Empirically-derived response trajectories of intensive residential treatment in obsessive-compulsive disorder: A growth mixture modeling approach

Falkenstein, Martha J.; Nota, Jacob A.; Krompinger, Jason W.; Schreck, Meghan; Garner, Lauryn E.; Potluri, Sriramya; Kirk, Nathaniel Van; Ponzini, Gabriella T.; Tifft, Eric D.; Brennan, Brian P.; Mathes, Brittany M.; Cattie, Jordan E.; Crosby, Jesse M.; Elias, Jason A.

doi:10.1016/j.jad.2018.11.075

Cited by 17 publications

(13 citation statements)

References 27 publications

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“…To the best of our knowledge, only two other centers have reported outcomes of such intensive residential/inpatient care in large samples, one being the McLean Hospital at Harvard in United States 5,[37][38][39][40][41] and the other being the National Health Service (NHS) in United Kingdom. 6 To put our findings in perspective, the similarities and differences in clinical characteristics of these two studies with those of our study have to be kept in mind.…”

Section: Discussionmentioning

confidence: 99%

Long-term Outcomes of Intensive Inpatient Care for Severe, Resistant Obsessive-Compulsive Disorder: Résultats à long terme de soins intensifs à des patients hospitalisés pour un trouble obsessionnel-compulsif grave et résistant

et al. 2020

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Objective: A substantial proportion of severely ill patients with obsessive-compulsive disorder (OCD) do not respond to serotonin reuptake inhibitors (SRIs) and are unable to practice cognitive behavioral therapy (CBT) on an out-patient basis. We report the short-term (at discharge) and long-term (up to 2 years) outcome of a multimodal inpatient treatment program that included therapist-assisted intensive CBT with adjunctive pharmacotherapy for severely ill OCD patients who are often resistant to SRIs and are either unresponsive or unable to practice outpatient CBT. Methods: A total of 420 patients, admitted between January 2012 and December 2017 were eligible for the analysis. They were evaluated using the Mini International Neuropsychiatric Interview, the Yale-Brown Obsessive Compulsive Scale (YBOCS), and the Clinical Global Impression (CGI) scale. All patients received 4 to 5 therapist-assisted CBT sessions per week along with standard pharmacotherapy. Naturalistic follow-up information at 3, 6, 12, and 24 months were recorded. Results: At baseline, patients were mostly severely ill (YBOCS = 29.9 ± 4.5) and nonresponsive to ≥2 SRIs (83%). Mean duration of inpatient stay was 42.7 ± 25.3 days. At discharge, there was a significant decline in the mean YBOCS score (29.9 ± 4.5 vs. 18.1 ± 7.7, P < .001, Cohen’s d = 1.64); 211/420 (50%) were responders (≥35% YBOCS reduction and CGI-I≤2) and an additional 86/420 (21%) were partial responders (25% to 35% YBOCS reduction and CGI-I≤3). Using latent class growth modeling of the follow-up data, 4 distinct classes were identified, which include “remitters” (14.5%), “responders” (36.5%), “minimal responders” (34.7%), and “nonresponders” (14.6%). Shorter duration of illness, better insight, and lesser contamination/washing symptoms predicted better response in both short- and long-term follow-up. Conclusion: Intensive, inpatient-based care for OCD may be an effective option for patients with severe OCD and should be considered routinely in those who do not respond with outpatient treatment.

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Section: Discussionmentioning

confidence: 99%

Long-term Outcomes of Intensive Inpatient Care for Severe, Resistant Obsessive-Compulsive Disorder: Résultats à long terme de soins intensifs à des patients hospitalisés pour un trouble obsessionnel-compulsif grave et résistant

et al. 2020

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“…The comprehensive nature of the program allows treatment to focus each patient's primary and comorbid conditions. The program is heavily organized around exposure therapy for OCD, however, any OCRD can be the target of treatment (see Falkenstein et al, 2019). Admission decisions are based on several factors including (a) the nature of the psychopathology (i.e., primary OCRDs), (b) clinical severity (e.g., patient need to show insufficient response to outpatient level of care), (c) other clinical considerations (e.g., acute suicidality needs to be stabilized before admission), (d) insurance coverage or ability for self-pay, and (e) other factors (e.g., geographic location and practical considerations).…”

Section: Participants and Treatment Settingmentioning

confidence: 99%

Higher order compulsivity versus grooming dimensions as treatment targets for the DSM‐5 obsessive–compulsive and related disorders

Snorrason

Conway

Falkenstein

et al. 2021

Depression and Anxiety

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Background: Transdiagnostic definitions of obsessive-compulsive and related disorders (OCRDs) may represent useful treatment targets. The current study sought to characterize higher order dimensions underpinning the OCRDs in the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition, and examine their course during treatment. Methods: Adult patients (N = 407) completed measures of OCRDs, depression, and worry before and after intensive/residential treatment for OCRDs. Structural equation modeling was used to examine the comorbidity structure and temporal course of the symptoms. Results: Covariation of the symptoms was best represented by three dimensions: distress (depression and worry), compulsivity (obsessive-compulsive disorder, hoarding, and body dysmorphia), and grooming (hair pulling and skin picking). Latent change score modeling revealed significant reduction in the means of all three dimensions across treatment (Cohen's ds = −1.04, −0.62, and −0.23 for distress, compulsivity, and grooming, respectively). There was a strong correlation between change in compulsivity and grooming (r = .67) and change in compulsivity and distress (r = .80), but a small correlation between change in grooming and distress (r = .35). Conclusions:The results indicate that OCRDs are underpinned by higher order compulsivity and grooming dimensions that differ in their association with distress.The results further suggest that the two dimensions may reflect promising intervention targets suitable for transdiagnostic treatment protocols.

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“…The latter is captured by the variances and covariances of subject-specific random effects. More recently, the focus of modelling such data has moved towards investigating whether there are multiple typical trajectories (see for example adolescent smoking [3], treatment response [4] and comorbidity [5]), leading to the characterisation of latent subgroups of individuals who share a common profile over time. Such groups are often referred to as "phenotypes" (e.g., early onset versus late onset of illness).…”

Section: Introductionmentioning

confidence: 99%

Identifying typical trajectories in longitudinal data: modelling strategies and interpretations

et al. 2020

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Individual-level longitudinal data on biological, behavioural, and social dimensions are becoming increasingly available. Typically, these data are analysed using mixed effects models, with the result summarised in terms of an average trajectory plus measures of the individual variations around this average. However, public health investigations would benefit from finer modelling of these individual variations which identify not just one average trajectory, but several typical trajectories. If evidence of heterogeneity in the development of these variables is found, the role played by temporally preceding (explanatory) variables as well as the potential impact of differential trajectories may have on later outcomes is often of interest. A wide choice of methods for uncovering typical trajectories and relating them to precursors and later outcomes exists. However, despite their increasing use, no practical overview of these methods targeted at epidemiological applications exists. Hence we provide: (a) a review of the three most commonly used methods for the identification of latent trajectories (growth mixture models, latent class growth analysis, and longitudinal latent class analysis); and (b) recommendations for the identification and interpretation of these trajectories and of their relationship with other variables. For illustration, we use longitudinal data on childhood body mass index and parental reports of fussy eating, collected in the Avon Longitudinal Study of Parents and Children.

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Empirically-derived response trajectories of intensive residential treatment in obsessive-compulsive disorder: A growth mixture modeling approach

Cited by 17 publications

References 27 publications

Long-term Outcomes of Intensive Inpatient Care for Severe, Resistant Obsessive-Compulsive Disorder: Résultats à long terme de soins intensifs à des patients hospitalisés pour un trouble obsessionnel-compulsif grave et résistant

Long-term Outcomes of Intensive Inpatient Care for Severe, Resistant Obsessive-Compulsive Disorder: Résultats à long terme de soins intensifs à des patients hospitalisés pour un trouble obsessionnel-compulsif grave et résistant

Higher order compulsivity versus grooming dimensions as treatment targets for the DSM‐5 obsessive–compulsive and related disorders

Identifying typical trajectories in longitudinal data: modelling strategies and interpretations

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