Review: Impact of urgent youth outpatient mental health care on patient and health system outcomes - a scoping review.

BACKGROUND: Young people often face barriers to psychiatric care and are increasingly seeking crisis services for mental health issues through the emergency department (ED). Urgent psychiatric care models provide youth in crisis with rapid access to time-limited mental health care on an outpatient basis. This scoping review aims to evaluate the impact of such urgent psychiatric services for youth aged 13-25 on patient and health system outcomes. METHODS: We conducted a literature search on PubMed, EMBASE, MEDLINE, PsycINFO, and the Cochrane Database of Systematic Reviews for studies published from inception to November 20, 2020. We included studies that described outpatient psychiatric services designed for youth aged 13 to 25, took place in a clinical setting, and offered any combination of assessment, treatment, and referral. We excluded studies describing suicide intervention programmes. RESULTS: Our search yielded six studies, four of which were descriptive studies and two of which were randomized controlled trials. Most studies found that access to urgent psychiatric care for youth was associated with reduced ED volumes, fewer health system costs, and fewer hospitalizations. None of the studies presented evidence that urgent psychiatric services are associated with improved patient symptomatology or functioning. CONCLUSIONS: The results of this scoping review highlight the scarcity of robust evidence evaluating the effectiveness of urgent care for youth mental health. Further experimental studies and a set of standardized quality measures for evaluating these services are needed to bridge this critical gap in mental health care for youth in crisis.

Limits on Spectral Resolution Measurements by Quantum Probes.

The limits of frequency resolution in nano-NMR experiments have been discussed extensively in recent years. It is believed that there is a crucial difference between the ability to resolve a few frequencies and the precision of estimating a single one. Whereas the efficiency of single frequency estimation gradually increases with the square root of the number of measurements, the ability to resolve two frequencies is limited by the specific timescale of the signal and cannot be compensated for by extra measurements. Here we show theoretically and demonstrate experimentally that the relationship between these quantities is more subtle and both are only limited by the Cramér-Rao bound of a single frequency estimation.

Fast Dynamical Decoupling of the Mølmer-Sørensen Entangling Gate.

Engineering entanglement between quantum systems often involves coupling through a bosonic mediator, which should be disentangled from the systems at the operation's end. The quality of such an operation is generally limited by environmental and control noise. One of the prime techniques for suppressing noise is by dynamical decoupling, where one actively applies pulses at a rate that is faster than the typical time scale of the noise. However, for boson-mediated gates, current dynamical decoupling schemes require executing the pulses only when the boson and the quantum systems are disentangled. This restriction implies an increase of the gate time by a factor of sqrt[N], with N being the number of pulses applied. Here we propose and realize a method that enables dynamical decoupling in a boson-mediated system where the pulses can be applied while spin-boson entanglement persists, resulting in an increase in time that is at most a factor of π/2, independently of the number of pulses applied. We experimentally demonstrate the robustness of our entangling gate with fast dynamical decoupling to σ_{z} noise using ions in a Paul trap.

[Smoking cessation amongst patients with mental disorders].

Cigarette smoking is very prevalent amongst patients suffering from mental disorders. In recent years additional scientific proof has been gathered regarding nicotine addiction mechanisms as effective treatments for smoking cessation. Some of these therapies are included in the "Basket of Health Services" of the State of Israel. Despite high smoking prevalence, the success rate for smoking cessation is low amongst patients with mental disorders. In this paper the possible reasons for this phenomenon are presented, as well as the possible biological and behavioral models that support this severe addiction amongst these patients. Scientifically based methods for smoking cessation are reviewed, including pharmacological and behavioral treatments. In addition, unique updated recommendations for smoking cessation amongst patients with mental disorders are presented.

Correlated noise in Brownian motion allows for super resolution.

Diffusion broadening of spectral lines is the main limitation to frequency resolution in non-polarized liquid state nano-NMR. This problem arises from the limited amount of information that can be extracted from the signal before losing coherence. For liquid state NMR as with most generic sensing experiments, the signal is thought to decay exponentially, severely limiting resolution. However, there is theoretical evidence that predicts a power law decay of the signal's correlations due to diffusion noise in the non-polarized nano-NMR scenario. In this work we show that in the NV based nano-NMR setup such diffusion noise results in high spectral resolution.

NV center based nano-NMR enhanced by deep learning.

The growing field of nano nuclear magnetic resonance (nano-NMR) seeks to estimate spectra or discriminate between spectra of minuscule amounts of complex molecules. While this field holds great promise, nano-NMR experiments suffer from detrimental inherent noise. This strong noise masks to the weak signal and results in a very low signal-to-noise ratio. Moreover, the noise model is usually complex and unknown, which renders the data processing of the measurement results very complicated. Hence, spectra discrimination is hard to achieve and in particular, it is difficult to reach the optimal discrimination. In this work we present strong indications that this difficulty can be overcome by deep learning (DL) algorithms. The DL algorithms can mitigate the adversarial effects of the noise efficiently by effectively learning the noise model. We show that in the case of frequency discrimination DL algorithms reach the optimal discrimination without having any pre-knowledge of the physical model. Moreover, the DL discrimination scheme outperform Bayesian methods when verified on noisy experimental data obtained by a single Nitrogen-Vacancy (NV) center. In the case of frequency resolution we show that this approach outperforms Bayesian methods even when the latter have full pre-knowledge of the noise model and the former has none. These DL algorithms also emerge as much more efficient in terms of computational resources and run times. Since in many real-world scenarios the noise is complex and difficult to model, we argue that DL is likely to become a dominant tool in the field.

Polysomnographic and actigraphic evidence of sleep fragmentation in patients with irritable bowel syndrome.

STUDY OBJECTIVE: To characterize the function and quality of sleep in patients with irritable bowel syndrome (IBS). DESIGN: A prospective study with a historic comparison group. SETTING: A regional hospital that also serves as a tertiary referral center. PATIENTS: Eighteen patients with IBS and a comparison group of 20 matched adults with mild benign snoring. INTERVENTIONS: A polysomnography study and a wrist actigraphy study. MEASUREMENTS: All subjects underwent sleep studies and completed self-report questionnaires (IBS severity, psychosocial variables, sleep function, and Epworth Sleepiness Scale). Fourteen IBS and 11 comparison patients underwent actigraphy. RESULTS: The IBS patients had more than 70% less slow-wave stage sleep (4.5 +/- 7.3% vs 19.3 +/- 12.9%; P = 0.006), compensated by increased stage 2 sleep (72.2 +/- 6.6% vs 60.1 +/- 16.8%; P = 0.01). The IBS group had significant sleep fragmentation with a significantly higher arousal and awakening index (P < 0.001), a longer wake period after sleep onset (P = 0.02), and more downward shifts to lighter sleep stages (P = 0.01). The 4-night actigraphy study supported the polysomnography findings. The sleep fragmentation index was significantly higher (P = 0.008) in the IBS group. The IBS patients reported greater daytime sleepiness (9.0 +/- 4.8 vs 6.4 +/- 4.8, Epworth Sleepiness Scale score, P < 0.01) and greater impairment in quality of life, which correlated significantly with the sleep fragmentation indexes. The difference between the groups was not due to differences in baseline anxiety/depression levels. CONCLUSIONS: Patients with IBS have impaired sleep quality, reduced slow-wave sleep activity, and significant sleep fragmentation. The cause-and-effect relationship of these findings with patients' daytime symptoms should be studied further.