Predictors of Dropout From Cognitive-Behavioral Group Treatment for Panic Disorder With Agoraphobia

Bélanger, Claude; Courchesne, Catherine; Leduc, Andréa G.; Dugal, Caroline; El‐Baalbaki, Ghassan; Marchand, André; Godbout, Natacha; Marcaurelle, Roger; Perreault, Michel

doi:10.1177/0145445516656614

Cited by 6 publications

(5 citation statements)

References 61 publications

(123 reference statements)

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“…; DSM - 5 ; American Psychiatric Association [APA], 2013) defines panic disorder (PD) as recurrent and unexpected panic attacks followed by concerns about their consequences for physical or social aspects. The estimated 12-month prevalence of PD in adults and adolescents across the United States and several European countries is around 2% to 3% (Bélanger et al, 2017). PD has a high comorbidity with agoraphobia disorder, with agoraphobic symptoms estimated to affect between 33% and 50% of patients with PD.…”

Section: Theoretical and Research Basis For Treatmentmentioning

confidence: 99%

Enhancing In Vivo Exposure in the Treatment of Panic Disorder and Agoraphobia Using Location-Based Technologies: A Case Study

Miralles

Granell

García‐Palacios

et al. 2019

Clinical Case Studies

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Panic disorder (PD) is quite prevalent and often appears along with agoraphobia (PD/A). The treatment of choice is cognitive behavioral therapy (CBT). Transdiagnostic intervention, an emotion-focused, cognitive behavioral intervention that has led to the Unified Protocol (UP), emphasizes the common underlying mechanisms that contribute to the development and maintenance of emotional disorders such as PD/A. A core feature of this treatment approach is in vivo exposure (IVE) to feared situations, which aims to prevent avoidance behaviors and encourages the patient to confront feared situations gradually. It is a difficult component for patients, especially when implementing the exposure on their own. Different feedback formats can be used to increase adequate IVE and reduce overt or subtle avoidance. The use of smartphones is a very useful option to initiate and sustain exposure behavior. The purpose of this study is to describe the use of location-based technologies (LBTs) during the IVE component of the UP treatment of a 47-year-old patient with PD/A. The acceptability and usability of the system were assessed. The Symptoms platform was employed during the exposure module, using LBT with a smartphone app. The patient reported positive expectations, high satisfaction scores, and an overall satisfactory experience. Enhancing key therapeutic components during treatment through the development of media-based tools is a very promising future research aim, and the possibility of using advanced smartphone features should be explored.

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Section: Theoretical and Research Basis For Treatmentmentioning

confidence: 99%

Enhancing In Vivo Exposure in the Treatment of Panic Disorder and Agoraphobia Using Location-Based Technologies: A Case Study

Miralles

Granell

García‐Palacios

et al. 2019

Clinical Case Studies

View full text Add to dashboard Cite

show abstract

“…In clinical practice and research, dropout during intervention is an important problem. Particularly, in the course of CBT for PD, a lot of participants leave treatment prematurely [2]. Regarding CBT for PD, personality traits have been suggested as a predictor of treatment efficacy [3].…”

Section: Introductionmentioning

confidence: 99%

“…Regarding CBT for PD, personality traits have been suggested as a predictor of treatment efficacy [3]. However, the predictors of dropping out from this intervention are not fully understood, with the exception of pre-treatment depression [2].…”

Section: Introductionmentioning

confidence: 99%

Predicting Dropout From Cognitive Behavioral Therapy for Panic Disorder Using Machine Learning Algorithms

Ogawa

2024

J Clin Med Res

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Background: Attrition is an important problem in clinical practice and research. However, the predictors of dropping out from cognitive behavioral therapy (CBT) for panic disorder (PD) are not fully understood. In this study, we aimed to build a dropout prediction model for CBT for PD using machine learning (ML) algorithms. Methods:We treated 208 patients with PD applying group CBT. From baseline data, the prediction analysis was carried out using two ML algorithms, random forest and light gradient boosting machine. The baseline data included five personality dimensions in NEO Five Factor Index, depression subscale of Symptom Checklist-90 Revised, age, sex, and Panic Disorder Severity Scale.Results: Random forest identified dropout during CBT for PD showing that the accuracy of prediction was 88%. Light gradient boosting machine showed that the accuracy was 85%. Conclusions:The ML algorithms could detect dropout after CBT for PD with relatively high accuracy. For the purpose of clinical decisionmaking, we could use this ML method. This study was conducted as a naturalistic study in a routine clinical setting. Therefore, our results in ML approach could be generalized to regular clinical settings.

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“…Even when individuals with AD enroll in treatment, they do not necessarily receive adequate therapy in terms of type or dosage, nor do they always complete a treatment. They may drop out of therapy (Fernandez et al 2015 ; Taylor et al 2012 ) prematurely, depending for example on attitudes and expectations towards treatment (Bélanger et al 2017 ; Santana and Fontenelle 2011 ). Treatment dropout is typically associated with increased economic costs of the illness (Konnopka et al 2009 ; Wittchen et al 2011 ).…”

Section: Introductionmentioning

confidence: 99%

Help-Seeking Behavior and Treatment Barriers in Anxiety Disorders: Results from a Representative German Community Survey

Heinig

Wittchen

Knappe

2021

Community Ment Health J

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Although effective therapies exist, treatment rates of anxiety disorders (AD) are low, raising the question why affected individuals do not receive treatment. We provide data from the nationally representative German Health Interview and Examination Survey-2011 (DEGS1) on the help-seeking behavior and perceived treatment barriers of 650 subjects with Diagnostic and Statistical Manual of Mental Disorders’ (DSM-IV AD). Only 26% of all cases with AD in the community reported having had contact with mental health services because of their anxiety problems in their lifetime. 16% were currently receiving professional help, most frequently by psychotherapists (8%), psychiatrists (5%) and general practitioners (5%). 40% of all cases never even considered seeking help and 31% reported barriers to treatment, such as self-reliance (18%) or beliefs that treatments were ineffective (9%), unavailable (8%) or too stigmatizing (7%). Measures to increase treatment rates should thus target individual as well as public attitudes and health literacy to increase awareness of and access to evidence-based interventions.

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Predictors of Dropout From Cognitive-Behavioral Group Treatment for Panic Disorder With Agoraphobia

Cited by 6 publications

References 61 publications

Enhancing In Vivo Exposure in the Treatment of Panic Disorder and Agoraphobia Using Location-Based Technologies: A Case Study

Enhancing In Vivo Exposure in the Treatment of Panic Disorder and Agoraphobia Using Location-Based Technologies: A Case Study

Predicting Dropout From Cognitive Behavioral Therapy for Panic Disorder Using Machine Learning Algorithms

Help-Seeking Behavior and Treatment Barriers in Anxiety Disorders: Results from a Representative German Community Survey

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