Multifaceted, Brief Intensive Home-Based Exposure Treatment in Patients with Obsessive-Compulsive Disorder Who are Nonresponsive to Regular Cognitive Behavior Therapy: An Uncontrolled Pilot Study.

OBJECTIVE: To test a multifaceted treatment program for patients with obsessive-compulsive disorder (OCD) who did not respond to regular cognitive behavior therapy (CBT). The treatment addresses several factors that may play a role in maintaining OCD. METHODS: We designed a treatment consisting of a 6-day intensive, individual exposure in vivo with response prevention (ERP) format, with 24 therapist-assisted treatment hours at the patient's home and 12 self-controlled ERP hours, including behavioral activation and family interventions. Next, we investigated the effect (obsessive-compulsive symptoms, comorbidity, functioning, quality of life, OCD-related interaction patterns) and feasibility (dropout, treatment satisfaction, and organization) of this program using pre-post-tests, pre-follow-up tests, and qualitative data from patients, family members, and therapists. RESULTS: In a sample of 22 participants, obsessive-compulsive symptoms (Y-BOCS pre: 28.7, post: 15.9; Wilcoxon S-R tests P<0.01) improved significantly, as did most other effect measures. Results were largely, but not completely, preserved at 3-month follow-up. There was only 1 dropout. Patients, family members, and therapists were satisfied with the treatment. Implementation of the treatment did not pose difficulties. CONCLUSIONS: In nonresponders with OCD, a multifaceted, brief, intensive home-based ERP program targeting factors maintaining OCD is promising and feasible. Extra care is needed to maintain improvement.

Cognitive behavioural therapy and third-wave approaches for anxiety and related disorders in older people.

BACKGROUND: Cognitive behavioural therapy (CBT) is the most researched psychological therapy for anxiety disorders in adults, and known to be effective in this population. However, it remains unclear whether these results apply to older adults, as most studies include participants between 18 and 55 years of age. This systematic review aims to provide a comprehensive and up-to-date synthesis of the available evidence on CBT and third wave approaches for older adults with anxiety and related disorders. OBJECTIVES: To assess the effects of Cognitive Behavioural Therapy (CT, BT, CBT and third-wave CBT interventions) on severity of anxiety symptoms compared with minimal management (not providing therapy) for anxiety and related disorders in older adults, aged 55 years or over. To assess the effects of CBT and related therapies on severity of anxiety symptoms compared with other psychological therapies for anxiety and related disorders in older adults, aged 55 years or over. SEARCH METHODS: We searched the Cochrane Common Mental Disorders Controlled studies Register (CCMDCTR), CENTRAL, Ovid MEDLINE, Ovid Embase and Ovid PsycINFO to 21 July 2022. These searches were updated on 2 February 2024. We also searched the international studies registries, including Clinicalstudies.gov and the WHO International Clinical Trials Registry Platform (ICTRP), to identify additional ongoing and unpublished studies. These sources were manually searched for studies up to 12 February 2024. SELECTION CRITERIA: We included randomised controlled trials (RCTs) in older adults (≥ 55 years) with an anxiety disorder, or a related disorder, including obsessive compulsive disorder (OCD), acute stress disorder and post-traumatic stress disorder (PTSD), that compared CBT to either minimal management or an active (non-CBT) psychological therapy. Eligible studies had to have an anxiety-related outcome. DATA COLLECTION AND ANALYSIS: Several authors independently screened all titles identified by the searches. All full texts were screened for eligibility according to our prespecified selection criteria. Data were extracted and the risk of bias was assessed using the Cochrane tool for RCTs. The certainty of evidence was evaluated using GRADE. Meta-analyses were performed for outcomes with quantitative data from more than one study. MAIN RESULTS: We included 21 RCTs on 1234 older people allocated to either CBT or control conditions. Ten studies focused on generalised anxiety disorder; others mostly included a mix of clinical diagnoses. Nineteen studies focused on the comparison between CBT and minimal management. Key issues relating to risk of bias were lack of blinding of participants and personnel, and participants dropping out of studies, potentially due to treatment preference and allocation. CBT may result in a small-to-moderate reduction of anxiety post-treatment (SMD -0.51, 95% CI -0.66 to -0.36, low-certainty evidence). However, compared to this benefit with CBT immediately after treatment, at three to six months post-treatment, there was little to no difference between CBT and minimal management (SMD -0.29, 95% CI -0.59 to 0.01, low-certainty evidence). CBT may have little or no effect on clinical recovery/ improvement post-treatment compared to minimal management, but the evidence is very uncertain (RR 1.56, 95% CI 1.20 to 2.03, very low-certainty evidence). Results indicate that five people would need to receive treatment for one additional person to benefit (NNTB = 5). Compared to minimal management, CBT may result in a reduction of comorbid depression symptoms post-treatment (SMD -0.57, 95% CI -0.74 to -0.40, low-certainty evidence). There was no difference in dropout rates post-treatment, although the certainty of the evidence was low (RR 1.19, 95% CI 0.80 to 1.78). Two studies reported adverse events, both of which related to medication in the control groups (very low-certainty evidence, no quantitative estimate). Only two studies compared CBT to other psychological therapies, both of which only included participants with post-traumatic stress disorder. Low-certainty evidence showed no difference in anxiety severity post-treatment and at four to six months post-treatment, symptoms of depression post-treatment, and dropout rates post-treatment. Other outcomes and time points are reported in the results section of the manuscript. AUTHORS' CONCLUSIONS: CBT may be more effective than minimal management in reducing anxiety and symptoms of worry and depression post-treatment in older adults with anxiety disorders. The evidence is less certain longer-term and for other outcomes including clinical recovery/improvement. There is not enough evidence to determine whether CBT is more effective than alternative psychological therapies for anxiety in older adults.

pyCEPS: A cross-platform electroanatomic mapping data to computational model conversion platform for the calibration of digital twin models of cardiac electrophysiology.

BACKGROUND AND OBJECTIVE: Data from electro-anatomical mapping (EAM) systems are playing an increasingly important role in computational modeling studies for the patient-specific calibration of digital twin models. However, data exported from commercial EAM systems are challenging to access and parse. Converting to data formats that are easily amenable to be viewed and analyzed with commonly used cardiac simulation software tools such as openCARP remains challenging. We therefore developed an open-source platform, pyCEPS, for parsing and converting clinical EAM data conveniently to standard formats widely adopted within the cardiac modeling community. METHODS AND RESULTS: pyCEPS is an open-source Python-based platform providing the following functions: (i) access and interrogate the EAM data exported from clinical mapping systems; (ii) efficient browsing of EAM data to preview mapping procedures, electrograms (EGMs), and electro-cardiograms (ECGs); (iii) conversion to modeling formats according to the openCARP standard, to be amenable to analysis with standard tools and advanced workflows as used for in silico EAM data. Documentation and training material to facilitate access to this complementary research tool for new users is provided. We describe the technological underpinnings and demonstrate the capabilities of pyCEPS first, and showcase its use in an exemplary modeling application where we use clinical imaging data to build a patient-specific anatomical model. CONCLUSION: With pyCEPS we offer an open-source framework for accessing EAM data, and converting these to cardiac modeling standard formats. pyCEPS provides the core functionality needed to integrate EAM data in cardiac modeling research. We detail how pyCEPS could be integrated into model calibration workflows facilitating the calibration of a computational model based on EAM data.

Patient Perceptions of Illness Causes and Treatment Preferences for Obsessive-Compulsive Disorder: A Mixed-Methods Study.

Obsessive-compulsive disorder (OCD) is a condition with high patient morbidity and mortality. Research shows that eliciting patient explanations about illness causes and treatment preferences promotes cross-cultural work and engagement in health services. These topics are in the Cultural Formulation Interview (CFI), a semi-structured interview first published in DSM-5 that applies anthropological approaches within mental health services to promote person-centered care. This study focuses on the New York City site of an international multi-site study that used qualitative-quantitative mixed methods to: (1) analyze CFI transcripts with 55 adults with OCD to explore perceived illness causes and treatment preferences, and (2) explore whether past treatment experiences are related to perceptions about causes of current symptoms. The most commonly named causes were circumstantial stressors (n = 16), genetics (n = 12), personal psychological traits (n = 9), an interaction between circumstantial stressors and participants' brains (n = 6), and a non-specific brain problem (n = 6). The most common treatment preferences were psychotherapy (n = 42), anything (n = 4), nothing (n = 4), and medications (n = 2). Those with a prior medication history had twice the odds of reporting a biological cause, though this was not a statistically significant difference. Our findings suggest that providers should ask patients about illness causes and treatment preferences to guide treatment choice.

Reducing suicides in mental healthcare: results from a 4-year follow-up implementation study in the Netherlands (SUPRANET).

Objective: In 2016, the SUicide PRevention Action NETwork (SUPRANET) was launched. The SUPRANET intervention aims at better implementing the suicide prevention guideline. An implementation study was developed to evaluate the impact of SUPRANET over time on three outcomes: 1) suicides, 2) registration of suicide attempts, and 3) professionals' knowledge and adherence to the guideline. Methods: This study included 13 institutions, and used an uncontrolled longitudinal prospective design, collecting biannual data on a 2-level structure (institutional and team level). Suicides and suicide attempts were extracted from data systems. Professionals' knowledge and adherence were measured using a self-report questionnaire. A three-step interrupted time series analysis (ITSA) was performed for the first two outcomes. Step 1 assessed whether institutions executed the SUPRANET intervention as intended. Step 2 examined if institutions complied with the four guideline recommendations. Based on steps 1 and 2, institutions were classified as below or above average and after that, included as moderators in step 3 to examine the effect of SUPRANET over time compared to the baseline. The third outcome was analyzed with a longitudinal multilevel regression analysis, and tested for moderation. Results: After institutions were labeled based on their efforts and investments made (below average vs above average), we found no statistically significant difference in suicides (standardized mortality ratio) between the two groups relative to the baseline. Institutions labeled as above average did register significantly more suicide attempts directly after the start of the intervention (78.8 per 100,000 patients, p<0.001, 95%CI=(51.3 per 100,000, 106.4 per 100,000)), and as the study progressed, they continued to report a significantly greater improvement in the number of registered attempts compared with institutions assigned as below average (8.7 per 100,000 patients per half year, p=0.004, 95%CI=(3.3 per 100,000, 14.1 per 100,000)). Professionals working at institutions that invested more in the SUPRANET activities adhered significantly better to the guideline over time (b=1.39, 95%CI=(0.12,2.65), p=0.032). Conclusion: Institutions labeled as above average registered significantly more suicide attempts and also better adhered to the guideline compared with institutions that had performed less well. Although no convincing intervention effect on suicides was found within the study period, we do think that this network is potentially able to reduce suicides. Continuous investments and fully implementing as many guideline recommendations as possible are essential to achieve the biggest drop in suicides.

Does a lack of emotions make chatbots unfit to be psychotherapists?

Mental health chatbots (MHCBs) designed to support individuals in coping with mental health issues are rapidly advancing. Currently, these MHCBs are predominantly used in commercial rather than clinical contexts, but this might change soon. The question is whether this use is ethically desirable. This paper addresses a critical yet understudied concern: assuming that MHCBs cannot have genuine emotions, how this assumption may affect psychotherapy, and consequently the quality of treatment outcomes. We argue that if MHCBs lack emotions, they cannot have genuine (affective) empathy or utilise countertransference. Consequently, this gives reason to worry that MHCBs are (a) more liable to harm and (b) less likely to benefit patients than human therapists. We discuss some responses to this worry and conclude that further empirical research is necessary to determine whether these worries are valid. We conclude that, even if these worries are valid, it does not mean that we should never use MHCBs. By discussing the broader ethical debate on the clinical use of chatbots, we point towards how further research can help us establish ethical boundaries for how we should use mental health chatbots.

ForCEPSS-A framework for cardiac electrophysiology simulations standardization.

BACKGROUND AND OBJECTIVE: Simulation of cardiac electrophysiology (CEP) is an important research tool that is increasingly being adopted in industrial and clinical applications. Typical workflows for CEP simulation consist of a sequence of processing stages starting with building an anatomical model and then calibrating its electrophysiological properties to match observable data. While the calibration stages are common and generalizable, most CEP studies re-implement these steps in complex and highly variable workflows. This lack of standardization renders the execution of computational CEP studies in an efficient, robust, and reproducible manner a significant challenge. Here, we propose ForCEPSS as an efficient and robust, yet flexible, software framework for standardizing CEP simulation studies. METHODS AND RESULTS: Key processing stages of CEP simulation studies are identified and implemented in a standardized workflow that builds on openCARP1 Plank et al. (2021) and the Python-based carputils2 framework. Stages include (i) the definition and initialization of action potential phenotypes, (ii) the tissue scale calibration of conduction properties, (iii) the functional initialization to approximate a limit cycle corresponding to the dynamic reference state according to an experimental protocol, and, (iv) the execution of the CEP study where the electrophysiological response to a perturbation of the limit cycle is probed. As an exemplar application, we employ ForCEPSS to prepare a CEP study according to the Virtual Arrhythmia Risk Prediction protocol used for investigating the arrhythmogenic risk of developing infarct-related ventricular tachycardia (VT) in ischemic cardiomyopathy patients. We demonstrate that ForCEPSS enables a fully automated execution of all stages of this complex protocol. CONCLUSION: ForCEPSS offers a novel comprehensive, standardized, and automated CEP simulation workflow. The high degree of automation accelerates the execution of CEP simulation studies, reduces errors, improves robustness, and makes CEP studies reproducible. Verification of simulation studies within the CEP modeling community is thus possible. As such, ForCEPSS makes an important contribution towards increasing transparency, standardization, and reproducibility of in silico CEP experiments.

Microsampling Techniques Suitable for Therapeutic Drug Monitoring of Antipsychotics.

BACKGROUND: Therapeutic drug monitoring (TDM) of antipsychotics for dose titration or detection of noncompliance is not uncommon in daily practice. Normally, TDM implies measuring a drug concentration in venous blood samples. This technique is invasive and requires trained assistants and patients normally need to go to an outpatient clinic. Over the past decades, sensitivity of analytical equipment has improved leading to a growing interest in microsampling techniques. These techniques are minimally invasive, require a small volume (<100 µL), usually result in stable samples, and can be collected by the patient or a caregiver at home. Before a microsampling technique can be used in daily routine, proper method development and a clinical validation study should be performed. METHOD: For this review, the databases of PubMed and Embase were systematically searched. Currently available microsampling techniques for antipsychotics in blood, serum, or plasma are summarized. Subsequently, it has also been assessed whether these techniques are sufficiently validated for TDM monitoring in daily practice. RESULTS: Several microsampling techniques are available today, for example, dried blood spot sampling, dried plasma extraction cards, and volumetric absorptive microsampling. Eighteen studies were identified in which a microsampling technique for 1 or a few antipsychotics was chemically analytically and clinically validated. However, the majority of these studies have relevant shortcomings that mean its usefulness for different antipsychotics is not yet well established. CONCLUSIONS: Microsampling for TDM can be recommended for patients using clozapine. For TDM of other antipsychotics, it is a very promising development.

Predicting postinfarct ventricular tachycardia by integrating cardiac MRI and advanced computational reentrant pathway analysis.

BACKGROUND: Implantable cardiac defibrillator (ICD) implantation can protect against sudden cardiac death after myocardial infarction. However, improved risk stratification for device requirement is still needed. OBJECTIVE: The purpose of this study was to improve assessment of postinfarct ventricular electropathology and prediction of appropriate ICD therapy by combining late gadolinium enhancement (LGE) and advanced computational modeling. METHODS: ADAS 3D LV (ADAS LV Medical, Barcelona, Spain) and custom-made software were used to generate 3-dimensional patient-specific ventricular models in a prospective cohort of patients with a myocardial infarction (N = 40) having undergone LGE imaging before ICD implantation. Corridor metrics and 3-dimensional surface features were computed from LGE images. The Virtual Induction and Treatment of Arrhythmias (VITA) framework was applied to patient-specific models to comprehensively probe the vulnerability of the scar substrate to sustaining reentrant circuits. Imaging and VITA metrics, related to the numbers of induced ventricular tachycardias and their corresponding round trip times (RTTs), were compared with ICD therapy during follow-up. RESULTS: Patients with an event (n = 17) had a larger interface between healthy myocardium and scar and higher VITA metrics. Cox regression analysis demonstrated a significant independent association with an event: interface (hazard ratio [HR] 2.79; 95% confidence interval [CI] 1.44-5.44; P < .01), unique ventricular tachycardias (HR 1.67; 95% CI 1.04-2.68; P = .03), mean RTT (HR 2.14; 95% CI 1.11-4.12; P = .02), and maximum RTT (HR 2.13; 95% CI 1.19-3.81; P = .01). CONCLUSION: A detailed quantitative analysis of LGE-based scar maps, combined with advanced computational modeling, can accurately predict ICD therapy and could facilitate the early identification of high-risk patients in addition to left ventricular ejection fraction.

Ercc1 DNA repair deficiency results in vascular aging characterized by VSMC phenotype switching, ECM remodeling, and an increased stress response.

Cardiovascular diseases are the number one cause of death globally. The most important determinant of cardiovascular health is a person's age. Aging results in structural changes and functional decline of the cardiovascular system. DNA damage is an important contributor to the aging process, and mice with a DNA repair defect caused by Ercc1 deficiency display hypertension, vascular stiffening, and loss of vasomotor control. To determine the underlying cause, we compared important hallmarks of vascular aging in aortas of both Ercc1Δ/- and age-matched wildtype mice. Additionally, we investigated vascular aging in 104 week old wildtype mice. Ercc1Δ/- aortas displayed arterial thickening, a loss of cells, and a discontinuous endothelial layer. Aortas of 24 week old Ercc1Δ/- mice showed phenotypical switching of vascular smooth muscle cells (VSMCs), characterized by a decrease in contractile markers and a decrease in synthetic markers at the RNA level. As well as an increase in osteogenic markers, microcalcification, and an increase in markers for damage induced stress response. This suggests that Ercc1Δ/- VSMCs undergo a stress-induced contractile-to-osteogenic phenotype switch. Ercc1Δ/- aortas showed increased MMP activity, elastin fragmentation, and proteoglycan deposition, characteristic of vascular aging and indicative of age-related extracellular matrix remodeling. The 104 week old WT mice showed loss of cells, VSMC dedifferentiation, and senescence. In conclusion, Ercc1Δ/- aortas rapidly display many characteristics of vascular aging, and thus the Ercc1Δ/- mouse is an excellent model to evaluate drugs that prevent vascular aging in a short time span at the functional, histological, and cellular level.

Is photoelectrocatalysis an efficient process to degrade endocrine disruptors chemicals?

Endocrine disruptors chemicals (EDCs) pose significant health risks, including cancer, behavioral disorders, and infertility. In this study, we employed the photoelectrocatalysis (PEC) technique with optimized tungsten oxide (WO3) nanostructures as a photoanode to degrade three diverse EDCs: methiocarb, dimethyl phthalate, and 4-tert-butylphenol. PEC degradation tests were carried out for individual contaminants and a mixture of them, assessing efficiency across different EDC families. Ultra High-Performance Liquid Chromatography and Mass Spectrometry was used to control the course of the experiments. For individual solutions, 4-tert-butylphenol and methiocarb were 100% degraded at 1 hour of PEC degradation. Among the tested EDCs, dimethyl phthalate showed the highest resistance to degradation when treated individually. However, when assessed in a mixture with the other EDCs, the degradation efficiency of dimethyl phthalate increased compared to its individual treatment. Furthermore, four degradation intermediates were identified for each contaminant. Finally, toxicity tests revealed that the initial solution was more toxic than the samples treated for all the contaminants tested, except for the phthalate.

Hybrid Neural State-Space Modeling for Supervised and Unsupervised Electrocardiographic Imaging.

State-space modeling (SSM) provides a general framework for many image reconstruction tasks. Error in a priori physiological knowledge of the imaging physics, can bring incorrectness to solutions. Modern deep-learning approaches show great promise but lack interpretability and rely on large amounts of labeled data. In this paper, we present a novel hybrid SSM framework for electrocardiographic imaging (ECGI) to leverage the advantage of state-space formulations in data-driven learning. We first leverage the physics-based forward operator to supervise the learning. We then introduce neural modeling of the transition function and the associated Bayesian filtering strategy. We applied the hybrid SSM framework to reconstruct electrical activity on the heart surface from body-surface potentials. In unsupervised settings of both in-silico and in-vivo data without cardiac electrical activity as the ground truth to supervise the learning, we demonstrated improved ECGI performances of the hybrid SSM framework trained from a small number of ECG observations in comparison to the fixed SSM. We further demonstrated that, when in-silico simulation data becomes available, mixed supervised and unsupervised training of the hybrid SSM achieved a further 40.6% and 45.6% improvements, respectively, in comparison to traditional ECGI baselines and supervised data-driven ECGI baselines for localizing the origin of ventricular activations in real data.

[Anxiety]. / Angst.

In this article, we will address 10 questions about anxiety that are relevant to doctors who encounter this in their practice. This often occurs in the primary care setting, where individuals with anxiety frequently present with somatic complaints. A focused medical history, including questions about the use and withdrawal of psychoactive substances, can assist in the diagnostic process. Psychoeducation may be sufficient, otherwise cognitive-behavioral therapy can be conducted. In cases of non-response, serotonergic antidepressants represent a treatment option. Half of the individuals with anxiety symptoms experience remission, while the other half have a recurrent or chronic course, which may be accompanied by comorbid depression.

Unveiling the Reaction Mechanisms of the Synthesis and the Excited State Intramolecular Proton Transfer of 2-(2'-hydroxyphenyl)imidazo[1,2-a]pyridine.

Given its wide variety of applications in the pharmaceutical industry, the synthesis of imidazo[1,2-a]pyridines has been extensively studied since the beginning of the last century. Here, we disclose the mechanism for the synthesis of imidazo[1,2-a]pyridines by means of the Ortoleva-King reaction. We also reveal the reaction pathway leading to the formation of a iodinated byproduct, demonstrating the challenge of preventing the formation of such a byproduct because of the low energy barrier to access it. Moreover, quantum chemistry tools were employed to investigate the mechanism of intramolecular proton transfer in the excited state, and connections with aromaticity were explored.

Acute Coronary Syndrome Subphenotypes Based on Repeated Biomarker Measurements in Relation to Long-Term Mortality Risk.

BACKGROUND: We aimed to identify patients with subphenotypes of postacute coronary syndrome (ACS) using repeated measurements of high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, and growth differentiation factor 15 in the year after the index admission, and to investigate their association with long-term mortality risk. METHODS AND RESULTS: BIOMArCS (BIOMarker Study to Identify the Acute Risk of a Coronary Syndrome) was an observational study of patients with ACS, who underwent high-frequency blood sampling for 1 year. Biomarkers were measured in a median of 16 repeated samples per individual. Cluster analysis was performed to identify biomarker-based subphenotypes in 723 patients without a repeat ACS in the first year. Patients with a repeat ACS (N=36) were considered a separate cluster. Differences in all-cause death were evaluated using accelerated failure time models (median follow-up, 9.1 years; 141 deaths). Three biomarker-based clusters were identified: cluster 1 showed low and stable biomarker concentrations, cluster 2 had elevated concentrations that subsequently decreased, and cluster 3 showed persistently elevated concentrations. The temporal biomarker patterns of patients in cluster 3 were similar to those with a repeat ACS during the first year. Clusters 1 and 2 had a similar and favorable long-term mortality risk. Cluster 3 had the highest mortality risk. The adjusted survival time ratio was 0.64 (95% CI, 0.44-0.93; P=0.018) compared with cluster 1, and 0.71 (95% CI, 0.39-1.32; P=0.281) compared with patients with a repeat ACS. CONCLUSIONS: Patients with subphenotypes of post-ACS with different all-cause mortality risks during long-term follow-up can be identified on the basis of repeatedly measured cardiovascular biomarkers. Patients with persistently elevated biomarkers have the worst outcomes, regardless of whether they experienced a repeat ACS in the first year.

The definition of treatment resistance in anxiety disorders: a Delphi method-based consensus guideline.

Anxiety disorders are very prevalent and often persistent mental disorders, with a considerable rate of treatment resistance which requires regulatory clinical trials of innovative therapeutic interventions. However, an explicit definition of treatment-resistant anxiety disorders (TR-AD) informing such trials is currently lacking. We used a Delphi method-based consensus approach to provide internationally agreed, consistent and clinically useful operational criteria for TR-AD in adults. Following a summary of the current state of knowledge based on international guidelines and an available systematic review, a survey of free-text responses to a 29-item questionnaire on relevant aspects of TR-AD, and an online consensus meeting, a panel of 36 multidisciplinary international experts and stakeholders voted anonymously on written statements in three survey rounds. Consensus was defined as ≥75% of the panel agreeing with a statement. The panel agreed on a set of 14 recommendations for the definition of TR-AD, providing detailed operational criteria for resistance to pharmacological and/or psychotherapeutic treatment, as well as a potential staging model. The panel also evaluated further aspects regarding epidemiological subgroups, comorbidities and biographical factors, the terminology of TR-AD vs. "difficult-to-treat" anxiety disorders, preferences and attitudes of persons with these disorders, and future research directions. This Delphi method-based consensus on operational criteria for TR-AD is expected to serve as a systematic, consistent and practical clinical guideline to aid in designing future mechanistic studies and facilitate clinical trials for regulatory purposes. This effort could ultimately lead to the development of more effective evidence-based stepped-care treatment algorithms for patients with anxiety disorders.

Treatment Preferences of Adolescents and Young Adults with Depressive Symptoms: A Discrete Choice Experiment.

BACKGROUND: Depression in adolescents and young adults is common and causes considerable disease burden while hampering their development, leading to adverse consequences in later life. Although treatment is available, young people are a vulnerable group regarding uptake and completion of treatment. To improve this, insight into youth's preferences for treatment is essential. OBJECTIVE: The aim of this study was to investigate patient preferences for depression treatment in a Dutch sample aged 16-24 years using a discrete choice experiment (DCE). METHODS: The study was conducted in The Netherlands between October 2018 and June 2019, and included 236 adolescents and young adults with current depressive symptoms or previous treatment. The DCE included five attributes (treatment type, frequency of appointment, waiting time, effectiveness, evaluation of therapeutic alliance) with corresponding levels. Results were analysed using latent class analysis. RESULTS: Results show a general preference for individual psychotherapy, treatment with high frequency, high effectiveness, short waiting time and a standard evaluation of the therapeutic alliance ('click' with the therapist) early in treatment. Latent class analysis revealed three different patterns of preferences regarding treatment type and willingness to engage in therapy. The first class showed a strong preference for individual therapy. The second class, including relatively older, higher educated and treatment-experienced participants, preferred high frequency treatment and was more open to different forms of therapy. The third class, including lower educated, younger and treatment-naïve adolescents showed reluctance to engage in therapy overall and in group therapy specifically. CONCLUSION: In this DCE, three classes could be identified that share similar preferences regarding treatment effectiveness, waiting time and evaluation of the therapeutic alliance, but varied considerably in their preference for treatment type (individual, group, or combined psychotherapy) and their willingness to engage. The results from this study may inform mental health care providers and institutions and help optimize professional care for adolescents and young adults with depressive symptoms, improving engagement in this vulnerable group.

Photoinduced Electron Transfer in Inclusion Complexes of Carbon Nanohoops.

ConspectusPhotoinduced electron transfer (PET) in carbon materials is a process of great importance in light energy conversion. Carbon materials, such as fullerenes, graphene flakes, carbon nanotubes, and cycloparaphenylenes (CPPs), have unusual electronic properties that make them interesting objects for PET research. These materials can be used as electron-hole transport layers, electrode materials, or passivation additives in photovoltaic devices. Moreover, their appropriate combination opens up new possibilities for constructing photoactive supramolecular systems with efficient charge transfer between the donor and acceptor parts. CPPs build a class of molecules consisting of para-linked phenylene rings. CPPs and their numerous derivatives are appealing building blocks in supramolecular chemistry, acting as suitable concave receptors with strong host-guest interactions for the convex surfaces of fullerenes. Efficient PET in donor-acceptor systems can be observed when charge separation occurs faster than charge recombination. This Account focuses on selected inclusion complexes of carbon nanohoops studied by our group. We modeled charge separation and charge recombination in both previously synthesized and computationally designed complexes to identify how various modifications of host and guest molecules affect the PET efficiency in these systems. A consistent computational protocol we used includes a time-dependent density-functional theory (TD-DFT) formalism with the Tamm-Dancoff approximation (TDA) and CAM-B3LYP functional to carry out excited state calculations and the nonadiabatic electron transfer theory to estimate electron-transfer rates. We show how the photophysical properties of carbon nanohoops can be modified by incorporating additional π-conjugated fragments and antiaromatic units, multiple fluorine substitutions, and extending the overall π-electron system. Incorporating π-conjugated groups or linkers is accompanied by the appearance of new charge transfer states. Perfluorination of the nanohoops radically changes their role in charge separation from an electron donor to an electron acceptor. Vacancy defects in π-extended nanohoops are shown to hinder PET between host and guest molecules, while large fully conjugated π-systems improve the electron-donor properties of nanohoops. We also highlight the role of antiaromatic structural units in tuning the electronic properties of nanohoops. Depending on the aromaticity degree of monomeric units in nanohoops, the direction of electron transfer in their complexes with C60 fullerene can be altered. Nanohoops with aromatic units usually act as electron donors, while those with antiaromatic monomers serve as electron acceptors. Finally, we discuss why charged fullerenes are better electron acceptors than neutral C60 and how the charge location allows for the design of more efficient donor-acceptor systems with an unusual hypsochromic shift of the charge transfer band in polar solvents.

Understanding and preventing nonadherence and treatment dropout in adolescents and young adults with anxiety and depressive disorders.

Dropout from psychological or pharmacological treatment for anxiety and depressive disorders is common. It is especially problematic in adolescents and young adults because of the adverse consequences for their development. Reasons for treatment dropout can be divided into therapy-process related factors, attitudinal aspects, and practical issues. Adjusting treatment to patient preferences and shared decision making, improving the therapeutic alliance, and interventions such as (family) psychoeducation, motivational interviewing, and help with practical issues are promising strategies to optimize engagement and adherence.