Client Engagement with an Early Psychosis Program and Post-Program Health Service Use: A Retrospective Cohort Study

Client Engagement with an Early Psychosis Program and Post-Program Health Service Use: A Retrospective Cohort Study | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 14 January 2026 V1 Latest version Share on Client Engagement with an Early Psychosis Program and Post-Program Health Service Use: A Retrospective Cohort Study Authors : Nathan K. Smith 0000-0002-8577-3023 [email protected] , Leslie Anne Campbell 0000-0003-2534-0450 , Candice Crocker , and Philip Tibbo Authors Info & Affiliations https://doi.org/10.22541/au.176837955.56188058/v1 147 views 59 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: Poor engagement with Early Intervention Services (EIS) for first-episode psychosis threatens program effectiveness, yet research often reduces engagement to a binary measure (engaged/disengaged), limiting understanding of those who disengage and re-engage. This study examined demographics, clinical characteristics, and health service utilization patterns among engaged, intermittently engaged, and disengaged patients of the Nova Scotia Early Psychosis Program (NSEPP). Methods: A retrospective cohort comprised of 331 individuals enrolled in NSEPP between July 22, 2005, and October 9, 2015, was constructed by linking clinical and administrative datasets. Engagement types (engaged, intermittently engaged, disengaged) were characterized in terms of baseline demographics and clinical factors, along with patterns of health service utilization before, during, and after program enrollment. Crude and adjusted associations between program engagement and post-program health service utilization (emergency department (ED) use and mental health-related hospital admissions) were assessed using negative binomial regression models. Results: During program enrollment, the intermittently engaged group had the greatest illness severity (35% spent 30+ days in hospital), and highest proportion of individuals with at least one ED visit (85%) and one hospital admission (55%). These during-program health service use factors were the strongest predictors of post-program health service use outcomes. Conclusions: The three engagement types show distinct health service utilization patterns, which may reflect differences in need or program effectiveness. These results provide evidence that dichotomization of engagement may mask important heterogeneity. Further characterization of the engagement continuum to include intermittent engagement may provide insights to reducing barriers and improving access to and uptake of EIS. Introduction Managing psychotic symptoms early in the course of illness through Early Intervention Services (EIS) for first episodes of psychosis has been shown to improve outcomes by offering early detection and timely, phase-appropriate care (Correll et al., 2018; Posselt, Albert, Nordentoft, & Hjorthøj, 2021; Robinson et al., 2022). However, engagement in care is a common challenge in mental health services, particularly among individuals following a first episode of psychosis. Poor engagement can hinder recovery and result in worse patient outcomes, threatening effectiveness of EIS programs (Dixon, Holoshitz, & Nossel, 2016). Despite broad eligibility criteria, publicly funded health care, and open referral systems, several barriers to accessing or engaging in care have been identified, including knowledge, symptom severity, substance use, absence of supportive relationships, stigma, and length of follow-up (Anderson et al., 2018; Mascayano et al., 2021; Robson & Greenwood, 2022; Tiller, Maguire, & Newman-Taylor, 2023). Disengagement can occur at any point in care: at the beginning of or during treatment, or during transfer from EIS to ongoing care. Disengagement from EIS has been reported to be as high as 53% (Robson & Greenwood, 2022), although great variation exists depending on the definition of engagement and length of follow-up (Doyle et al., 2014; Mascayano et al., 2021; Robson & Greenwood, 2022). Outcomes of those who completely disengage are often difficult to ascertain due to loss to follow-up, and this remains a limitation in the literature (Robinson et al., 2022). However, it is common for individuals to re-engage after a period of disengagement, and few studies have examined this intermittently engaged group (Kim et al., 2019; Mlay, Paruk, Tomita, & Lessells, 2025; Robson & Greenwood, 2022). Despite a continuum of engagement, studies often use a binary classification of engaged vs disengaged, with varying definitions. This coarse and inconsistent classification impedes comparisons across studies and risks grouping clinically distinct subgroups of patients, potentially masking informative heterogeneity. In addition to demographic and clinical factors, patterns of health service utilization may be particularly information when investigating engagement, as they can act as key indicators at different points in the care pathway: pre-EIS may reflect the severity of illness or health service utilization preferences, during-EIS may reflect sub-optimal management of illness or worsening of symptoms during program engagement, and post-EIS utilization may be used as an outcome of EIS. This is reinforced by recent findings that referrals to EIS from urgent services may be associated with subsequent urgent health care use during EIS care (Senger et al., 2024), suggesting that understanding patterns of health care use throughout the treatment pathway (pre-, during, and post-EIS) may provide insight into relationships between EIS engagement and health service use outcomes. Thus, the overarching aim of this study was to understand the differences in sociodemographic, clinical, and health service use factors among engaged, intermittently engaged, and disengaged patients of a Canadian EIS. To meet this aim, this study had two specific research objectives: 1. Characterize three EIS engagement types (engaged, intermittently engaged, and disengaged) in terms of sociodemographic, clinical, and health service use factors. 2. Determine whether EIS engagement type is associated with post-program health service use before and after adjustment for sociodemographic, clinical, and health service use factors. Design and Setting We conducted a retrospective cohort study of individuals enrolled in the Nova Scotia Early Psychosis Program (NSEPP) between July 22 nd , 2005, and October 9 th , 2015, using linked administrative and clinical databases. NSEPP is a community focused EIS program, based in the Nova Scotia Health Central Zone, in Halifax, Nova Scotia for individuals aged 12 to 35 years experiencing first-episode psychosis. The multidisciplinary team follows patients for 5 years after program entry, following over 300 patients at any one time. Data Sources Emergency department (ED) utilization data between February 18, 2006, to August 29, 2022, were obtained from the Emergency Department Information System (EDIS) database, which captures ED use in the Nova Scotia Health Central zone. Information regarding hospital discharges between April 1, 2009, to June 30, 2022, were acquired from the Discharge Abstract Database (DAD), which captures all hospital discharges in Nova Scotia (note: discharges from inpatient substance withdrawal management units were not included prior to April 1, 2014). Hospitalization records were included if clients were discharged from a mental health and addictions (MHA) unit or had an MHA-related discharge diagnosis in the most responsible diagnosis field, which were reported using the tenth revision of the International Classification of Diseases with Canadian enhancements (ICD-10-CA) codes (Canadian Institute for Health Information, 2022). Area-level income data and urban/rural status were obtained from the 2016 Canadian Census, linked via postal code to census dissemination area using the Postal Code Conversion File Plus (PCCF+) version 7D (Statistics Canada, 2021). Additional dissemination area-level indicators were acquired from the 2016 Canadian Marginalization Index (CAN-Marg) (Matheson, Dunn, Smith, Moineddin, & Glazier, 2012). Other demographic and clinical variables were obtained from the NSEPP database. Health Service Utilization Time Periods We considered three time periods relative to the index date of a patient’s program enrollment: one year pre-program enrollment, a five-year period of program enrollment (“during program”), and three years post-program follow-up. Given the enrollment dates and data availability periods for health service utilization sources noted above, a full observation period was not available for all individuals. To create comparable observation periods and reduce the risk of selection bias, an individual’s health service utilization data were included only if 75% of their observation period was captured (i.e., at least 9 months out of the one-year pre-program period, 45 months out of the five-year during program period, and 27 months out of the three-year post program period). Variables Engagement The engagement type of each patient was assigned by applying the following definitions: Engaged: Patients who remain in NSEPP care from enrollment until discharge; typically for 5 years. The case and database notes indicate no active refusal or untraceable contact with the treatment team for a continuous period of 3 months or greater. Intermittent: Patients with brief periods of disengagement (i.e., at least 3 months of loss to follow-up) who return to the program for a clinically meaningful period and remain engaged until the point of discharge. Disengaged: Patients with active refusal or untraceable contact with the treatment team at any point during treatment for a continuous period of at least 3 months and who remain lost to follow-up to the 5-year time point post enrollment. Individuals noted as deceased, transferred, moved out of province, or in forensic services were assigned their pre-event engagement type. Individuals noted as deceased or moved out of province were not included in analyses of during or post-program health service utilization. Demographics Individual-level demographic variables included age in years at NSEPP enrollment, biological sex (male/female), and race (White, Black and mixed race, Mid-east, and other). Area-level demographics included an urban/rural indicator, pre-tax area-level median household income, and the 2016 Can-MARG immigration and visible minority quintiles. Quintiles were collapsed into two categories: highest 60% and lowest 40% to maximize sample size per comparison group. Symptoms and Function At NSEPP enrollment, symptoms were measured using the Positive and Negative Syndrome Scale (PANSS) (Kay, Fiszbein, & Opler, 1987). Function was measured using both the Social and Occupational Functioning Assessment Scale (SOFAS) (Morosini, Magliano, Brambilla, Ugolini, & Piolo, 2001) and the Global Assessment of Functioning Scale (GAF) (Moos, McCoy, & Moos, 2000). Health Service Utilization Health service utilization was captured by the number of ED visits (any reason) and mental health-related hospital admissions, operationalized as binary variables (any vs none) for descriptive statistics and as counts for regression models. For each health service use type (i.e., hospital admissions and ED visits), consecutive records were collapsed into a single record if the discharge date was the same as the subsequent admission date (suggesting a transfer or repeat visit for the same issue). The length of hospital stay was used as indicator of severity of illness, with individuals spending 30 or more days in hospital in any given study period considered to have greater severity than those with shorter stays. Statistical Analysis Descriptive statistics included counts and percentages for categorical variables, and medians and interquartile range bounds for continuous variables (objective 1). The relationship between engagement and post-program health service utilization was assessed via negative binomial regression models for counts of ED visits and mental health-related hospital admissions (objective 2). Negative binomial models were employed to account for overdispersion of the count data and were confirmed to provide better fit than Poisson models via likelihood ratio tests. An offset was included in the models to account for differences in post-program observation period. Three models were run for each outcome: Model 1 was unadjusted, Model 2 was adjusted for demographics and clinical factors at baseline, and Model 3 was further adjusted for health service utilization. Variable selection for adjusted models was guided by the literature and aimed to have representation from the key blocks of variables noted above (i.e., demographics, clinical factors, health service utilization). In the face of missing data and limited sample size, candidate variables within these blocks were chosen to reduce redundancy and maximize sample size while maintaining clinical relevance. A sensitivity analysis was conducted to exclude all health service utilization outliers greater than or equal to three standard deviations above the mean. Postal code conversion using PCCF+ was run in SAS software version 9.4 ( SAS 9.4 Software , 2023). All statistical analyses were conducted using R version 4.2.3 (R Core Team, 2024). Results Sample Characteristics by Engagement Type Demographics and Clinical Factors at Baseline The NSEPP cohort includes 332 individuals enrolled between July 22 nd , 2005, to October 9 th , 2015. Of these, one individual was determined not to have psychotic illness, leaving a total sample of 331. This sample was predominantly male (73%), white (78%), and had a median age of 22.2 years at enrollment (Table 1). Of these 331 individuals, 178 (53.8%) remained engaged throughout their 5-year enrollment period. Eighty-six individuals (26%) disengaged before the end of the 5 years, and 67 (20.2%) were intermittently engaged. Table 1. Sample Characteristics by Engagement Type Characteristic n a Overall ( n = 331 a ) Engaged ( n = 178 a ) Disengaged (n = 86 a ) Intermittent (n = 67 a ) Age Enrollment 330 (100%) 22.2 (20.4, 25.8) 22.2 (20.4, 26.0) 22.2 (20.5, 25.1) 22.3 (20.4, 25.3) Missing 1 0 1 0 Sex 331 (100%) Female 88 (27%) 51 (29%) 21 (24%) 16 (24%) Male 243 (73%) 127 (71%) 65 (76%) 51 (76%) Ethnicity 209 (63%) White 163 (78%) 89 (82%) 43 (78%) 31 (69%) Black and Mixed Race 19 (9.1%) 7 (6.4%) 4 (7.3%) 8 (18%) Mid-East 15 (7.2%) 7 (6.4%) 4 (7.3%) 4 (8.9%) Other 12 (5.7%) 6 (5.5%) 4 (7.3%) 2 (4.4%) Missing 122 69 31 22 Urban/Rural 326 (98%) Urban 264 (81%) 139 (80%) 72 (84%) 53 (79%) Rural 62 (19%) 34 (20%) 14 (16%) 14 (21%) Missing 5 5 0 0 CANMARG Minority 311 (94%) Top 60% 225 (72%) 124 (76%) 51 (62%) 50 (76%) Bottom 40% 86 (28%) 39 (24%) 31 (38%) 16 (24%) Missing 20 15 4 1 PANSS Positive 313 (95%) 18 (14, 22) 19 (14, 23) 18 (13, 21) 18 (15, 24) Missing 18 10 5 3 PANSS Negative 313 (95%) 15 (11, 20) 15 (11, 21) 14 (10, 17) 17 (11, 21) Missing 18 10 5 3 PANSS General Psychopathy 310 (94%) 35 (30, 42) 34 (29, 41) 35 (30, 41) 37 (31, 44) Missing 21 13 5 3 GAF 294 (89%) 40 (31, 40) 40 (31, 42) 40 (31, 41) 40 (35, 40) Missing 37 18 13 6 SOFAS 294 (89%) 41 (35, 53) 44 (35, 55) 41 (35, 53) 41 (40, 51) Missing 37 18 13 6 Pre-Program ED Visits 271 (82%) None 80 (30%) 45 (30%) 19 (29%) 16 (29%) 1+ 191 (70%) 104 (70%) 47 (71%) 40 (71%) Missing 60 29 20 11 During Program ED Visits 313 (95%) None 78 (25%) 40 (25%) 28 (33%) 10 (15%) 1+ 235 (75%) 123 (75%) 57 (67%) 55 (85%) Missing 18 15 1 2 Post-Program ED Visits 303 (92%) None 159 (52%) 84 (54%) 48 (56%) 27 (43%) 1+ 144 (48%) 71 (46%) 37 (44%) 36 (57%) Missing 28 23 1 4 Pre-Program Admissions 194 (59%) None 96 (49%) 49 (45%) 23 (55%) 24 (57%) 1+ 98 (51%) 61 (55%) 19 (45%) 18 (43%) Missing 137 68 44 25 During Program Admissions 223 (67%) None 139 (62%) 71 (61%) 45 (80%) 23 (45%) 1+ 84 (38%) 45 (39%) 11 (20%) 28 (55%) Missing 108 62 30 16 Post-Program Admissions 301 (91%) None 251 (83%) 132 (86%) 71 (85%) 48 (76%) 1+ 50 (17%) 22 (14%) 13 (15%) 15 (24%) Missing 30 24 2 4 Pre-Program Severity 194 (59%) <30 Days in Hospital 176 (91%) 97 (88%) 39 (93%) 40 (95%) 30+ Days in Hospital 18 (9.3%) 13 (12%) 3 (7.1%) 2 (4.8%) Missing 137 68 44 25 During Program Severity 223 (67%) <30 Days in Hospital 163 (73%) 81 (70%) 49 (88%) 33 (65%) 30+ Days in Hospital 60 (27%) 35 (30%) 7 (13%) 18 (35%) Missing 108 62 30 16 Post Program Severity 301 (91%) <30 Days in Hospital 265 (88%) 135 (88%) 78 (93%) 52 (83%) 30+ Days in Hospital 36 (12%) 19 (12%) 6 (7.1%) 11 (17%) Missing 30 24 2 4 a Median (IQR Bounds); n (%). SOFAS = Social and Occupational Functioning Assessment Scale. PANNS = Positive and Negative Syndrome Scale. The groups were similar in terms of most demographic and clinical characteristics with some notable differences (Table 1). The intermittent group had a higher proportion of black individuals (18% compared to 7.3% and 6.4% for disengaged and engaged, respectively), and the disengaged group had a higher proportion of individuals from minority areas (38% vs 24%). In terms of clinical factors, PANNS negative scores were lowest in the disengaged group, and highest in the intermittent group (median 14 vs 17). In terms of substance use, the disengaged group had higher use across the board (the only exception being cocaine, where intermittent was higher, Table S1). Health Service Utilization No clear health service utilization patterns were observed pre-program, though during the program a clear gradient emerged: The intermittent group had the highest proportion of individuals with at least one ED visit (85%), one hospital admission (55%), and 30 days spent in hospital (35%), while disengaged had the lowest (67%, 20%, 13%, respectively). The difference between engaged and disengaged was reduced during the post-program period, but intermittent still had the highest proportion on all three metrics (Figure 1). These findings are robust to removal of outliers (Figure S2). Figure 1. Health Service Utilization by Engagement Type Figure 1 shows the proportion of individuals in each engagement type with at least one mental health-related hospital admission (admiss), one emergency department visit (ED), and at least 30 days in hospital (severity) before (pre), during (dur), and after (post) the program. These patterns are also reflected in the count data with the largest differences between groups reflected in the during-program hospital admissions (Figure 2), and the post-program ED visits (Figure S2). Figure 2. During Program Health Service Utilization by Engagement Type Figure 2 shows boxplots of mental health-related hospital admissions, emergency department visits, and number of days in hospital for each engagement type during the five-year program period. Post-program counts can be seen in Table S1. Engagement and Post-Program ED Visits Prior to adjustment, those who disengaged with the program had 0.60 times lower incidence of ED visits over the three-year post-program period compared to those who remained engaged (incidence rate ratio [IRR] 0.60, 95% CI = 0.37, 0.99, Table 2). However, this association lost statistical significance after adjusting for demographics and clinical factors. Those intermittently engaged with the program were not statistically different compared to those who remained engaged before or after adjustment. In the fully adjusted model, only during-program ED visits (IRR 1.22, 95% CI = 1.13, 1.33) and severity (IRR 2.01, 95% CI = 1.00, 4.17) remained significant. After removing outliers, the unadjusted association lost statistical significance, but the adjusted associations remained consistent (Table S3). Table 2. Negative Binomial Models for Post-Program Emergency Department Visits Characteristic IRR 95% CI IRR 95% CI IRR 95% CI Engagement Type Engaged — — — — — — Disengaged 0.60 0.37, 0.99 0.66 0.39, 1.15 0.75 0.40, 1.41 Intermittent 1.11 0.66, 1.89 1.04 0.58, 1.88 1.19 0.64, 2.27 Age at NSEPP Enrollment 0.98 0.93, 1.03 0.98 0.93, 1.05 Sex Female — — — — Male 0.91 0.54, 1.52 1.13 0.63, 2.01 Median Income (area-level) 0.98 0.91, 1.06 1.03 0.94, 1.12 CANMARG Minority Top 60% — — — — Bottom 40% 1.15 0.69, 1.94 1.04 0.60, 1.80 PANSS Positive 1.00 0.95, 1.05 0.98 0.93, 1.04 PANSS Negative 0.98 0.93, 1.02 0.98 0.93, 1.04 PANSS General Psychopathy 1.03 0.98, 1.07 1.01 0.96, 1.06 SOFAS 0.98 0.96, 1.01 0.99 0.96, 1.03 During Program ED Visits 1.22 1.13, 1.33 During Program Admissions 0.94 0.77, 1.15 During Program Severity <30 Days in Hospital — — 30+ Days in Hospital 2.01 1.00, 4.17 a Model 1 is unadjusted (n = 303). Model 2 adjusts for demographics, symptoms and function at enrollment (n = 246). Model 3 additionally adjusts for during program health service utilization (n = 179). The Incidence Rate Ratio (IRR) for income represents a change of $10,000. SOFAS = Social and Occupational Functioning Assessment Scale. PANNS = Positive and Negative Syndrome Scale. Bold p-values indicate statistical significance at α = 0.05. Engagement and Post-Program Hospital Admissions Engagement type was not significantly associated with post-program hospital admissions in unadjusted or adjusted models (Table 3). Male sex (IRR = 2.98, 95% CI = 1.05, 8.94) was statistically significant in the demographic, symptom, and function-adjusted model, but lost significance after adjusting for health service utilization. In the fully adjusted model, only during-program hospitalizations (IRR = 1.56, 95% CI = 1.24, 2.00) and severity (IRR = 2.59, 95% CI = 1.01, 6.67) remained significant. After removing outliers, the intermittent group became statistically significant in the unadjusted model with an IRR of 2.19 (95% CI = 1.01, 4.84, Table S4). However, this lost significance when adjusting for demographics and clinical factors. Similar to the main analysis, further adjusting for during-program health service utilization resulted in the intermittent coefficient changing from positive to negative, suggesting a confounding effect. Only during-program severity remained statistically significant in the fully adjusted model with outliers removed (Table S4). Table 3. Negative Binomial Models for Post-Program Hospital Admissions Characteristic IRR 95% CI IRR 95% CI IRR 95% CI Engagement Type Engaged — — — — — — Disengaged 0.67 0.29, 1.56 0.38 0.13, 1.06 0.80 0.29, 2.06 Intermittent 1.60 0.70, 3.82 1.10 0.41, 3.00 0.81 0.34, 1.89 Age at NSEPP Enrollment 1.00 0.90, 1.10 0.99 0.90, 1.09 Sex Female — — — — Male 2.98 1.05, 8.94 1.82 0.66, 5.98 Median Income (area-level) 0.95 0.84, 1.08 1.11 0.99, 1.24 CANMARG Minority Top 60% — — — — Bottom 40% 1.14 0.47, 2.79 1.38 0.65, 2.90 PANSS Positive 0.97 0.88, 1.05 0.99 0.91, 1.06 PANSS Negative 0.98 0.90, 1.06 0.97 0.90, 1.03 PANSS General Psychopathy 1.04 0.97, 1.12 1.04 0.97, 1.10 SOFAS 0.97 0.92, 1.01 1.00 0.96, 1.05 During Program ED Visits 0.97 0.87, 1.06 During Program Admissions 1.56 1.24, 2.00 During Program Severity <30 Days in Hospital — — 30+ Days in Hospital 2.59 1.01, 6.67 a Model 1 is unadjusted (n = 301). Model 2 includes demographics, symptoms and function at enrollment, and engagement type (n = 244). Model 3 additionally includes during program health service utilization (n = 177). The incidence rate ratio (IRR) for income represents a change of $10,000. CANMARG = Canadian Marginalization Index. PANSS = Positive and Negative Syndrome Scale. SOFAS = Social and Occupational Functioning Assessment Scale. Bold values indicate statistical significance at α = 0.05. Discussion In this retrospective cohort study, we examined program engagement and health service use patterns among clients of NSEPP, a Canadian EIS program for first episode psychosis. The results illustrate that health service use patterns differ between engagement types during the program, with those intermittently engaged having the highest levels of use across all metrics (i.e., ED visits, hospital admissions, days in hospital), and those disengaged having the lowest. In addition, these during-program health service use factors were the strongest predictors of post-program health service use outcomes relative to engagement, demographics, and clinical characteristics. In light of similar baseline characteristics and pre-program health service utilization, first episode psychosis may be too early in the course of disease to differentiate these individuals. However, diverging health service utilization patterns during the program, particularly between the disengaged and intermittently engaged groups, may reflect emerging differences in severity of illness or management of disease. Previous findings support the idea that disengaged individuals may have lower severity of illness (Mascayano et al., 2021; Robson & Greenwood, 2022). Additionally, the higher substance use in this group is consistent with previous findings (Mlay et al., 2025), and may suggest these individuals seek care less often due to engaging in more coping and self-soothing behaviors. In contrast, higher illness severity in the intermittent group may act as a barrier, making it more difficult to remain engaged. Furthermore, intermittent engagement may lead to suboptimal disease management, resulting in more crisis-driven service utilization. While this study cannot disentangle these complex relationships, and both the intermittent and disengaged groups are likely heterogenous mixtures of individuals experiencing different barriers and levels of need, one thing remains clear: the intermittently engaged group displays unique health service use patterns, and this differential utilization is the strongest predictor of post-program health service use outcomes. This finding provides evidence that the intermittent group should be distinguished from definitions of engaged or disengaged, and that continued monitoring during the program may be required to ensure individuals are able to successfully engage. This may be particularly important for longer EIS programs (e.g., 5 years), as the longer follow-up offers more opportunity to disengage and re-engage. These results also highlight potential equity concerns. In terms of possible barriers, in addition to greater illness severity, the intermittent group had a higher proportion of individuals who identify as Black, potentially suggesting a racial disparity. For context, the 2021 Canadian Census estimates that only 3% of the Nova Scotian population identifies as Black (Statistics Canada, 2023) – a stark contrast to the 9.1% in the NSEPP sample, and 18% in the intermittent group. Assuming non-differentially missing data, this large over-representation of Black individuals in the intermittent group further emphasizes the need to move beyond a binary classification of engagement. A lack of consideration of this intermittent category may be why some studies have failed to find an association between race and engagement (Mascayano et al., 2021). Unfortunately, in the present study, the race variable had a high proportion of missing data, so it was not possible to include individual-level race in the adjusted models (although CANMARG minority quintile was used as a proxy). The main strengths of this study lie in addressing two key gaps in the literature, namely, differentiating those intermittently engaged, and capturing the post-program outcomes of those who disengaged from EIS, both of which are often lacking in empirical EIS research. However, some limitations should be noted. All individuals were assigned the same duration of program enrollment (5 years), despite differences in actual during-program exposure. Regardless, disengaged individuals had the lowest during-program health service utilization during a 5-year observation window, suggesting that accounting for their shorter program duration would not significantly alter the results. Additionally, it is possible that the disengaged group includes individuals who were lost to follow-up due to severe illness. However, given our province-wide health service use data capture and the relatively stable nature of the population in terms of out of province migration, those truly missing are likely a very small portion of the disengaged group. Lastly, ED visits were captured in the Central Zone only, so some individuals’ counts are under-reported if they visited EDs outside of this area. However, this is expected to be minimal as a sensitivity analysis determined that the Central Zone accounted for 94.6%, 95.7%, and 87.6% of all pre-, during, and post-program ED visits (respectively) from cohort members during the study period. Conclusion This study finds that among EIS service users, intermittently engaged individuals use more health services during program enrollment. This suggests that refining the definitions of engagement is key to understanding the course of disease, and for properly identifying and addressing barriers and inequities in EIS for first-episode psychosis. In future studies, capturing detailed information on periods of disengagement would strengthen a more accurate characterization of the continuum of engagement. Ethics Statement This study was approved by the Nova Scotia Health Research Ethics Board (File #1021590). Patient consent was not required for this linkage of de-identified records. Declaration of Conflicting Interests The authors have no conflicts of interest to declare. Funding This work was supported by the Dalhousie University Department of Psychiatry Research Fund. Acknowledgements The authors are grateful to Patryk Simon for his expertise in the health administrative databases used in the study. Data Availability Data are not publicly available due to privacy restrictions regarding health administrative databases. ORCID IDs Nathan Smith 0000-0002-8577-3023 Leslie Anne Campbell 0000-0003-2534-0450 Candice Crocker 0000-0001-8102-1716 Phillip Tibbo 0000-0002-2070-6495 References Anderson, K. K., Norman, R., MacDougall, A. G., Edwards, J., Palaniyappan, L., Lau, C., & Kurdyak, P. (2018). Disparities in Access to Early Psychosis Intervention Services: Comparison of Service Users and Nonusers in Health Administrative Data. The Canadian Journal of Psychiatry , 63 (6), 395–403. doi: 10.1177/0706743718762101Canadian Institute for Health Information. (2022). Canadian coding standards for version 2022 ICD-10-CA and CCI . Ottawa, ON: CIHI. Retrieved from https://secure.cihi.ca/free_products/canadian-coding-standards-2022-en.pdfCorrell, C. 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Early intervention in psychosis services: A systematic review and narrative synthesis of barriers and facilitators to seeking access. European Psychiatry , 66 (1), e92. doi: 10.1192/j.eurpsy.2023.2465 Information & Authors Information Version history V1 Version 1 14 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords early intervention early psychosis health services research psychotic disorders treatment engagement Authors Affiliations Nathan K. Smith 0000-0002-8577-3023 [email protected] Dalhousie University Department of Community Health and Epidemiology View all articles by this author Leslie Anne Campbell 0000-0003-2534-0450 Dalhousie University View all articles by this author Candice Crocker Dalhousie University Department of Psychiatry View all articles by this author Philip Tibbo Dalhousie University Department of Psychiatry View all articles by this author Metrics & Citations Metrics Article Usage 147 views 59 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Nathan K. Smith, Leslie Anne Campbell, Candice Crocker, et al. Client Engagement with an Early Psychosis Program and Post-Program Health Service Use: A Retrospective Cohort Study. Authorea . 14 January 2026. DOI: https://doi.org/10.22541/au.176837955.56188058/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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