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Skjold SH, Hagen K, Wheaton MG, Kallestad H, Hjelle KM, Björgvinsson T, Hansen B. Insomnia as a predictor of treatment outcomes in adolescents receiving concentrated exposure treatment for OCD. BMC Psychiatry 2024; 24:702. [PMID: 39425125 PMCID: PMC11492211 DOI: 10.1186/s12888-024-06183-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 10/14/2024] [Indexed: 10/21/2024] Open
Abstract
BACKGROUND Research suggests that individuals with obsessive-compulsive disorder (OCD) frequently experience insomnia. Some previous studies have suggested that insomnia may predict treatment outcomes, but the evidence is limited, especially for adolescents. This study examined the prevalence of insomnia in an adolescent OCD patient sample, explored the correlation between OCD and insomnia, and tested whether levels of insomnia at baseline predict outcomes for adolescent patients receiving the Bergen 4-Day Treatment (B4DT) for OCD. METHODS Forty-three adolescent OCD patients who received B4DT were selected for this study. Treatment outcome was quantified as change in Children Yale-Brown Obsessive Compulsive Scale (CY-BOCS) scores across time from pre- to posttreatment and 3-month follow-up. Insomnia symptoms were measured by the Bergen Insomnia Scale (BIS). Linear mixed models were used to examine the relationship between the BIS and changes in CY-BOCS scores. We controlled for symptoms of general anxiety disorder measured by the GAD-7 and depression symptoms measured by the PHQ-9. RESULTS In this sample, 68.4% of the patients scored above the cutoff for insomnia on the BIS. There was a moderate correlation between baseline CY-BOCS and BIS that did not reach statistical significance (r = .32, p = .051). High BIS scores before treatment were significantly associated with poorer treatment outcomes, as measured by changes in CY-BOCS over time (p = .002). The association between baseline insomnia and change in OCD symptoms remained significant (p = .033) while controlling for GAD-7 and PHQ-9. CONCLUSION Insomnia is common among adolescents with OCD, and these data suggest that these patients may be at increased risk for poor treatment outcomes. Future research to explore mechanisms and adjunctive treatments is warranted. TRIAL REGISTRATION The study was approved by the Regional Committee for Medical and Health Research Ethics of Northern Norway (REK Nord: 2023/606482).
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Affiliation(s)
- Solvei Harila Skjold
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway.
- Center for Crisis Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway.
- Haukeland University Hospital, OCD-team, Bergen, Norway.
| | - Kristen Hagen
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway
- Møre and Romsdal Hospital Trust, Molde, Norway
| | - Michael G Wheaton
- Barnard College, Columbia University, New York, USA
- Center for OCD and Related Disorders, Massachusetts General Hospital, Boston, USA
| | | | - Kay Morten Hjelle
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway
- Center for Crisis Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | | | - Bjarne Hansen
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway
- Center for Crisis Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
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Provenza NR, Reddy S, Allam AK, Rajesh SV, Diab N, Reyes G, Caston RM, Katlowitz KA, Gandhi AD, Bechtold RA, Dang HQ, Najera RA, Giridharan N, Kabotyanski KE, Momin F, Hasen M, Banks GP, Mickey BJ, Kious BM, Shofty B, Hayden BY, Herron JA, Storch EA, Patel AB, Goodman WK, Sheth SA. Disruption of neural periodicity predicts clinical response after deep brain stimulation for obsessive-compulsive disorder. Nat Med 2024; 30:3004-3014. [PMID: 38997607 PMCID: PMC11485242 DOI: 10.1038/s41591-024-03125-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 06/11/2024] [Indexed: 07/14/2024]
Abstract
Recent advances in surgical neuromodulation have enabled chronic and continuous intracranial monitoring during everyday life. We used this opportunity to identify neural predictors of clinical state in 12 individuals with treatment-resistant obsessive-compulsive disorder (OCD) receiving deep brain stimulation (DBS) therapy ( NCT05915741 ). We developed our neurobehavioral models based on continuous neural recordings in the region of the ventral striatum in an initial cohort of five patients and tested and validated them in a held-out cohort of seven additional patients. Before DBS activation, in the most symptomatic state, theta/alpha (9 Hz) power evidenced a prominent circadian pattern and a high degree of predictability. In patients with persistent symptoms (non-responders), predictability of the neural data remained consistently high. On the other hand, in patients who improved symptomatically (responders), predictability of the neural data was significantly diminished. This neural feature accurately classified clinical status even in patients with limited duration recordings, indicating generalizability that could facilitate therapeutic decision-making.
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Affiliation(s)
- Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, USA
| | - Sandesh Reddy
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Anthony K Allam
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Sameer V Rajesh
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nabeel Diab
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Gabriel Reyes
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Rose M Caston
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Kalman A Katlowitz
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ajay D Gandhi
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Raphael A Bechtold
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Huy Q Dang
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ricardo A Najera
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nisha Giridharan
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | | | - Faiza Momin
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Mohammed Hasen
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Garrett P Banks
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Brian J Mickey
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | - Brent M Kious
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Benjamin Y Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Jeffrey A Herron
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Eric A Storch
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ankit B Patel
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Wayne K Goodman
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA.
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Klein CS, Hollmann K, Kühnhausen J, Alt AK, Pascher A, Seizer L, Primbs J, Ilg W, Thierfelder A, Severitt B, Passon H, Wörz U, Lautenbacher H, Bethge WA, Löchner J, Holderried M, Swoboda W, Kasneci E, Giese MA, Ernst C, Barth GM, Conzelmann A, Menth M, Gawrilow C, Renner TJ. Lessons learned from a multimodal sensor-based eHealth approach for treating pediatric obsessive-compulsive disorder. Front Digit Health 2024; 6:1384540. [PMID: 39381777 PMCID: PMC11460578 DOI: 10.3389/fdgth.2024.1384540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 09/04/2024] [Indexed: 10/10/2024] Open
Abstract
Introduction The present study investigates the feasibility and usability of a sensor-based eHealth treatment in psychotherapy for pediatric obsessive-compulsive disorder (OCD), and explores the promises and pitfalls of this novel approach. With eHealth interventions, therapy can be delivered in a patient's home environment, leading to a more ecologically valid symptom assessment and access to experts even in rural areas. Furthermore, sensors can help indicate a patient's emotional and physical state during treatment. Finally, using sensors during exposure with response prevention (E/RP) can help individualize therapy and prevent avoidance behavior. Methods In this study, we developed and subsequently evaluated a multimodal sensor-based eHealth intervention during 14 video sessions of cognitive-behavioral therapy (CBT) in 20 patients with OCD aged 12-18. During E/RP, we recorded eye movements and gaze direction via eye trackers, and an ECG chest strap captured heart rate (HR) to identify stress responses. Additionally, motion sensors detected approach and avoidance behavior. Results The results indicate a promising application of sensor-supported therapy for pediatric OCD, such that the technology was well-accepted by the participants, and the therapeutic relationship was successfully established in the context of internet-based treatment. Patients, their parents, and the therapists all showed high levels of satisfaction with this form of therapy and rated the wearable approach in the home environment as helpful, with fewer OCD symptoms perceived at the end of the treatment. Discussion The goal of this study was to gain a better understanding of the psychological and physiological processes that occur in pediatric patients during exposure-based online treatment. In addition, 10 key considerations in preparing and conducting sensor-supported CBT for children and adolescents with OCD are explored at the end of the article. This approach has the potential to overcome limitations in eHealth interventions by allowing the real-time transmission of objective data to therapists, once challenges regarding technical support and hardware and software usability are addressed. Clinical Trial Registration www.ClinicalTrials.gov, identifier (NCT05291611).
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Affiliation(s)
- Carolin S. Klein
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Karsten Hollmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Jan Kühnhausen
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Annika K. Alt
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Anja Pascher
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Lennart Seizer
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Jonas Primbs
- Department of Computer Science, Communication Networks, University of Tübingen, Tübingen, Germany
| | - Winfried Ilg
- Hertie Institute for Clinical Brain Research, Section for Computational Sensomotorics, University of Tübingen, Tübingen, Germany
| | - Annika Thierfelder
- Hertie Institute for Clinical Brain Research, Section for Computational Sensomotorics, University of Tübingen, Tübingen, Germany
| | - Björn Severitt
- ZEISS Vision Science Lab, University of Tübingen, Tübingen, Germany
| | - Helene Passon
- Economics and Management of Social Services, Institute for Health Care and Public Management, University of Hohenheim, Hohenheim, Germany
| | - Ursula Wörz
- Information Technology Division, University Hospital Tübingen, Tübingen, Germany
| | | | - Wolfgang A. Bethge
- Center for Clinical Studies Tübingen, University Hospital Tübingen, Tübingen, Germany
| | - Johanna Löchner
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Martin Holderried
- Department of Medical Development, Process and Quality Management, University Hospital Tübingen, Tübingen, Germany
| | - Walter Swoboda
- Faculty of Health Management, University of Applied Sciences Neu-Ulm, Neu-Ulm, Germany
| | - Enkelejda Kasneci
- Department of Educational Sciences, Human-Centered Technologies for Learning, TUM School of Social Sciences and Technology München, München, Germany
| | - Martin A. Giese
- Hertie Institute for Clinical Brain Research, Section for Computational Sensomotorics, University of Tübingen, Tübingen, Germany
| | - Christian Ernst
- Economics and Management of Social Services, Institute for Health Care and Public Management, University of Hohenheim, Hohenheim, Germany
| | - Gottfried M. Barth
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
- Department of Psychology (Clinical Psychology II), PFH—Private University of Applied Sciences, Göttingen, Germany
| | - Michael Menth
- Department of Computer Science, Communication Networks, University of Tübingen, Tübingen, Germany
| | - Caterina Gawrilow
- DZPG (German Center for Mental Health), Tübingen, Germany
- Department of Psychology, University of Tübingen, Tübingen, Germany
| | - Tobias J. Renner
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Tübingen, Tübingen, Germany
- DZPG (German Center for Mental Health), Tübingen, Germany
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Level 2 Polysomnography for the Diagnosis of Sleep Disorders: A Health Technology Assessment. ONTARIO HEALTH TECHNOLOGY ASSESSMENT SERIES 2024; 24:1-157. [PMID: 39372311 PMCID: PMC11450293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Background It is estimated that half of Canadians have insufficient sleep, which over time is associated with poor physical and mental health. Currently, the only publicly funded option for the diagnosis of sleep disorders in Ontario is an in-person overnight sleep study, performed in a hospital or independent health facility (known as a level 1 polysomnography). Level 2 polysomnography has been proposed as an alternative that can be conducted at home for the diagnosis of suspected sleep disorders, if considered to have sufficient diagnostic accuracy. We conducted a health technology assessment of level 2 polysomnography for the diagnosis of suspected sleep disorders in adults and children, which included an evaluation of the test performance, cost-effectiveness, and budget impact of publicly funding level 2 polysomnography, and the experiences, preferences, and values of people with suspected sleep disorders. Methods We performed a systematic literature search of the clinical evidence to identify diagnostic accuracy, test failures and subjective measures of patient preferences. We assessed the risk of bias of each included study (using the Quality Assessment of Diagnostic Accuracy Studies [QUADAS-2] tool) and the quality of the body of evidence (according to Grading of Recommendations Assessment, Development, and Evaluation [GRADE] Working Group criteria). We performed a systematic literature search of economic evidence and conducted a primary economic evaluation and budget impact analysis to determine the cost-effectiveness and additional costs of publicly funding level 2 polysomnography for adults and children with suspected sleep disorders in Ontario. To contextualize the potential value of using level 2 polysomnography, we spoke with people with sleep disorders. Results We included 10 studies that reported on diagnostic accuracy and found level 2 polysomnography had sensitivity ranging between 0.76-1.0 and specificity ranging between 0.40-1.0 (GRADE: Moderate to Very low) when compared with level 1 polysomnography. Studies reported test failure rates from 0% to 20%, with errors present in both level 1 and level 2 tests conducted (GRADE: Very low). As well, some of these studies reported patients were found to have mixed opinions about their experiences, with more people preferring their experience with level 2 testing at home and having better quality of sleep compared with when they underwent level 1 testing (GRADE not conducted).Our primary economic evaluation showed that for adults with suspected sleep disorders, the new diagnostic pathway with level 2 polysomnography was equally effective (outcome: confirmed diagnosis at the end of the pathway) as the current practice diagnostic pathway with level 1 polysomnography. With the assumption of a lower technical fee for level 2 polysomnography, the new diagnostic pathway with level 2 polysomnography was less costly than the current practice diagnostic pathway (a saving of $27 per person with a wide 95% credible interval [95% CrI, -$137 to $121]), indicating that the results are highly uncertain. For children, a new diagnostic pathway with level 2 polysomnography was associated with additional costs (mean, $9.70; 95% CrI, -$125 to $190), and similarly, this estimate was highly uncertain.We estimated that the budget impact of publicly funding level 2 polysomnography for adults is uncertain and could range from savings of $22 million to additional costs of $43 million. Publicly funding a diagnostic pathway with level 2 polysomnography for children could result in additional costs of about $0.005 million over the next 5 years.People with whom we spoke reported that their sleep disorder negatively impacted their day-to-day lives, mental health, social and family relationships, and work. Participants who had experience with in-clinic (level 1) polysomnography described negative experiences they had at the clinic. Most people said they would prefer at-home (level 2) polysomnography over in-clinic (level 1) polysomnography, citing comfort and convenience as the main reasons; however, some people who have physical limitations preferred level 1 (in-clinic) polysomnography because they needed assistance to set up the equipment. Conclusions Level 2 polysomnography may have good test performance for adults and children, with adequate diagnostic accuracy, compared with level 1 polysomnography. The economic analyses showed that level 2 polysomnography for adults with suspected sleep disorders could be potentially cost saving but there is high uncertainty in the cost-effectiveness results. Given very limited information, the cost-effectiveness of this technology is also highly uncertain for children and young adults with suspected sleep disorders. The budget impact of publicly funding level 2 polysomnography for adults could range from savings of $22 million to additional costs of $43 million. Publicly funding level 2 polysomnography in children would require additional costs of about $0.005 million over the next 5 years. A clearer understanding of uptake of the technology, test costs, and the implementation pathway for adopting the technology is needed to improve the certainty of the cost-effectiveness and budget impact estimates. People with sleep disorders highlighted how important getting a diagnosis had been in order to be able to seek proper treatment for their sleep disorder and improve their lives. For many people with suspected sleep disorders, undergoing a sleep study at home would be a more comfortable and convenient option than undergoing a sleep study in clinic.
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Li M, Li W, Liang S, Liao X, Gu M, Li H, Chen X, Liu H, Qin H, Xiao J. BNST GABAergic neurons modulate wakefulness over sleep and anesthesia. Commun Biol 2024; 7:339. [PMID: 38503808 PMCID: PMC10950862 DOI: 10.1038/s42003-024-06028-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 03/08/2024] [Indexed: 03/21/2024] Open
Abstract
The neural circuits underlying sleep-wakefulness and general anesthesia have not been fully investigated. The GABAergic neurons in the bed nucleus of the stria terminalis (BNST) play a critical role in stress and fear that relied on heightened arousal. Nevertheless, it remains unclear whether BNST GABAergic neurons are involved in the regulation of sleep-wakefulness and anesthesia. Here, using in vivo fiber photometry combined with electroencephalography, electromyography, and video recordings, we found that BNST GABAergic neurons exhibited arousal-state-dependent alterations, with high activities in both wakefulness and rapid-eye movement sleep, but suppressed during anesthesia. Optogenetic activation of these neurons could initiate and maintain wakefulness, and even induce arousal from anesthesia. However, chronic lesion of BNST GABAergic neurons altered spontaneous sleep-wakefulness architecture during the dark phase, but not induction and emergence from anesthesia. Furthermore, we also discovered that the BNST-ventral tegmental area pathway might participate in promoting wakefulness and reanimation from steady-state anesthesia. Collectively, our study explores new elements in neural circuit mechanisms underlying sleep-wakefulness and anesthesia, which may contribute to a more comprehensive understanding of consciousness and the development of innovative anesthetics.
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Affiliation(s)
- Mengyao Li
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning, 530004, China
| | - Wen Li
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China
| | - Shanshan Liang
- Brain Research Center and State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, 400038, China
| | - Xiang Liao
- Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing, 400044, China
| | - Miaoqing Gu
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning, 530004, China
| | - Huiming Li
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, China
| | - Xiaowei Chen
- Advanced Institute for Brain and Intelligence, School of Medicine, Guangxi University, Nanning, 530004, China
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing, 400064, China
| | - Hongliang Liu
- Department of Anesthesiology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
| | - Han Qin
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing, 400064, China.
| | - Jingyu Xiao
- Department of Anesthesiology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
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Bernstein EE, Klare D, Weingarden H, Greenberg JL, Snorrason I, Hoeppner SS, Vanderkruik R, Harrison O, Wilhelm S. Impact of sleep disruption on BDD symptoms and treatment response. J Affect Disord 2024; 346:206-213. [PMID: 37952909 PMCID: PMC10842714 DOI: 10.1016/j.jad.2023.11.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 08/08/2023] [Accepted: 11/09/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Body dysmorphic disorder (BDD) is severe, undertreated, and relatively common. Although gold-standard cognitive behavioral therapy (CBT) for BDD has strong empirical support, a significant number of patients do not respond. More work is needed to understand BDD's etiology and modifiable barriers to treatment response. Given its high prevalence and impact on the development, maintenance, and treatment of related, frequently comorbid disorders, sleep disruption is a compelling, but not-yet studied factor. METHODS Data were drawn from a randomized controlled trial of guided smartphone app-based CBT for BDD. Included participants were offered 12-weeks of treatment, immediately (n = 40) or after a 12-week waitlist (n = 37). Sleep disruption and BDD symptom severity were assessed at baseline, week-6, and week-12. RESULTS Hypotheses and analysis plan were pre-registered. Two-thirds of patients reported significant insomnia symptoms at baseline. Baseline severity of sleep disruption and BDD symptoms were not related (r = 0.02). Pre-treatment sleep disruption did not predict BDD symptom reduction across treatment, nor did early sleep improvements predict greater BDD symptom improvement. Early BDD symptom improvement also did not predict later improvements in sleep. LIMITATIONS Limitations include the small sample, restricted ranges of BDD symptom severity and treatment response, and few metrics of sleep disruption. CONCLUSIONS Although insomnia was disproportionately high in this sample and both BDD symptoms and sleep improved in treatment, results suggest sleep and BDD symptoms may function largely independent of one another. More work is encouraged to replicate and better understand findings as well as potential challenges and benefits of addressing sleep in BDD.
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Affiliation(s)
- Emily E Bernstein
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America.
| | - Dalton Klare
- Massachusetts General Hospital, United States of America
| | - Hilary Weingarden
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America
| | - Jennifer L Greenberg
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America
| | - Ivar Snorrason
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America
| | - Susanne S Hoeppner
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America
| | - Rachel Vanderkruik
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America
| | | | - Sabine Wilhelm
- Massachusetts General Hospital, United States of America; Harvard Medical School, United States of America
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Estivill-Domènech C, Rodriguez-Morilla B, Estivill E, Madrid JA. Case report: Diagnosis and intervention of a non-24-h sleep-wake disorder in a sighted child with a psychiatric disorder. Front Psychiatry 2024; 14:1129153. [PMID: 38250267 PMCID: PMC10797120 DOI: 10.3389/fpsyt.2023.1129153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 12/11/2023] [Indexed: 01/23/2024] Open
Abstract
Circadian rhythm sleep-wake disorders (CRSWD) are sleep dysfunctions related to circadian functioning. They are characterized by symptoms of insomnia or excessive sleepiness that occur because the intrinsic circadian pacemaker is not entrained to a 24-h light/dark cycle. Affected individuals with a free-running disorder or hypernycthemeral syndrome (N24SWD) have a longer sleep-wake cycle that produces a sleep pattern that typically delays each day. The disorder is seen in 70% of blind people, and among people with healthy vision, it is a rare pathology. Among sighted cases, 80% are young men and 28% have a psychiatric disorder. The patient was a 14-year-old boy with a psychiatric pathology diagnosed with a PANDAS syndrome (pediatric autoimmune neuropsychiatric disorders associated with streptococci), a sudden acute and debilitating onset of intense anxiety and mood lability accompanied by obsessive compulsive-like issues and/or tics, in association with a streptococcal A infection that occurs immediately prior to the symptoms. As a comorbidity, he exhibited severe insomnia due to an irregular sleep pattern that strongly delayed his sleep schedule day to day. It affected his daily routines, as he was not going to school, and aggravated, furthermore, the psychiatric symptoms. He was referred for sleep consultation, where the case was explored by ambulatory circadian monitoring (ACM) using the novel system Kronowise® (Chronolab, University of Murcia) and diagnosed with a non-24-h sleep-wake disorder (N24SWD). The first treatment approach for the patient was focused on improving symptoms during the acute infection and psychiatric symptoms. Additionally, sleep pathology was treated by light therapy and melatonin. After 8 months and different trials, it was possible to establish a treatment to normalize the symptoms and fix his sleep rhythm in a normal schedule as well as to reduce anxious symptoms during the day. The association of PANDAS and N24SWD has not previously been reported in the literature.
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Affiliation(s)
| | | | | | - Juan Antonio Madrid
- Chronobiology Lab, Department of Physiology, College of Biology, University of Murcia, IUIE, IMIB, Murcia, Spain
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Cox RC, Knowles KA, Jessup SC, Adamis AM, Olatunji BO. Psychometric properties of a daily obsessive-compulsive symptom scale for ecological momentary assessment. J Obsessive Compuls Relat Disord 2023; 39:100840. [PMID: 37808900 PMCID: PMC10552676 DOI: 10.1016/j.jocrd.2023.100840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Despite growing interest in ecological momentary assessment (EMA) in psychopathology and clinical observation of day-to-day fluctuations in obsessive-compulsive disorder (OCD) symptoms, there is not a standardized EMA measure of such symptoms that can guide systematic research. In the absence of such a measure, prior EMA research in OCD has utilized heterogeneous approaches to sampling momentary and daily OCD symptoms, which limits the ability to compare results between studies. The present study sought to examine the psychometric properties of a daily OCD symptom (d-OCS) measure that assesses common OCD symptom themes (e.g., contamination, checking, intrusive thoughts) in a sample of adults with OCD (n = 20), psychiatric controls (n = 27), and healthy controls (n = 27). Participants completed the d-OCS 3 times per day for 1 week. The d-OCS distinguished those with OCD from psychiatric controls and healthy controls. The d-OCS demonstrated good internal consistency, adequate test-retest reliability, and good convergent validity. These findings offer initial psychometric support for the use of the d-OCS in EMA research examining day-to-day fluctuations in symptoms of OCD. Additional investigation is needed to examine the discriminant validity of the d-OCS and generalize these findings to more diverse samples.
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Affiliation(s)
| | - Kelly A. Knowles
- Vanderbilt University
- Anxiety Disorders Center, Institute of Living/Hartford Hospital
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Frank AC, Li R, Peterson BS, Narayanan SS. Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review. JMIR Ment Health 2023; 10:e45572. [PMID: 37463010 PMCID: PMC10394606 DOI: 10.2196/45572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 05/27/2023] [Accepted: 06/13/2023] [Indexed: 07/21/2023] Open
Abstract
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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Affiliation(s)
- Adam C Frank
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Ruibei Li
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Bradley S Peterson
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Division of Child and Adolescent Psychiatry, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Shrikanth S Narayanan
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
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Merrill RM, Ashton MK, Angell E. Sleep disorders related to index and comorbid mental disorders and psychotropic drugs. Ann Gen Psychiatry 2023; 22:23. [PMID: 37245028 DOI: 10.1186/s12991-023-00452-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 05/13/2023] [Indexed: 05/29/2023] Open
Abstract
PURPOSE Mental disorders positively associate with sleep disorders. This study will explore the moderating influence of comorbid mental disorders and whether selected psychotropic drugs correlate with sleep disorders after adjusting for mental disorders. METHODS A retrospective cohort study design was employed using medical claim data from the Deseret Mutual Benefit Administrators (DMBA). Mental disorders, psychotropic drug use, and demographic data were extracted from claim files for ages 18-64, years 2016-2020. RESULTS Approximately 11.7% filed one or more claims for a sleep disorder [insomnia (2.2%) and sleep apnea (9.7%)]. Rates for selected mental disorders ranged from 0.09% for schizophrenia to 8.4% for anxiety. The rate of insomnia is greater in those with bipolar disorder or schizophrenia than in other mental disorders. The rate of sleep apnea is greater in those with bipolar disorder and depression. There is a significantly positive association between mental disorders and insomnia and sleep apnea, more so for insomnia, especially if they had other comorbid mental disorders. Psychotropic drugs other than CNS stimulants, primarily sedatives (non-barbiturate) and psychostimulants, explain much of the positive association between anxiety, depression, and bipolar disorder with insomnia. Psychotropic drugs with the largest effect on sleep disorders are sedatives (non-barbiturate) and psychostimulants for insomnia and psychostimulants and anticonvulsants for sleep apnea. CONCLUSION Mental disorders positively correlate with insomnia and sleep apnea. The positive association is greater when multiple mental illness exists. Bipolar disorder and schizophrenia are most strongly associated with insomnia, and bipolar disorder and depression are most strongly associated with sleep disorders. Psychotropic drugs other than CNS stimulants, primarily sedatives (non-barbiturate) and psychostimulants for treating anxiety, depression, or bipolar disorder are associated with higher levels of insomnia and sleep apnea.
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Affiliation(s)
- Ray M Merrill
- Department of Public Health, College of Life Sciences, Brigham Young University, Provo, UT, 84602, USA.
| | - McKay K Ashton
- Department of Public Health, College of Life Sciences, Brigham Young University, Provo, UT, 84602, USA
| | - Emily Angell
- Department of Public Health, College of Life Sciences, Brigham Young University, Provo, UT, 84602, USA
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Soffer-Dudek N. Obsessive-compulsive symptoms and dissociative experiences: Suggested underlying mechanisms and implications for science and practice. Front Psychol 2023; 14:1132800. [PMID: 37051604 PMCID: PMC10084853 DOI: 10.3389/fpsyg.2023.1132800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 03/03/2023] [Indexed: 03/29/2023] Open
Abstract
A strong and specific link between obsessive-compulsive disorder or symptoms (OCD/S) and a tendency for dissociative experiences (e.g., depersonalization-derealization, absorption and imaginative involvement) cannot be explained by trauma and is poorly understood. The present theoretical formulation proposes five different models conceptualizing the relationship. According to Model 1, dissociative experiences result from OCD/S through inward-focused attention and repetition. According to Model 2, dissociative absorption causally brings about both OCD/S and associated cognitive risk factors, such as thought-action fusion, partly through impoverished sense of agency. The remaining models highlight common underlying causal mechanisms: temporo-parietal abnormalities impairing embodiment and sensory integration (Model 3); sleep alterations causing sleepiness and dreamlike thought or mixed sleep-wake states (Model 4); and a hyperactive, intrusive imagery system with a tendency for pictorial thinking (Model 5). The latter model relates to Maladaptive Daydreaming, a suggested dissociative syndrome with strong ties to the obsessive-compulsive spectrum. These five models point to potential directions for future research, as these theoretical accounts may aid the two fields in interacting with each other, to the benefit of both. Finally, several dissociation-informed paths for further developing clinical intervention in OCD are identified.
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Affiliation(s)
- Nirit Soffer-Dudek
- The Consciousness and Psychopathology Laboratory, Department of Psychology, Ben-Gurion University of the Negev, Be’er Sheva, Israel
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