Distinctive Trajectory Groups of Mental Health Functioning among Assertive Community Treatment Clients: An Application of Growth Mixture Modelling Analysis

Wilk, Piotr; Vingilis, Evelyn; Bishop, Joan; He, Wenqing; Braun, John R.; Forchuk, Cheryl; Seeley, Jane; Mitchell, Beth

doi:10.1177/070674371305801204

Cited by 5 publications

(3 citation statements)

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“…Thus, its strength is to ''identify rather than assume distinctive groups of trajectories.'' 14(p139) GMM has been used to study trajectories in substance use, [17][18][19][20][21][22] criminal behaviour, 23,24 mental illness, [25][26][27] and risky behaviours in specific samples, 28 as well as to describe the natural history of phenomena 27 and response to interventions, 24,29 including randomised trials. 30 To our knowledge, however, only 3 studies have used GMM to examine trajectories of housing stability as an outcome among homeless individuals.…”

Section: Limitationsmentioning

confidence: 99%

“…The literature on outcomes of HF programs is rich, but there is less coherent literature on the predictors of housing outcomes in homeless individuals with mental health issues specifically, but variables likely to be important were inferred from research on broader outcomes such as QoL or studies including homelessness among other variables for high-risk populations. 26,43,44 These studies identified that severity of mental illness, poor physical health, the presence of chronic medical conditions, lack of social support, and victimization are important. We also used the original HF logic model, qualitative findings from a 10% sample of trial participants interviewed at baseline and 18 months, 12,45 and quantitative analyses for 2 subsamples (predictors of persistent homelessness in one site and predictors for those in the intervention that did not achieve stable housing 46,47 ) to build an initial theoretical model of the variables (and their timing) that might distinguish trajectories ( Figure 1).…”

Section: The Modelling Approachmentioning

confidence: 99%

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Outcome Trajectories among Homeless Individuals with Mental Disorders in a Multisite Randomised Controlled Trial of Housing First

et al. 2016

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Purpose: Housing First (HF) has been shown to improve housing stability, on average, for formerly homeless adults with mental illness. However, little is known about patterns of change and characteristics that predict different outcome trajectories over time. This article reports on latent trajectories of housing stability among 2140 participants (84% followed 24 months) of a multisite randomised controlled trial of HF.Methods: Data were analyzed using generalised growth mixture modeling for the total cohort. Predictor variables were chosen based on the original program logic model and detailed reviews of other qualitative and quantitative findings. Treatment group assignment and level of need at baseline were included in the model. Results: In total, 73% of HF participants and 43% of treatment-as-usual (TAU) participants were in stable housing after 24 months of follow-up. Six trajectories of housing stability were identified for each of the HF and TAU groups. Variables that distinguished different trajectories included gender, age, prior month income, Aboriginal status, total time homeless, previous hospitalizations, overall health, psychiatric symptoms, and comorbidity, while others such as education, diagnosis, and substance use problems did not.

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Section: Limitationsmentioning

confidence: 99%

Section: The Modelling Approachmentioning

confidence: 99%

Outcome Trajectories among Homeless Individuals with Mental Disorders in a Multisite Randomised Controlled Trial of Housing First

et al. 2016

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“…12 and 15 months post-baseline in COMBINE and Project MATCH, respectively). Given previous studies demonstrating heterogeneity of treatment response [17][18][19], we hypothesized those individuals who exceeded heavy drinking limits (i.e. treatment 'failures') would be a heterogeneous group defined by subsets of individuals with discrete levels of psychosocial functioning.…”

Section: Purposementioning

confidence: 99%

Finding success in failure: using latent profile analysis to examine heterogeneity in psychosocial functioning among heavy drinkers following treatment

et al. 2016

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Aims To estimate differences in post-treatment psychosocial functioning among treatment “failures” (i.e., heavy drinkers, defined as 4+/5+ drinks for women/men) from two large multi-site clinical trials, and to compare these levels of functioning to those of the purported treatment “successes” (i.e., non-heavy drinkers). Design Separate latent profile analyses of data from COMBINE and Project MATCH, comparing psychosocial outcomes across derived classes of heterogeneous treatment responders. Setting Eleven U.S. academic sites in COMBINE, 27 U.S. treatment sites local to nine research sites in Project MATCH. Participants 962 individuals in COMBINE (69% male, 77% white, mean age: 44 years) treated January 2001 to January 2004 and 1,528 individuals in Project MATCH (75% male, 80% white, mean age: 40 years) treated April 1991 to September 1994. Measurements In COMBINE, we analyzed health, quality of life, mental health symptoms, and alcohol consequences 12-months post-baseline. In Project MATCH, we examined social functioning, mental health symptoms, and alcohol consequences 15-months post-baseline. Findings Latent profile analysis of measures of functioning in both samples supported a three-profile solution for the group of treatment “failures,” characterized by high-functioning, average-functioning, and low-functioning individuals. The high-functioning treatment “failures” were generally performing better across measures of psychosocial functioning at follow-up than participants designated treatment “successes” by virtue of being abstainers or light drinkers. Conclusions Current Food and Drug Administration guidance to use heavy drinking as indicative of treatment “failure” fails to take into account substantial psychosocial improvements made by individuals who continue to occasionally drink heavily post-treatment.

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The modeling of trajectories in psychotic illness

Clark

Schubert

Baune

2020

Personalized Psychiatry

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Distinctive Trajectory Groups of Mental Health Functioning among Assertive Community Treatment Clients: An Application of Growth Mixture Modelling Analysis

Abstract: Our study suggests general stability in overall functioning for the sampled ACT clients over 2 years, but significant heterogeneity in trajectories of functioning.

Cited by 5 publications

References 68 publications

Outcome Trajectories among Homeless Individuals with Mental Disorders in a Multisite Randomised Controlled Trial of Housing First

Outcome Trajectories among Homeless Individuals with Mental Disorders in a Multisite Randomised Controlled Trial of Housing First

Finding success in failure: using latent profile analysis to examine heterogeneity in psychosocial functioning among heavy drinkers following treatment

The modeling of trajectories in psychotic illness

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