This chapter covers the case study of @ease, a youth mental health initiative based on peer support in the Netherlands. The case study includes an assessment of @ease against the five best practice criteria, policy options to enhance performance and an assessment of its transferability to other OECD and EU27 countries.
Mental Health Promotion and Prevention
Best Practices in Public Health
Abstract
Description: @ease is a youth mental health initiative providing peer-based accessible support to increase mental health resilience and prevent worsening of psychological distress and symptoms. Fifteen @ease centres are available in 12 municipalities in the Netherlands. Volunteer young adult peers, including those with lived experience, serve as counsellors to young people that might walk in or have booked an appointment, at no cost and without referral. Youth peers operating in these non-clinical environments are trained in active listening, solution-focussed strategies and motivational interviewing, and are supervised by a healthcare professional on site.
Best practice assessment:
|
Criteria |
Assessment |
|---|---|
|
Effectiveness |
Psychological distress and functioning improve over time for young people returning to @ease after a first visit. @ease returnees do also seem more likely to receive mental health support in the past three months, and less likely to be absent from school, although with less certainty. |
|
Efficiency |
@ease relies mostly on voluntary work, which reduces the cost of the intervention. |
|
Equity |
@ease reaches young people in vulnerable circumstances, but to a limited extent. Only a small share of young people who seek @ease are not in employment or education or training, in an unstable housing situation or of a gender minority. |
|
Evidence‑base |
Although @ease has a routine outcome monitoring in place, the studies produced with these data face important limitations such as absence of a control group, (potentially) high missing data, and self-selection into monitoring. |
|
Extent of coverage |
@ease succeeds in removing barriers on access to mental health support, covering a group of people with high distress and suicidal ideation, and who often did not receive formal mental health care in the recent past. |
Enhancement options: To enhance effectiveness of @ease, efforts should be conducted to increase the return rate and continuity of support. To enhance equity, efforts should focus on increasing the representation of traditionally underserved groups such as gender/sexual and ethnic minorities. This can be done through increased dissemination in respective social circles, recruiting peers from these groups which can act as ambassadors and provide linguistically and culturally adapted support, and setting up new @ease centres in strategic locations. To enhance the evidence‑base, better data collection is essential to assess @ease results. Conducting a controlled study and a cost-effectiveness evaluation are highly recommended. To enhance the extent of coverage, it is important to diversify the communication channels (e.g. telephone, videoconference) and increase opening hours.
Transferability: A high-level transferability analysis using clustering suggests that 18 of the 38 countries included in the analysis would present many of the characteristics needed to ensure a successful transferability of @ease.
Conclusion: @ease centres provide an innovative form of youth mental health support based on trained volunteer peers, easily and freely accessed by young people, and have the potential to improve their psychological distress and functioning. Enhancements in the continuity of support, uptake by traditionally underserved groups and data collection would maximise the potential of @ease and favour its establishment as a key intervention for youth mental health.
1. At the time of writing this report funding had been attributed to study both the comparative effectiveness and the cost-effectiveness of @ease but the studies were still in the preparation phase.
Youth is a critical life‑phase for mental health and for the onset of mental disorders (Kessler et al., 2007[1]; Solmi et al., 2022[2]). Mental disorders are the main cause of disability among adolescents and young adults in high-income countries (Gore et al., 2011[3]; Erskine et al., 2015[4]), with suicide being the fourth leading cause of death for those aged 15‑29 years old (WHO, 2021[5]). Still, a large part of young people experiencing mental health problems do not receive formal support (De Graaf, Ten Have and van Dorsselaer, 2010[6]; Slade, Teeson and Burgess, 2009[7]). Several factors contribute to this treatment gap, even in countries with well-established child and adolescent mental health services (CAMHS). These barriers arise at the individual level, for example due to stigma, lack of mental health literacy or concerns with privacy and confidentiality (Corry and Leavey, 2017[8]; MacDonald et al., 2021[9]), as well as the service level, for example complex referral processes and waiting lists, or the disconnection between CAMHS and adult mental health services (AMHS) that hinders care continuation into adulthood (Appleton et al., 2021[10]; Gerritsen et al., 2022[11]; Signorini et al., 2018[12]).
The treatment gap and the mismatch between services available and young people’s needs have motivated the development of several initiatives aimed at improving access and appropriateness of care for youth. In the Netherlands, @ease was founded in 2017, and the first centre applying the @ease method opened in 2018, in Maastricht.
Origin and mission
@ease is a Dutch initiative designed to reach young people in need of mental support, with the objectives of increasing mental health resilience and thereby the chance of positive development, as well as preventing aggravation of emerging or existing mental health and developmental problems (Leijdesdorff et al., 2022[13]). The initiative follows from a Foundation with the same name and consists of a set of walk-in centres targeting young people aged 12 to 25. The centres are characterised by being youth-friendly and embedded in a non-clinical environment, where an intervention according to the @ease method is delivered by youth peers with on-site professional supervision (Boonstra et al., 2023[14]).
@ease was founded in 2017, and the first centre opened in 2018. Today, the programme counts 15 centres across 12 municipalities: Maastricht, Amsterdam, Heerlen, Rotterdam, Leiden, Groningen, Leeuwarden, Haarlem, Zwolle, Eindhoven, Roermond, Apeldoorn. (Boonstra et al., 2023[14]; @ease, n.d.[15]).
Intervention
@ease can be characterised as low-barrier support provided by trained peers. It is free and requires no referral, no appointment, no intake session and no clinical diagnosis or even identification of the young person, which can remain anonymous if they prefer. Young people in need of support can walk into the @ease centre and seek help from trained peers, which do usually work in pairs. During their time with the peers, young people can discuss a multitude of topics that range from their mental health to their physical health, but also sexual, financial, vocational, and social problems (Boonstra et al., 2023[14]).
The intervention consists of peer-to-peer conversations based on the principles of active listening and counselling, provided by trained youth peers, including experts by experience. @ease’s motivational and solution-focussed working method aims at activating visitors’ (social) participation, in terms of opportunities and through alternate coping strategies (Boonstra et al., 2024[16]). Peers are volunteers aged 18 to approximately 30, who apply to @ease, and are screened by location managers to assess their motivation, past conduct, lived experience, and conditions to deal with visitor problems and complex situations. Following the screening, peers undertake a 2‑day training that is solution-focussed and covers techniques of active listening and motivational interviewing (Slot and van Aken, 2010[17]; Spanjaard and Slot, 2015[18]). The training also includes elements of the suicide prevention training offered by the national Dutch suicide prevention centre 113 (https://www.113.nl/english), to support peers in dealing with young people’s suicidal thoughts and crisis situations. During an initial period following the training, peers are monitored to determine their suitability to the programme and commitment to the role (Leijdesdorff et al., 2022[13]). Reinforced training is offered along the programme.
Young people in need of support can access @ease centres by walking in unannounced during opening hours or by scheduling an appointment, either online (chat) or by telephone. There are no financial costs to the young people, no referral requirements, waiting lists, or intake/admission procedures that could discourage and delay access to support. There is also no limit to the number of visits per person. The young person is the one to decide if and when visiting again, without the need of announcement. This also means that there is not necessarily a trajectory of consecutive sessions with the same peer. The content of the counselling and the peer may vary at every visit and the topics can be situational: what is required at that time is determined in each visit. During the COVID‑19 pandemic, @ease launched an online chat to enable remote conversations. The online chat tool is still available today during the opening hours of @ease locations.
The peer-led conversation is tailored to the need of the visitor, providing either early intervention, first support and facilitation of further help-seeking, offering support during waiting time for formal care, or complementing or bridging care provided by a practitioner (in parallel) (Leijdesdorff et al., 2022[13]).
Organisational structure
Each @ease location operates on one to three afternoons a week, with three to five peers working in the centre. Depending on locations and volunteers, peers work on average two afternoons per month. Peers are often experts by experience, ranging from experience of psychological distress, family problems, and other challenges experienced by youth, to a diagnosed mental disorder and an experience of formal mental health care. Supervision of young peers in each centre is done by a healthcare professional: most often a psychologist or a social worker, but possibly also a psychiatry resident, behavioural scientist, or a specialised nurse. The supervision consists of preliminary discussions with the peers of potentially complex situations and mandatory discussions following each individual conversation, in which the peers and the professional evaluate the session together. If needed, the professional can join the session to support the peer in interacting with the visitor (Leijdesdorff et al., 2022[13]).
Each team also has access to on-call psychiatric support, which can be activated by the on-site healthcare professional. One psychiatrist per region would be available during @ease centres’ opening hours for telephone consultations and referrals to the crisis intervention team, if needed (Leijdesdorff et al., 2022[13]; Boonstra et al., 2023[14]). Last, each centre is managed by a site manager, who takes care of logistical aspects such as organising the peers’ schedule and registration.
Premises where @ease centres are located vary by the municipality, and are decided together with local stakeholders, based on needs but also considering easy access by foot or public transport (i.e. central in the city). Example of locations include public libraries, youth centres, private buildings (renting small workspaces) and study-cafés.
Monitoring and evaluation
Routine outcome monitoring is part of @ease design and is conducted by collecting data at the end of each visit on a tablet device, provided that the visitor consents. Data collection starts with the presentation of an informed consent form which outlines the research purposes, confirms that the participation is not mandatory, and that the data collection can be stopped at any moment. For those that do not object (passive informed consent), the questionnaire consists of a first part answered by the visitor, with questions about demographic characteristics, access to @ease and validated measures of psychosocial distress and quality of life. A second part of the questionnaire is then completed by the peers that provided the support, collecting data on suicidal ideation, need for referral and social functioning. Table 10.1 describes the information collected in more detail. When data from a first visit has already been collected, only part of the questionnaire needs to be answered in follow-up visits. Furthermore, each consent form also asked visitors about the possibility of receiving follow-up questionnaires, by text or email, at three, six and 12 months after their last visit to the site (Boonstra et al., 2023[14]).
Notes: According to the protocol paper (Boonstra et al., 2023[14]) the collection of past mental health support was restricted to healthcare, and guided by the question “During the last three months, how often did you go to a healthcare professional for mental health issues or addiction problems?”. Furthermore, the school absenteeism was instead named Truancy. In (Boonstra et al., 2024[16]), the authors justify that “truancy might also be a less accurate term at tertiary education levels if attendance is less often or not mandatory, or when the education largely consists of self-study”.
Source: Adapted from Leijdesdorff et al. (2022[13]), “Who is @ease? Visitors” characteristics and working method of professionally supported peer-to-peer youth walk-in centres, anonymous and free of charge”, https://doi.org/10.1111/eip.13294, Boonstra et al. (2023[14]), “@ease peer-to-peer youth walk-in centres in The Netherlands: A protocol for evaluating longitudinal outcomes, follow-up results and cost-of-illness”, https://doi.org/10.1111/eip.13443 and Boonstra et al. (2024[16]), “Evaluating changes in functioning and psychological distress in visitors of the @ease youth mental health walk-in centres”, https://doi.org/10.1192/bjo.2024.58.
This section analyses @ease against the five criteria within OECD’s Best Practice Identification Framework – Effectiveness, Efficiency, Equity, Evidence‑base and Extent of coverage (see Box 10.1 for a high-level assessment). Further details on the OECD Framework can be found in Annex A.
Effectiveness
Psychological distress and functioning improve over time for young people returning to @ease after a first visit. Positive changes over time are also observed for @ease returnees on the likelihood of receiving mental health support in the past three months, and on school absenteeism, although with less certainty. These findings only represent visitors coming back to the @ease centre and willing to complete the questionnaires and therefore not generalizable to all @ease users.
Efficiency
@ease relies mostly on voluntary work, which reduces the cost of the intervention.
Equity
@ease reaches young people in vulnerable circumstances, but to a limited extent. The analysis of visitor demographics shows that only a small share of young people who seek @ease are not in employment or education, in an unstable housing situation or of a gender minority.
Evidence‑base
Although @ease routinely monitors outcomes, the studies produced with these data face important limitations. These include the lack of a control group and (potentially) high levels of missing data and selection into monitoring which cannot be evaluated due to the lack of information for visitors who do not agree with data collection, happening post-intervention.
Extent of coverage
@ease succeeds in removing barriers on access to mental health support, covering a group of people with high distress and suicidal ideation, and who often did not receive formal mental health care in the recent past.
Effectiveness
The routine outcome monitoring of @ease includes measures of effectiveness covering domains such as psychological distress (CORE‑10), social and occupational functioning (SOFAS), previous school absenteeism and previous mental health support, suicidal ideation and planning, and quality of life (EQ‑5D‑5L; see Table 10.1 for details on the instruments). Evidence presented in this section comes mostly from the first outcome evaluation (Boonstra et al., 2024[16]). Changes in these domains could only be evaluated for the subgroup of young people with more than one visit: 168 out of the 754 visitors that filled questionnaires between January 2018 and December 2022. The exact size of this subgroup, designated as returnees in the remainder of the chapter, varies considerably for each outcome due to missing data. To note, the group of returnees was significantly older than one‑off visitors and had higher proportions of male and native visitors, visitors not living with their parents, visitors with parental mental health problems, and visitors not in education (Boonstra et al., 2024[16]).
Psychological distress and functioning improve over time for @ease returnees. Of the 95 returnees who completed the psychological distress assessments at both the first and last visit (only 56.6% of all 168 returnees), 43.2% improved their self-rated psychological distress to a better clinical CORE‑10 category, and 28.4% improved by decreasing 6 or more CORE‑10 points, indicating reliable change. These improvements occurred over a short period of time, as about half (49.1%) of those who completed the CORE‑10 questions had their last visit within six weeks after their first visit. Of the 91 returnees scoring above the CORE‑10 cut-off of 11 points, only 8.8% had a clinically significant change to a score below 11 points.
Peer-rated social and occupational functioning also improved over time. Based on the data from 53 returnees completing questionnaires at the first and last visits, 39.6% improved social and occupational functioning by at least one category (10+ points in SOFAS, considered a reliable change) and 28.0% had a clinically significant change, moving from below to above the cut-off of 69.
An increase over time was also observed in the proportion of returnees receiving mental health support from a school-based adviser, mentor, therapist, community worker or other professional: from 34% before the first visit (mean number of days with support 2.30), 49.7% before second visit (mean 3.13 days) and 60.4% before third visit (mean 4.96 days). Estimates obtained from mixed models on the odds of receiving mental health support confirmed statistically significant increases over time. This was not the case for school absenteeism, for which there was no statistically significant difference over time, although the proportion of returnees with at least one absence from school in the previous three months decreased from 43.8% before first visit (with mean of absent days 3.10 days), to 35.2% before second visit (3.04 days) and 16.7% before third visit (2.07 days) (Boonstra et al., 2024[16]).
For suicidal ideation and planning, trends over time do not depict a clear change. The proportion of returnees with suicidal ideation ranged from 29.9% after the first visit (out of 77) to 31.2% after the second visit (out of 93) and 24.4% after the third visit (out of 41). From the individuals with suicidal ideation, 43.5%, 39.3% and 20.0% had suicidal plans, respectively after each visit. Quality of life results are not available at this time, due to limited number of individuals assessed repeatedly. Overall, visitors reported high satisfaction with @ease (4.5 out of 5 on average; 59.8% very satisfied, 33.5% satisfied, 4.2% neutral and 2.5% not satisfied) (Boonstra et al., 2024[16]).
Importantly, the interpretation of findings about the effectiveness of @ease should be done with caution, due to at least three methodological limitations. First, such pre‑post comparisons without a control group cannot account for natural trends, shocks, or other factors that visitors may be exposed to during visits and which may drive changes over time rather than the intervention. It is also not possible to account for statistical artefacts such as regression to the mean. Therefore, any improvements described above might be solely a result of time passing, or other exposures to which visitors are subjected in between @ease visits. Second, the @ease effect may be underestimated, particularly in terms of psychological distress, due to the lack of a baseline measure prior to any intervention (instead, questionnaires were administered at the end of the @ease visits). Last, missing data resulting both from visitors not agreeing to the informed content and from peers’ incomplete responses, are likely to introduce selection bias into the findings, whose direction and magnitude are unknown. More recent data from 2023 suggest that 78% of the visitors completed the questionnaires, but there is no indication of such a proportion for visitors between 2018 and 2022. Some evidence is available on the effectiveness of other youth mental health initiatives (Box 10.2), although the differences between these interventions and @ease should be taken into account when comparing results.
Despite the large number of youth mental health care initiatives in place worldwide for several years, outcome analyses are scarce (Boonstra et al., 2023[14]) and it has not been possible to definitely conclude whether these initiatives are effective (Hetrick et al., 2017[19]). Lack of outcome evaluations has been justified by the lack of consensual measures on mental health in youth (Kwan and Rickwood, 2015[20]) and challenges to capture the broad scope of these interventions in youth development in a holistic manner (Filia et al., 2021[21]).
Most outcome evaluations were identified for headspace Australia and Jigsaw Ireland. Following a pre‑post design, these analyses measure increasing indicators of change over time.
headspace, Australia: The most recent evaluation included 58 233 young people accessing 108 headspace centres for the first time between 1 April 2019 to 30 March 2020 (Rickwood et al., 2023[22]). Between the first visit and the last data collection, 35.5% had significant improvements in psychological distress (Kessler‑10), 36.1% in social and occupational functioning (SOFAS score), 46.9% in self-reported quality of life (MyLifeTracker, a headspace co-developed measure), and 71.0% in any of the three outcomes. The respective proportions of visitors with clinically significant change were, 22.4%, 37.8%, 29.9% and 51.7%. These results were obtained based on less than half of the initial sample, corresponding to individuals for which at least two data points were available. The results are generally comparable to the outcomes reported in a previous study (Rickwood et al., 2015[23]). In both 2015 and 2023 studies, 90‑day follow-up data showed that distress scores further decreased with time, but the extremely low response rate at this time point (3.1% and 4%) advises for caution when interpreting follow-up results (Rickwood et al., 2023[22]; Rickwood et al., 2015[23]).
Jigsaw, Ireland: The outcome analysis focusses on psychological distress, measured by CORE‑10 and YP-CORE. On a study looking at 2 420 visitors between January and December 2013, 62% had a reliable and clinically significant improvement in their psychological distress measured by CORE‑10, and 68% of participants had a reliable improve in YP-CORE (O’Keeffe et al., 2015[24]).
Caution is required in comparing results above to @ease findings, because of different country contexts, the lack of a control group and most of all the differences in service models. headspace Australia and Jigsaw Ireland have a stronger medical focus than @ease and provide an enhanced blend of primary and specialised care. This could range from therapeutic approaches provided by trained practitioners (general counselling, cognitive behaviour therapy, acceptance and commitment therapy, among others) to support by multidisciplinary teams, while @ease support is provided by peers and follows mostly counselling-based techniques such as active listening and solution-focus techniques (O’Reilly et al., 2022[25]; Rickwood et al., 2023[22]).
Efficiency
@ease cost-effectiveness has not been studied.1 From a cost perspective, the intervention mostly relying on voluntary (unpaid) work of young peers (Leijdesdorff et al., 2022[13]) leads to a relatively small investment in workforce being needed. Based on the average @ease centre, workforce costs total about EUR 60 000 per year related to hiring a location manager for each centre, volunteer training and related activities. This corresponds to about 60% of the annual costs, which are complemented by rent and office related expenses (25%) and marketing (6%). Two particularities of the Dutch model are that each @ease centre contributes with an annual fee to the @ease central organisation (10%) for support provided at the national level in aspects such as strategy, marketing, IT and volunteer management; and that the costs of the healthcare professional and psychiatric care backup are covered by partner organisations of the initiative or voluntarily by the healthcare professional (representing an annual budget of approximately EUR 150 000).
Being based on peer’s voluntary work, the scale‑up of @ease may face fewer limitations related to workforce availability or funding. From the health system perspective, it is unclear whether @ease reduces the care utilisation: it might increase appointments with general practitioner (GP) or psychologist in a first instance, by lowering the barriers to seek care and identifying its need; it might also lower consumption of specialist services at a later stage by preventing acute and severe situations.
Equity
@ease reaches young people in vulnerable circumstances, but to a limited extent. The analysis of visitor demographics shows that a relatively small share of young people who seek @ease support were in vulnerable situations (Boonstra et al., 2024[16]):
@ease supported a considerable proportion of young people with at least one parent having mental health problems (32.8% for one‑time visitors and 41.3% for returnees). Among those having a mother with mental health problems, depressive disorder was the most reported by the visitor (53.8%), followed by anxiety disorder (9.9%). For fathers, most-reported disorders were also depressive disorders (36.7%), followed by addiction (16.3%) and trauma-related disorders (10.2%).
About 8% of the visitors (51 out of 611) were not in education or employment.
In terms of living situation, there were 18 visitors (2.9% out of 619) in a potentially vulnerable situation (e.g. homeless, “staying over”, assisted housing) plus 8 living with a caregiver and 9 in “other” situation.
Gender-wise, 2.4% of the visitors identified as non-binary, with the proportion being 4.6% among returnees.
Foreign-born individuals made up a large proportion of the visitors (41.3% of one‑time visitors and 36.9% returnees), but more than 85% of these come from European countries. The large group of users born in Europe results from @ease centres being primarily located in university cities and differs from the national demographics, in which most foreign-born young people have a non-western background.
Peer training materials are made available in Dutch but also in English, supporting the coverage of non-Dutch English speakers. Through the recent outreach initiative “Everybody @ease”, peer counsellors have been visiting neighbourhoods to reach young people where they reside, including those harder to reach. The existence of an online chat available at the national level, initiated during COVID‑19 and kept in function during @ease centres opening hours should also improve @ease impacts on equity for the most recent years of activity (Boonstra et al., 2024[16]). From June 2020 to December 2023 peers engaged in 5 657 online chat conversations with 3 309 individual visitors (monthly average of 132 chats with 77 unique individuals).
Evidence‑based
The evidence on the @ease intervention is mainly collected from the study by Boonstra et al. (Boonstra et al., 2024[16]). The routine outcome monitoring of @ease represents a core element of the initiative, and plans to use the data collected have been published early on, in the form of a protocol paper. However, the key weaknesses of the study by Boonstra et al. (2024) are the lack of a control group and of an accurate baseline characterisation of the visitors’ clinical outcome. Following the advice by a youth panel, the data collection questionnaire and corresponding informed consent are only presented to the visitor at the end of each @ease visit. This means that there is no data collection prior to the intervention (at baseline). There is also a lack of information on the number and characteristics of visitors who did not consent to data collection, and the data collected is incomplete, including on outcomes evaluated by the peer following the visit. In fact, the number of visitors with information on functioning, which is rated by the peer, is lower than visitors with information on psychological distress, which is self-reported. The lack of data prevents the accurate assessment of selection bias, confounders and withdrawals and dropouts. Additionally, from an intervention perspective, the lack of data from past visits hinders the continuity of care. This is particularly important given that the peers who provide support often change between visits.
The Quality Assessment Tool for Quantitative Studies assesses the quality of evidence as strong in the domain of “Data collection methods”, moderate in “Study Design”, and weak in “Selection Bias”, “Confounders”, “Blinding” and “Withdrawals and Dropouts” (see Table 10.2) (Effective Public Health Practice Project, 1998[26]).
Source: Effective Public Health Practice Project (1998[26]) “Quality assessment tool for quantitative studies”, https://www.nccmt.ca/knowledge-repositories/search/14; Boonstra et al. (2024[16]), “Evaluating changes in functioning and psychological distress in visitors of the @ease youth mental health walk-in centres”, https://doi.org/10.1192/bjo.2024.58.
Extent of coverage
@ease succeeds in removing barriers on access to mental health support, covering a group of young people who have clinical symptoms of mental ill-health and/or suicidal ideation and have mostly not received mental health support in the past three months. Data collected after the first visit show that 90.7% of visitors and 97.1% of returnees had clinically significant psychological distress. Visitors also had moderate impairment in social functioning. Two-thirds of visitors had not received mental health support in the past three months. This was also the case among those with clinical levels of psychological distress (71.1% of one‑time visitors and 64.1% of returnees) which would possibly have continued undetected if not visiting @ease. More than a quarter of visitors (27.6% out of 481) were rated by peers as having suicidal ideations, and the majority of these did not previously seek for support or treatment (65.5% of one‑time visitors and 57.1% of returnees with suicidal ideation) (Boonstra et al., 2024[16]).
Visitors tend to freely access @ease centres without barriers. Two-thirds of the visitors between 2018 and 2020 came into the centre by walking in, without an appointment (Leijdesdorff et al., 2022[13]). In terms of the intensity of support provided, 586 out of the 754 (77.7%) respondents visited once, 109 visited twice and 59 visited three times or more (168 returnees in total, 22.3%). The average number of visits was 1.65 for all visitors (standard error (s.e.) 0.15) and 3.90 (s.e. 0.66) for returnees; second and third visits happened on average 12 weeks and 17 weeks after the first one (Boonstra et al., 2024[16]).
The geographic coverage of @ease has been expanded across the Netherlands, with centres in Maastricht, Amsterdam, Heerlen, Rotterdam, Groningen, Leiden, Leeuwarden, Zwolle, Haarlem, Roermond, Eindhoven and Apeldoorn. However, @ease centres are mostly located in urban environments, which might make it difficult to access for youth living in rural areas – although the country benefits from a good public transportation system. Furthermore, each @ease centre opens only a few afternoons a week, and the support is therefore not immediately available at all times for young people in need or at the moment they decide to seek for care.
However, as with the other domains of the framework assessment, the evaluation of coverage is constrained by the lack of data regarding the actual number of @ease visitors. This is because there is no count of those who did not want to complete the questionnaire.
Enhancing effectiveness
Expanding the design of @ease to include better links with mental health services and promote integrated care. A stronger emphasis on integrated care could be achieved by dedicated referral pathways for non-crisis visitors or the adoption of the one‑stop shop format used in other youth mental health initiatives (Hetrick et al., 2017[19]), particularly with regards to linking youth support services provided by municipalities or work and education support services. In headspace Denmark, for example, there are “seconded” municipality employees at the headspace centres, promoting integration with municipal services (headspace, n.d.[27]). An even simpler approach would be to create guidance for the peers on the systematic provision of information on support available in the Dutch health and social care systems. Reinforcing the links with the mental health care system is particularly relevant for two subgroups of @ease visitors: young people with severe symptoms and those at the transition to adulthood. Among @ease visitors, there is a cohort of young people with severe and complex mental conditions and potentially not accompanied anywhere else. While this is a positive result of efforts to remove barriers in access to care by @ease, it also represents a challenge to ensure that this group of young people receive appropriate support beyond peer-led appointments (McGorry et al., 2022[28]). Evidence from other countries’ youth care initiatives suggests that those with more severe symptoms and higher functional impairment respond less to the support received, potentially requiring more intensive expert care (Hetrick et al., 2017[19]). Furthermore, young adults around 18 years old are often caught in the transitional gap between children and adolescent mental health services (CHAMS) and adult mental health services (AMHS). In fact, one main objective of other (integrated primary) youth mental health care initiatives has been to shift the upper boundary of youth mental health care from age 18 to 25. @ease is also well-placed to play an important role in preventing young adults from falling through the system cracks.
Increasing continuity in @ease support. By design, @ease intervention is freely accessible, meaning that the visitor decides if and when to return to @ease. Such design was selected to match young people preferences and to overcome barriers that apply to traditional services (Boonstra et al., 2023[14]). However, this approach may prevent continuous engagement, potentially leading to lost opportunities for further benefit from @ease visitors. There are options to nudge visitors into continuous support while still empowering them to own and decide about their support journeys. For instance, in cases of high visitor satisfaction and need for additional care, the peers could immediately suggest an appointment for a follow-up visit. Follow-up with the same peer should also be prioritised to ensure the build-up of a therapeutic relationship which is likely to improve outcomes.
Enforcing more consistent data collection. This would be beneficial in informing subsequent interactions with the returnees, which are often conducted by different peers, and in monitoring the intervention effectiveness. It is recommended that efforts are made to reduce the non-response rate and increase the completeness of the questionnaire responses. This should be done both with visitors and peers.2 Peers could be provided with (non-)financial incentives for data collection. Visitors could be presented with information justifying the need for data collection and explained the relevance of this information. The timing of data collection could also be revisited to allow a proper characterisation of the baseline, at least for the first visit (see Enhancing the evidence‑base).
Enhancing efficiency
Ensuring that peers deliver maximum value in their ways of working is key to increase @ease cost-effectiveness, for example in terms of better data collection. Peer incentives can be either financial or non-financial (such as guidelines or standards).
Enhancing equity
Increasing the proportion of traditionally underserved populations reaching to @ease. These population groups include, for example, youth not in employment, education or training (NEET) or in instable housing situations, from the LGBTQI+ community or from low socio-economic groups or minoritised ethnicities. These groups are traditionally harder to reach by traditional services, but youth mental health initiatives in other countries have been successful in doing so (Hetrick et al., 2017[19]). To increase the representation of these groups, @ease should invest in dissemination among the respective social circles and active recruitment of peers that can act as ambassadors, as well as peers with cultural and linguistically diverse backgrounds. In further expansions of @ease, priority should be given to opening new centres in socially disadvantaged neighbourhoods and/or rural areas and investing in alternative channels such as promoting the online chat to reach out to underrepresented groups that may face barriers such as stigma, costs and time of transportation. For instance, telephone and online appointments are used in other youth mental health care initiatives (McGorry et al., 2022[28]).
Enhancing the evidence‑base
Enhance data collection. The evaluation of @ease is limited due to missing data on visitors, which raises concerns about the internal and external validity of the results, and prevents the generalizability of the findings. A minimum set of variables should be collected for all individuals (e.g. gender, age, country of birth), allowing a better characterisation of non-respondents. For young people who consent to have their data collected, there should be a focus on increasing the proportion of questions responded, namely the peer-rated information which does not depend on the visitor. Data collection should be reinforced as part of peers training and strongly enforced by the local manager and on-site healthcare practitioner. Incentivising peers might also be a solution to improve the completeness of the data reported.
Revisiting the timing of data collection. Visitors are currently only requested to complete a questionnaire at the end of the @ease visit. Unfortunately, this restricts the ability to conduct baseline characterisation (which measures the situation before the intervention) and introduces inaccuracies into routine outcome monitoring, in particular for psychological distress. For instance, data on psychological distress could be collected at the beginning of the conversation and presented as relevant to inform the advice. For visitors who decline to provide data at the beginning of the visit, the peer should provide detailed information on data privacy and the relevance of the data collection after the visit. This should be followed by an opportunity for visitors to re‑consider their decision. For those providing information prior to the visit, the peer would enquire about their availability to complete additional information after the conversation (e.g. satisfaction with @ease).
Conducting a randomised experiment with a control group. It might be worth revisiting the moral concerns surrounding the randomisation of young people in need of care in the context of resource scarcity. This is particularly relevant when considering the equally important ethical implications of investing in interventions without a strong evidence basis (Kisely and Looi, 2022[29]). The experiment could make use of an active control group that would either receive standard-of-care or an alternative option (e.g. digital self-help tools). Alternatively, statistical methods and econometric tools exist to allow for causal inference in observational settings (e.g. matching method). The use of quasi‑experimental designs could be considered in further expansion of @ease, by following a staggered implementation and/or taking advantage of secondary data, for example the microdata infrastructure of Statistics Netherlands. Linking current research to administrative data would allow measuring long-term outcomes in health, education and labour market participation. These outcomes are highly relevant for the estimation of @ease benefits and cost-effectiveness, particularly given the large proportion of university students using the programme.
Enhancing extent of coverage
Investing in sustained mental health support through @ease. While @ease is designed with a high degree of flexibility, the high proportion of visitors who are both satisfied and in clinical need after the first visit indicate the need for active efforts to increase the return rate. To achieve this, peers could present the benefits of continued support during the conversation and immediately schedule a follow-up appointment after the visit. There is potential for an expansion in the number of opening days, opening hours and channels available for remote follow-up (online, telephone, video) (Hetrick et al., 2017[19]; O’Reilly et al., 2022[25]).
This section explores the transferability of @ease and includes three components: 1) an examination of previous transfers; 2) a transferability assessment using publicly available data; and 3) additional considerations for policymakers interested in transferring @ease.
Previous transfers
Several youth mental health care initiatives have been implemented worldwide in the last 20 years. Among these, some initiatives feature youth participation as a key aspect in their service models. Several care networks (Foundry, ACCESS Open Minds and ICCT in Canada and New Zealand Youth One Stop Shop and single centres (The Junction in the United Kingdom, CHAT in Singapore, SPOT in US, and KYDS Youth Development Service in Australia) have been described as offering peer support to visitors (Hetrick et al., 2017[19]). Most initiatives include peers as an additional form of care provision. It is less common for these initiatives to strongly rely on peer-delivered care, as @ease. Only headspace Denmark, started in 2013, has been identified with a similar design (McGorry et al., 2022[28]), having its centres run by peers: a small group of paid youth counsellors helped by volunteers of all ages and supported by a local manager and often a municipality worker and psychiatry practitioner as well (headspace, n.d.[27]).
Transferability assessment
This section outlines the methodological framework to assess transferability followed by analysis results.
Methodological framework
A few indicators to assess the transferability of @ease were identified (see Table 10.3). Indicators were drawn from international databases and surveys to maximise coverage across OECD and non-OECD European countries. Please note, the assessment is intentionally high level given the availability of public data covering OECD and non-OECD European countries.
Results
The main findings of the transferability assessment are summarised below. Due to 50% or more of the indicators missing, five countries were removed from the analysis.
a) In the Netherlands, the share of individuals volunteering time to an organisation in the past month is 32%, in the highest quartile of the distribution of OECD and EU countries studied. This suggests that the Dutch population is more used to engage in volunteering than most countries being considered for @ease transfer.
b) The number of psychologists per 1 000 population in the Netherlands (0.94) is higher than for most of OECD and EU countries with data (median 0.43). In eight countries with lower number of psychologists, the higher number of mental health nurses can compensate for the practitioners needed to implement @ease.
c) The Netherlands reported that talking therapy is provided by “some” primary care providers, while only Estonia and Norway responded “all”. Widespread psychological support in primary care might favour @ease implementation and co‑ordination with the mental health care system.
d) The Netherlands did not provide information on having a strategy or action plan to guide the implementation of mental health policy. However, the positive answer of the vast majority of countries (90%) suggests that implementing @ease would benefit from existing infrastructure and experience.
e) Most countries (90%) do also have policies and programmes to support and promote the mental health of children and adolescents, including the Netherlands. The implementation of @ease can benefit from the prioritisation of this policy area in most countries.
f) As six other countries, the Netherlands does not have policies and programmes to enable mental health promotion, prevention and treatment of mental health conditions in primary healthcare. For the countries with such programmes, the implementation of @ease might be facilitated but it is also important to align its objectives and adapt to other existing initiatives with similar goals.
g) The Netherlands allocates 0.58% of its GDP to prevention, which is above the median of the countries studied (0.40%). Countries with a higher spending on prevention are more likely to have economic support for the transfer of @ease.
A darker shade indicates @ease is more suitable for transferral in that particular country
Note: n/a = no available data. The shades of blue represent the distance each country is from the country in which the intervention currently operates, with a darker shade indicating greater transfer potential based on that particular indicator (see Annex A for further methodological details). The full names and details of the indicator can be found in Table 10.3.
Source: Gallup (2023[30]), Share of individuals volunteering time to an organization in the past month (%); OECD (2021[31]), A New Benchmark for Mental Health Systems: Tackling the Social and Economic Costs of Mental Ill-Health, https://doi.org/10.1787/4ed890f6-en; OECD/WHO Regional Office for Europe (2023[32]), Mental Health Systems Capacity Questionnaire 2023 - Strategy or action plan that guide implementation of the mental health policy; OECD/WHO Regional Office for Europe (2023[33]), Mental Health Systems Capacity Questionnaire 2023 - Policies and programmes to support and promote mental health of children and adolescents; OECD/WHO Regional Office for Europe (2023[34]), Mental Health Systems Capacity Questionnaire 2023 - Policies and programmes to enable mental health promotion, prevention and treatment of mental health conditions in primary health care; OECD (2024[35]), OECD Data Explorer - Prevention spending as a percentage of GDP, http://data-explorer.oecd.org/s/1nl.
To help consolidate findings from the transferability assessment above, countries have been clustered into three groups, based on indicators reported in Table 10.3. Countries in clusters with more positive values have the greatest transfer potential. While this analysis provides a high-level overview assuming some simplifications, it is important to note that countries in lower-scoring clusters may also have the capacity to adopt the intervention successfully. For further details on the methodological approach used, please refer to Annex A. Key findings from each of the clusters are below with further details in Figure 10.1 and Table 10.5:
Countries in cluster one have population, sector, political, and economic conditions in place that would support the introduction of @ease. This cluster consists of 14 countries.
Countries in cluster two have population, sector-specific and economic indicators favourable to the implementation of @ease, although these countries may wish to consider ensuring that the implementation aligns with political priorities. This cluster consists of four countries, including the Netherlands.
Countries in the remaining cluster may wish to undertake further analyses to ensure the programme has populational, sector-specific and economic arrangements to support its implementation. This group includes 20 countries.
Note: Bar charts show percentage difference between cluster mean and dataset mean, for each indicator.
Source: OECD analysis.
Note: Due to high levels of missing data, the following countries were omitted from the analysis: Bulgaria, Croatia, Cyprus, Malta, and Romania.
Source: OECD analysis.
New indicators to assess transferability
Data from publicly available datasets alone are not ideal to assess the transferability of public health interventions. Box 10.3 outlines several new indicators policymakers could consider before transferring @ease.
In addition to the indicators within the transferability assessment, policymakers are encouraged to collect information for the following indicators:
Population context
What is the level of stigma about mental health conditions in the population and amongst youth?
Sector specific context
What is the performance of the Children and Adolescents Mental Health services (CAMHS): ratio of psychologists per capita, waiting lists, transition to Adult Mental Health services (AMHS)?
Is access to CAMHS referred by general practitioners?
Is youth mental health support provided in primary care and by whom (e.g. general practitioners or dedicated professionals such as mental health nurses and psychologists)?
What is the country’s reliance on charities, community groups and NGOs for youth mental health support and youth support more broadly?
Political context
Do municipalities or other local structures have any responsibility in providing support to youth mental health?
Economic context
Are there dedicated funds to implement initiatives to prevent mental ill-health in youth, either at the local or at national level?
@ease provides peer-based low-barrier support to young people walking-in or with an appointment at @ease centres, anonymously, at no cost and without referral. Support is provided in non-clinical settings by volunteer young adult peers trained in active listening, solution-focussed strategies and motivational interviewing, and supervised by an on-site health professional.
@ease may improve the psychological distress and functioning in young people returning after the first visit, but definitive conclusions about effectiveness have so far been hampered by the lack of a control group and the small number of visitors with outcome information. Existing evidence suggests that @ease returnees improve over time in terms of psychological distress, social and occupational functioning, and potentially school absenteeism in the last three months. Returnees also appear to increase their use of mental health support between the first, the second and the third visits. Given the high proportion of visitors in clinical need and satisfied with the support received, the effectiveness of @ease could be maximised by increasing the continuity of support and promoting a therapeutic relationship between the peer and the visitor. The current @ease working method could also be extended to better support integration of care, facilitating visitors’ access to either social services or mental health care.
@ease covers a group of young people with considerable clinical needs, often with suicidal ideation and who have mostly not received mental health support in the recent past. Expanding the opening hours of @ease centres and channels to provide support (e.g. online, videoconference) as well as increasing the return rate would maximise the current extent of coverage. Additional efforts are needed to reach to traditionally underserved groups, such as gender and sexual minorities, minority ethnic groups or those with low socio-economic status.
Better data collection is essential to produce @ease results. This includes increasing the proportion of young people consenting to data collection and increasing questionnaire completeness, in particular peer-reported data. The provision of (non-)financial incentives might be a tool to achieve the latter objective. Conducting a controlled study to evaluate the effectiveness of @ease and complementing it with an economic evaluation will allow for a more accurate picture of the potential cost-effectiveness of @ease. The use of volunteer peers, which result in low workforce costs, will also be a key factor in the programme’s evaluation.
@ease transferability analysis suggests that the initiative would mostly find positive conditions for a transfer in 18 countries. For the remaining 20 countries, additional analyses would be needed to ensure that population, sector-specific and economic arrangement are in place to support the transfer.
Box 10.4 outlines next steps for policymakers and funding agencies.
Next steps for policymakers and funding agencies to enhance @ease are listed below:
Improve the return rate of users and the continuity of support through incentivising follow-up appointments, expanding @ease centres opening hours and using alternative communication channels.
Expand the scope of @ease to promote integration of care and to support youth in further accessing mental health care and social services, particularly at the transition to adulthood (when there are coverage gaps).
Improve the data collected through routine outcome monitoring both by increasing the number of young people who consent to data collection and by increasing the completeness of the data, such as peer-reported variables.
Conduct a controlled study, preferably with randomisation by using an active control group, and a cost-effectiveness study.
Implement mechanisms to minimise the risk of fidelity loss while quickly scaling @ease through the opening of centres across the Netherlands.
Improve the ability of @ease to attract and support traditionally underserved groups, such as gender and sexual minorities, minority ethnic groups or those with low socio-economic status.
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← 1. In fact, anecdotal evidence provided by the @ease research team suggests that refusal to complete the questionnaire by the visitors is low and a part of the visitors without data might be due to peers not administering the questionnaire (and respective consent).