Investigating the subjective and objective efficacy of a cognitive behavioural therapy for insomnia (CBT-I)-based smartphone app on sleep: A randomised controlled trial.

Due to insufficient treatment options for insomnia, effective solutions are urgently needed. We evaluated the effects of a CBT-I-based app combining sleep training with subjective and objective sleep monitoring on (i) sleep and (ii) subjective-objective sleep discrepancies (SOSD). Fifty-seven volunteers (20-76 years; MAge = 45.67 ± 16.38; 39 female) suffering from sleep problems were randomly assigned to an experimental group (EG, n = 28) or a waitlist control group (CG, n = 29). During the 6-week app phase, the EG used the CBT-I-based programme and a heart rate sensor for daily sleep monitoring and -feedback, while the CG used sleep monitoring only. Sleep was measured (i) subjectively via questionnaires (Insomnia Severity Index, ISI; Pittsburgh Sleep Quality Index, PSQI), (ii) objectively via ambulatory polysomnography (PSG), and (iii) continuously via heart-rate sensor and sleep diaries. Data revealed interactions for ISI (p = 0.003, ƞ2 part = 0.11) and PSQI (p = 0.050, ƞ2 part = 0.05), indicating training-specific improvements in EG, yet not in CG. While PSG-derived outcomes appear to be less training-specific, a tendential reduction in wake after sleep onset (WASO) was found in EG (p = 0.061, d = 0.55). Regarding changes in SOSD, the results indicate improvements during the app phase (EG) for sleep efficiency, sleep onset latency, and WASO (p ≤ 0.022, d ≥ 0.46); for total sleep time both groups showed a SOSD reduction. The findings indicate beneficial effects of a novel smartphone app on sleep and SOSD. More scientific evaluation of such digital programmes is needed to ultimately help in reducing the gap in non-pharmacological insomnia treatment.

From Pulses to Sleep Stages: Towards Optimized Sleep Classification Using Heart-Rate Variability.

More and more people quantify their sleep using wearables and are becoming obsessed in their pursuit of optimal sleep ("orthosomnia"). However, it is criticized that many of these wearables are giving inaccurate feedback and can even lead to negative daytime consequences. Acknowledging these facts, we here optimize our previously suggested sleep classification procedure in a new sample of 136 self-reported poor sleepers to minimize erroneous classification during ambulatory sleep sensing. Firstly, we introduce an advanced interbeat-interval (IBI) quality control using a random forest method to account for wearable recordings in naturalistic and more noisy settings. We further aim to improve sleep classification by opting for a loss function model instead of the overall epoch-by-epoch accuracy to avoid model biases towards the majority class (i.e., "light sleep"). Using these implementations, we compare the classification performance between the optimized (loss function model) and the accuracy model. We use signals derived from PSG, one-channel ECG, and two consumer wearables: the ECG breast belt Polar® H10 (H10) and the Polar® Verity Sense (VS), an optical Photoplethysmography (PPG) heart-rate sensor. The results reveal a high overall accuracy for the loss function in ECG (86.3 %, κ = 0.79), as well as the H10 (84.4%, κ = 0.76), and VS (84.2%, κ = 0.75) sensors, with improvements in deep sleep and wake. In addition, the new optimized model displays moderate to high correlations and agreement with PSG on primary sleep parameters, while measures of reliability, expressed in intra-class correlations, suggest excellent reliability for most sleep parameters. Finally, it is demonstrated that the new model is still classifying sleep accurately in 4-classes in users taking heart-affecting and/or psychoactive medication, which can be considered a prerequisite in older individuals with or without common disorders. Further improving and validating automatic sleep stage classification algorithms based on signals from affordable wearables may resolve existing scepticism and open the door for such approaches in clinical practice.

On the Efficacy of a CBT-I-Based Online Program for Sleep Problems: A Randomized Controlled Trial.

There is an urgent need for easily accessible treatment options for sleep problems to reduce the current treatment gap in receiving cognitive behavioral therapy for insomnia (CBT-I). Using a randomized controlled trial, we evaluated the efficacy of a CBT-I-based online program on sleep. Fifty-three volunteers (21-71 years; MAge = 44.6 ± 12.5; 27 female) suffering from impaired sleep were randomly allocated either to the experimental group (EG, n = 27) or to an active control group (CG, n = 26). The EG participated in a 6-week CBT-I-based online program, while the CG received psychoeducation and sleep hygiene instructions. Sleep was assessed both objectively via ambulatory polysomnography (PSG) as well as subjectively via questionnaires at three time points (baseline, pre- and post-intervention). A one-month follow-up assessment was performed using questionnaires. The EG showed small but reliable improvements from pre- to post-intervention in PSG-derived wake after sleep onset (from 58.6 min to 42.5 min; p < 0.05) and sleep efficiency (from 86.0% to 89.2%; p < 0.05). Furthermore, subjective sleep quality (assessed via Pittsburgh Sleep Quality Index) improved significantly during intervention (p = 0.011) and follow-up (p = 0.015) in the EG alone. The Insomnia Severity Index decreased from pre- to post-intervention in both groups (EG: p = 0.003, CG: p = 0.008), while it further improved during follow-up (p = 0.035) in the EG alone. We show that a CBT-I-based online program can improve sleep not only subjectively but also objectively and can be a viable alternative when face-to-face interventions are not available.

The Virtual Sleep Lab-A Novel Method for Accurate Four-Class Sleep Staging Using Heart-Rate Variability from Low-Cost Wearables.

Sleep staging based on polysomnography (PSG) performed by human experts is the de facto "gold standard" for the objective measurement of sleep. PSG and manual sleep staging is, however, personnel-intensive and time-consuming and it is thus impractical to monitor a person's sleep architecture over extended periods. Here, we present a novel, low-cost, automatized, deep learning alternative to PSG sleep staging that provides a reliable epoch-by-epoch four-class sleep staging approach (Wake, Light [N1 + N2], Deep, REM) based solely on inter-beat-interval (IBI) data. Having trained a multi-resolution convolutional neural network (MCNN) on the IBIs of 8898 full-night manually sleep-staged recordings, we tested the MCNN on sleep classification using the IBIs of two low-cost (

Evaluation of a Low-Cost Commercial Actigraph and Its Potential Use in Detecting Cultural Variations in Physical Activity and Sleep.

The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural data including low-income countries. We evaluated physical activity and sleep-related measures and discussed the potential application of such devices for large-scale step and sleep data acquisition. To that end, we conducted two separate studies. In Study 1, we evaluated the performance of MB by comparing it to the GT3X (ActiGraph, wGT3X-BT), a scientific actigraph used in research, as well as subjective sleep reports. In Study 2, we distributed the MB across four countries (Austria, Germany, Cuba, and Ukraine) and investigated physical activity and sleep among these countries. The results of Study 1 indicated that MB step counts correlated highly with the scientific GT3X device, but did display biases. In addition, the MB-derived wake-up and total-sleep-times showed high agreement with subjective reports, but partly deviated from GT3X predictions. Study 2 revealed similar MB step counts across countries, but significant later wake-up and bedtimes for Ukraine than the other countries. We hope that our studies will stimulate future large-scale sensor-based physical activity and sleep research studies, including various cultures.

Sleep during COVID-19 lockdown: A cross-cultural study investigating job system relevance.

Our study aimed to assess the change in the sleep patterns during the Coronavirus lockdown in five regions (Austria/Germany, Ukraine, Greece, Cuba and Brazil), using online surveys, translated in each language. Part of the cohort (age 25-65, well-educated) was collected directly during lockdown, to which retrospective cross-sectional data from and after lockdown (retrospective) questionnaires were added. We investigated sleep times and sleep quality changes from before to during lockdown and found that, during lockdown, participants had (i) worse perceived sleep quality if worried by COVID-19, (ii) a shift of bedtimes to later hours during workdays, and (iii) a sleep loss on free days (resulting from more overall sleep during workdays in non-system relevant jobs), leading to (iv) a marked reduction of social jetlag across all cultures. For further analyses we directly compared system relevant and system irrelevant jobs, because it was assumed that the nature of the lockdown's consequences is dependent upon system relevance. System relevant jobs were found to have earlier wake-up times as well as shorter total sleep times on workdays, leading to higher social jetlag for people in system relevant jobs. Cultural differences revealed a general effect that participants from Greece and Ukraine had later bedtimes (on both work and free days) and wake-up times (on workdays) than Cuba, Brazil and Austria, irrespective of COVID-19 lockdown restrictions.

No robust differences in fear conditioning between patients with fear-related disorders and healthy controls.

Fear conditioning and extinction serve as a dominant model for the development and maintenance of pathological anxiety, particularly for phasic fear to specific stimuli or situations. The validity of this model would be supported by differences in the physiological or subjective fear response between patients with fear-related disorders and healthy controls, whereas the model's validity would be questioned by a lack of such differences. We derived pupillometry, skin conductance response and startle electromyography as well as unconditioned stimulus expectancy in a two-day fear acquisition, immediate extinction and recall task and compared an unmedicated group of patients (n = 73) with phobias or panic disorder and a group of patients with posttraumatic stress disorder (PTSD, n = 21) to a group of carefully screened healthy controls (n = 35). Bayesian statistics showed no convincing evidence for a difference in physiological and subjective responses between the groups during fear acquisition, extinction learning or recall. Only the PTSD subgroup had altered startle reactions during extinction learning. Our data do not provide evidence for general differences in associative fear or extinction learning in fear-related pathologies and thereby question the diagnostic validity of the associative fear learning model of these disorders.

The role of spatial selective attention in the processing of affective prosodies in congenitally blind adults: An ERP study.

The question whether spatial selective attention is necessary in order to process vocal affective prosody has been controversially discussed in sighted individuals: whereas some studies argue that attention is required in order to process emotions, other studies conclude that vocal prosody can be processed even outside the focus of spatial selective attention. Here, we asked whether spatial selective attention is necessary for the processing of affective prosodies after visual deprivation from birth. For this purpose, pseudowords spoken in happy, neutral, fearful or threatening prosodies were presented at the left or right loudspeaker. Congenitally blind individuals (N = 8) and sighted controls (N = 13) had to attend to one of the loudspeakers and detect rare pseudowords presented at the attended loudspeaker during EEG recording. Emotional prosody of the syllables was task-irrelevant. Blind individuals outperformed sighted controls by being more efficient in detecting deviant syllables at the attended loudspeaker. A higher auditory N1 amplitude was observed in blind individuals compared to sighted controls. Additionally, sighted controls showed enhanced attention-related ERP amplitudes in response to fearful and threatening voices during the time range of the N1. By contrast, blind individuals revealed enhanced ERP amplitudes in attended relative to unattended locations irrespective of the affective valence in all time windows (110-350 ms). These effects were mainly observed at posterior electrodes. The results provide evidence for "emotion-general" auditory spatial selective attention effects in congenitally blind individuals and suggest a potential reorganization of the voice processing brain system following visual deprivation from birth.

Turning I into me: Imagining your future self.

A widely endorsed belief is that perceivers imagine their present selves using a different representational format than imagining their future selves (i.e., near future=first-person; distant future=third-person). But is this really the case? Responding to the paucity of work on this topic, here we considered how temporal distance influences the extent to which individuals direct their attention outward or inward during a brief imaginary episode. Using a non-verbal measure of visual perspective taking (i.e., letter-drawing task) our results confirmed the hypothesized relation between temporal distance and conceptions of the self. Whereas simulations of an event in the near future were dominated by a first-person representation of the self, this switched to a third-person depiction when the event was located in the distant future. Critically, this switch in vantage point was restricted to self-related simulations. The theoretical and practical implications of these findings are considered.