Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis
BackgroundThe youth mental health crisis in the United States continues to worsen, and research has shown poor mental health treatment engagement. Despite the need for personalized engagement strategies, there is a lack of research involving youth. Due to complex youth develo...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2023-09-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2023/1/e47917 |
| _version_ | 1797690535587086336 |
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| author | Kate Gliske Katie R Berry Jaime Ballard Clare Schmidt Elizabeth Kroll Jonathan Kohlmeier Michael Killian Caroline Fenkel |
| author_facet | Kate Gliske Katie R Berry Jaime Ballard Clare Schmidt Elizabeth Kroll Jonathan Kohlmeier Michael Killian Caroline Fenkel |
| author_sort | Kate Gliske |
| collection | DOAJ |
| description |
BackgroundThe youth mental health crisis in the United States continues to worsen, and research has shown poor mental health treatment engagement. Despite the need for personalized engagement strategies, there is a lack of research involving youth. Due to complex youth developmental milestones, there is a need to better understand clinical presentation and factors associated with treatment engagement to effectively identify and tailor beneficial treatments.
ObjectiveThis quality improvement investigation sought to identify subgroups of clients attending a remote intensive outpatient program (IOP) based on clinical acuity data at intake, to determine the factors associated with engagement outcomes for clients who present in complex developmental periods and with cooccurring conditions. The identification of these subgroups was used to inform programmatic decisions within this remote IOP system.
MethodsData were collected as part of ongoing quality improvement initiatives at a remote IOP for youth and young adults. Participants included clients (N=2924) discharged between July 2021 and February 2023. A latent profile analysis was conducted using 5 indicators of clinical acuity at treatment entry, and the resulting profiles were assessed for associations with demographic factors and treatment engagement outcomes.
ResultsAmong the 2924 participants, 4 profiles of clinical acuity were identified: a low-acuity profile (n=943, 32.25%), characterized by minimal anxiety, depression, and self-harm, and 3 high-acuity profiles defined by moderately severe depression and anxiety but differentiated by rates of self-harm (high acuity+low self-harm: n=1452, 49.66%; high acuity+moderate self-harm: n=203, 6.94%; high acuity+high self-harm: n=326, 11.15%). Age, gender, transgender identity, and sexual orientation were significantly associated with profile membership. Clients identified as sexually and gender-marginalized populations were more likely to be classified into high-acuity profiles than into the low-acuity profile (eg, for clients who identified as transgender, high acuity+low self-harm: odds ratio [OR] 2.07, 95% CI 1.35-3.18; P<.001; high acuity+moderate self-harm: OR 2.85, 95% CI 1.66-4.90; P<.001; high acuity+high self-harm: OR 3.67, 95% CI 2.45-5.51; P<.001). Race was unrelated to the profile membership. Profile membership was significantly associated with treatment engagement: youth and young adults in the low-acuity and high-acuity+low–self-harm profiles attended an average of 4 fewer treatment sessions compared with youth in the high-acuity+moderate–self-harm and high-acuity+high–self-harm profiles (ꭓ23=27.6, P<.001). Individuals in the high-acuity+low–self-harm profile completed treatment at a significantly lower rate relative to the other 2 high-acuity profiles (ꭓ23=13.4, P=.004). Finally, those in the high-acuity+high–self-harm profile were significantly less likely to disengage early relative to youth in all other profiles (ꭓ23=71.12, P<.001).
ConclusionsThis investigation represents a novel application for identifying subgroups of adolescents and young adults based on clinical acuity data at intake to identify patterns in treatment engagement outcomes. Identifying subgroups that differentially engage in treatment is a critical first step toward targeting engagement strategies for complex populations. |
| first_indexed | 2024-03-12T02:00:51Z |
| format | Article |
| id | doaj.art-062094cc9621451fa5920dc86fc00542 |
| institution | Directory Open Access Journal |
| issn | 2561-326X |
| language | English |
| last_indexed | 2024-03-12T02:00:51Z |
| publishDate | 2023-09-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj.art-062094cc9621451fa5920dc86fc005422023-09-07T13:02:25ZengJMIR PublicationsJMIR Formative Research2561-326X2023-09-017e4791710.2196/47917Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile AnalysisKate Gliskehttps://orcid.org/0000-0001-6109-3624Katie R Berryhttps://orcid.org/0000-0001-8340-3259Jaime Ballardhttps://orcid.org/0000-0002-2506-9034Clare Schmidthttps://orcid.org/0000-0002-4493-5591Elizabeth Krollhttps://orcid.org/0009-0008-1840-3939Jonathan Kohlmeierhttps://orcid.org/0000-0002-3571-8210Michael Killianhttps://orcid.org/0000-0002-2287-9007Caroline Fenkelhttps://orcid.org/0000-0003-0601-9020 BackgroundThe youth mental health crisis in the United States continues to worsen, and research has shown poor mental health treatment engagement. Despite the need for personalized engagement strategies, there is a lack of research involving youth. Due to complex youth developmental milestones, there is a need to better understand clinical presentation and factors associated with treatment engagement to effectively identify and tailor beneficial treatments. ObjectiveThis quality improvement investigation sought to identify subgroups of clients attending a remote intensive outpatient program (IOP) based on clinical acuity data at intake, to determine the factors associated with engagement outcomes for clients who present in complex developmental periods and with cooccurring conditions. The identification of these subgroups was used to inform programmatic decisions within this remote IOP system. MethodsData were collected as part of ongoing quality improvement initiatives at a remote IOP for youth and young adults. Participants included clients (N=2924) discharged between July 2021 and February 2023. A latent profile analysis was conducted using 5 indicators of clinical acuity at treatment entry, and the resulting profiles were assessed for associations with demographic factors and treatment engagement outcomes. ResultsAmong the 2924 participants, 4 profiles of clinical acuity were identified: a low-acuity profile (n=943, 32.25%), characterized by minimal anxiety, depression, and self-harm, and 3 high-acuity profiles defined by moderately severe depression and anxiety but differentiated by rates of self-harm (high acuity+low self-harm: n=1452, 49.66%; high acuity+moderate self-harm: n=203, 6.94%; high acuity+high self-harm: n=326, 11.15%). Age, gender, transgender identity, and sexual orientation were significantly associated with profile membership. Clients identified as sexually and gender-marginalized populations were more likely to be classified into high-acuity profiles than into the low-acuity profile (eg, for clients who identified as transgender, high acuity+low self-harm: odds ratio [OR] 2.07, 95% CI 1.35-3.18; P<.001; high acuity+moderate self-harm: OR 2.85, 95% CI 1.66-4.90; P<.001; high acuity+high self-harm: OR 3.67, 95% CI 2.45-5.51; P<.001). Race was unrelated to the profile membership. Profile membership was significantly associated with treatment engagement: youth and young adults in the low-acuity and high-acuity+low–self-harm profiles attended an average of 4 fewer treatment sessions compared with youth in the high-acuity+moderate–self-harm and high-acuity+high–self-harm profiles (ꭓ23=27.6, P<.001). Individuals in the high-acuity+low–self-harm profile completed treatment at a significantly lower rate relative to the other 2 high-acuity profiles (ꭓ23=13.4, P=.004). Finally, those in the high-acuity+high–self-harm profile were significantly less likely to disengage early relative to youth in all other profiles (ꭓ23=71.12, P<.001). ConclusionsThis investigation represents a novel application for identifying subgroups of adolescents and young adults based on clinical acuity data at intake to identify patterns in treatment engagement outcomes. Identifying subgroups that differentially engage in treatment is a critical first step toward targeting engagement strategies for complex populations.https://formative.jmir.org/2023/1/e47917 |
| spellingShingle | Kate Gliske Katie R Berry Jaime Ballard Clare Schmidt Elizabeth Kroll Jonathan Kohlmeier Michael Killian Caroline Fenkel Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis JMIR Formative Research |
| title | Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis |
| title_full | Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis |
| title_fullStr | Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis |
| title_full_unstemmed | Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis |
| title_short | Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis |
| title_sort | predicting youth and young adult treatment engagement in a transdiagnostic remote intensive outpatient program latent profile analysis |
| url | https://formative.jmir.org/2023/1/e47917 |
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