Open Dialogue services around the world : a scoping survey exploring organizational characteristics in the implementation of the Open Dialogue approach in mental health services

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Open Dialogue services around the world : a scoping survey exploring organizational characteristics in the implementation of the Open Dialogue approach in mental health services © 2023 the Authors Published version Pocobello, Raffaella; Camilli, Francesca; Alvarez-Monjaras, Mauricio; Bergström, Tomi; von Peter, Sebastian; Hopfenbeck, Mark; Aderhold, Volkmar; Pilling, Stephen; Seikkula, Jaakko; el Sehity, Tarek Josef Pocobello, R., Camilli, F., Alvarez-Monjaras, M., Bergström, T., von Peter, S., Hopfenbeck, M., Aderhold, V., Pilling, S., Seikkula, J., & el Sehity, T. J. (2023). Open Dialogue services around the world : a scoping survey exploring organizational characteristics in the implementation of the Open Dialogue approach in mental health services. Frontiers in Psychology, 14, Article 1241936. https://doi.org/10.3389/fpsyg.2023.1241936 2023 Frontiers in Psychology 01 frontiersin.org Open Dialogue services around the world: a scoping survey exploring organizational characteristics in the implementation of the Open Dialogue approach in mental health services RaffaellaPocobello 1 *, FrancescaCamilli 1, MauricioAlvarez-Monjaras 2, TomiBergström 3,4, SebastianvonPeter 5, MarkHopfenbeck 6, VolkmarAderhold 7, StephenPilling 2, JaakkoSeikkula 3,8 and TarekJosefelSehity 1,9* 1 Institute of Cognitive Sciences and Technologies, CNR, Rome, Italy, 2 Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom, 3 Department of Psychology, University of Jyväskylä, Jyväskylä, Finland, 4 Department of Psychiatry, Länsi-Pohja Hospital District, Kemi, Finland, 5 Brandenburg Medical School Theodor Fontane, Brandenburg an der Havel, Germany, 6 Department of Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway, 7 Independent Researcher, Hamburg, Germany, 8 Department of Psychology, University of Agder: Kristiansand, Kristiansand, Norway, 9 Faculty of Psychology, Sigmund Freud Private University, Vienna, Austria Objective: This cross-sectional study investigates the characteristics and practices of mental health care services implementing Open Dialogue (OD) globally. Methods: A structured questionnaire including a self-assessment scale to measure teams’ adherence to Open Dialogue principles was developed. Data were collected from OD teams in various countries. Confirmatory Composite Analysis was employed to assess the validity and reliability of the OD selfassessment measurement. Partial Least Square multiple regression analysis was used to explore characteristics and practices which represent facilitating and hindering factors in OD implementation. Results: The survey revealed steady growth in the number of OD services worldwide, with 142 teams across 24 countries by 2022, primarily located in Europe. Referrals predominantly came from general practitioners, hospitals, and self-referrals. A wide range of diagnostic profiles was treated with OD, with psychotic disorders being the most common. OD teams comprised professionals from diverse backgrounds with varying levels of OD training. Factors positively associated with OD self-assessment included a high percentage of staff with OD training, periodic supervisions, research capacity, multi-professional teams, self-referrals, outpatient services, younger client groups, and the involvement of experts by experience in periodic supervision. Conclusion: The findings provide valuable insights into the characteristics and practices of OD teams globally, highlighting the need for increased training opportunities, supervision, and research engagement. Future research should follow the development of OD implementation over time, complement selfassessment with rigorous observations and external evaluations, focus on involving different stakeholders in the OD-self-assessment and investigate the long-term outcomes of OD in different contexts. OPEN ACCESS EDITED BY Antonio Iudici, University of Padua, Italy REVIEWED BY Dominik Havsteen-Franklin, Brunel University London, UnitedKingdom Dorothea Jäckel, Charité University Medicine Berlin, Germany *CORRESPONDENCE Raffaella Pocobello [email protected].it Tarek Josef el Sehity Tarek.el-[email protected] RECEIVED 17 June 2023 ACCEPTED 28 September 2023 PUBLISHED 10 November 2023 CITATION Pocobello R, Camilli F, Alvarez-Monjaras M, Bergström T, von Peter S, Hopfenbeck M, Aderhold V, Pilling S, Seikkula J and el Sehity TJ (2023) Open Dialogue services around the world: a scoping survey exploring organizational characteristics in the implementation of the Open Dialogue approach in mental health services. Front. Psychol. 14:1241936. doi: 10.3389/fpsyg.2023.1241936 COPYRIGHT © 2023 Pocobello, Camilli, Alvarez-Monjaras, Bergström, von Peter, Hopfenbeck, Aderhold, Pilling, Seikkula and el Sehity. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Original Research PUBLISHED 10 November 2023 DOI 10.3389/fpsyg.2023.1241936 Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 02 frontiersin.org KEYWORDS Open Dialogue, mental health services, self-assessment, peer support, scoping survey, implementation, mental health training, global survey 1. Introduction Finding its roots in Need-Adapted Treatment (Alanen et al., 1991; Alanen, 1997), OD emerged as an innovative approach within the Finnish Western Lapland mental health services during the 1980s and 1990s. Seven principles became evident during the first research programs and psychotherapy training: (1) immediate help, (2) a social network perspective, (3) flexibility and mobility, (4) responsibility, (5) psychological continuity, (6) tolerance of uncertainty, and (7) dialogism (Seikkula etal., 2001). The first five principles regard the organizational logistics in which mental health services are provided, while the last two refer to the dialogic practice in which mental health professionals engage during network meetings with clients (Seikkula etal., 2003). Since the 1990s, positive outcomes associated with OD have been documented in Western Lapland (Seikkula etal., 2006). Researchers observed that 82% of patients experiencing acute psychosis following the OD treatment showed no symptoms at the 5-years follow-up. Moreover, 86% of the patients had returned to a full-time job or studies, whereas only 14% were on disability allowance. Encouraging results were also observed during the following decade. A follow-up study confirmed that more than 80% of patients treated with the OD approach were fully employed or engaged in their studies after 2 years (Seikkula etal., 2011). Moreover, the study highlighted a cultural change in the use of the mental health service that led to earlier initiation of treatment, with a shorter duration of untreated psychosis and patients’ first contact happening at a lower age. Findings from a nineteen–year outcomes study indicated that many positive outcomes documented in previous studies are sustained over a long period (Bergström etal., 2018, 2022). By 2011, OD was “well-established” in Western Lapland but still “little-known elsewhere” (Thomas, 2011). However, in the following decade, the approach started to beapplied globally in different contexts and with disparate results. A review which focused on OD implementation in Scandinavia outside of Finland highlighted a significant variety of OD applications that, according to the authors, could be related to the intentional lack of operationalization of the OD principles (Buus etal., 2017). Other authors suggested that the different integrations of the OD approach into clinical practice may depend on the double challenge of introducing a transformation at the individual and the service level (Freeman etal., 2019). Notwithstanding the heterogeneous panorama of OD applications, the approach has been investigated mainly using a naturalistic research design. The first randomized controlled trial on OD, evaluating the approach’s clinical and cost-effectiveness, was launched in the UK in 2017. The trial is part of the ODDESSI (Open Dialogue: Development and Evaluation of a Social Network Intervention for Severe Mental Illness) research program and compares OD against standard treatment in six mental health services in the UK. Results are expected in 2024 (Pilling etal., 2022). Overall, the gradual implementation of OD into mental health services has not been described in detail, not even in Finland, despite the breadth of studies reporting on the origin of the approach (Buus et al., 2021). Research focusing on the implementation obstacles has been very scarce for many years, with one study describing organizational challenges observed among the nursing staff in Finland (Haarakangas etal., 2007) and a case study reporting the difficulties of an outreach team practising OD in Denmark (Søndergaard, 2009). More recent research (Gordon etal., 2016; Heumann etal., 2023; Skourteli etal., 2023) highlighted organizational and ideological barriers such as lack of time and resources, rigid professional hierarchy and the burden of working across two different models at the same time (Dawson etal., 2021; von Peter etal., 2023). Although these qualitative studies suggest some adaptation strategies, more global and quantitative research on the implementation of the OD approach is still needed. Moreover, the fact that the OD approach has not gone through the process of manualisation – that is, the development of a procedure that can bereplicated with sufficient uniformity (Waters etal., 2021) poses additional challenges, especially in assessing OD-fidelity. A measure called COMFIDE (Alvarez Monjaras, 2019; Alvarez- Monjaras etal., 2023) was developed as part of the ODDESSI trial to evaluate a good standard of care for community mental health services providing OD and standard crisis and community care. Although more research on OD-fidelity is needed to identify specific and measurable elements (Waters etal., 2021), items and topics from the COMFIDE scale may currently beused for fidelity assessments at a global level. Different approaches to implement Peer supported Open Dialogue (POD), connecting social and professional networks, have also been described in the last years (Razzaque and Stockmann, 2016; Kemp etal., 2020; Lorenz-Artz etal., 2023). Bellingham etal. (2018) reported that several models of POD had been embedded into clinical practice. In some cases, peer supporters may have a role very similar to that of professional therapists, whereas, in others, they have more limited space. For example, persons with lived experience may not participate in network meetings but beinvolved as supporters of the community. In other models, they may participate in the network meetings but not attend the reflection spaces addressed only to the clinicians (Bellingham etal., 2018). Due to the heterogeneity of models and scarcity of research on peer workers, a more comprehensive investigation is needed in this area (Kemp etal., 2020). Pivotal elements in the development of OD services are training, supervision and intervision which need to be“carefully planned” and considered an integral part of the approach (Buus etal., 2017) – intervision is hereby a form of colleague-based supervision practised in Peer-Supported Open Dialogue (see Razzaque, 2019). In Western Lapland, the training of the staff members was one of the three central components of the Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 03 frontiersin.org community psychiatric system (Alakare and Seikkula, 2021), together with the “Family and Team-centeredness” and the research project (Seikkula etal., 2011). Training activities cover theory, supervision, and seminars in which participants are required to analyze their background and family of origin. Experiences of training from different countries, including Norway, the US, the UK, Australia and Italy, have been reported in the literature (Hopfenbeck, 2015; Aderhold and Borst, 2016; Buus etal., 2017; Cubellis, 2020; Florence etal., 2020; Hopper etal., 2020; Jacobsen etal., 2021; Schubert etal., 2021; Pocobello, 2021b). Intervision, intended as a form of colleague-based supervision, and training, including “intentional peer support,” are also part of the activities for peer workers (Hopfenbeck, 2015; Razzaque and Stockmann, 2016; Razzaque, 2019; Hopper etal., 2020). As far as weknow, there has been no global investigation on the extent of training and supervision practices in OD services worldwide. Quantitative data on how many people involved in OD services have completed or are completing the training are unavailable. Moreover, the frequency and type of supervision have not been explored so far. Overall, the requirements for and barriers to the implementation of OD on both the level of organizational structures and staff competencies need to beaddressed in research and require a deeper investigation (Mosse etal., 2023). The present scoping survey was designed to map and explore the existing evidence about the implementation of OD-services globally (Pocobello, 2021a) and to investigate the impact of factors such as OD-training, supervision, research, the involvement of experts by experience and organizational characteristics on services’ OD-self-assessment (OD-SA). In this context, the term “expert by experience” refers to an individual who has/had personal, lived experience with mental health challenges or the mental health care system. This term acknowledges that individuals who have gone through these experiences possess a unique and valuable perspective that can contribute significantly to the improvement of mental health services, policies, and practices (Gupta etal., 2023). The objectives of the global scoping survey can besummarized as follows: a. To describe services practising Open Dialogue around the globe; b. To pilot testing and validating an Open Dialogue Service Survey Scale including an OD- self-assessment (OD-SA) scale; c. To construct an exploratory model of the organizational predictors of OD self-assessment; d. To provide a measure of teams’ degree of self-assessed adherence to the seven OD principles and e. To identify services ready for outcome evaluation studies. The study is part of the project HOPEnDialogue, 1 financed by the Open Excellence Foundation, which aims at investigating the implementation and effectiveness of Open Dialogue in different mental health care contexts around the world. 1 https://www.hopendialogue.net/ 2. Methods The study is reported according to the CROSS Checklist for Reporting Survey Studies (Sharma et al., 2021) to ensure rigor and credibility. 2.1. Study design We used a cross-sectional study design to collect data from multiple teams providing OD services in mental health care across different countries. The study design involved (1) the development and validation of a OD-self-assessment scale and (2) a quantitatively structured questionnaires to gather information on various aspects of OD services, including their structural characteristics, personnel OD-trainings, as well as practices regarding supervisions, involvement of experts by experience, and research activities. 2.2. Ethical clearance All respondents to the survey have completed an informed consent form embedded in the first page of the questionnaire. A skiplogic survey method was in place in the online form to ensure no collecting of information from respondents who disagreed with the informed consent question. Respondents were informed about the possibility of withdrawing from the survey at any time. Respondents could leave questions not answered. The survey was not anonymous, since the address of the service and personal contact information of the professional completing the survey on behalf of the OD team was used to check for accuracy and prevent multiple participation. Confidentiality was guaranteed by limiting access to this information to the research team of the ISTC-CNR and saving electronic data on passwordprotected computers. Ethical clearance with authorization value was not necessary for this study. 2.3. Respondents Team members of OD-services with leadership responsibility were invited to complete the survey on behalf of the entire facility or OD-team. Individual OD practitioners were excluded. As the survey is part of the project HOPEnDialogue, it was advertised and primarily distributed through its website Members of the HOPEnDialogue advisory board helped disseminate the survey in their different countries and networks through social media and mailing lists. Wehave contacted professionals from countries not represented on the board to ask for their support in spreading the survey at a national or local level. The first round of data was collected online using the Survey Monkey platform from January to September 2020. In total, 136 questionnaires were filled out online. The data were exported into Excel. The second round of data collection happened from January 2021 to February 2022 and involved six teams just concluding their foundation training. The questionnaires were filled and sent as PDFs to RP and FC, who added them to the Excel data set. The reason for this late recruitment was related to our intention to Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 04 frontiersin.org include all the services contacting us to have as much as possible comprehensive view of OD implementation globally. In total, 142 services participated in the survey. 2.4. Data diagnostics Data was checked and controlled for consistency. Where available and possible, missing data were completed by checking back with survey responders via email. Of the 142 questionnaires received during the data collection period, the data of 24 OD-services had to beexcluded due to incomplete datasets, mainly from the 6th item (clients’ characteristics served in the center) onwards. Often, the unavailability of informants made it impossible to assist in completing the missing questionnaire sections. Weundertook a missing data diagnosis on the data from the remaining 118 centers and did not detect systematic patterns (checking summary statistics for variables, counting the number of missing and non-missing values for each variable, correlations to examine if the missingness in one variable is associated with another variable). 2.5. Data analysis strategy To evaluate the statistical validity and reliability of the measurement model of the OD-self-assessment (OD-SA) scale, non-parametric Confirmatory Composite Analysis (CCA; Dijkstra and Henseler, 2011; Schuberth et al., 2018) was calculated with SmartPLS 4 ® (Ringle etal., 2022). Wefollowed the procedural steps for CCA outlined by Hair etal. (2020). The reliability of the variables was tested using Cronbach’s Alpha and Composite Reliability (ρA). Descriptive data of the survey have been checked for consistency in Excel spreadsheets and transferred to SPSS® 27.0 (IBM Corp, 2020) for the descriptive and explorative Cluster analysis. For the descriptive analysis Continuous variables were described using means (M) and standard deviation (SD); for discrete count variables, proportions were reported. The Shapiro–Wilk test was used to assess the normal distribution of continuous variables. As a non-parametric test for differences in group value of ps Kruskal-Wallis’ test was used. Association between structural aspects of OD-services was assessed using Loglinear modeling when it concerned the frequency of categorical data (see structural characteristics). The significance level was determined as p < 0.05 for all analyses. For the explorative data analysis bivariate non-parametric correlations were computed between the services OD-SA score and the descriptor variables to identify significant associations. • To explore structural characteristics of the MHS in which OD-teams emerged and operated, an unsaturated model was chosen using SPSS Statistics’ hierarchical loglinear model selection process with a backwards elimination stepwise procedure; • To explore professional taxonomies in OD-services hierarchical cluster analysis was used; Provided the sample size of n = 118 teams, the number of clusters was estimated to range between n/30 = 4 and n/60 = 2. To identify equally sized clusters, hierarchical cluster analysis with Ward’s method was used. Count values per variable of the eight professional profiles was standardized to correct for important differences in the counts of personnel in teams. A chi-squared measure of distance was used as a similarity measure; • A Kruskal-Wallis’ test was calculated to test for significant differences between the OD-teams belonging to different professional clusters. Visual inspection of boxplots was used to assess the similarity of the distributions of OD-SA scores (OD-SA 15) of groups/clusters. Pairwise comparisons were performed using Dunn’s (1961) procedure with a Bonferroni correction for multiple comparisons. Adjusted value of ps are presented. Finally, partial least squares (PLS) regression analysis was conducted to explain the variance of OD-Teams self-assessment scores based on teams- and their services’ characteristics. PLS regression, is a statistical method used in the presence of many predictor variables which may be highly correlated. It is especially useful when the number of predictor variables is larger than the number of observations, a situation where traditional regression methods like ordinary least squares (OLS) struggle (Hair etal., 2018). The Breusch-Pagan test was used to assess Heteroskedasticity; the PLS algorithm was set to heteroskedasticity consistent standard errors (HC3) to handle the distribution in case of a positive Breusch-Pagan test. HC3 correction calculates robust standard errors that take into consideration the potential heteroskedasticity in the data. It provides more accurate standard errors that are less affected by the presence of heteroskedasticity. This, in turn, ensures that hypothesis tests and confidence intervals derived from the regression analysis are more reliable and valid, even when heteroskedasticity is present (Kaufman, 2013). To deal with missing data the algorithm was set to mean replacement (no weighting vector was used). 2.6. Instruments: the Open Dialogue teams survey scale development RP and TeS developed a first draft of the questionnaire after reviewing the current literature on OD implementation. All authors revised the first draft, and RP further refined the revisions until a consensus was reached. At the end of the development process, 65 questions were finalized for this survey. The full questionnaire is attached as Supplementary material to the article. The items related to OD-team’s transparency, self-disclosure, intervision, intended as a form of colleague-based supervision (Razzaque, 2019) and training were adapted from the OD addendum of the COMFIDE- Questionnaire (Alvarez Monjaras, 2019). The questionnaire was then pilot tested with one OD team, but no changes to the survey content were necessary. The survey was structured in six sections, each dedicated to an independent dimension of mental health services. In the general part (1) the year the OD-service first started, (2) the presence of other therapeutic models integrated in the mental health service; (3) the age range of patients the OD-service was dedicated to; (4) what diagnostic groups of patients the OD-service works were inquired. Furthermore, three characteristics of the structural domain of mental health services were inquired: (a) the sector to which the MHS belongs [public/other (private, third sector); since the distinction between the private and third sectors was not always clear to respondents, wecollapsed these two categories into one category (‘non-public sector’)]; (b) whether the MHS operates as an inpatient or outpatient service, or both; (c) if Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 05 frontiersin.org the MHS is stand-alone- or integrated with other services or other. We further asked about estimating the number of professionals (nurses/occupational therapists/peer-support workers/psychiatrists/ psychologists/psychotherapists/social workers /support workers/ others) constituting the OD-team. 2.6.1. OD-self-assessment scale: development and validation For the teams’ OD-self-assessment (OD-SA), wedeveloped 17 items by reviewing the literature on good practice in Open Dialogue. The starting point for the development of the items were the seven principles of OD (Seikkula etal., 2003) with the aim of formulating a minimum of two items for each principle as affirmative statements. Respondents were asked to indicate for each statement the extent to which it reflected the clinical practice in their services over the past 3 months on a five-point Likert scale from 1 = “never,” 2 = “rarely,” 3 = “sometimes,” 4 = “frequently” to 5 = “almost always.” Consequently, higher scores reflected better OD-self-assessment (OD-SA) than lower scores. 2.6.2. Scale validation: confirmatory composite analysis The content validity of the 17 items composing the OD-self- assessment scale is based on the conceptual review of the OD-Principles formulated by Seikkula etal. (2003). Discriminant validity refers to the extent to which model constructs may bedistinguished from each other. Different to the first five organizational principles, principles 6 (Tolerating Uncertainty) and 7 (Dialogicallity) relate to the way of being and engaging with clients during the network meetings. Due to a low discriminant validity of the two scales – Heterotrait-Monotrait ratio (HTMT) of 0.917 was above the recommended 0.900 threshold (Henseler etal., 2015) – they were merged into one four-item scale of ‘OD-Adherence’ (OD-ADH). For the resulting scales the values of average variance extracted (AVE) exceeded the Fornell and Larcker (1981) criterion (a minimum of 0.5) and HTMT ratio was significantly below 0.90 indicating a good discriminant validity. Assessing first Cronbach’s alpha reliability of the constructs, it turned out to be‘good’ for P1 (r = 806) and P2 (r = 0.806), acceptable for ‘ADH’ (r = 0.767) however ‘doubtful’ for P3 (r = 0.683), P5 (r = 0.632), and ‘not acceptable’ for P4 (r = 0.332). Reviewing all factor loadings, weeliminated two critically low loading items (I26: λ = 0.52 -> P3; I30: λ = 0.63 -> P4) from each of the two scales, turning the P4 scale into a single-item construct consisting of I29 only and the P3 scale into a three-item scale with close to ‘acceptable’ reliability (r = 0.698); the internal consistency of P5 (r = 0.623) remained low according to the generally applied Cronbach’s Alpha criterion (r = 0.705). New research suggests that the use of a single criterion for established instruments as well as newly explored and developed studies – as the one at hand – may betoo conservative for scales developed within the context of the latter (see Hair etal., 2019, p.9; Hair et al., 2021, p. 119). Composite reliability is therefore recommended for the reliability assessment of newly developed scales (Hair etal., 2018) and the values evidence the scales acceptable level of reliability according to the standards for exploratory studies (see ρ A in Table1). Multicollinearity appeared not to bean issue for our indicators since each indicator’s Variance Inflation Factor (VIF) value was less than 5. Convergent validity and reliability results are presented in Table1. Confirmatory Composite Analysis provided evidence of the measurement model’s construct validity based on the assessment of its convergent and discriminant validity. Nomological validity is confirmed through the positive correlations of the six subscales. The full OD-FID15 scale had a high level of internal consistency, as determined by Cronbach’s alpha of r = 0.823. The computed Cramér-von Mises test statistic (CVM = 0.16, df = 118, p = 0.017) for the composite scores indicated a significant deviation from the normal distribution (skewness = −0.238, kurtosis = −0.203). 3. Results During the timespan January 2020 – February 2022, a total of 142 OD-Teams from 24 different countries responded to the call to participate in the survey. 118 OD-teams (82%) completed the questionnaire responding to the entire OD-self-assessment (OD-SA) scale. Wereport the number of respondents for each item related to the quantitative data. 3.1. Descriptive data The first OD-mental health services participating in our survey were established in Finland during the 1990ies. This Finnish service remained for about half a decade the pioneering mental health center for the treatment of severe mental illness using OD; in 1995, another center started to offer the OD approach in Norway. The year 2006 marked a significant turning point in the spread of the OD approach, from where on weobserved a stable growth rate of new OD-services of about 24% (SD = 17%) on a yearly basis from five OD-services in Finland and Norway in 2006 to over 100 centers in the year 2020in 24 countries on five continents (see Supplementary Figure 1). Geographically, 85% of OD services were based in Europe, with a presence in almost all North-European countries (except Sweden and Island) and Western Europe (except Austria and Luxemburg; see Figure1). 3.1.1. Structural characteristics of OD-services Of the 118 OD-services who completed the survey, 57 (48%) were mental health departments, 42 (36%) were registered associations, 9 (8%) were private practices, and 4 (3%) were foundations; 6 (5%) did not report their legal form of entity. Most teams (62%) belonged to MHS of the public sector, and 45 (38%) OD-teams belonged either to the private sector (n = 25) or to the third sector (n = 20). None of the teams reported to belong to MHS offering only inpatient service but 42 (36%) offer in-& outpatient service; 76 (64%) offer only outpatient service (see Table2). Exploring the structural characteristics associated with the MHS in which OD-teams emerged and operated, resulted in a model including all main effects and two two-way associations: (1) Service Sector * Integration; (2) Service Sector * Service Modality. The likelihood ratio goodness-of-fit test indicated that the model offered a moderate fit to the observed data [χ 2 (2) = 4.929, p = 0.085]; the Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 06 frontiersin.org FIGURE1 Global map of OD-Teams in mental health services responding to the HOPEnDialogue survey. TABLE1 Measurement model of the 15 items of the OD-self-assessment (OD-SA) scale: descriptive statistics, factor loadings (λ), Cronbach’s alpha, composite reliabilities (ρA, and ρc), average variance extracted (AVE). Reliability measures P1 P2 P3 P4 P5 P6-7: ADH M (SD)2.96 (1.01) 3.80 (0.91) 4.51 (0.55) 3.83 (1.16) 4.29 (0.83) 4.10 (0.73) Cronbach’s alpha 0.806 0.806 0.698 0.632 0.767 Composite reliability (ρA)0.826 0.808 0.695 0.710 0.774 Composite reliability (ρC)0.911 0.886 0.832 0.839 0.851 Average variance extracted (AVE) 0.836 0.721 0.622 0.724 0.588 Principle Item M SD Λt-statistic p value VIF P1 P2 P3 P4 P5 P6-7: ADH P1 I18 2.47 0.99 0.897 32.489 0 1.835 0.897 0.493 0.371 0.352 0.120 0.369 P1 I19 3.46 1.21 0.931 62.854 0 1.835 0.931 0.517 0.383 0.337 0.261 0.533 P2 I20 3.36 1.34 0.852 30.298 0 1.815 0.493 0.852 0.377 0.353 0.423 0.424 P2 I21 3.68 1.05 0.854 32.305 0 1.729 0.535 0.854 0.431 0.313 0.317 0.593 P2 I22 4.36 0.79 0.840 21.63 0 1.707 0.376 0.840 0.510 0.338 0.410 0.464 P3 I23 4.64 0.62 0.763 13.651 0 1.299 0.313 0.438 0.763 0.368 0.476 0.455 P3 I24 4.61 0.68 0.825 15.518 0 1.683 0.309 0.341 0.825 0.361 0.330 0.413 P3 I25 4.29 0.77 0.778 12.506 0 1.413 0.348 0.427 0.778 0.236 0.283 0.367 P4 I29 3.83 1.16 1.000 0.375 0.393 0.406 1.000 0.254 0.394 P5 I27 4.31 0.95 0.914 30.719 0 1.271 0.277 0.405 0.431 0.218 0.914 0.501 P5 I28 4.27 0.98 0.782 11.021 0 1.271 0.045 0.362 0.358 0.221 0.782 0.230 P6-7 I31 3.98 1.00 0.790 20.743 0 1.488 0.421 0.472 0.399 0.351 0.448 0.790 P6-7 I32 4.17 0.96 0.753 12.016 0 1.530 0.359 0.392 0.373 0.207 0.261 0.753 P6-7 I33 4.28 0.95 0.803 13.863 0 1.615 0.385 0.490 0.467 0.340 0.362 0.803 P6-7 I34 3.92 0.88 0.718 12.317 0 1.365 0.367 0.428 0.364 0.290 0.304 0.718 N = 118. Shaded values in each column highlight the cross-loadings between items belonging to one scale (=OD-principle). Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 07 frontiersin.org specific effects reported in Table3, however, are mostly significant and support the notion that the structural variables are importantly related (see Table3). We found that the odds of an OD-team belonging to integrated services were 3.73 times higher for OD-teams in public services than for OD-teams in non-public services. Furthermore, a significant association emerged with respect to OD-teams’ Service Integration and Service Modality: the odds for OD-teams working in outpatient MHS not to work in integrated services was 5.71 times higher than for teams working in MHS with in- and outpatient services. The analysis proposes that OD-teams tend to emerge in organizational environments which are public, operate integrated services and offer both inpatient and outpatient services (see Table4). 3.1.2. Access to OD-services and services’ therapeutic context Clients-referrals: Most respondents report referrals to OD-services occur via general practitioners (87%; 90/104); 61% (64/104) of the OD-teams reported referrals from hospitals, and 39% (41/104) referrals from social services. Some services report on established partnerships with associations sharing similar values (e.g., recovery groups) becoming OD-teams’ primary referrals. An important share of referrals to OD-teams reported are selfreferrals: 46% (48/104) report referrals through “word of mouth” or direct requests as described in a comment by a respondent of the Finnish team: “Anyone can ask help for anyone (for themselves, for family members, for clients etc.) via phone, letters, walking to the office etc. Usually, people call the local service number (one number 24/7 for the whole region). Nurses on duty survey what the main problem is and when and where people want to meet (meetings can bearranged within 24 h, but usually, people/patients/clients want the first meeting to bearranged within 2–3 weeks from contact). Then she/he starts to arrange network meetings by calling workers from local outpatient clinics and/or other important people to join the process. Official referrals are not required, but they can beused as well.” Clients-age groups: Almost all the OD-teams (93%; 110/118) work with clients aged 18–65; about 30% of OD-teams offer their services also to clients under 18 years of age, and about 43% of the OD-services reported an upper age limit of 65 years. Clients-diagnostic profile: Most OD-teams work with clients with psychotic disorders (92%), mood disorders (86%), anxiety and fearrelated disorders (81%), to a lesser degree on disorders associated to stress (64%), and other disorders (57%). Therapeutic models mentioned in the OD-services besides the Open Dialogue approach are social psychiatry (10%) and recoveryoriented approaches (9%). 3.1.3. OD workforce Hours of teams’ OD practice per week: An average of 14.2 (Mdn = 10; SD = 12.4) hours per week was reported. 22% (19/87) reported more than 26 h per week of OD practice. The median number of OD-trained staff members in OD-teams amounted to 14 (S.E. = 2.74) with a median of five members being trained in OD and a median of one member being in OD-training at the time point of study. 61% (72/118) of the teams offered their OD-service less than 20 weekly hours. Table5 reports the professional profile of the staff in OD-teams. Using chi-square test of independence, the professional profile of the staff differed significantly between teams operating in the public and non-public sector [X 2 (14; 1,604) = 407.793; p < 0.001], with clinical personnel such as nurses (34%) and psychiatrists (11%) dominating the OD-teams in the public sector. On the other hand, wefound that Support Workers (25%), Social Workers (19%) and Peer-support Workers (13%) dominate the professional profile in OD-teams operating in the non-public sector. Psychologists and TABLE2 Observed frequencies and percentages for sector, modality, and type of OD-service. In which sector is your service? Modality of services Integration of services n (%) Non-public sector [Private- and Third sector (n = 45; 21%)] In- & Outpatient (8) Integrated service 6 (5%) Stand-alone service 2 (2%) Outpatient (37) Integrated service 9 (8%) Stand-alone service 28 (24%) Public sector (n = 73; 62%) In- & Outpatient (34) Integrated service 29 (25%) Stand-alone service 5 (4%) Outpatient (39) Integrated service 27 (23%) Stand-alone service 12 (10%) N = 118. Percentages appear in parentheses. TABLE3 Log-linear parameter estimates, values, and goodness-of-fit index for Service Sector, Service Integration, and Service Modality. Effect λz P [non-public sector] X [Standalone] −1.885 −4.4858 <0.001 [Outpatient] X [Standalone] 1.715 3.622 <0.001 [non-public sector service] −1.317 −4.531 <0.001 [Outpatient service] 0.028 0.119 0.906 [Standalone service] −2.389 −5.180 <0.001 G2(2, N = 118) = 4.929, p = 0.085. TABLE4 Partial associations for Service Sector, modality of service, and Service Integration. Effect Partial association X2 (df = 1) Sig. (p-value) Service Sector * In-&Outpatient 3.445 0.063 Service Sector * Service Integration (Standalone vs. Integrated) 14.919 <0.001 In-&Outpatient * Service Integration (Standalone vs. Integrated) 8.449 0.004 Service Sector 6.708 0.010 Modality of Service (In-&Outpatient) 9.937 0.002 Integration 4.916 0.027 Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 08 frontiersin.org TABLE5 Professional characteristics of the OD-trained workforces. Items Categories N = 118 Percent of Cases Public Sector (n = 73) Non-Public (Private- & Third Sector; n = 45) 35. Current number of staff members (Professional profiles of OD-teams); X2(14; 1,604) = 407.793; p < 0.001 N= 1,035 N= 569 1: Nurses 439 27% 353 (34%) 86 (15%) 2: Occupational Therapists 85 5% 57 (6%) 28 (5%) 3: Peer-support workers 151 9% 77 (7%) 74 (13%) 4: Psychiatrists 139 9% 116 (11%) 23 (4%) 5: Psychologists/Psychotherapists 263 16% 188 (18%) 75 (13%) 6: Social workers 271 17% 163 (16%) 108 (19%) 7: Support workers 178 11% 33 (3%) 145 (25%) 8: Others 78 5% 48 (5%) 30 (5%) Number of staff in OD-Teams (n = 72) M= 19.83; S.E. = 2.74; Median = 14.0; Caseload size currently (n = 72) Median = 15.5; *Maximum caseload (n = 72) Median = 30.0; *Number of Staff-training in progress (n = 72) M= 4.19; S.E. = 1.63; Median = 1.0 Number of OD-trained staff in teams (n = 72) M= 8.71; S.E. = 1.37; Median = 5.0 Categories significantly underrepresented are indicated in italic (adjusted residual < −1.96 at p < 0.05); categories significantly overrepresented are indicated in bold (adjusted residual > 1.96 at p < 0.05). *Median values of Maximum caseload and Caseload are in many cases based on subjective estimates only since (especially) public services in many countries are required to offer services as requested. occupational therapists contribute equally to both sectors (see Table5). 3.1.3.1. OD team taxonomy To explore potential taxonomies of professional configurations in OD-teams, weran a cluster analysis based on the standardized counts of professionals in each of the eight professional categories in 118 teams. Ward’s linkage method with chi-squared distance metric was employed for the hierarchical clustering process. Missing values were treated as missing in the analysis. The agglomeration schedule revealed that clusters were formed in 95 stages, with Ward’s linkage coefficients ranging from 0.000 to 31.171. A dendrogram was utilized to visualize the hierarchical structure of the data clusters (see Supplementary Figure 2) and cluster membership for each case was saved in a new variable. Coefficients increased moderately from 16.987 to 17.659 to 18.463, and then took a much larger leap from 22.888 to 25.236, and then another jump from 27.993 to 31.171 which indicated a good cut-off point at 27.993 with four clusters of OD-teams based on the following professional characteristics (see Table6): - “Multi-professionals teams” (n = 17): are characterized by the highly heterogeneous professional profile in which 5–6 professions are on average presented; - “Clinical Psy-Teams” (n = 33): are dominated by clinical professions (psychologists/psychotherapists, psychiatrists, and nurses) with a low degree of professional heterogeneity; - “Teams with a prevalence of Nurses and Occupational therapists” (n = 30): are characterized by the highest share nurses, occupational therapists and peer-support workers; - “Teams with a prevalence of Social workers” (n = 16): are dominated by the highest share of social workers (47%), a high share of nurses (23%), and it is the only group characterized by the absence of psychiatrists (0%). Peer-support workers were represented equally in all clusters, with a share of about 10%. Exploring whether the OD-teams with professional profiles differed in their OD-SA score, revealed that median scores were statistically significantly different between the different clusters [χ 2 (3) = 13.816, p = 0.003]: “Teams with a prevalence of Social worker” (Mdn = 3.58) scored statistically significantly lower on the OD-SA scale (OD-FID15) than “Multi-professional teams” (Mdn = 4.20; p = 0.030) and also lower than “Teams with a prevalence of Nurses and Occupational therapists” (Mdn = 4.28; p = 0.002) but not with respect to “Clinical Psy-teams” (Mdn = 4.07; p = 0.146). OD-teams composed of multiple professions yielded significantly higher OD-FID15 scores [χ2(3) = 20.571, p < 0.001; see Table6]. 3.1.4. OD staff training 1,192 staff members were reported to have taken recognized OD-training. Furthermore, 448 OD trainings were undertaken at the time of the survey, so a 38% growth rate of active OD practitioners could beprojected for the upcoming years. With respect of the share of OD-trained personnel in services: • 4 = 26% (n = 27) of the OD-teams had all their clinical staff trained or undergoing a recognized OD-training program; • 3 = 15% (n = 16) had only a small number of exceptions (e.g., a couple of members of staff who have recently joined, but are expecting to start training soon) not being OD-trained; • 2 = 17% (n = 18) had most clinical staff completed or are undergoing a recognized OD training, and most of the remaining staff were due to betrained soon; Pocobello et al. 10.3389/fpsyg.2023.1241936 Frontiers in Psychology 15 frontiersin.org sharing the list of OD trainings. We also want to thank all the practitioners participating in the study and our sponsor, Open Excellence, for making this research possible. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could beconstrued as a potential conflict of interest. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Supplementary material The Supplementary material for this article can befound online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1241936/ full#supplementary-material SUPPLEMENTARY FIGURE 1 Historical development of OD-services in different countries from 1990–2022. SUPPLEMENTARY FIGURE 2 Dendrogram of the cluster analysis using Ward linkage. SUPPLEMENTARY DATASHEET 1 HOPEnDialogue-Survey Questionnaire 2020. 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