Comparing effects of detached mindfulness and cognitive restructuring in obsessive‐compulsive disorder using ecological momentary assessment

Rupp, Christian; Gühne, Daniela; Falke, Charlotte; Doebler, Philipp; Andor, Fabian; Buhlmann, Ulrike

doi:10.1002/cpp.2418

Cited by 10 publications

(6 citation statements)

References 23 publications

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“…The data were quite noisy; however, approximately 28.11% (851/3027) of the noise was removed during data cleansing [ 58 ]. A separate study assessed the results of these psychotherapy interventions and found no significant differences between the detached mindfulness and cognitive restructuring therapies in the frequency of their use, perceived difficulty, or the experience of relief after treatment [ 60 ].…”

Section: Resultsmentioning

confidence: 99%

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

Frank¹,

Li²,

Peterson³

et al. 2023

JMIR Ment Health

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Background Smartphones and wearable biosensors can continuously and passively measure aspects of behavior and physiology while also collecting data that require user input. These devices can potentially be used to monitor symptom burden; estimate diagnosis and risk for relapse; predict treatment response; and deliver digital interventions in patients with obsessive-compulsive disorder (OCD), a prevalent and disabling psychiatric condition that often follows a chronic and fluctuating course and may uniquely benefit from these technologies. Objective Given the speed at which mobile and wearable technologies are being developed and implemented in clinical settings, a continual reappraisal of this field is needed. In this scoping review, we map the literature on the use of wearable devices and smartphone-based devices or apps in the assessment, monitoring, or treatment of OCD. Methods In July 2022 and April 2023, we conducted an initial search and an updated search, respectively, of multiple databases, including PubMed, Embase, APA PsycINFO, and Web of Science, with no restriction on publication period, using the following search strategy: (“OCD” OR “obsessive” OR “obsessive-compulsive”) AND (“smartphone” OR “phone” OR “wearable” OR “sensing” OR “biofeedback” OR “neurofeedback” OR “neuro feedback” OR “digital” OR “phenotyping” OR “mobile” OR “heart rate variability” OR “actigraphy” OR “actimetry” OR “biosignals” OR “biomarker” OR “signals” OR “mobile health”). Results We analyzed 2748 articles, reviewed the full text of 77 articles, and extracted data from the 25 articles included in this review. We divided our review into the following three parts: studies without digital or mobile intervention and with passive data collection, studies without digital or mobile intervention and with active or mixed data collection, and studies with a digital or mobile intervention. Conclusions Use of mobile and wearable technologies for OCD has developed primarily in the past 15 years, with an increasing pace of related publications. Passive measures from actigraphy generally match subjective reports. Ecological momentary assessment is well tolerated for the naturalistic assessment of symptoms, may capture novel OCD symptoms, and may also document lower symptom burden than retrospective recall. Digital or mobile treatments are diverse; however, they generally provide some improvement in OCD symptom burden. Finally, ongoing work is needed for a safe and trusted uptake of technology by patients and providers.

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Section: Resultsmentioning

confidence: 99%

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

Frank¹,

Li²,

Peterson³

et al. 2023

JMIR Ment Health

View full text Add to dashboard Cite

show abstract

“…Ecological momentary assessment is accepted as an important and reliable evaluation in demonstrating the efficacy of treatment of OCD. 35 In this context, in a study, the authors compared the effectiveness of detached mindfulness (DM) and cognitive restructuring in patients with OCD received in a randomized manner to the treatment groups. As a result of this study, the researchers reported that DM and cognitive restructuring methods showed similar results.…”

Section: Resultsmentioning

confidence: 99%

“…As a result of this study, the researchers reported that DM and cognitive restructuring methods showed similar results. 35 In a controlled study in a randomized manner on patients with OCD, a study team compared the efficacy of the MCT with ERP in 100 patients diagnosed with OCD in an outpatient setting and planned to examine the treatment effect of 2 modalities, measured by Y-BOCS at the beginning, after the treatment period, and at 6 and 30 months follow-up. 16 In this ongoing registered trial, investigators aimed to see that the MCT would have a potential effect compared to the ERP which is the gold standard psychotherapeutic approach in OCD treatment.…”

Section: Resultsmentioning

confidence: 99%

Metacognitive Therapy in Patients with ObsessiveCompulsive Disorder: A review

Atmaca¹

2022

ALPHA PSYCHIATRY

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Metacognitive therapy is a relatively novel and growing psychotherapeutic approach. Within the last 20 years, several metacognitive-oriented therapy methods have been developed. They are metacognitive therapy which was developed by Wells, metacognitive training which was produced by Moritz et al. especially for patients with psychotic disorder, and metacognitive reflection and insight therapy for psychotic patients. Among them, the most structured one seems the metacognitive therapy. The main notion of metacognitive therapy is to alter the dysfunctional metacognitive interpretations and strategies underlying psychopathology. However, it should be emphasized that it has some fundamental differences from cognitive behavioral therapy because metacognitive therapy is a relatively new school of cognitive therapy, its effectiveness in the treatment of many psychiatric disorders continues to be evaluated intensively. Obsessive-compulsive disorder is one of these disorders. As obsessive-compulsive disorder is a lifelong disorder that causes significant loss of workforce and pharmacotherapy is sometimes insufficient, psychotherapeutic approaches are of great importance. In this context, exposure and response prevention still seems to be an important treatment option in terms of psychotherapeutic approaches. However, it is clear that a new approach is required in psychiatry practice in cases where exposure and response prevention and classical cognitive behavioral therapy are not sufficient and remain with residual symptoms. In this respect, metacognitive therapy can be an important alternative to fill this gap. However, more evidence needs to be created with studies with much larger samples.

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“…For the early diagnosis of tristimania, the current clinical diagnosis of tristimania has many obvious shortcomings, including patient denial, poor sensitivity and subjective bias, which can lead to inaccurate diagnosis results, thus affecting the timely treatment of patients and resulting in illness delay. In general, compared with language and facial expressions, physiological signals can relatively and objectively reflect the dynamic changes of the central nervous system and have been applied in various studies [3].…”

Section: Introductionmentioning

confidence: 99%

Multi-feature data fusion based on common space model and recurrent convolutional neural networks for EEG tristimania recognition used in upper limb rehabilitation exercises

Sun¹

2018

ICST Transactions on Scalable Information Systems

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Traditional tristimania recognition methods cannot accurately recognize the mood of patients, which cannot provide effective adjuvant therapy for rehabilitation. Therefore, this paper proposes a new multi-feature data fusion method for Electroencephalography (EEG) tristimania recognition. It combines common space model and recurrent convolutional neural networks to classify the tristimania group and control group. According to the phase lock value, the phase synchronization functional network between electrode channels is constructed, and the functional connection modes of two kinds under different frequency bands are analyzed. The Xception network and LSTM are used as two non-interfering parts to extract two feature matrices from EEG tristimania signals. They are fused into a single feature matrix by merge algorithm. The single feature matrix is input into the recurrent convolutional neural networks (RCNN) for feature extraction and pooling. L2 regularized Softmax function is used as the classifier to complete the training and testing of RCNN. Finally, combining the Fisher score feature selection method and the classifier dependency structure, a low dimensional and efficient feature subset is obtained. Experimental results on public tristimania data sets validate that the proposed method has better effect in terms of accuracy and PLV compared with other strategies.

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Comparing effects of detached mindfulness and cognitive restructuring in obsessive‐compulsive disorder using ecological momentary assessment

Cited by 10 publications

References 23 publications

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

Metacognitive Therapy in Patients with ObsessiveCompulsive Disorder: A review

Multi-feature data fusion based on common space model and recurrent convolutional neural networks for EEG tristimania recognition used in upper limb rehabilitation exercises

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