Although dropout is the consequence of a personal decision, it is always influenced by environmental, school, family and individual factors. Therefore, the dropout risk is grounded in the identification of presence and intensity of influence of several risk factors in the environment where student lives (Jovanović, Čekić Marković, Veselinović, Vušurović & Jokić, 2016). There is more chance that a student with the history of absenteeism and grade repetition (Lee & Burkam, 1992; 2003), an underachieving student (Bryk & Thum, 1989) or a student who has somehow alienated from school life or is enrolled in schools will leave school at a certain point (Hammond et all., 2007; Lee & Burkam, 2003; Aikens & Barbarin, 2008; Hanushek et all., 2009; Ingersoll, 1999).

According to The Survey on Income and Living Conditions (SILC, 2017) a total of 38,7% of the population of the Republic of Serbia (three million people) is at risk of poverty or social exclusion. Children (up to the age of 18) and youth (aged 18-24) are at the highest risk of poverty (30.2% and 3.7%), after social transfers, compared to other target groups. Dropout rate decreased from 8% to 6% from 2014 to 2019, but number of children who use social services and welfare benefits constantly growing (22,2% from 2011-2015) (DevInfo, 2019; Žegarac, 2017). This, however, fails to reduce the risk of poverty among children in Serbia and contributes to school dropout, especially among vulnerable groups, like Roma children, girls and  children in rural areas. Through adequate identification of at-risk students and assessing the risk level they are under, it is possible to make more guided and structured individual support measures (Jovanović, Marković-Čekić, Jokić & Ranković, 2017; UNICEF, 2017), which are better adjusted to the individual students’ needs, context and risks. The Instrument for identification of students at risk of dropout (Jovanović et al., 2016) enables the calculation of the Risk Index (RI) for each student. The RI is presented as composite score, calculated on the basis of the weighted influence of risk factors (socioeconomic status, absenteeism, academic achievement, student behaviour, peer acceptance, the existence of the conditions for acquiring social welfare). In order to represent the weight ( ) as a percentage influence onto the composite risk index (RI), we ensure that Σ i is equal to 1 (1 represents 100% influence) (Jovanović, 2017). If the RI is higher than 60, this means that the student is at a very high dropout risk, and the index below 30 implies a student who is not at dropout risk (Jovanović et al., 2016). Schools also provided various other measures within piloted model for dropout prevention, which proved very effective (Čekić Marković et al, 2017; Jovanović et al., 2017). Having in mind that new education policy measures were applied after the project, regarding guidance of schools to create individual support plans for students at risk, additional support systems need to be establish in order to have more comprehensive and effective support. Whereas social welfare system in Serbia has its own weaknesses, it was needed to develop very precise proposal of intersectional measures of dropout prevention that are feasible (3,6% of users of financial support of population in Serbia, 412 users of social security support measures come on one social worker, 92% of budget of social security goes to the financial support). The RI is posted in that way that all children who receives support from social welfare system are at highest dropout risk, so this research could be seen as finding ways for joint response of two system at general.

Sample. After comprehensive desk analysis about legislative and capacities of social welfare system, we selected three municipalities by mixed criteria - expert criteria (advanced social welfare services) and by composite municipality index which recognise municipalities with the highest dropout risk (Jovanović, 2017). The sample included schools participating in the project Prevention of dropouts of students in the education system of the Republic of Serbia (Jovanović et al., 2016) and successfully implemented the Dropout prevention model (DPM), as well as schools from urbanized municipalities with a larger number students at risk. Those CSW’s are at the same time distinguished by the quality of work and from the municipalities that are distinguished by the number of pupils at risk of drop-outs - municipalities with a larger number of students from internally displaced families, from de-industrialized areas and from major urban centres with a higher share of the Roma population. A total of 20 representatives of social welfare centres took part in focus groups and 10 school representatives who have experience in application of (DPM) in three focus groups. The initial activities dealt with mutual prejudices and stereotypes, followed by exchange of information on the situation and circumstances in both systems . Main topics in focus groups were chosen in order to ensure various suggestions for measures for improving joint response of education and social welfare system in dropout prevention (key barriers, chances, threats, opportunities, capacities, challenges).

Findings from focus groups are in line with desk analysis findings: main barriers in creating joint response in dropout prevention are the overload of professionals in CSW, the structure of the social welfare budget that is focused on cash benefits, small focus on the prevention and intervention of social exclusion and small allocations at the local level to the development of various community based social services. The main finding is that participant sees possibilities for the improvement of cooperation between schools and centres for social work should be developed by defining criteria for determining the unambigous priorities when, whom and how to refer student in risk of dropout to CSW. School have to send focused, relevant and timely information about students at the highest risk of dropouts, along with a description and clarification of previously undertaken activities at school. Another key finding with focus groups and interviews is that both school and centre representatives agree that it is necessary to band together cachbenefits and regularschool attendance. Inspired with “Integration Ladder” first used by Munday (2007) in co creation process with professionals from schools and CSWs we proposed new 1) criteria for referral of students form school to CSWs (based on RI) – prioritisation of highest risk with a report of measures implemented by school; 2) a clear banding of regular attendance at school and the use of cashl benefits; 3) ensuring mandatory school reports to CSW after 25 unexcused absences, according to law; 4) feedback from CSWs to schools about provision of support services; 5) early Joint Identification and Monitoring System. New template sensitive to RI was created for addressing social security system by schools. According to Munday (2007), model of integration is shaped as a planed and sustained service co-operation and coordination in dropout prevention and response in Serbia.

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