Statistical network models describing multivariate dependency structures in psychological data have gained increasing popularity. Such comparably novel statistical techniques require specific ...guidelines to make them accessible to the research community. So far, researchers have provided tutorials guiding the estimation of networks and their accuracy. However, there is currently little guidance in determining what parts of the analyses and results should be documented in a scientific report. A lack of such reporting standards may foster researcher degrees of freedom and could provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific work. We conclude by discussing how the network literature specifically can benefit from such guidelines for reporting and transparency.
Translational Abstract
In recent years, network models have become increasingly popular in the field of psychology. Such comparably novel statistical techniques require specific guidelines to make them accessible to the research community. So far, researchers have provided tutorials guiding how network analysis can be applied to psychological data. However, there is currently little guidance in determining what parts of the analyses and results should be documented in a scientific report. A lack of such reporting standards may result in researchers being confronted with too much choice in reporting their results, which in turn might provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific work. We conclude by discussing how the network literature specifically can benefit from such guidelines for reporting and transparency.
Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment ...of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.
The COVID-19 pandemic imposes a long period of stress on people worldwide and has been shown to significantly affect sleep duration across different populations. However, decreases in sleep quality ...rather than duration are associated with adverse mental health effects. Additionally, the one third of the general population suffering from poor sleep quality was underrepresented in previous studies. The current study aimed to elucidate effects of the COVID -19 pandemic on sleep quality across different levels of pre-pandemic sleep complaints and as a function of affect and worry.
Participants (n = 667) of the Netherlands Sleep Registry (NSR) were invited for weekly online assessment of the subjective severity of major stressors, insomnia, sleep times, distress, depression, and anxiety using validated scales.
To investigate the overall impact of the COVID-19 pandemic on the sleep quality of people with and without a history of insomnia, we performed a mixed model analysis using pre-pandemic insomnia severity, negative affect, and worry as predictors.
The effect of COVID -19 on sleep quality differs critically across participants, and depends on the pre-pandemic sleep quality. Interestingly, a quarter of people with pre-pandemic (clinical) insomnia experienced a meaningful improvement in sleep quality, whereas 20% of pre-pandemic good sleepers experienced worse sleep during the lockdown measures. Additionally, changes in sleep quality throughout the pandemic were associated with negative affect and worry.
Our data suggests that there is no uniform effect of the lockdown on sleep quality. COVID-19 lockdown measures more often worsened sleep complaints in pre-pandemic good sleepers, whereas a subset of people with pre-pandemic severe insomnia symptoms underwent a clinically meaningful alleviation of symptoms in our sample.
•The effect of COVID -19 on sleep quality differs across participants, and depends on the pre-pandemic sleep quality.•A quarter of people with pre-pandemic (clinical) insomnia experienced a meaningful improvement in sleep quality.•Pre-pandemic good sleepers most often experienced worse sleep during the lockdown measures.•Changes in sleep quality throughout the pandemic were associated with negative affect and worry.
For a very long time in the COVID-19 crisis, behavioural change leading to physical distancing behaviour was the only tool at our disposal to mitigate virus spread. In this large-scale naturalistic ...experimental study we show how we can use behavioural science to find ways to promote the desired physical distancing behaviour. During seven days in a supermarket we implemented different behavioural interventions: (i) rewarding customers for keeping distance; (i) providing signage to guide customers; and (iii) altering shopping cart regulations. We asked customers to wear a tag that measured distances to other tags using ultra-wide band at 1Hz. In total N = 4, 232 customers participated in the study. We compared the number of contacts (< 1.5 m, corresponding to Dutch regulations) between customers using state-of-the-art contact network analyses. We found that rewarding customers and providing signage increased physical distancing, whereas shopping cart regulations did not impact physical distancing. Rewarding customers moreover reduced the duration of remaining contacts between customers. These results demonstrate the feasibility to conduct large-scale behavioural experiments that can provide guidelines for policy. While the COVID-19 crisis unequivocally demonstrates the importance of behaviour and behavioural change, behaviour is integral to many crises, like the trading of mortgages in the financial crisis or the consuming of goods in the climate crisis. We argue that by acknowledging the role of behaviour in crises, and redefining this role in terms of the desired behaviour and necessary behavioural change, behavioural science can open up new solutions to crises and inform policy. We believe that we should start taking advantage of these opportunities.
Summary Meta-analyses and systematic reviews have reported surprisingly few consistent insomnia-characteristics with respect to cognitions, mood, traits, history of life events and family history. ...One interpretation of this limited consistency is that different subtypes of insomnia exist, each with its own specific multivariate profile of characteristics. Because previously unrecognized subtypes will be differentially represented in individual studies and dilute effect sizes of subtype-dependent characteristics of importance, they are unlikely to be reported consistently in individual studies, let alone in meta-analyses. This review therefore aims to complement meta-analyses by listing previously reported psychometric characteristics of insomnia, irrespective of the degree of consistency over studies. The review clearly indicates that characteristics of insomnia may not be limited to sleep. Reports suggest that at least some individuals with insomnia may deviate from people without sleep complaints with respect to demographics, mental and physical health, childhood trauma, life events, fatigue, sleepiness, hyperarousal, hyperactivity, other sleep disorders, lifetime sleep history, chronotype, depression, anxiety, mood, quality of life, personality, happiness, personality, worry, rumination, self-consciousness, sensitivity, dysfunctional beliefs, self-conscious emotion regulation, coping, nocturnal mentation, wake resting-state mentation, physical activity, food intake, temperature perception and hedonic evaluation. The value of this list of characteristics is that (1) internet has now made it feasible to asses them all in a large sample of people suffering from insomnia, and (2) statistical methods like latent class analysis and community detection can utilise them for a truly bottom-up data-driven search for subtypes. The supplement to this review provides a blueprint of this multivariate approach as implemented in the Sleep registry platform ( www.sleepregistry.nl ), that allows for bottom-up subtyping and fosters cross-cultural comparison and worldwide collaboration on insomnia subtype finding - and beyond.
•Introducing a united framework to bridge the gap between network neuroscience and psychopathological networks.•Showcasing three methodological avenues to introduce networks of brain and behavioral ...data.•Creating a common language that allows to exploit synergies.
In recent years, there has been an increase in applications of network science in many different fields. In clinical neuroscience and psychopathology, the developments and applications of network science have occurred mostly simultaneously, but without much collaboration between the two fields. The promise of integrating these network applications lies in a united framework to tackle one of the fundamental questions of our time: how to understand the link between brain and behavior. In the current overview, we bridge this gap by introducing conventions in both fields, highlighting similarities, and creating a common language that enables the exploitation of synergies. We provide research examples in autism research, as it accurately represents research lines in both network neuroscience and psychological networks. We integrate brain and behavior not only semantically, but also practically, by showcasing three methodological avenues that allow to combine networks of brain and behavioral data. As such, the current paper offers a stepping stone to further develop multi-modal networks and to integrate brain and behavior.
Persistent insomnia is among the most frequent complaints in general practice. To identify genetic factors for insomnia complaints, we performed a genome-wide association study (GWAS) and a ...genome-wide gene-based association study (GWGAS) in 113,006 individuals. We identify three loci and seven genes associated with insomnia complaints, with the associations for one locus and five genes supported by joint analysis with an independent sample (n = 7,565). Our top association (MEIS1, P < 5 × 10
) has previously been implicated in restless legs syndrome (RLS). Additional analyses favor the hypothesis that MEIS1 exhibits pleiotropy for insomnia and RLS and show that the observed association with insomnia complaints cannot be explained only by the presence of an RLS subgroup within the cases. Sex-specific analyses suggest that there are different genetic architectures between the sexes in addition to shared genetic factors. We show substantial positive genetic correlation of insomnia complaints with internalizing personality traits and metabolic traits and negative correlation with subjective well-being and educational attainment. These findings provide new insight into the genetic architecture of insomnia.
Summary
Insomnia disorder comprises symptoms during night and day that strongly affect quality of life and wellbeing. Prolonged sleep latency, difficulties to maintain sleep and early morning ...wakening characterize sleep complaints, whereas fatigue, reduced attention, impaired cognitive functioning, irritability, anxiety and low mood are key daytime impairments. Insomnia disorder is well acknowledged in all relevant diagnostic systems: Diagnostic and Statistical Manual of the American Psychiatric Association, 5th revision, International Classification of Sleep Disorders, 3rd version, and International Classification of Diseases, 11th revision. Insomnia disorder as a chronic condition is frequent (up to 10% of the adult population, with a preponderance of females), and signifies an important and independent risk factor for physical and, especially, mental health. Insomnia disorder diagnosis primarily rests on self‐report. Objective measures like actigraphy or polysomnography are not (yet) part of the routine diagnostic canon, but play an important role in research. Disease concepts of insomnia range from cognitive‐behavioural models to (epi‐) genetics and psychoneurobiological approaches. The latter is derived from knowledge about basic sleep–wake regulation and encompass theories like rapid eye movement sleep instability/restless rapid eye movement sleep. Cognitive‐behavioural models of insomnia led to the conceptualization of cognitive‐behavioural therapy for insomnia, which is now considered as first‐line treatment for insomnia worldwide. Future research strategies will include the combination of experimental paradigms with neuroimaging and may benefit from more attention to dysfunctional overnight alleviation of distress in insomnia. With respect to therapy, cognitive‐behavioural therapy for insomnia merits widespread implementation, and digital cognitive‐behavioural therapy may assist delivery along treatment guidelines. However, given the still considerable proportion of patients responding insufficiently to cognitive‐behavioural therapy for insomnia, fundamental studies are highly necessary to better understand the brain and behavioural mechanisms underlying insomnia. Mediators and moderators of treatment response/non‐response and the associated development of tailored and novel interventions also require investigation. Recent studies suggest that treatment of insomnia may prove to add significantly as a preventive strategy to combat the global burden of mental disorders.
Objective
To investigate the association of the severity of temporomandibular disorders (TMD) pain and dysfunction with the frequency of self-reported awake bruxism (AB), sleep bruxism (SB), and ...stress in an adult TMD-patient population.
Materials and Methods
This cross-sectional study included 237 TMD patients based on the Diagnostic Criteria for TMD. Age, sex, frequency of self-reported AB and SB, and stress were included as independent variables. TMD pain and TMD dysfunction were included as dependent variables in regression analyses. Univariate and multivariable linear regression analyses were used to predict TMD pain and TMD dysfunction in two separate models. Finally, network analysis was performed to investigate the associations between all variables.
Results
In the univariate analyses, TMD pain was significantly associated with self-reported AB-frequent (unstandardized coefficient (B) = 3.196, 95%CI 1.198-5.195,
p
= 0.002). TMD dysfunction was significantly associated with AB-frequent (B = 2.208, 95%CI 0.177-4.238,
p
= 0.033) and SB-sometimes (B = 1.698, 95%CI 0.001-3.394,
p
= 0.050). In the multivariable analyses, TMD pain was significantly associated with TMD dysfunction (B = 0.370,
p
< 0.001), stress (B=0.102,
p
< 0.001). TMD dysfunction was significantly associated with TMD pain (B = 0.410,
p
< 0.001) only. Network analysis showed that TMD pain is a bridge factor between AB, stress, and TMD dysfunction.
Conclusions
TMD pain is directly associated with AB, stress, and TMD dysfunction, while TMD dysfunction is only associated with TMD pain.
Clinical Relevance
Reducing pain may improve pain-related dysfunction, and the management of AB and stress may improve TMD pain and dysfunction, and vice versa.
Abstract
Study Objectives
Objective sleep impairments in insomnia disorder (ID) are insufficiently understood. The present study evaluated whether whole-night sleep stage dynamics derived from ...polysomnography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters.
Methods
Eighty-eight participants aged 21–70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported study were used to validate the generalizability of findings. The second night was used to obtain, in addition to conventional sleep parameters, probabilities of transitions between stages and bout duration distributions of each stage. Group differences were evaluated with nonparametric tests.
Results
People with ID showed higher empirical probabilities to transition from stage N2 to the lighter sleep stage N1 or wakefulness and a faster decaying stage N2 bout survival function. The increased transition probability from stage N2 to stage N1 discriminated people with ID better than any of their deviations in conventional sleep parameters, including less total sleep time, less sleep efficiency, more stage N1, and more wake after sleep onset. Moreover, adding this transition probability significantly improved the discriminating power of a multiple logistic regression model based on conventional sleep parameters.
Conclusions
Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than—and independently of—any conventional sleep parameter.
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