Integration and differentiation in collaboration between services for youth not in employment, education, or training (NEET)

ABSTRACT

The need for a holistic social work-like approach to labour market inclusion is widely acknowledged. When considering the case of youth not in employment, education, or training (NEETs), services from different public service organisations are often needed. To succeed in providing holistic, integrated services, interagency collaboration is necessary. Drawing on 24 semi-structured interviews with managers and practitioners, this paper aims to investigate how services in different municipalities work to enable integrated service delivery to NEETs with complex problems. The study takes place in six Norwegian municipalities, three of which had higher NEET shares than predicted and three with lower NEET shares. The municipalities are compared to explore whether there are systematic differences and similarities regarding the collaboration between services for young people in vulnerable situations. The findings suggest that the municipalities with lower NEET shares than predicted had more integrated services compared to those with higher NEET shares. The municipalities handled differentiation in collaboration differently. In the municipalities with higher NEET shares, differentiation had caused disconnections between services, while the municipalities with lower NEET shares worked to achieve a common ground through strategies such as more extensive and closer collaboration, clearer communication, and more organised information sharing across services.

SAMMENDRAG

Behovet for en helhetlig, sosialfaglig tilnærming til arbeidsinkludering er bredt anerkjent. Forskning viser at unge som ikke er i arbeid, utdanning eller opplæring (NEET) ofte har utfordringer på flere områder i livet, som krever tjenester fra ulike tjenester og organisasjoner. For å lykkes med å tilby helhetlige, integrerte tjenester er samarbeid mellom ulike aktører nødvendig. Denne artikkelen belyser hvordan tjenester i ulike kommuner jobber for å integrere tjenesteleveringen til NEETs med komplekse utfordringer. Studien er basert på 24 semistrukturerte intervjuer med ledere og praktikere i seks norske kommuner, hvorav tre kommuner hadde høyere NEET-andel enn forventet, basert på deres strukturelle forutsetninger, og tre kommuner hadde lavere NEET-andel enn forventet. Kommunene sammenlignes for å undersøke om det er systematiske forskjeller og likheter når det gjelder samarbeidet mellom tjenester til unge i utsatte situasjoner. Funnene viser at kommunene med lavere NEET-andel enn forventet hadde en høyere grad av integrerte tjenester. Kommunene håndterte differensiering i samarbeid på ulike måter. I kommunene med høy NEET-andel hadde differensieringen ført til fragmenterte tjenester, mens kommunene med lav NEET-andel jobbet for å gjøre differensieringen produktiv. Strategiene som ble brukt inkluderte mer omfattende og tettere samarbeid, tydeligere kommunikasjon og mer organisert kunnskapsdeling på tvers av tjenester.

KEYWORDS:

• NEET
• Interagency collaboration
• Complex problems
• Integrated services
• Differentiation in collaboration

NØKKELORD:

• NEET
• tverretatlig samarbeid
• komplekse problemer
• integrerte tjenester
• differensiering i samarbeid

Introduction

Due to the increased focus on people with complex problems at the margins of the labour market, the requirement for a more holistic, social work-like approach, in contrast to traditional employment measures, has been widely recognised in recent years (Andreassen & Natland, 2022; Heidenreich & Aurich-Beerheide, 2014; Heidenreich & Rice, 2016). In taking such an approach, comprehensive support across sectors is required, including social, educational, health, and employment services (Heidenreich & Rice, 2016; Van Berkel, 2017).

For young people not in employment, education, or training (NEETs), the need for comprehensive social services can be even more pressing (Saltkjel et al., 2021). Although this is a highly diverse group, research shows that youth outside of education and employment often deal with multiple problems in different areas of their lives, such as early school leaving, health problems, loneliness, economic problems, and other social issues (Assmann & Broschinski, 2021; Frøyland et al., 2022; Ose & Jensen, 2017). These youth often need services that cross disciplinary boundaries (e.g. from social, educational, and mental health services) and are therefore among those who would benefit from more integrated services (Boon et al., 2004; Fisher & Elnitsky, 2012). Integration and integrated service delivery refer to connecting contributions from different actors to create comprehensive services to meet people’s complex needs (Willumsen, 2008). This is necessary to succeed in providing holistic, integrated services while also avoiding delays, unclear responsibilities, and duplication (Kodner & Spreeuwenberg, 2002). Interagency collaboration is, however, challenged by differentiation, which refers to the fact that actors from different services bring with them different sets of orientations, skills, competencies, professional cultures, and structural conditions to the collaboration (Willumsen, 2008). If not handled correctly, this could lead to disagreements and conflicts in the collaboration; however, it is also these differences that make interagency collaboration both necessary and rewarding. Integrating different professionals’ knowledge and skills creates a new shared knowledge base that could not be achieved if they were working on their own (Green & Johnson, 2015). Professionals also bring different organisational resources with them, which means that they can offer various measures and more opportunities to the service users. However, an important part of interagency collaboration is also what makes it so challenging: managing to take advantage of the differentiation rather than allowing for it to become too prohibitive.

According to Caswell et al. (2017) and Loyens (2019), there is a need for further research at the micro-level on the relations and interactions between different service providers that are needed for people with complex needs. Saltkjel et al. (2021) have also pointed to a lack of research on collaborative approaches to employment for youth in vulnerable life situations. This paper addresses this gap by studying integration and differentiation in interagency collaboration through the experiences of professionals in different services relevant to the follow-up of NEETs.

This study involved a quantitative analysis of all Norwegian municipalities to identify those with higher and lower NEET rates than predicted, controlling for various factors influencing the risk of becoming NEET. Through interviews with local professionals regarding local work with NEETs, I investigated how the municipalities had integrated their services and the strategies they used to deal with differentiation in collaborative efforts. The study included six municipalities, three of which had higher NEET rates than predicted, and three with lower NEET rates than predicted. The municipalities were compared with the aim of investigating whether there are systematic differences and similarities in collaboration between services for young people in vulnerable situations.

Literature review

Integration and differentiation in interagency collaboration

The concept of integration and differentiation includes both interpersonal and inter-organisational aspects. Willumsen (2008) highlights several factors influencing collaboration among different actors: interpersonal dynamics like skills, competencies, and attitudes, as well as inter-organisational factors such as resources, organisational structures, and governance. Additionally, dynamic factors like the collaboration process, trust, and power struggles, along with contextual factors such as primary tasks and legal mandates, play a significant role (Willumsen, 2008).

As the main objective of this study is to examine the collaboration between different professionals within different services, I employ the term ‘interagency collaboration’ and adhere to the following definition: ‘the process in which different professional services work together to try and positively impact care’ (Cooper et al., 2016, p. 327).

In this study, I do not differentiate between the interpersonal and the organisational level. Instead, my focus is on assessing whether services are effectively integrated and understanding the dynamic factors that either facilitate or hinder this integration. These dynamic factors are influenced by interpersonal as well as inter-organisational factors (Willumsen, 2008). Specifically, the dynamic factors being examined here are concerned with perceptions of problems and solutions, which can be shaped by profession-specific culture and views, organisational aspects like mandates and resources, as well as personal attitudes and experiences.

Young people not in employment, education, or training (NEETs)

The NEET term refers to young people between the ages of 15 and 29 who are in a situation of being neither in employment, education, or training (Eurofound, 2022). While most young people in such circumstances manage to successfully transition into employment or education, the global NEET rate remains high, leading to a decline in the overall number of youths participating in the workforce (International Labour Organization, 2020).

The category of NEET encompasses a widely diverse group of individuals, which spans from young people who choose to be in a NEET situation temporarily, to other NEETs facing more intricate challenges (Eurofound, 2016). Either way, being excluded from the educational system and job market at a young age can consequently result in long-term disconnection, affecting both society and the individual. Research shows that long-term unemployment has detrimental effects on an individual’s health, financial situation, and overall well-being (Clark & Lepinteur, 2019; Halvorsen & Hvinden, 2018; Monsef & Mehrjardi, 2018). To counter this, a holistic approach with attention and help from a variety of professionals in different services is often required. In fact, working across sectors such as education, employment, and health are highlighted as essential in both policy documents and youth research to combat youth exclusion (e.g. Eurofound, 2017; European Commission, 2018; 2020; Hawley et al., 2012; Saltkjel et al., 2021). However, achieving meaningful and effective interagency collaboration is challenging.

Finding a balance between differentiation and integration

Divisions of labour are necessary – the boundaries are inevitable – but the disconnections are destructive. (Glouberman & Mintzberg, 2001, p. 65)

The natural dynamic of differentiation and integration challenges effective collaboration. Preventing differentiation from causing disconnections in the collaboration is essential, and reaching a shared understanding of the problem and its solutions is crucial (Ansell & Gash, 2007; Ødegård, 2005). In fact, Mellberg et al. (2022) found that in addition to covering all identified NEET subgroups in local networks, successfully assisting vulnerable youth requires network members to share an understanding of the problem and its solutions.

When working with complex, or ‘wicked’, problems (Rittel & Webber, 1973), where the core problem and solutions are unclear, collaboration becomes more demanding. Morgan et al. (2019) identified different ‘world views’ as the primary obstacle in collaborative efforts for young people with complex needs. These varying perspectives on the problem and solutions can result in conflicting goals, serving as barriers to interagency work. Thus, effective communication to uncover and resolve these differences, as well as actors who want to see things from a different perspective, are essential (Morgan et al., 2019).

A high degree of differentiation makes integration challenging and may lead to conflicts and power struggles. While conflicts themselves are not negative, how they manifest in actions matters. Irreconcilable disagreement can lead to withdrawal or disengagement among collaborating actors (Hvinden, 1994). Instead of comprehensive service delivery, services risk being provided without being seen in relation to each other (parallel services), or one at a time from different actors (sequential services; Yule & Kelly, 2019).

Bakken and van der Wel (2022) found that the Norwegian Labour and Welfare Organisation (NAV) and health services struggled to collaborate due to a lack of shared understanding, communication, and trust. Additionally, in studying collaboration between youth services, Timonen-Kallio (2019) points to the absence of shared knowledge and ways of communicating as hindering collaboration. Achieving integrated service delivery and common ground despite differentiation requires that the collaborating actors invest time in communicating and addressing the differences (Andersson et al., 2011; Winters et al., 2015). Loyens (2019), in accordance with Ansell and Gash (2007), found that shared goals and a history of constructive collaboration benefit collaborative relations. Particularly in the field of assisting young people with complex needs, Holliman et al. (2023) highlight the need for good, continued communication with the service users and collaboration between different services to be important for successful services. In a literature review of the outcomes of interagency collaboration in children and young people’s mental health, Cooper et al. (2016) recommend that practitioners should strive for a better understanding of other services, establish effective communication channels, and cultivate positive individual relationships.

Study context

This study is part of a larger research project on the local organisation of service provision and inter-organisational collaboration in relation to NEETs in Norwegian municipalities.

In the Norwegian welfare state, central services for young people in vulnerable life situations include the Norwegian Labour and Welfare Organisation (NAV), the Follow-Up Services (FUS), and the Substance Abuse and Mental Health Service (SAMH).

In Norway, NAV provides both state-funded labour market services and municipal social services. They are responsible for delivering labour market measures to NEETs and also preventing work. NAV’s mission is to contribute to creating an inclusive society and working life, and a well-functioning labour market. NAV is also responsible for the provision of income through different benefit schemes.

FUS has the primary task of helping young people aged 15–21 who are not in education or employment to find work, training, and/or other competence-enhancing measures. Different Norwegian counties may organise FUS differently. For instance, in Nordland County, they emphasise that FUS should secure interagency collaboration and assist in efforts to reduce dropout rates (Rosvold, 2021).

SAMH has the primary task of helping people with addiction and/or mental health problems master their life skills, achieve better health, and increase their quality of life. Although they do not solely focus on young people, they often have dedicated professionals who work specifically with young adults.

Empirical materials and analytical approach

This study is based on 24 interviews conducted in six of 20 municipalities included in the main research project of which this study is a part. Following a procedure developed by a Swedish research team (see Mellberg et al., 2022), the selection of the 20 municipalities was based on a two-level random intercept logistic regression analysis of anonymised register data for the whole Norwegian population. This analysis controlled for individual factors as well as factors related to the regional context that were shown to affect the risk of ending up in a NEET situation (for details, see the Appendix). The municipalities were ranked according to their estimated random intercept (i.e. municipal-level residual) in each year, with positive residuals indicating a greater NEET likelihood than otherwise expected, while negative residuals indicate a lower likelihood. Using the average rank over five years, we selected 10 municipalities where the observed NEET rate was consistently lower than what could be expected based on their pre-conditions and 10 municipalities where the observed NEET rate was consistently higher than what could be expected. Throughout the paper, I will refer to these municipalities as having ‘Higher and lower NEET shares’. For a detailed description, see the Appendix.

The municipalities were grouped in pairs, each consisting of one with a high NEET share and one with a low NEET share, with similar characteristics regarding location and population size. These pairs are referred to as ‘twin municipalities’. The interviews for this study were distributed among three ‘twin municipality’ pairs, representing different parts of the country (north, southwest, and east). The number of inhabitants ranged from 7916 to 19488.

Semi-structured interviews were conducted in late 2021 or early 2022. The interviews covered various topics, including the informants’ backgrounds, local youth characteristics, organisational details, and interagency collaboration.

The project was approved by the Norwegian Agency for Shared Services in Education and Research (ref. 520790) and has been carried out in accordance with national norms for research ethics. No other ethical approval was required. Prior to their participation, the informants received written information about the project, and their participation was based on verbal consent.

Informants

There were 25 informants represented in the 24 interviews. 11 informants were from NAV, six from FUS, six from SAMH, and two from services deemed particularly important – the apprentice manager for youth in training, and the manager of a municipal department for ‘Children, Youth, and Family’. All informants had several years of work experience in their respective fields, although ranging from one to 18 years in their current position. They represented a range of professional backgrounds, from no formal education to those with law degrees or social work backgrounds. Over a third had a social work background, but no informants within the same municipality shared the same profession. There were no specific differences between informants in municipalities with high or low NEET populations.

One informant from each service was interviewed, whereas key informants were FUS coordinators and service managers. FUS coordinators offer unique insights due to being the ones in their positions in the municipalities. Given the study’s focus on the organisation of interagency collaboration and the dynamics affecting it, the perspectives of the service managers were considered valuable. Street-level managers (SLMs) are ultimately responsible for shaping the services and service delivery to a local target population (Gassner & Gofen, 2018), in this case, NEETs. As a result, they play a critical role in determining resource allocation and fostering collaborative initiatives. To get different perspectives, we interviewed both the office manager and the youth team manager in NAV. In one of the NAV offices, there was no current NAV office manager, instead, two practitioners handling different areas of the NAV office’s youth follow-up were interviewed. All informants from SAMH held managerial positions.

Analytical approach

With the aim of analysing how the municipalities worked to enable integrated service delivery to NEETs with complex problems, I closely examined interview data about interagency collaborations. The analyses drew from thorough interview notes, interview recordings, and the transcription of specific segments. Following a thematic approach (Ryan & Bernard, 2003) the initial themes were derived from the interview guide, where questions concerning formal and informal collaboration, shared perceptions of problems and solutions, and knowledge exchange were important. Utilising the ‘cutting and sorting’ technique (Ryan & Bernard, 2003), multiple subthemes emerged, like ‘Engagement’, ‘Collaboration Levels’ and ‘Perspectives on Collaboration’. These subthemes converged into three main themes, highlighting noteworthy commonalities and distinctions among the municipalities:

1. Degree of integration in municipal services

2. Differentiation in the reported collaborative relations

3. Approaches to managing differentiation

Initially, individual informant interviews underwent separate analysis, which was then used to discern commonalities and distinctions within each municipality, resulting in the creation of six unique ‘municipality profiles’. The twin municipalities within each pair were subsequently compared to unveil similarities and differences. Finally, each twin pair were analysed collectively to identify patterns between and across the municipalities that had higher and lower NEET shares than predicted.

In the findings, the municipalities are presented with numbers and letters. The numbers represent the twin pair, while the letters represent the share of NEETs, where L means lower NEET shares, and H means higher NEET shares. Twin Municipality Pair 1, therefore, has the designations 1L and 1H, Pair 2 has the designations 2L and 2H, and Pair 3 is designated by 3L and 3H.

Findings

The aim of this study was to investigate how different municipalities (i.e. municipalities with a higher and lower NEET rate than predicted) address integrated service delivery to NEETs. The findings are presented in three subsections. First, I present patterns regarding the extent of integrated municipal services in both high and low-NEET-rate municipalities based on professionals’ accounts of collaborative relations. Second, I present findings regarding differentiation within the reported collaborations, analysing coherence in problem understanding and preferred solutions. These findings encompass three sub-themes: ‘descriptions of the challenges of the local NEET group’, ‘experiences of coherence in perceptions of the problem’, and ‘coherence in the perception of solutions’. Lastly, patterns for addressing differentiation in collaboration are presented, highlighting communication and knowledge exchange efforts to reach common ground (or lack thereof).

Integrated or differentiated municipal services

The analyses show that in the municipalities with lower NEET shares, there was more extensive and structured collaboration between the services, regardless of whether it was formal or informal, than in the H municipalities.

A pattern emerged in which the services in the municipalities with lower NEET shares were more concerned with and engaged in collaboration. Collaboration often took place in individual cases, at an organisational level, and at a system level. They expressed great interest and perceived value in collaborating with other services regarding NEETs to provide holistic services. For example, the NAV office manager in municipality 1L said the following:

We have had interactions between services at various levels in the municipality before, but we have systematised it in a better way to get an overview of what the other services see and what measures the others have. […] So, we have established an interdisciplinary team to keep track of and inform each other about what we are seeing, which gives us the opportunity to implement, perhaps bigger, targeted efforts.

Also expressing interest in and value of interagency collaboration is SAMH in municipal 2L, who reported the following:

We are a municipality that is conscious of working in an intersectoral way. […] They [the municipality] are very concerned about prevention and early intervention.

In the municipalities with higher NEET shares, there were less extensive collaboration. Collaboration in these municipalities was characterised by the fact that it was between the individual caseworkers on individual cases (although more formal collaboration at an organisational level emerged after 2018). The informants in these municipalities described working in silos, fragmented service delivery, and the need to clarify and define areas of responsibility. Furthermore, the manager of the NAV office in municipality 1H described conflicts and problems in municipal management, which led them to not have or want any formal collaboration with the other services. An informant from SAMH in municipal 1H said the following:

I have worked in many municipalities, and what is perhaps the challenge here is that it is very much silo thinking. […] There is very little flow in the collaboration. It’s starting to get better, but I think that the interdisciplinary collaboration opportunities have been a challenge.

In municipality 2H, the collaboration mostly concerned individual cases and transitions between services (i.e. sequential services). In municipality 3H, services were provided without coherence. The NAV office manager described the situation as follows:

We [the services] work very fragmentedly. Many of our service users also have services elsewhere in the municipality. […] There are many people who have worked with that service user, each with their own approach. […] None of us provides good services when we work like that. And, of course, for the municipality as well, it costs quite a lot. After all, we are burning resources in a double sense, so to speak, instead of delivering coherent services. There is no holistic follow-up around that citizen.

This quote from the NAV office manager in municipality 3H shows that services were provided in parallel without being seen in coherence when the informant clearly thinks that the service user needed comprehensive, integrated services.

Differentiation in collaborative relations

Differentiation was studied here based on whether the informants had similar descriptions of the local NEET group’s challenges, and whether they experienced shared perceptions of the problem and solutions in the reported collaboration.

When asked to describe the challenges of the local NEET group, the informants in each municipality identified similar problem areas (those more often mentioned were substance abuse, early school leaving, isolation, and mental health problems). This suggested a general consensus among the informants regarding the challenges faced by NEETs. However, some nuances emerged. Some informants highlighted specific problems that others did not explicitly mention, either due to personal concerns or because of their service’s particular focus. For example, in municipality 1L, all informants emphasised school dropout as one of the main challenges for the local NEETs. Still, FUS called this out as the dominant problem without saying more about the underlying reasons for dropping out, while the department manager for SAMH also highlighted young people with ‘heavy’ diagnoses that required round-the-clock staffing and other conditions, such as Asperger’s and ADHD.

Further, the analysis revealed that there might have been differences in how the problems were understood. For example, in municipality 1H, all the informants pointed to the NEET group as having difficulties within the school system, but the problems were described using different words. The informant from FUS said that youth struggled with ‘school refusal’ and elaborated that young people had difficulties in school because they were forced to be there, even though they were not ready for it. The informant from NAV pointed to the group having ‘school challenges’, without saying more about what that consisted of. This may indicate that, even if they agree that the problem is that young people have school challenges, their interpretations of the underlying causes might differ.

These nuances in the informants’ descriptions of the challenges of the local NEET group were visible in all the municipalities, regardless of whether the municipality had high or low NEET shares.

Regarding experiences of coherence in perceptions of the problem, the informants reported that, most of the time, they shared the perceptions of the group. However, interesting nuances also emerged here that could challenge this shared view. For instance, some municipalities highlighted person dependencies (this applies to both the perceptions of the problem and the solutions). For example, in municipality 3L the NAV department manager said that whether they experienced common views depended on the person with whom they collaborated, and that they had experienced both agreement and disagreements with different FUS coordinators. Furthermore, organisational matters and boundaries introduced certain challenges. This was illustrated in municipality 2H, where the services were organised with clear boundaries between them. This sometimes made it irrelevant to collaborate or to discuss problems and working methods with others. On this point, the informant for FUS (2H) said the following:

It’s a bit complex [whether they share perceptions of the group of NEETs] because we have a target group that is younger than what NAV has. It’s not always as relevant for us to collaborate with NAV because the youth are younger than 18. NAV has an age group that is between 18 and 30, and that exceeds our age group.

The informants mainly reported coherence in perceptions of the problem, although the analyses revealed interesting differences that may point to the root of the problem sometimes being understood differently. This, again, can lead to different preferred solutions, which might be the reason why all the municipalities reported lower coherence in the perception of solutions. Disagreements about working methods and preferred solutions typically arose between NAV and the specialist healthcare service. One example was in municipality 3L, where the department manager in NAV reported the following:

The specialist healthcare service wants to finish treatment before the service user starts looking for a job, but we at NAV want to combine the job and the treatment.

Another example was in municipality 1H (where the tables had turned). The quote below also emphasises how each service’s knowledge about the service user can affect which solutions are preferred:

No, we don’t [have a common view]. You can say that we [NAV] have knowledge of the labour market, we have health information from doctors, and we may have access to reports about their [the youth’s] childhood. Then, the specialist healthcare service wants the youth to engage in a job. Very often, we [NAV] can say that, according to the previous ten years, a job is not the right thing now, but perhaps some activity is. […] So here we are not completely in sync.

The findings showed that there were no clear differences between the municipalities with high and low NEET shares concerning the degree of agreement about problems and solutions. In Pair 1, there was disagreement in both municipalities, and in Pair 2, there was agreement in both municipalities, while in pair 3, there was a slight difference between the municipalities, where a greater degree of agreement was expressed in municipality L than in H.

Dealing with differentiation

How the services worked to handle the differentiation was studied based on the informants’ answers to questions about knowledge exchange and communication between services, as well as information given throughout the interview about how they worked through these differences.

There were differences between the municipalities in each of the three ‘twin pairs’ regarding communication and knowledge exchange. A pattern emerged where the municipalities with lower NEET shares had more extensive and structured information sharing compared to those with higher NEET shares. In the L municipalities, information sharing was structured through regular meetings, forums, and informative presentations. This facilitated the sharing of knowledge and information related to individual cases, their service, and broader systemic issues.

Extensive communication and collaboration in the L municipalities seemed to be maintained, regardless of the degree of differentiation. In cases where shared perceptions of the problem and solutions were achieved, this common ground was the result of years of close collaboration. In cases where common ground was not present, efforts were made to enhance collaboration and communication, aiming to reach an agreement. For example, in municipality 1L (where a high degree of differentiation was expressed), they planned for a partial co-location between NAV and FUS to work more closely together. An informant from NAV (1L) described this situation as follows:

We have worked on talking together about how we work. We have spent time clarifying our roles and how we should work with the group.

The high degree of information sharing across services in the L municipalities, is likely to have strengthened their understanding of each other’s professional fields, services, and discussions around solutions. This was illustrated in municipality 3L, where collaboration and communication were used to bridge disconnections and take advantage of their differences. The NAV office manager (3L) characterised this in the following way:

We [the services] did not understand each other. [We had] neither insight nor understanding of how we [the services] worked and how to make it work. […] [Agreement on solutions] is something that has come as a natural part of us working together so closely and understanding each other. We must think of health as part of the concept of work, and they must think of work as part of the concept of health. And we achieve that to a much, much greater extent now.

In the higher NEET rate municipalities (H), informants also reported both sharing and receiving information from other services, but expressed a wish for more extensive, formalised, and structured knowledge exchange. Knowledge exchange primarily revolved around individual cases and was provided upon direct request from other services. A quote from SAMH in municipality 2H illustrates this:

Yes, we do share knowledge, but only on specific requests for information. I would like us to get to know each other and what the various services can contribute. I want more professional knowledge to be shared with each other across services.

In all three H municipalities, there was a stronger emphasis on highlighting the distinctions between services. The focus was on legislation and other organisational conditions that differentiated the services rather than efforts to reach common ground. For example, in municipality 1H, the manager-informants emphasised sharing information about what the services could and could not do and used meetings to draw boundaries between the services. These boundaries had become so pronounced that discussions about shared understanding were deemed necessary only in exceptional cases. The following extract from the interview with the NAV office manager (1H) illustrates this:

Interviewer:

Do you agree on working methods?

NAV office manager 1H:

What prerequisite do I have to say that they [the other services] are doing it wrong or right? They have their own working methods to follow, and we must trust that they do what they can for our shared service users. I don’t have anything to teach the school about pedagogy, and it’s the same with SAMH about mental illnesses. It is not in NAV’s field of expertise; it’s just not.

Interviewer:

So, are you not discussing agreement on methods? Does each service independently manage its own domain?

NAV office manager 1H:

Yes, they do.

Rather than collaborating and communicating to reach common ground, the differentiation, in this case, led to reduced communication and collaboration among the services. The same situation was evident in municipality 3H, where the disconnections between the services were maintained through scarce communication and fragmented service delivery. However, the NAV office manager (3H) did report the following:

We are probably not always in sync, but we have come so far that we at least dare to talk about it, and we dare to discuss it.

Furthermore, this NAV office manager (3H) explained what could make communication about differences challenging:

What can be challenging is keeping this up and prioritising and allocating resources towards it. […] And then there is the fact that in all units, some employees leave, and new ones come in. […] Then we kind of have to start all over again and gain a new understanding of the collaborative dynamics. It goes much better when we work together over time and have stable personnel.

In summary, the higher NEET rate (H) municipalities differed from the low NEET rate (L) municipalities in how they approached differentiation. The H municipalities tended to maintain and reinforce boundaries between services, expressing acceptance that this was just the way it was, which, in turn, may have resulted in more fragmented service delivery. In contrast, the L municipalities actively worked to break down boundaries and demonstrated a commitment to improving communication and collaboration to bridge service disconnections.

Discussion and conclusion

This study aimed to explore how six different Norwegian municipalities organised their services to provide holistic, integrated service delivery to people with complex needs, more specifically youth not in employment, education, or training (NEETs). Furthermore, it aimed to identify any systematic differences and similarities between municipalities with higher and lower NEET rates than predicted.

The findings indicate that municipalities with lower NEET rates had more integrated services and were engaged in more frequent collaboration not limited to individual cases, compared to municipalities with higher NEET rates. However, there were no clear differences between these municipalities regarding consensus about problems and solutions. Yet, great differences emerged in how they addressed differentiation. In the municipalities with higher NEET shares, differentiation had caused disconnections between services, while the municipalities with lower NEET shares worked to achieve a common ground through strategies such as more extensive and closer collaboration, clearer communication, and more organised information sharing across services.

Consistent with existing literature, communication and knowledge exchange stand out in this study as crucial aspects to enable integrated service delivery, particularly when dealing with complex problems that are challenging to define and resolve. While this study’s informants mostly had shared understandings of the problem, there were differing perspectives on its core issues. Different understandings of the problem lead to different preferred solutions, a common issue when dealing with wicked problems (Rittel & Webber, 1973). For instance, in municipality 1H, all informants pointed to problems within the school system among the NEETs. However, one informant pointed to the youth’s unwillingness to attend school, and the other informant mentioned only ‘school challenges’, which could also point to learning difficulties or something outside of their own unwillingness. These differing perspectives would require different solutions to the problem; one might want to solve the ‘outsiderness’ by suggesting other activities than education, while the other professional might focus on finding alternative educational courses. As found by Morgan et al. (2019), these kinds of problems could be significant barriers to collaboration. Thus, effective communication is essential, as assumptions about shared understanding of the problem may not hold true.

Open communication around differences to achieve common ground and shared understandings have been highlighted as important elements for the success of collaboration (e.g. Andersson et al., 2011; Ødegård, 2005; Winters et al., 2015). These ideas are consistent with the results of this study, which show that when services continue to collaborate and actively communicate, common ground will be reached. In the municipalities with lower NEET rates than predicted, reaching an agreement was considered important and valuable for assisting this group of NEETs. The municipalities that experienced shared understandings reported close collaboration and extensive knowledge exchange over many years. Loyens (2019) pointed to the same type of findings, indicating that a history of constructive collaboration benefits collaborative relationships. In municipality 1L, it was shown that this was ongoing work, with professionals trying to reach more common understandings through closer collaboration and ‘talking about how they work’.

Conversely, a lack of communication and trust hinders interagency collaboration (Morgan et al., 2019; Bakken & van der Wel, 2022; Timonen-Kallio, 2019). This can result in disconnections and passivity among participants (Hvinden, 1994). This is what appears to have happened in two of the municipalities with higher NEET rates (1H and 3H). In these municipalities, a lack of communication and collaboration had made the differentiation prohibitive, with services provided in parallel or sequentially without coherence. All the municipalities with a higher NEET rate focused on what set their services apart, rather than how they complemented each other. Consequently, communication had been reduced to a minimum, the boundaries had become quite rigid, and collaboration was essentially impossible or not wanted.

Regardless of whether there may be agreement, what remains crucial is the continual communication and collaboration among those involved, allowing them to harness each other’s strengths instead of allowing differences to become destructive to the collaboration.

This study underscores the importance of services desiring to reach common ground and actively making efforts to achieve it through consistent communication and collaboration (i.e. that the services are able to balance differentiation into integrated services). It highlights the importance of well-functioning collaborative networks that have sound organisational structures, as well as professionals that enable integrated service delivery to populations in need of multiple services. This study cannot establish a causal relationship between integrated service provision and specific outcomes for NEETs. Still, the results indicate that municipalities with lower NEET shares (than predicted) tend to have more integrated services and more effective communication for resolving potential conflicts among collaborating actors, making such practices an important aspect to consider in the follow-up of NEETs.

Limitations

This study has some limitations. Firstly, there is a time gap between the data used for municipality selection and interview data collection, due to the availability of register data. However, steps were taken to mitigate potential issues. Municipality selection was based on 5-year outcomes, capturing long-term differences. During interviews, we specifically inquired about the 2013–2018 coordination measures and whether any important changes had occurred during recent years. Secondly, this study relies on a limited number of informants representing various municipal services. The informants held positions that enabled them to offer comprehensive insights into the interagency collaboration concerning the local NEETs. Nevertheless, it is important to note that the findings are based on the informants’ descriptions and experiences, which may not fully represent all perspectives within the municipality.

Acknowledgements

This research article is part of the project ‘Organizing for Outcomes (O4O): Links between service integration and transitions to employment for citizens with complex service needs’. This project is based on a study design developed by Renate Minas and Thomas Korpi, Stockholm University. Their generosity is greatly appreciated.

I thank the project group and the project’s stakeholder panel for valuable discussions in the early phase of the article, and a special thank you to Tone Alm Andreassen and Therese Saltkjel for their valuable comments on earlier drafts. I also wish to express my thanks to the informants who have shared their thoughts and ideas with us. Finally, I would like to thank the journal’s anonymous reviewers for very valuable suggestions for the improvement of the first version of this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research project of which this study is a part was supported by the Research Council of Norway [grant number 301943].

Notes on contributors

Marthine Thøgersen

Marthine Thøgersen is a PhD Candidate at the Centre for the Study of Professions at Oslo Metropolitan University. In her PhD project, she is researching the organisation of service provision and interagency collaboration concerning youth not in employment, education, or training (NEETs) in Norway. Marthine is a social worker and holds a master’s degree in Collaborative Management in Health and Social Services.

Appendix 1

Selection of municipalities

Empirically, the study applies a two-step approach to the selection of municipalities: The first step was a quantitative multi-level regression analysis of individual NEET risk in all Norwegian municipalities. The aim was to identify deviant municipalities once individual and structural variables previously found to be important for NEET risk had been considered. A 2-level mixed-effects logistic regression analysis was conducted in which the likelihood of an individual being NEET was regressed on a set of individual and municipal variables. For the analysis, anonymized register data from Statistics Norway for the whole Norwegian population was used.

We followed a procedure developed by a Swedish research team (see Mellberg et al., 2022), based on the definition of NEETs used in other Swedish register-based studies including 16- to 24-year-olds who during a calendar year only worked or studied for a very limited extent.

In the regression analysis, the independent variables included indicators measuring the demographic composition of local youth, indicators capturing the local labour market structure, as well as indicators measuring the local provision of education and health care. The factors controlled for are structural factors such as the municipalities’ local labour market, unemployment rate, education and care provision as well as individual factors such as age, gender, immigrant background, level of education and whether one has children aged 0 to 6 years. The analysis spanned a 5-year period (2014–2018) with each year analysed separately. The municipalities were ranked according to their estimated random intercept (i.e. municipal-level residual) in each year, and an average rank across the five years was calculated.

In the second step, 10 among the 20 municipalities with the highest average rank and 10 among the 20 with the lowest average rank were selected. These 20 municipalities in other words consistently deviated from what could be expected given their structural pre-conditions, the former in that their expected NEET rate tended to be higher than their actual rate and the latter in that their expected rate tended to be lower. With this selection procedure, it is controlled for individual factors as well as factors related to the regional context that are shown to affect the risk of becoming a NEET.

The municipalities were selected in pairs of one highest ranked and one lowest ranked with similar territorial location with respect to the dimensions of centre-periphery and size (number of inhabitants). This procedure allows for a comparison of municipalities that are similar with respect to contextual factors that are assumed to influence inter-sectoral coordination and collaboration.