stable and sufficient family income, where at least one of the parents has a stable job with little or no qualification and the family has no important financial needs; medium: family income is stable and comes from medium-skill jobs; high: household income is stable and comes from highly qualified jobs). Information about caregivers was provided in terms of nationality (non-migrant/migrant, years of residence) and education level (no education -primary school not completed-, basic education level -primary school completed-, and high school or university studies). The sex and age of the children at home were also reported. Psychosocial Risk Assessment The practitioners reported at pretest about the psychosocial risk level of each family in terms of satisfaction of the children’s needs in a Likert scale from 0 (very low risk) to 10 (extremely high risk). Child Well‑Being The satisfaction of the basic child needs was assessed using the Spanish version of the Child Well-Being Scales (CWBS, Magura & Moses, 1986), which was validated in the Spanish context by De Paul & Arruabarrena (1999). The CWBS consists of 43 items and provides a family score (28 items, e.g., “Consistency of discipline”), a child score (14 items, e.g., “Academic performance”) and a global score (43 items, e.g., “Parental relations”); the family score was used in this study. The items are rated by practitioners as informants on 4to 6-point scales, ranging from adequacy to increasing degrees of inadequacy, which are then converted to scales of 1–100 points, with 100 indicating that the evaluated dimension is satisfied. CWBS evaluates the degree of existing problems and not the degree of competence, thus any score below 100 indicates that child well-being is compromised. Child & Youth Care Forum (2025) 54:435–452 440 Procedure The results presented in this paper refer to the longitudinal assessment of child well-being (CWB) and related variables from all families that benefited from FIP throughout the study in the norther region of Spain. A time-series evaluation design (T1–T12) of the population of families receiving the FIP intervention throughout the study was followed, allowing us to examine the CWB slopes as a function of the FIP intervention length in relation to child and family variables (Yanovitzky & VanLear, 2008). CPS practitioners refer to the FIP of those families that, after an in-depth, rigorous assessment, exhibit inadequate parenting competences and related child or adolescent risk for negative developmental outcomes. Child welfare service practitioners contacted the families to enroll in the FIP intervention if they met the following criteria: (1) being enrolled in child welfare services; (2) having a child under 18 considered to be at risk for negative developmental outcomes; (3) inadequate parenting competencies with room for improvement as determined by child welfare services; and (4) both parents and children consenting the treatment. For those families enrolled in the FIP intervention, recruitment to participate in the study was carried out by the FIP practitioners during the first month since starting the treatment. In the recruitment session, the participants were informed about the main characteristics of the treatment, as well as the objectives of the trial. The families were informed about the aims of the project and the confidential and anonymous nature of the data. Every family participated in this study voluntarily, after signing an informed consent form in accordance with the Declaration of Helsinki. This study is adhered to the legal requirements of data protection in Spain, and ethical approval was obtained from the service that implements the FIP. No monetary incentives were offered. The FIP practitioners filled in the measures described above. The socio-demographic profile and the risk assessment were informed at pretest. Child well-being scales were filled in T1 (three months from pretest) and every six months up to the end of the intervention, collecting data up to T12 (up to month 69). Thus, at T1, 289 subjects completed the evaluation, whereas, at T2, the sample decreased to 237 participants (completed the treatment: n = 26, other reasons: n = 26), and 162 participants remained at T3 (completed the treatment: n = 40, other reasons: n = 35). At T4, there were 111 participants (completed the treatment: n = 39, other reasons: n = 12), dropping to 70 at T5 (completed the treatment: n = 34, other reasons: n = 17), and, finally, 19 participants completed the evaluation in T6 (completed the treatment: n = 33, other reasons n = 18). Then, from T6 to T12, these subjects remained in the study until the end of the treatment. The main reason for leaving the trial was ending the treatment. Other frequent reasons included: abandoning the treatment; children’s integrity in jeopardy, requiring an out-of-home measure; and moving to another city. Less frequent reasons referred to the absence of positive results from the treatment or children reaching legal adulthood. Data Analyses The effects of the intervention were examined at the family level. Preliminary and descriptive analyses were performed using SPSS software v.18 (SPSS Inc., 2009). Evolution of CWB from T1 to T12 was analyzed to determine the impact of the FIP length and, thus, the optimum length of the intervention. To this end, multi-level regression Child & Youth Care Forum (2025) 54:435–452 441 equations were performed using SPSS software v.18 (SPSS Inc., 2009). PseudoR2 was examined as the effect size indicator. This value was obtained by squaring the correlation between the value predicted in the dependent variable by the model and the real value of that dependent variable (Singer & Willett, 2003). The individual trajectories on child well-being through the intervention and the moderating role of individual and family variables in such change from T1 to T7 were examined through linear hierarchical model analyses using HLM v-7 statistical software (Raudenbush etal., 2011). Six models were tested: the null model examined between-person variability in CWB over time; model 1 of random intercepts and slopes tested between-person variability on intercepts and on slopes (level-1 model); and models 2–6 analyzed the effect of moderating variables both on intercepts and on slopes (M2: socio-economic level, 1 = extreme, 2 = precarious, 3 = low, 4 = medium, 5 = high; M3: family structure, 0 = twoparent, 1 = single-parent; M4: nationality, 0 = non-migrant, 1 = migrant; M5: child sex, 0 = boy, 1 = girl; M6: child age, years). Two types of indexes were examined as goodnessof-fit indicators. Firstly, the deviance index for each model was provided (the lower the better, Raudenbush & Bryk, 2002), as well as the comparative deviance between consecutive models (with a significance test on the difference between chi square statistics). Secondly, pseudoR2, level-1 pseudoR2 (reduction in residual variance from level 1 compared to the null model), intercept pseudoR2 (reduction in intercept residual variance from level 2 in consecutive models) and slope pseudoR2 (reduction in slope residual variance from level 2 in consecutive models) were computed (Singer & Willett, 2003). PseudoR2 scores were interpreted as negligible if < 0.02, small if > 0.02 and < 0.15, medium if > 0.15 and < 0.35, and large if > 0.35. Results In order to examine the evolution of CWB, the descriptive statistics from T1 to T12 are provided in Table1. CWB was 86.72 in T1 and increased to 90.58 in T7, where the highest mean CWB score was observed. Therefore, a multi-level regression equation was computed considering T1-to-T7 scores. The regression slope was 0.10, with a significance level of p = 0.001 Table 1 CWB means and standard deviations from T1–T12 Min. – Max M SD T1–3months 54.24-100 86.72 6.92 T2–9months 66.24-100 87.52 7.18 T3–15months 57.78-100 88.61 7.83 T4–21months 60.08-100 88.99 7.54 T5–27months 56.12-100 88.42 8.76 T6–33months 55.90-97.93 89.20 9.99 T7–39months 79.37-98.83 90.58 5.79 T8–45months 80.79-100 90.32 6.09 T9–51months 76.16-93.45 85.43 6.80 T10–57months 87.33-94.03 89.51 2.41 T11–63months 84.49-95.62 88.94 4.83 T12–69months 84.08-93.21 88.64 6.46 Child & Youth Care Forum (2025) 54:435–452 442 and an associated PseudoR2 of 0.013, indicating a significant increase of CWB from T1 to T7, with 1.3% of variance being explained by time. A second regression equation was computed from T7 to T12, in order to test the stabilization of CWB during that period. The regression slope was 0.001 with a significance level of p = 0.993 and an associated PseudoR2 of 0.003, indicating no significant increase of CWB from T7 to T12. Once CWB stabilization was established in T7, linear hierarchical models on CWB individual trajectories and the moderating role of individual and family variables were examined from T1 to T7. Table2 shows the beta values, t-values and significance level for each variable in each model. Goodness-of-fit indexes in terms of (comparative) deviance and pseudoR2s are provided. Variance components for tested models are also reported. The null model showed significant between-person differences over time in CWB, such as 𝜎2 r 0 = 41.497 , χ2 (276) = 2330.45, p < 0.001. This value, along with the residual variance ( 𝜎2 e = 16.963 ) allowed calculating the intraclass correlation, as follows: The intraclass correlation of the null model expressed that 70.98% of variability in CWB was due to between-person differences. The null model deviance was 5615.60. M1 of random intercepts and slopes showed between-person variability on the intercepts ( 𝜎2 r 0 = 40.741, p < 0.001) and on the slopes ( 𝜎2 r 1 = 0.103, p < 0.001), expressing differences between families in baseline and different trajectories through the intervention, as well as an improvement of 47.8% in within-variance by incorporating time into the equation. The comparison with the null model showed a significant decrease in the deviance ( Δ deviance = 191.63, p < 0.001). PseudoR2 for M1 was 0.013, serving as a starting point for comparing with level-2 models. The inclusion of the family socio-economic level in M2 showed a significant decrease in the deviance ( Δ deviance = 14.39, p < 0.001) and a relevant increase of PseudoR2 to 0.072. Thus, the family socio-economic level increased the predictive capacity of the model to 7.2%. The β slope was 0.07, with a significant t value (t275 = 2.26, p < 0.05), indicating higher improvement on CWB for those families with better socio-economic status. M3 showed a significant decrease in the deviance ( Δ deviance = 17.31, p < 0.001) and a relevant increase of PseudoR2 to 0.138. Thus, the family structure increased the predictive capacity of the model to 13.80%. The slope showed that single-parent families increased CWB to a greater extent with respect to two-parent families (β = 0.08, t274 = 2.27, p < 0.05). M4 did not show a significant decrease in the deviance ( Δ deviance = 3.33, non-significant), but an increase of PseudoR2 to 0.162. Thus, nationality increased the predictive capacity of the model to 16.20%. The slope showed that migrant and non-migrant families draw parallel trajectories throughout the intervention (β = 0.07, t273 = 1.12, non-significant). Similarly, M5 did not provide a significant decrease in the deviance ( Δ deviance = 0.36, non-significant), but a slight increase of PseudoR2 to 0.166. Thus, the children’s sex increased the predictive capacity of the model to 16.60%. The slope indicates similar trajectories throughout the intervention regardless of the sex of the children (β = -0.02, t272 = -0.34, non-significant). 𝜌 = 𝜎 2 r0 𝜎2 r 0 +𝜎2 e = 41.497 41.497 +16.963 = 0.7098 R 2 e = 16.963 −8.850 16.963 = 0.478 Child & Youth Care Forum (2025) 54:435–452 443 Council of Europe. (2011). Recommendation Rec (2011)12 of the Committee of Ministers to member states on children’s rights and social services friendly to children and families. https:// rm. coe. int/ 16804 6ccea Council of Europe. (2016). Council of Europe Strategy for the Rights of the Child (2016–2021). Council of Community Pediatrics. (2009). The role of preschool home–visiting programs in improving children´s developmental and health outcomes. 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Authors and Affiliations Victoria Hidalgo García1 · Javier Pérez‑Padilla2,3 · Carlos Camacho Martínez‑Vara de Rey4 · Lucía Jiménez García1 * Javier Pérez-Padilla [email protected] Victoria Hidalgo García [email protected] Carlos Camacho Martínez-Vara de Rey var[email protected] Lucía Jiménez García [email protected] 1 Developmental andEducational Psychology Department, Faculty ofPsychology, University ofSeville, Seville, Spain 2 Psychology Department, Faculty ofHumanities andEducational Sciences, University ofJaen, Campus de Las Lagunillas, 23071Jaén, Spain 3 Research Group HUM604: Lifestyle Development intheLife Cycle andHealth Promotion ofUniversity ofHuelva, Huelva, Spain 4 Experimental Psychology Department, Faculty ofPsychology, University ofSeville, Seville, Spain Child & Youth Care Forum (2025) 54:435–452 452